Medical Physiology A Cellular and Molecular Approach, Updated 2nd Ed.

Appendix: Webnotes

Feedback Control

In proportional control, the set point is not reached because the difference signal would disappear, and control would come to an end. Engineers devised a way around this. They took the time integral of the difference signal and used that to activate the effector mechanism to achieve integral control that would allow return to the set point. There was another problem. Because there is a time delay in processing the input signal, there is a delay in returning to the set point. Engineers also had a way around that. They took the time derivative of the difference signal and added that to the corrective signal, speeding up the return toward the set point.

Another problem arose. If you have a heater and a cooler, each with its own thermostat, and you want the room to be 23°C to 25°C, you must set the thermostat for the heater to go on at temperatures below 23°C but to shut off at 23°C or above. The thermostat for the cooler has to go on above 25°C but to shut off the cooler at 25°C or below to avoid running the heater and cooler simultaneously. If the room is cold, the heater will warm it up to 23°C and then shut off. If the room is warm, the cooler will cool it down to 25°C and then shut off. By analogy, the body has separate systems for shivering and sweating so that both do not occur at once. One can picture that anabolic and catabolic pathways should cycle separately and not simultaneously. Many body systems such as respiratory and circulatory controls oscillate between slightly above and slightly below the desired average, searching for it rather than sitting on a single ideal value. In case the control system is less precise, the swings become wider, as they do when a drunk driver wanders back and forth across the road while proceeding home.

Contributed by Arthur DuBois

Sphingomyelins

The polar head group of sphingomyelins can be either phosphocholine, as shown in Figure 2–2D on p. 12 of the text, or phosphoethanolamine (analogous to the phosphoethanolamine moiety in Fig. 2–1A on p. 10). Note that sphingomyelins are both (1) sphingolipids because they contain sphingosine and (2) phospholipids because they contain a phosphate group, as do the glycerol-based phospholipids shown in Figures 2–1A and 2–2A–C.

Contributed by Emile Boulpaep and Walter Boron

Diversity of Lipids in a Bilayer

In the accompanying figure, the upper leaflet of this lipid bilayer contains, from left to right, phosphatidylinositol, phosphatidylserine, cholesterol, phosphatidylinositol, phosphatidylcholine, and cholesterol.

image

Contributed by Michael Caplan

Membrane Microdomains

According to current models (Anderson and Jacobson, 2002Edidin, 2003), lipids and proteins are not uniformly distributed in the plane of the membranes that surround cells and organelles. Instead, certain lipids and associated proteins cluster to form microdomains that differ in composition, structure, and function from the rest of the membrane that surrounds them. These microdomains can be thought of as small islands bordered by the “lake” of lipids and proteins that constitute the bulk of the membrane. These two-dimensional structures are composed of lipids that tend to form close interactions with one another, resulting in the self-assembly of organized domains that include specific types of lipids and exclude others. The lipids that tend to be found in microdomains include sphingomyelin, cholesterol, and glycolipids. The physical interactions responsible for the tendency of these lipids to self-assemble into microdomains have yet to be fully elucidated. Proteins that are able to interact closely with microdomain-forming lipids can also become selectively incorporated into these microdomains. A number of different names are used to refer to these microdomains, the most common of which are caveoli and rafts.

Caveolae (p. 43 in the text) were originally defined in the electron microscope as flask-shaped invaginations of the plasma membrane. They carry a coat composed of proteins called caveolins, and they tend to be at least 50–80 nm in diameter. Caveolae have been shown to participate in endocytosis of specific subsets of proteins and are also richly endowed with signaling molecules, such as receptor tyrosine kinases.

Rafts are less well understood structures, which are defined by the biochemical behaviors of their constituents when the surrounding membrane is dissolved in nonionic detergents. Lipid microdomains rich in sphingomyelin, cholesterol, and glycolipids tend to resist solubilization in these detergents under certain conditions and can be recovered intact by density centrifugation. Again, a number of interesting proteins involved in cell signaling and communication, including kinases, ion channels, and G proteins, tend to be concentrated in rafts or to become associated with rafts upon the activation of specific signal transduction pathways. Rafts are thought to collect signaling proteins into small, highly concentrated zones, thereby facilitating their interactions and hence their ability to activate particular pathways. Rafts are also involved in membrane trafficking processes. In polarized epithelial cells, the sorting of a number of proteins to the apical plasma membrane is dependent on their ability to partition into lipid rafts that form in the plane of the membrane of the trans-Golgi network. Little is known about what lipid rafts actually look like in cell membranes in situ. It is currently thought that they are fairly small (<100 nm), although it is possible that they can be induced to coalesce into larger structures in certain circumstances. Much remains to be learned about the structures and functions of rafts and caveolae, but it is clear that they are dynamic and important entities that subdivide membrane into specialized regions that cells exploit for a wide variety of tasks.

REFERENCE

Anderson RG and Jacobson K: A role for lipid shells in targeting proteins to caveolae, rafts, and other lipid domains. Science 296:1821–1825, 2002.

Edidin M: The state of lipid rafts: From model membranes to cells. Annu Rev Biophys Biomol Struct 32:257–283, 2003.

Contributed by Michael Caplan

Cell Locomotion

At least in some cases, the interactions that contribute to cellular motility are geometrically and biochemically quite distinct from those that underlie muscle contraction. For example, the amoebic cells of the bread mold Dictyostelium discoideum are able to continue crawling despite the elimination—by genetic deletion—of all of their myosin. Although motility in these altered cells is not normal, that it persists at all provides ample proof that the paradigms that apply to smooth and striated muscle are by no means the only schemes that nature has devised to generate actin filament-based motion.

Contributed by Michael Caplan

Other Roles of Actin and Myosin

In addition to the examples discussed in the text, actin and myosin may play important roles in other processes. Actin filaments and various newly discovered isoforms of myosin may be involved in the shuttling of intracellular cargoes in much the same way that microtubules and their associated motor proteins participate in this function. Certain types of myosin appear to serve as motors that drive the movements of vesicles and other organelles along tracks composed of actin filaments. The precise role and relative importance of these movements in the physiology of the cell has yet to be fully elucidated. Despite this uncertainty, it is clear that the actin and myosin cytoskeleton subserves a multitude of functions, ranging from its classical role in the macroscopic contractions of skeletal muscles to its contributions to motility at subcellular scales.

Contributed by Michael Caplan

Günter Blobel

http://www.nobel.se/medicine/laureates/1999/index.html

George Palade

http://www.nobel.se/medicine/laureates/1974/index.html

The Porosome

Porosomes are the universal secretory machinery in cells. In the past decade, this new cellular structure at the cell plasma membrane, measuring only a few nanometers, provides a molecular understanding of the secretory process in cells. Porosomes are supramolecular, lipoprotein structures at the cell plasma membrane, where membrane-bound secretory vesicles transiently dock and fuse to release intravesicular contents to the outside during cell secretion. The mouth of the porosome opening to the outside ranges in size from 150 nm in diameter in acinar cells of the exocrine pancreas to 12 nm in neurons. The mouth dilates during cell secretion, returning to its resting size following completion of the process [Fig. 1].

The past decade has witnessed the elucidation of the composition of the porosome, as well as its structure, its dynamics at nm resolution and in real time, and its functional reconstitution into artificial lipid membranes. Experiments have also demonstrated the molecular mechanism of secretory vesicle fusion at the porosome base, and secretory vesicle swelling enabling expulsion of intravesicular contents. It has become clear that secretory vesicles transiently dock, fuse, partially expel their contents, and dissociate, allowing multiple rounds of docking-fusion-expulsion-dissociation. It has been further determined that swelling of secretory vesicles is required for the expulsion of intravesicular contents during cell secretion, and the extent of swelling is directly proportional to the amount of vesicular contents expelled. These findings have led to a paradigm shift in our understanding of cell secretion, resolving the long held conundrum in the generation of partially empty vesicles as seen in electron micrographs following cell secretion.

REFERENCES:

1. Jena BP: Functional organization of the porosome complex and associated structures facilitating cellular secretion. Physiology 24: 367–376, 2009.

2. Cho SJ, Jeftinija K, Glavaski A, Jeftinija S, Jena BP, Anderson LL: Structure and dynamics of the fusion pores in live GH-secreting cells revealed using atomic force microscopy. Endocrinology 143: 1144–1148, 2002.

3. Jena BP, Schneider SW, Geibel JP, Webster P, Oberleithner H, Sritharan KC. Gi regulation of secretory vesicle swelling examined by atomic force microscopy. Proc Natl Acad Sci USA 94: 13317–13322, 1997.

4. Jeremic A, Kelly M, Cho SJ, Stromer MH, Jena BP. Reconstituted fusion pore. Biophys J 85:2035–2043, 2003.

Contributed by Bhanu P. Jena

image

FIG 1. Porosome: the secretory portal in mammalian cells. (A) A high resolution AFM micrograph shows a single pit with four 100-180 nm porosomes within (blue arrowhead) at the apical plasma membrane in a live pancreatic acinar cell. (B) An electron micrograph depicting a porosome (blue arrowhead) close to a microvilli (MV) at the apical plasma membrane (PM) of a pancreatic acinar cell. Note the association of the porosome membrane (yellow arrowhead), and the zymogen granule membrane (ZGM) (red arrow head) of a docked ZG (inset). Cross section of a circular complex at the mouth of the porosome is seen (blue arrow head). (C) Schematic diagram of pits (yellow arrow) and porosomes (blue arrow) at the cell plasma membrane. ZG’s the secretory vesicles in exocrine pancreas called dock and transiently fuse at the porosome base to expel intravesicular contents. (D) Several porosomes within a pit are shown at zero time, 5 min and 30 min following stimulation of secretion. Section analysis across three porosomes is shown in the top panel, with the blue arrowhead pointing at a porosome. Note the dialation of the porosome at the 5 min time point and its return to near resting size after 30 min. following stimulation of secretion. (E) This panel shows % total cellular amylase release in the presence (yellow bars) and absence (blue bars) of the secretagogue Mas7. Note the increase in porosome diameter, correlating with an increase in total cellular amylase release at 5 min following stimulation of secretion. At 30 min following a secretory stimulus, there is a decrease in porosome diameter and no further increase in amylase secretion beyond the 5-min time point. No significant changes in amylase secretion or porosome diameter were observed in control cells in either the presence or absence of the non-stimulatory mastoparan analogue (Mas17). (F) Electron micrograph of a porosome (blue arrowhead) at the nerve terminal, in association with a synaptic vesicle (SV) at the presynaptic membrane (Pre-SM). Notice the central plug-like structure at the neuronal porosome opening. (G) AFM micrograph of a neuronal porosome in physiological buffer, also showing the central plug (blue arrowhead) at its opening. The central plug in the neuronal porosome complex may regulate its rapid close-open conformation during neurotransmitter release. The neuronal porosome is an order of magnitude smaller (10-15 nm) compared to porosome in the exocrine pancreas (100-180 nm). Note the central plug and eight interconnected ridges within the porosome complex. (H) Electron density maps of negatively stained electron micrographs of isolated neuronal porosome protein complex. Note the ~12 nm complex exhibiting a circular profile and having a central plug, with 8 interconnected protein densities at the rim of the complex. Bar = 5 nm. (I) Atomic force micrograph of a pit and three porosomes within (one shown by the blue arrowhead) in pancreatic acinar cell, and the specific immunolocalization of amylase-specific immunogold (yellow spots) demonstrating amylase secretion through the structure. (J) Electron micrographs of liposome-reconstituted porosome complex isolated from pancreatic acinar cell. Note the cup-shaped basket-like morphology of the porosome complex reconstituted in a 500-nm lipid vesicle. Bar = 100 nm. (K) The lipid bilayer-reconstituted porosome complex is functional. Top panel shows a schematic drawing of the EPC9 setup, for electrophysiological measurements. Isolated zymogen granules added to the cis compartment of the bilayer chamber, dock and fuse with the reconstituted porosomes at the bilayer, and is detected as an increase in capacitance and current activity, and a concomitant time dependent release of amylase to the trans compartment of the bilayer chamber determined using immunoblot assay.

Sugar Uptake into the Golgi

The attachment of a sugar molecule to the growing N-linked sugar chain occurs in a series of four steps:

Step 1: In the cytosol, the sugar is covalently coupled to a nucleoside diphosphate (either UDP or GDP, depending on the sugar to be transported). The result of this reaction is a sugar nucleoside diphosphate(e.g., UDP-galactose). (An exception to this rule is sialic acid, where the sugar is coupled to CMP, a nucleoside monophosphate, rather than a diphosphate.)

Step 2: A carrier protein in the membrane of the Golgi moves the sugar nucleoside diphosphate from the cytoplasm to the lumen of the Golgi.

Step 3: The sugar transferases use the sugar nucleoside diphosphate (e.g., UDP-galactose) as a substrate by catalyzing a reaction that couples the sugar residue (e.g., galactose) to the growing N-linked chain. As a by-product, this reaction generates a nucleoside diphosphate (e.g., UDP), which is then converted to a nucleoside monophosphate (UMP) plus inorganic phosphate.

Step 4: The same carrier protein that imports the sugar nucleoside diphosphate (e.g., UDP-galactose) exports the nucleoside monophosphate (e.g., UMP) that is the by-product of the preceding transferase reaction. Because the carrier protein simultaneously imports the sugar nucleoside diphosphate and imports the nucleoside monophosphate, this carrier protein is an example of an exchanger (see p. 128 in the textbook).

Contributed by Michael Caplan

Familial Hypercholesterolemia: A Defect in Receptor-Mediated Endocytosis

The critical physiological role played by endocytic receptors is underscored by the molecular pathogenesis of a relatively common human genetic disease. Cholesterol is carried through the bloodstream bound to binding proteins, one of which is known as low-density lipoprotein (LDL). Many cells throughout the body express receptors for LDL at their plasma membranes. These cells internalize receptor-bound LDL and utilize its cargo of cholesterol for membrane synthesis and in various biochemical pathways. The imported cholesterol also serves to inhibit the cells’ endogenous de novo synthesis of cholesterol. The disease known as familial hypercholesterolemia (FHC) is caused by a defect in the gene encoding the LDL receptor, resulting in the synthesis of receptors that either do not bind LDL or fail to be internalized.

In the absence of functional LDL receptors, cells are unable to import exogenous cholesterol. Even though serum cholesterol levels rise to extraordinarily high levels, cells are oblivious to its presence, inasmuch as they lack the machinery that allows them to endocytose LDL. Consequently, their cholesterol synthesis continues uninhibited. The excess cholesterol synthesis results in the buildup of cholesterol-filled lipid droplets in cells throughout the body. Accumulation of these cholesterol inclusions in the cells lining arterial walls produces atherosclerotic plaques, which can go on to occupy and occlude the lumens of the blood vessels. When these plaques appear in the coronary arteries, which supply the heart (see p. 581 of the text), they impede coronary blood flow and thus prevent the heart from receiving sufficient oxygen. Not surprisingly, patients who are afflicted with FHC often succumb to heart disease at relatively early ages. Patients who are homozygous for defective LDL receptors usually experience their first myocardial infarction (“heart attack”) in their early teens, whereas heterozygotes (whose cells express half the normal complement of functional LDL receptor) generally experience cardiac symptoms in midlife. The heterozygous form of familial hypercholesterolemia affects approximately 1 in 500 people. Our current understanding of receptor-mediated endocytosis, and of the molecular interactions on which it depends, owes a tremendous amount to insights gained through the study of FHC by Brown and Goldstein, whose work earned them the 1985 Nobel Prize in Medicine or Physiology. (http://www.nobel.se/medicine/laureates/1985/index.html).

Contributed by Michael Caplan

Role of Cell–Cell Adhesion Molecules in Development

Formation of the first polarized epithelial cells in the developing mammalian embryo occurs when the adhesion proteins are synthesized and adhering junctions form. If these cell–cell interactions become disrupted during early embryogenesis, the embryonic cells separate from one another, preventing further development.

Contributed by Michael Caplan

β-Catenins

The concentration of β-catenin in the cytoplasm is also regulated by a cluster of cytosolic proteins (including the adenomatous polyposis coli protein that is mutated in some colon cancers) that bind β-catenin and target it for degradation. Thus, inhibition of this regulatory pathway, such as occurs following activation of Wnt signaling during organ development, can also result in a rise in-catenin levels and enhanced nuclear localization and transcriptional regulation.

Contributed by Lloyd Cantley

WNK Kinases

This is a serine/threonine kinase. WNK stands for “with no K”—that is, no lysine residue (the single-letter code for lysine is “K”) in the catalytic domain (specifically, subdomain II) of the enzyme. In nearly all other kinases, this lysine residue is conserved.

Contributed by Lloyd Cantley

Alfred Gilman and Martin Rodbell

http://www.nobel.se/medicine/laureates/1994/index.html

Compartmentalization of Second Messenger Effects

In the textbook, we referred only to whole-cell levels of intracellular second messengers (e.g., cAMP), as if these messengers were uniformly distributed throughout the cell. However, some cell physiologists and cell biologists believe that local effects of intracellular second messengers may be extremely important in governing how signal transduction processes work. One piece of evidence for such local effects is that the receptors for hormones and other extracellular agonists often are a part of macromolecular clusters of proteins that share a common physiological role. For example, a hormone receptor, its downstream heterotrimeric G protein, an amplifying enzyme (e.g., adenylyl cyclase) that generates the intracellular second messenger (e.g., cAMP), other proteins (e.g., the A kinase anchoring protein [AKAP]), and the effector molecule (e.g., protein kinase A) may all reside in a microdomain at the cell membrane. Thus, it is possible that a particular hormone could act by locally raising [CAMP]i to levels much higher than in neighboring areas so that—of all the cellular proteins potentially sensitive to cAMP—the newly formed cAMP may only activate a local subset of these targets.

A second piece of evidence for the local effects of cAMP is the wide distribution of phosphodiesterases, which would be expected to break down cAMP and limit its ability to spread throughout the cell.

Contributed by Laurie Roman

Earl W. Sutherland, Jr.

http://www.nobel.se/medicine/laureates/1971/index.html

Edmond H. Fischer and Edwin S. Krebs

http://www.nobel.se/medicine/laureates/1992/index.html

Acyl Groups

As noted on p. 10 of the text, phosphatidyl inositols and phosphatidyl cholines can each contain a variety of acyl groups. Therefore, the phosphoinosides derived from them can also contain a variety of acyl groups.

Contributed by Emile Boulpaep and Walter Boron

IP3 Receptor Diversity

As noted in the textbook, the IP3 receptor is a tetramer composed of subunits of approximately 260 kDa, and at least four different genes encode the receptor subunits. These genes are subject to alternative splicing, further increasing the potential for receptor diversity. IP3 receptors bind their ligand with high affinity (KD = 2–10 nM) or low affinity (KD = 40 nM). However, the extent to which these different affinities correlate with particular forms of the receptor has not been established.

Contributed by Laurie Roman

Phospholipase A2

Phospholipase A2 (PLA2) catalyzes the hydrolytic cleavage of glycerol-based phospholipids (see Fig. 2–2A–C in the textbook) at the second carbon of the glycerol backbone, yielding AA and a lysophospholipid (see Fig. 3-10 in the textbook). Some of the cytosolic PLA2 enzymes require Ca2+ for activity. In addition, raising [Ca2+]i from the physiological level of approximately 100 nM to approximately 300 nM facilitates the association of cytoplasmic PLA2with cell membranes, where the PLA2 can be activated by specific G proteins.

Contributed by Laurie Roman

Cyclooxygenase

Cyclooxygenase (COX) catalyzes the stepwise conversion of arachidonic acid into the intermediates prostaglandin G2 (PGG2) and prostaglandin H2 (PGH2). Thus, this enzyme is also referred to as prostaglandin-H synthetase (PGHS). As noted in the box at the top of p. 65 in the textbook, it is the same enzyme that catalyzes both reactions. COX exists in two isoforms, COX-1 (a 2.8-kb transcript) and COX-2 (a 4.1-kb transcript).

Contributed by Laurie Roman

Names of Arachidonic Acid Metabolites

5-HPETE = 5-S-hydroperoxy-6-8-trans-11, 14-cis-eicosatetraenoic acid

5-HETE = 5-hydroxyeicosatetraenoic acid

EET = cis-epoxyeicosatrienoic acid

Contributed by Emile Boulpaep and Walter Boron

Epoxygenase

As shown in Figure 3-11 in the textbook, one pathway of arachidonic acid metabolism begins with the transformation of arachidonic acid by epoxygenase (a cytochrome P-450 oxidase) to two major products: hydroxyeicosatetraenoic acids (HETEs) and cis-epoxy-eicosatrienoic acids (EETs). Epoxygenase requires molecular oxygen (i.e., it is an oxidase) and has several required cofactors, including cytochrome P-450 reductase, NADPH/NADP+, and/or NADH/NAD+.

Contributed by Emile Boulpaep and Walter Boron

Actions of Prostanoids

The prostanoids may participate in regulation of the Na-K pump, which plays a central role in salt and water transport in the kidney and the maintenance of ion gradients in all cell types. For example, the inhibition of the Na-K pump produced by IL-1 appears to be mediated by the formation of PGE2. Indeed, IL-1 stimulates the formation of PGE2, and application of exogenous PGE2 inhibits Na-K pump activity directly. Moreover, COX blockers prevent the Na-K pump inhibition induced by IL-1. This action on the Na-K pump is not limited to the kidney; AA metabolites also inhibit the pump in the brain.

Prostaglandins are also vasoactive and are important in the regulation of renal blood flow.

Contributed by Laurie Roman

Actions of Leukotrienes

LTC4, D4, E4, and F4 are often referred to as the “cysteinyl leukotrienes” or sometimes as the “peptideleukotrienes.” As summarized in Figure 3-11 in the textbook, the enzyme glutathione-S-transferase (GST) conjugates LTA4, which is unstable, to the sulfhydryl group of the cysteine in glutathione (GSH; the branched tripeptide Glu-Cys-Gly) to produce LTC4. (See p. 991 in the textbook for a description of how the liver uses GSH for conjugation reactions.) The enzyme γ-glutamyl transferase clips off the glutamate residue of LTC4 to produce LTD4 (which is conjugated to -Cys-Gly). A dipeptidase clips the dipeptide bond between Cys and Gly to release the terminal Gly as well as LTE4 (which is conjugated to only the -Cys).

Leukotrienes have multiple effects on the vascular endothelium during inflammation. Various regulatory processes may interact at the level of the small blood vessels to increase the margination (i.e., the attachment to the vessel wall) of subgroups of leukocytes, increase the permeability at the postcapillary venule, and evoke diapedesis (i.e., the migration of the cell through the endothelium) of the adherent leukocytes to create a focus of interstitial inflammation. Each of these steps can be affected by leukotrienes as well as other agents.

The infiltration of leukocytes begins when the cells adhere to the endothelium of the postcapillary venule. Mediators that can increase the adhesiveness of leukocytes include LTB4 and several of the cysteinyl LTs. Increased vascular permeability, influenced by the pulling apart of adjacent endothelial cells, can occur in response to LTC4, LTD4, and LTE4. After adherent leukocytes accumulate—and the size of the interendothelial cell pores increases—a stimulus for diapedesis produces an influx of leukocytes into the interstitial space. Once in the interstitial space, the leukocytes come under the influence of LTB4, a potent chemotactic factor (i.e., chemical attractant) for neutrophils (a type of white blood cell that phagocytoses invading organisms) and less so for eosinophils (another type of white blood cell). LTB4 is also chemokinetic (i.e., speeds up chemotaxis) for eosinophils.

In the lungs, the cysteinyl LTs appear to stimulate the secretion of mucus by the bronchial mucosa. Nanomolar concentrations of LTC4 and LTD4 stimulate the contraction of the smooth muscles of bronchi as well as smaller airways.

Both LTB4 (generated by a hydrolase from the unstable LTA4) and the cysteinyl leukotrienes (i.e., LTC4, LTD4, and LTE4) act as growth or differentiation factors for a number of cell types in vitro. LTB4stimulates myelopoiesis (formation of white blood cells) in human bone marrow, whereas LTC4 and LTD4 stimulate the proliferation of glomerular epithelial cells in the kidney. Picomolar concentrations of LTB4 stimulate the differentiation of a particular type of T lymphocytes referred to as competent suppressor or CD8+ lymphocytes. Additional immunologic regulatory functions that may be subserved by LTB4include the stimulation of INF - γ and IL-2 production by T cells.

Contributed by Laurie Roman

The Electrochemical Potential Energy Difference for an Ion across a Cell Membrane

The chemical potential energy, or partial molar Gibbs free energy, µX, of an uncharged solute X is:

Equation 1

image

where [X] is the concentration (more precisely, the chemical activity) of the solute, R is the gas constant (R = 8.314 J/(°K mole), and T is the temperature in degrees Kelvin (°K = 273.16 + °C). Thus, µX has the units of energy per mole of X (joule/mole). Note that “potential” in the often-used term chemical potential is shorthand for “chemical potential energy.” In the case of a cell, we must consider the chemical potential energy, both on the inside (μX,i) and on the outside (μX,o):

Equation 2

image

Thus, if µX,o >μX,i (i.e., if [X]o > [X]i), then X will spontaneously move from the outside to the inside. On the other hand, if µX,o < µX,i then X will spontaneously move from the inside to the outside.

We can define the chemical potential energy difference (ΔμX) as

Equation 3

image

If solute X is charged, we must also consider the difference in partial molar free energy (ΔμX, Elec) due to the voltage difference across the cell membrane. If the voltage inside the cell is Ψi and the voltage outside the cell is Ψo, then this voltage difference is (Ψi–Ψo), which is also known as the membrane voltage (Vm). This electrical portion of the partial molar free energy change is the electrical work (joules/mole) needed to move the charge, which is on X, across the membrane, into the cell. According to the laws of physics, the electrical work per mole is the product of the voltage difference and the amount of charge/mole moved. Thus, we must multiply the voltage difference (joules/coulomb) by Faraday’s constant (coulombs/mole) and the valence of the ion X, zX (unitary charges/ion):

Equation 4

image

The total free energy change (image) required to move X into the cell is simply the sum of the chemical and electrical terms:

Equation 5

image

Equation 5 is the same as Equation 5–6 on p. 111 in the main text.

Contributed by Peter Aronson, Emile Boulpaep, and Walter Boron

Atrial Natriuretic Peptide

Granular inclusions in atrial myocytes, called Palade bodies, contain proANP, the precursor of atrial natriuretic peptide (ANP; also called atrial natriuretic factor). ProANP, comprising 126 amino acids, is derived from the precursor known as pre-pro-ANP (151 residues in humans). The converting enzyme corin—a cardiac transmembrane serine protease—cleaves the proANP during or after release from the atria, yielding the inactive N-terminal fragment of 98 residues and the active C-terminal 28-amino acid peptide called ANP. Release is primarily caused by stretch of the atrial myocytes. Hormones such as angiotensin, endothelins, arginine vasopressin, and glucocorticoid modulate ANP expression and release. It is noteworthy that expression of corin is reduced in heart failure, which blunts the release of ANP in the failing heart. This blunting might contribute to the inappropriate increase of extracellular fluid volume in heart failure.

ANP is a member of the NP (natriuretic peptide) family of peptides. The biological effects of ANP are potent vasodilation, diuresis, natriuresis, and kaliuresis, as well as inhibition of the renin–angiotensin–aldosterone system.

At least three types of natriuretic peptide receptors (NPRs) exist: NPR-A (also called GC-A; GC, guanylyl cyclase), NPR-B (also called GC-B), and NPR-C. NPR-A and NPR-B are receptors with a single transmembrane domain coupled to a cytosolic guanylyl cyclase (see pp. 68–69 of the text). Activation of NPR-A or NPR-B leads to the intracellular generation of cGMP. In smooth muscle, intracellular cGMP activates the cGMP-dependent protein kinase that phosphorylates myosin light-chain kinase (MLCK). Phosphorylation of MLCK inactivates MLCK, leading to the dephosphorylation of myosin light chains, allowing muscle relaxation.

The ANP C-type receptor NPR-C is not coupled to a messenger system but serves mainly to clear the natriuretic peptides from the circulation.

The heart, brain, pituitary, and lung synthesize an ANP-like compound termed BNP, originally known as brain natriuretic peptide (32 residues in humans). The biological actions of BNP are similar to those of ANP.

The hypothalamus, pituitary, and kidney synthesize C-type natriuretic peptide (CNP), which is highly homologous to ANP and BNP. CNP binds only to NPR-B and is only a weak natriuretic but a strong vasodilator.

The kidney also synthesizes an ANP-like natriuretic compound known as urodilatin (URO). URO has four additional amino acids compared to ANP and binds also to the ANP A-type receptor. Its biologic effect in the target tissue is also transduced by cGMP.

Contributed by Emile Boulpaep

Insulin and IGF-1 Receptors

Activation of insulin and IGF-I receptors (see Fig. 51–5 on p. 1081) occurs by a somewhat different mechanism that we discuss in detail on p. 1081. In brief, these receptors are tetrameric; they are composed of two α and two β subunits. The α subunit contains a cysteine-rich region and functions in ligand binding. The β subunit is a single-pass transmembrane protein with a cytoplasmic tyrosine kinase domain. The α and β subunits are held together by disulfide bonds (as are the two α subunits), forming a heterotetramer. Ligand binding produces conformational changes that appear to cause allosteric interactions between the two α and β pairs, as opposed to the dimerization characteristic of the first class of RTKs (see Fig. 3–12C on p. 68). Thus, insulin binding results in the autophosphorylation of tyrosine residues in the catalytic domains of the β subunits. The activated insulin receptor also phosphorylates cytoplasmic substrates such as IRS-1 (insulin-receptor substrate-1; see p. 1081 and Fig. 51–6 on p. 1082), which, once phosphorylated, serves as a docking site for additional signaling proteins.

Contributed by Emile Boulpaep and Walter Boron

Transcription Factors Phosphorylated by MAP Kinase

The following table summarizes some transcription factors that MAP kinase phosphorylates, together with the site of phosphorylation on the transcription factor and the effect.

Transcription Factor

Site

Effect

c-Myc

Ser-62

Stabilizes protein

c-Jun

Ser-243 (Ser-63/Ser-73 in activation domain are phosphorylated by distinct Ras-dependent kinase)

Inhibits DNA binding

c-Fos

Ser-374 (direct)

Ser-362 (indirect via ribosomal S6 kinase, which is activated by MAP kinase)

Stimulates transrepression

P62TCF (Elk-1)

Multiple

Stimulates transactivation and possibly also DNA binding

C/EBPβ (LAP, NF–IL-6)

Thr-235

Stimulates transactivation

ATF-2

Thr-69 and Thr-71 (via p38 and JNK MAP kinases)

Stimulates transactivation

Contributed by Peter Igarashi

Multimeric Composition of Tyrosine Kinase–Associated Receptors

In the textbook, we pointed out that the IL-3 and the GM-CSF receptors are heterodimers (αβ) that share a common β subunit that has transducing activity. A similar example is the group of three receptors for interleukin-6 (IL-6), oncostatin M (OncM), and interleukin-11 (IL--11). These three receptors use a common transducer subunit called gp130 as well as a unique subunit for ligand binding.

Contributed by Laurie Roman

Nongenomic Effects of Steroid Hormones

A theme that is developing in the literature is that certain steroid hormones, when applied to cells in culture, produce biological effects that are too rapid to be mediated by altered gene expression. An example is aldosterone, which—in several cell lines—can cause [Ca2+]i to decrease so rapidly that the effect simply could not be due to altered protein synthesis. Moreover, treatments that block protein synthesis fail to inhibit the ability of aldosterone to lower [Ca2+]i. It is not clear how such rapid, nongenomic effects of steroid hormones may occur. One possibility is that the aldosterone interacts with an alternate receptor (i.e., not the mineralocorticoid receptor that it would normally bind to in the cytoplasm). Another possibility is that aldosterone might bind to the mineralocorticoid receptor, which could have a rapid effect in addition to the traditional, slower genomic effect. Finally, it is possible that the aldosterone nonspecifically interacts with elements of another signaling cascade. Regardless of the mechanism, the rapid action of aldosterone is an exception to the general rule that all of the actions of steroid-type hormones occur by modulating transcription.

Review:

Ngarmukos C, Grekin RJ: Nontraditional aspects of aldosterone physiology. Am J Physiol: Endocrinol Metab 281:E1122–E127, 2001.

Paper:

Zhou ZH, Bubien JK: Nongenomic regulation of ENaC by aldosterone. Am J Physiol: Cell Physiol 281:C1118–C1130, 2001.

Contributed by Emile Boulpaep and Walter Boron

Role of Tat in Transcript Elongation

Regulation of elongation appears to be critical for the expression of certain genes, such as some genes of the human immunodeficiency virus (HIV-1), the causative agent of acquired immunodeficiency syndrome (AIDS). HIV-1 is a retrovirus (RNA virus) that preferentially infects cells of the immune system. After infection, the RNA viral genome is “reverse” transcribed into double-stranded DNA, which integrates into the host genome. A viral promoter that is located in the long terminal repeat of the viral genome then drives expression of the viral genes. Immediately downstream from the promoter—and within the 5′ untranslated region—is a regulatory element known as the trans-activation response element (TAR). Unlike the regulatory elements that we have discussed previously, this element is active in transcribed RNA. The sequence of TAR contains an inverted repeat, and a stretch of nucleotides on one part of the TAR pairs with nucleotides on the other part to create a hairpin structure in this viral transcript (see the accompanying figure). Because the inverted repeat is imperfect, the hairpin contains a “bulge.” Elongation of transcription cannot occur unless a virally encoded protein called Tat binds to this bulge in the TAR portion of the RNA transcript. In the absence of Tat, transcription initiates but elongation does not proceed past the TAR; the resulting truncated transcripts do not encode proteins. In the presence of Tat, pol II can read through the TAR and elongation proceeds normally, producing full-length RNA. It appears that the function of TAR is to recruit Tat to the promoter. Tat, in turn, associates with P-TEFb, a kinase that phosphorylates the CTD of pol II (see p. 88 as well as Fig. 4–11 on p. 88) and stimulates transcription elongation.

image

Role of Tat in transcript elongation. A, The TAR (trans-activation response element) of the newly transcribed RNA forms a hairpin loop with a bulge. In the absence of Tat, transcription terminates prematurely and releases a short strand of RNA. B, Tat binds to the bulge and recruits a coactivator that allows transcript elongation to form full-length RNAs.

Contributed by Peter Igarashi

Sequential Assembly of General Transcription Factors

image

The sequential assembly of general transcription factors and RNA polymerase II (pol II) results in the formation of the basal transcriptional machinery.

Contributed by Peter Igarashi

Binding of Specific Transcription Factors to Promoter Elements on DNA

image

In this example, specific transcription factors bind to enhancer elements on the DNA and interact with the basal transcriptional machinery to increase the efficiency of gene transcription.

Contributed by Peter Igarashi

Typical Eukaryotic Gene Promoters

image

A promoter consists of modules of simple DNA sequences or “elements.”

Contributed by Peter Igarashi

Locus Control Region for the β-Globin Gene Family

image

A, The β-globin gene locus control region (LCR) lies upstream from the genes that encode the image, γG, γA, Δ and β globin subunits. The five vertical arrows indicate sites at which the DNA is unusually sensitive to degradation by deoxyribonuclease (DNase). B, The LCR ensures that the genes are expressed in a temporally colinear manner, with image and γ expressed early during development and image and β expressed later.

Contributed by Peter Igarashi

Grouping of Transcription Factors According to Transactivation Domain

The following table groups some of the transcription factors (described in the textbook) on the basis of the type of transactivation domain (i.e., the domain that activates transcription).

Type of Transactivation Domain

Transcription Factors with this domain

Acidic blob (rich in negatively charged amino acids—aspartate and glutamate)

GAL4 (a yeast transcription factor)

VP16 (a herpesvirus transcription factor)

Proline-rich:

CTF

NF-1 (nuclear factor-1)

Glutamine-rich

SP1 (stimulating protein-1)

Serine/threonine-rich

GHF-1

Pit-1

Contributed by Peter Igarashi

Dimerization of Basic Helix–Loop–Helix Transcription Factors

The MyoD family of transcription factors includes MyoD as well as myogeninmyf5, and MRF4. All are involved in controlling the differentiation of muscle. MyoD and an E protein generally bind to DNA as heterodimers.

Some bHLH transcription factors contain additional domains—located immediately adjacent to the helix–loop–helix domain—that mediate protein dimerization. A leucine zipper motif is contained in bHLH-Zip proteins such as c-Myc and SREBP, and a PAS domain is contained in bHLH-PAS proteins such as HIF-1α.

Contributed by Peter Igarashi

Novel Families of Transcription Factors

In the textbook (see pp. 86–87), we described four families of transcription factors: zinc finger, basic zipper, basic helix–loop–helix, and helix–turn–helix. In each case, an α-helix in the transcription factor binds in the major groove of the DNA. Some transcription factors use an antiparallel β-pleated sheet for DNA binding. The β-sheet fills the major groove of DNA, and amino acid side chains that are exposed on the face of the β-sheet contact the DNA bases.

In addition to transcription factors that bind to DNA via β-pleated sheets, several other transcription factors do not appear to fall into one of the four structural families listed on pp. 86–87. Thus, it seems likely that other structural motifs can also mediate DNA binding. Examples include the forkhead domain. It is also important to note that some transcription factors bind to DNA through more than one domain. Examples include the POU family, in which the POU-specific domain is required in addition to the POU homeodomain for DNA binding.

Contributed by Peter Igarashi

Phosphorylation of CTD

The carboxyl-terminal domain (CTD) of the largest subunit of pol II can be phosphorylated in vitro by TFIIH and by cdc2 kinase (a regulatory component of the cell cycle). However, the identity of the kinase that is responsible for phosphorylation of the CTD in vivo remains uncertain. There is some evidence that phosphorylation of the CTD may mediate responses to viral transcriptional activators, such as VP16.

Contributed by Peter Igarashi

Modes of Action of Transcriptional Repression

image

Transcriptional repressor modes of action.

Contributed by Peter Igarashi

Examples of RIP

In addition to SREBP noted in the text, other proteins that undergo regulated intramembrane proteolysis (RIP) are Notch and APP—all span the membrane at least once.

Notch is a plasma membrane receptor whose cytoplasmic domain is released in response to Delta, a membrane-bound ligand that regulates cell fate during development.

Amyloid precursor protein (APP) is a protein of unknown function that is cleaved in the membrane to produce the extracellular amyloid β peptide implicated in Alzheimer’s disease. For Notch and APP, the intramembrane cleavage does not take place until a primary cleavage event removes the bulk of the protein on the extracytoplasmic face. Although the cleaved sites differ in these proteins, the net effect of the first step is to shorten the extracytoplasmic domain to less than 30 amino acids, allowing the second cleavage to release a portion of the cytoplasmic domain.

The epithelial Na+ channel ENaC—a heterotrimer that consists of α, β, and γ subunits—also undergoes intramembrane proteolysis. While the ENaC is still in the vesicular subcompartment of the secretory pathway, the protease furin cleaves the extracellular domain of the subunit twice (after consensus RXXR motifs), releasing a peptide of 26 amino acids. By itself, this modification increases the open probability of ENaC to approximately 0.30. Furin also cleaves the γ subunit, but only once. A variety of extracellular proteases—including prostasin, elastase, and plasmin—can make a second cut after the protein has reached the plasma membrane. The result of the γ-subunit cleavages is to increase Po to nearly 1.0. Thus, both examples of proteolysis greatly increase the activity of the channel.

REFERENCE

Hughey RP, Carattino MD, and Kleyman TR: Role of proteolysis in the activation of epithelial sodium channels. Curr Opin Nephrol Hypertens 16:444–450, 2007.

Contributed by Peter Igarashi

Transcription Factors Phosphorylated by MAP Kinase

The following table summarizes some transcription factors that MAP kinase phosphorylates, together with the site of phosphorylation on the transcription factor and the effect.

Transcription Factor

Site

Effect

c-Myc

Ser-62

Stabilizes protein

c-Jun

Ser-243 (Ser-63/Ser-73 in activation domain are phosphorylated by distinct Ras-dependent kinase)

Inhibits DNA binding

c-Fos

Ser-374 (direct)

Ser-362 (indirect via ribosomal S6 kinase, which is activated by MAP kinase)

Stimulates transrepression

p62TCF (Elk-1)

Multiple

Stimulates transactivation and possibly also DNA binding

C/EBPβ (LAP, NF–IL-6)

Thr-235

Stimulates transactivation

ATF-2

Thr-69 and Thr-71 (via p38 and JNK MAP kinases)

Stimulates transactivation

Contributed by Peter Igarashi

Dimerization of Basic Helix–Loop–Helix Transcription Factors

The MyoD family of transcription factors includes MyoD as well as myogeninmyf5, and MRF4. All are involved in controlling the differentiation of muscle. MyoD and an E protein generally bind to DNA as heterodimers.

Some bHLH transcription factors contain additional domains—located immediately adjacent to the helix–loop–helix domain—that mediate protein dimerization. A leucine zipper motif is contained in bHLH-Zip proteins such as c-Myc and SREBP, and a PAS domain is contained in bHLH-PAS proteins such as HIF-1α.

Contributed by Peter Igarashi

Determination of the Volume of Body Fluid Compartments

The total body water (TBW) can be determined by the use of a volume-of-distribution technique. The first step is to infuse intravenously a known quantity of a tracer for water (2HOH or 3HOH) that will distribute everywhere there is water. Because water readily permeates most cell membranes, a tracer for water distributes into both the extracellular and the intracellular fluid.

For example, suppose a 70-kg male is injected with 108 counts per minute (cpm) of 3H2O contained in a small volume of physiological saline. After an equilibration period of 2 h, a sample of the blood plasma is drawn and the 3H2O concentration in the plasma is found to be 2.5 × 103 cpm/mL plasma. Measurement also reveals that 5 × 105 cpm of 3H2O has been lost in urine, as well as from the skin and lungs. From this information, we can calculate the volume of distribution of the tracer, which is the same as the TBW:

image

In this male, the TBW of 39.8 L is 57% of the 70-kg body weight.

How can we determine how this water is distributed among the various fluid compartments? In particular, we need to know the fraction of the TBW that is intracellular and the fraction that is extracellular. In practice, the intracellular fluid (ICF) volume is calculated as the difference between TBW and extracellular fluid (ECF) volume. The ECF volume is determined by using a marker that distributes uniformly throughout the compartments accessible to water but that does not enter the cells. Unfortunately, different markers thought to distribute within the ECF yield different values. For example, large polysaccharides (e.g., inulin) or polyalcohols (e.g., mannitol) that cannot cross cell membranes do not penetrate fully into dense connective tissue and bone. On the other hand, ions that are largely extracellular (e.g., Na+ and Cl) are able to enter cells to some extent. Using the previous techniques, the best estimate is that the total ECF represents between 20 and 25% of body weight (~40% of TBW). This leaves approximately 35–40% of the body weight (~60% of the TBW) as intracellular water or ICF volume.

The plasma volume can be determined by measuring the volume of distribution of labeled albumin. Because albumin escapes only very slowly from the vascular compartment, measuring the final concentration of labeled albumin in the plasma and then using the previous equation to compute the volume of distribution of the albumin label will yield the plasma volume.

Contributed by Peter Aronson, Emile Boulpaep, and Walter Boron

Osmolality versus Osmolarity

Osmolality is a measure of the number of osmotically active particles per kilogram of H2O. The number of particles is expressed in units of moles. Thus, 1 osmole (Osm) is 1 mole (mol) of osmotically active particles. Note that we express osmolality in terms of the mass of solvent (H2O), not the mass of the entire solution (i.e., solutes and solvent). Unfortunately, it is rather impractical to measure the mass of H2O in a solution (e.g., you could weigh the material before and after evaporating all the H2O). For that reason, chemists have introduced osmolarity, the number of osmotically active particles per liter of total solution. It is easy to determine this volume. For very dilute solutions, the osmolality and osmolarity are quantitatively almost identical. Even for interstitial fluid, osmolality and osmolarity differ by less than 1%. Thus, for all practical purposes, one could use these terms interchangeably. On the other hand, the osmometers used to determine the number of osmoles in body fluids are usually calibrated with standards that are labeled in terms of osmoles per kg H2O (i.e., osmolality). Therefore, in this text, we express the osmotic activity of solutions in terms of osmolality.

Blood plasma presents a special problem. Plasma proteins occupy approximately 7% of the total volume of plasma but cannot cross the capillary wall. The solution that equilibrates across the capillary wall is the protein-free part of the blood plasma, which clinicians refer to as “plasma H2O.” Therefore, osmolality of the interstitial fluid will be the same as the osmolality of the protein-free portion of blood plasma. This value is approximately ~290 milliosmoles/kg or 290 mOsm. The osmolality of the total volume of the blood plasma (i.e., the protein-free portion plus the proteins) is only 291 mOsm. The extra 1 mOsm is the osmotic pressure of the plasma proteins. This extra 1 mOsm has a special name—colloid osmotic pressure or oncotic pressure (see p. 133 of the textbook). The reason the plasma proteins contribute so little is that although they have a large mass, they have a high molecular weight and thus represent very few particles.

Contributed by Peter Aronson, Emile Boulpaep, and Walter Boron

The Electrochemical Potential Energy Difference for an Ion across a Cell Membrane

The chemical potential energy, or partial molar Gibbs free energy, µX, of an uncharged solute X is:

Equation 1

image

where [X] is the concentration (more precisely, the chemical activity) of the solute, R is the gas constant (R = 8.314 J/(K mole), and T is the temperature in Kelvin (K = 273.16 + °C). Thus, μX has the units of energy per mole of X (joule/mole). Note that “potential” in the often-used term chemical potential is shorthand for “chemical potential energy.” In the case of a cell, we must consider the chemical potential energy, both on the inside (μX,i) and on the outside (μX,o):

Equation 2

image

Thus, if μX,o >μX,i (i.e., if [X]o > [X]i), then X will spontaneously move from the outside to the inside. On the other hand, if μX,o < μX,i then X will spontaneously move from the inside to the outside.

We can define the chemical potential energy difference (ΔμX) as

Equation 3

image

If solute X is charged, we must also consider the difference in partial molar free energy (ΔμX,Elec) due to the voltage difference across the cell membrane. If the voltage inside the cell is Ψi and the voltage outside the cell is Ψo, then this voltage difference is (Ψi–Ψo), which is also known as the membrane voltage (Vm). This electrical portion of the partial molar free energy change is the electrical work (joules/mole) needed to move the charge, which is on X, across the membrane, into the cell. According to the laws of physics, the electrical work per mole is the product of the voltage difference and the amount of charge/mole moved. Thus, we must multiply the voltage difference (joules/coulomb) by Faraday’s constant (coulombs/mole) and the valence of the ion X, zX (unitary charges/ion):

Equation 4

image

The total free energy change (image) required to move X into the cell is simply the sum of the chemical and electrical terms:

Equation 5

image

Equation 5 is the same as Equation 5–6 on p. 111 in the main text.

Contributed by Peter Aronson, Emile Boulpaep, and Walter Boron

Difference between Vm and EX

Equation 5–6 on p. 111 in the text states that for ion X, the electrochemical potential energy difference across the cell membrane is

Equation 1

image

Here, each of the three major terms enclosed by horizontal braces has the dimension of energy per mole (e.g., joules/mole or kcal/mole). If we divide Equation 1 through by zXF, we obtain

Equation 2

image

Each of the three major terms in Equation 2 now has the dimension of voltage. In other words, in dividing an energy term (units: joules/mole) by zXF (units: coulombs/mole), we are left with joules/coulomb, which is the definition of a volt. The first term on the right side of Equation 2 is nothing more than the negative of the Nernst potential that we introduced in Equation 5–8 on p. 111 in the text. The second term on the right side of Equation 2 is, of course, membrane potential. When Vm = EX, the ion is in equilibrium. Otherwise, the difference (Vm-EX) is the net electrochemical driving force—expressed in units of volts—that acts on ion X as the ion crosses the membrane. On p. 157 of the text, we use this force to derive an expression in Equation 6–15 for the electrical current carried by ion X as the ion crosses the membrane:

Equation 3

image

Equation 3 is written in such a way that an inward current (i.e., the movement of a positively charged species into the cell or of a negatively charged species out of the cell) is negative.

Equation 3 allows us to predict the direction that ion X will passively move (if indeed it can move at all) across the membrane. Of course, if Vm = EX, there will be no net movement of the ion at all. If Vm is more negative than EX, then the membrane voltage is too negative for X to be in equilibrium. As a result, if X is positive, the cation will tend to passively enter the cell. For example, Na+ generally tends to enter cells passively because Vm (e.g., -80 mV) is generally more negative than ENa (e.g., +67 mV in Fig. 6–10 on p. 157). If X is negative, the anion will tend to passively exit the cell. For example, Clgenerally tends to exit cells passively because, in most cells, Vm (-60 mV) is generally more negative than ECl (e.g.,-47 mV).

The opposite is true, of course, if Vm is more positive than EX.

Contributed by Emile Boulpaep and Walter Boron

60 mV per 10-fold Concentration Change

We start with Equation 5–8 on p. 111 in the text:

image

R is 8.314 joule/(K mole), F is 96,484 coulombs/mole, and T is the temperature in Kelvin (K = 273.16 + °C). In order to convert the natural logarithm to the logarithm to the base 10, we must multiply the “ln” term by ln(10), which is approximately 2.303. For the term 2.303 RT/F to be exactly 60 mV, the temperature must be 29.5°C (302.66 K):

image

Indeed, this is Equation 5–9 on p. 111 in the text.

Contributed by Emile Boulpaep and Walter Boron

Definition of Permeability Coefficient

The permeability coefficient (P) is

image

where D is the diffusion coefficient (cm2/s), β is the partition coefficient (concentration in the lipid divided by the concentration in the bulk aqueous phase; a dimensionless number), and a is the thickness of the membrane (cm). Thus, the units of the permeability coefficient are cm/s.

image

Contributed by Emile Boulpaep and Walter Boron

Peter Agre

http://nobelprize.org/nobel_prizes/chemistry/laureates/2003/index.html

The SLC Superfamily of Solute Carriers

The SLC superfamily was the subject of a series of reviews—one per family member—in 2004. The following reference is the introduction to the series.

REFERENCE

Hediger MA, Romero MF, Peng J-B, Rolfs A, Takanaga H, and Bruford EA: The ABCs of solute carriers: Physiological, pathological and therapeutic implications of human membrane transport proteins. Pflügers Arch 447:465–468, 2004.

Contributed by Emile Boulpaep and Walter Boron

The SLC Superfamily of Solute Carriers

The SLC superfamily was the subject of a series of reviews—one per family member—in 2004. The following reference is the introduction to the series.

REFERENCE

Hediger MA, Romero MF, Peng J-B, Rolfs A, Takanaga H, and Bruford EA: The ABCs of solute carriers: Physiological, pathological and therapeutic implications of human membrane transport proteins. Pflügers Arch 447:465–468, 2004.

Contributed by Emile Boulpaep and Walter Boron

Jens C. Skou

http://www.nobel.se/chemistry/laureates/1997/index.html

Crystal Structure of SERCA1

The sarcoplasmic and endoplasmic reticulum calcium ATPase (SERCA) is a P-type ATPase, as is the Na–K pump. In 2000, Toyoshima et al. determined the X-ray crystal structure of SERCA with two Ca2+ions bound. This was the first crystal structure of any P-type pump or ATPase. In 2002, Toyoshima et al. determined the X-ray crystal again, but with no Ca2+ bound. In their 2004 paper, Toyoshima and Mizutani crystallized the protein with a bound ATP analogue (AMP–PNP, which cannot be hydrolyzed) and one Mg2+ (under physiological conditions, ATP—the energy source—binds as a complex with Mg2+), as well as two Ca2+ ions (the transported species) occluded within a channel in the protein.

REFERENCE

Toyoshima C, and Mizutani T: Crystal structure of the calcium pump with a bound ATP analogue. Nature 430:529–535, 2004.

Toyoshima C, and Nomurai H: Structural changes in the calcium pump accompanying the dissociation of calcium. Nature 418:605–611, 2002.

Toyoshima C, Nakasako M, Nomura H, and Ogawa H: Crystal structure of the calcium pump of sarcoplasmic reticulum at 2.6 Å resolution. Nature 405:647–655, 2000.

Toyoshima C, Nomura H, and Sugita Y: Structural basis of ion pumping by Ca2+-ATPase of sarcoplasmic reticulum. FEBS Lett 555:106–110, 2003.

Contributed by Emile Boulpaep and Walter Boron

The ATP Synthase: A Pump in Reverse

The apparent paradox of how the same “pump” protein can act both as an ATPase and as an ATP synthase can be resolved if we recognize that the pump can either hydrolyze ATP and use the energy to pump H+ out of the mitochondrion or—in the physiological direction—use the energy of the inwardly directed H+ gradient to synthesize ATP.

Contributed by Emile Boulpaep and Walter Boron

Paul D. Boyer and John E. Walker

http://www.nobel.se/chemistry/laureates/1997/index.html

Peter D. Mitchell

http://nobelprize.org/nobel_prizes/chemistry/laureates/1978/index.html

ATPs Synthesized per NADH

Glycolysis and the citric acid cycle generate the reducing equivalents NADH and FADH2, and then the inner membrane of the mitochondria converts the energy of these reducing equivalents to ATP in two steps. First, the electron transport chain uses the energy from NADH and FADH2 to pump H+ from the mitochondrial matrix into the intermembrane space between the mitochondrial inner and outer membranes, converting O2 to H2O in the final step. Second, the ATP synthase uses the energy stored in the H+ gradient to generate ATP from ATP plus inorganic phosphate.

Generation of the H+ gradient. For each NADH consumed in the inner matrix of the mitochondrion, it appears that complex I and complex III of the electron transport chain (see Fig. 5–9 on p. 123 of the text) each pump 4 H+from the matrix, across the inner membrane, and into the intermembrane space, and complex IV pumps out an additional 2 H+. Thus, for each NADH, the consensus is that the mitochondrion pumps 10 H+. The FADH2 from succinate feeds into the electron transport chain at complex II (which is actually succinate dehydrogenase), bypassing complex I. Thus, for each FADH2, the consensus is that the mitochondrion pumps 6 H+.

Generation of ATP. Regardless of whether the reducing equivalents come from NADH or FADH2, the result of their being processed by the electron transport chain is a steep electrochemical H+ gradient across the inner membrane. The F0F1 ATPase, also located in the inner membrane, uses the energy in this inwardly directed H+ gradient to synthesize ATP from ADP and inorganic phosphate. In other words, the F0F1ATPase usually functions as an ATP synthase. As outlined in the text on p. 122 and in Figure 5-9 on p. 123, the ATP synthase consists of (1) a group of 10–12 “c” subunits that forms an H+ channel, which rotates like a turbine in the plane of the membrane as protons pass through the channel, (2) a shaft (consisting of the γ and image subunits), which rotates with the turbine and extends into the mitochondrial matrix and which projects deeply into (3) a stationary globular structure that consists of three pairs of αβ subunits. In addition, an “a,” two “b,” and a Δ subunit hold the complex together.

At any one time, the β subunit of one αβ pair is empty (β-empty), the β subunit of another binds ADP + Pi (β-ADP), and the β subunit of the third binds ATP (β-ATP). It is believed that each time three H+ pass through the ATP synthase, the turbine (10–12 “c” subunits) and the shaft (γ and image subunits) rotate together by 120 degrees. This rotation brings the tip of the γ subunit into contact with a new pair of αβ subunits in the stationary F1 portion of the ATP synthase, causing this β subunit to shift from the β-ATP to the β-empty conformation—releasing a just-synthesized ATP. Simultaneously, the previously empty β subunit shifts from the β-empty to the β-ADP conformation (ready to create a new ATP), and the β subunit that previously was binding ADP + Pi creates a new ATP by shifting to the β-ATP conformation. Thus, each time a trio of protons passes through the ATP synthase into the mitochondrial inner matrix, the shaft rotates by 120 degrees and completes the synthesis of one ATP molecule. A complete 360-degree rotation of the shaft (which would require nine protons) would generate three new ATP molecules, with each αβ pair passing through each of the three possible conformations. It is important to note that the preceding H+/ATP stoichiometry is inferred from the structure of the ATP synthase (three αβ pairs of subunits) as well as a wealth of biochemical experiments.

Ancillary transport processes. Although the ATP synthase per se appears to have a stoichiometry of one ATP for every three protons, we have not addressed the overall process of ATP synthesis. The mitochondrion must accomplish two additional tasks in order to complete the process.

First, the mitochondrion must transport one inorganic phosphate molecule (Pi) into its inner matrix for each ATP to be synthesized. This uptake of Pi appears to be accomplished by an H+/H2PO4 cotransporter. In other words, the mitochondrion must take up one H+ (previously pumped out by the electron transport chain) to energize the uptake of each Pi.

Second, the mitochondrion must import one ADP3- molecule for each ATP to be synthesized. In addition, the mitochondrion must export the newly synthesized ATP4- molecule. Both jobs are accomplished by the same ADP–ATP exchanger, which is energized in part by the electrical gradient (ΔΨ) that the electron transport chain generates along with the chemical H+ gradient as it pumps H+ out across the mitochondrial inner membrane.

Thus, the consensus is that the mitochondrion needs to import four H+ to synthesize one ATP molecule:

1. Three H+ to energize a 120-degree turn of the ATP synthase and thus convert one ADP + one Pi to one ATP.

2. One H+ to take up the Pi.

Overall ATP/NADH stoichiometry. In summary, it appears that for each NADH processed, the electron transport chain extrudes 10 protons. Furthermore, it appears that the ATP synthase and ancillary transporters can generate 1 ATP molecule from the inward movement of 4 protons. Thus, the overall ATP/NADH stoichiometry would be 2.5 ATP molecules for each NADH molecule. Because the processing of FADH2 results in the extrusion of only 6 protons, the overall ATP/FADH2 stoichiometry would be 1.5 ATP molecules for each FADH2 molecule. Keep in mind that these figures—which we use in examples throughout the text in the first three printings of the book—are the best current estimates.

NADH shuttle mechanisms. An additional consideration is the access of NADH to complex I in the respiratory chain. In animal cells, the NADH must approach complex I from the matrix side of the mitochondrial inner membrane. This is not a problem for NADH generated inside the mitochondrial matrix by pyruvate dehydrogenase or the citric acid cycle (see Fig. 58–11 on p. 1229). However, NADH generated by glycolysis (see Fig. 58–6A on p. 1218) cannot directly cross the mitochondrial inner membrane. As a result, animal cells use two complicated shuttle mechanisms to move the NADH reducing equivalents indirectly across the mitochondrial inner membrane.

Cells throughout most of the body—but not skeletal muscle or brain—use the malate–aspartate shuttle to bring NADH equivalents across the mitochondrial inner membrane into the mitochondrial matrix. The process, which is described in comprehensive biochemistry texts, involves six steps:

1. Malate dehydrogenase uses NADH and H+ to convert oxaloacetate to malate in the intermembrane space, regenerating NAD+ in the process.

2. The malate–α-ketoglutarate exchanger in the mitochondrial inner membrane imports the malate into the matrix.

3. Malate dehydrogenase in the mitochondrial matrix uses NAD+ to convert the newly imported malate back to oxaloacetate, regenerating NADH+ and H+ in the process.

4. Aspartate aminotransferase in the matrix converts the oxaloacetate and a glutamate to α-ketoglutarate and aspartate.

5. The aforementioned malate–α-ketoglutarate exchanger recycles the α-ketoglutarate back to the intermembrane space, and the glutamate–aspartate exchanger does the same for aspartate.

6. In the intermembrane space, aspartate aminotransferase converts the newly exited aspartate and α-ketoglutarate to glutamate and oxaloacetate, completing the cycle.

The net effect is to shuttle NADH indirectly into the matrix, where it can approach complex I. Using NADH shuttled in this way, the electron transport chain can pump 10 protons from the matrix into the intermembrane space—a number that can produce 2.5 ATP molecules.

Skeletal muscle and brain use a very different two-step method to process the NADH that is produced by glycolysis, the glycerol 3-phosphate shuttle. First, the cytosolic enzyme glycerol-3-phosphate dehydrogenase uses NADH and H+ to convert dihydroxyacetone phosphate to glycerol 3-phosphate, regenerating NAD+ in the process. Second, the enzyme glycerol-3-phosphate dehydrogenase on the outer surface of the mitochondrial inner membrane converts glycerol-3-phosphate dehydrogenase in the intermembrane space to dihydroxyacetone phosphate, thereby regenerating the latter and releasing it into the intermembrane space. In the process, the dehydrogenase converts FAD to FADH2. Because this FADH2 enters the electron transport chain at complex III, it can fuel the extrusion of only six protons across the mitochondrial inner membrane. Thus, using reducing equivalents shuttled this way, the electron transport chain has an ATP/NADH stoichiometry of only 1.5 ATP molecules per NADH molecule.

Note that in the first three printings of the book, we have used the values of 2.5 or 1.5 ATP per NADH to indicate that the energy yield depends on the shuttle system. In the brain, of course, we can simply refer to the value of 1.5 (see discussion of Fig. 11–10 on p. 303 in the text).

Our confidence in the cited figures for the ATP/NADH stoichiometry. Although the figures of 2.5 or 1.5 ATP molecules per NADH are the general consensus, they should not be considered absolute at this time. Although investigators have invested considerable effort in attempting to determine the stoichiometry experimentally, the task is a daunting one for several reasons. First, some of the protons extruded by the electron transport chain can leak back into the mitochondrial matrix by pathways other than the ATP synthase. In fact, brown fat cells make use of this bypass to generate heat (see discussion of Fig. 57–5 on p. 1207 of the text). Second, the proton traffic is computed from measured pH changes and values of buffering power that are sometimes difficult to know with certainty. Third, the precise stoichiometry of the H+/H2PO4 cotransporter depends on the precise pH values on either side of the mitochondrial inner image membrane because the reaction image has a pK of approximately 6.8. Fourth, the intricacies of the ATP synthase have yet to be fully worked out (i.e., the stoichiometry may not always be precisely one ATP synthesized for every three protons entering through the ATP synthase per se).

Contributed by Emile Boulpaep and Walter Boron

Regulation of the CFTR Channel by ATP

CFTR is phosphorylated by PKA at several sites within its R domain (see the figure). Modest phosphorylation causes a conformational change in the R domain that makes NBD1 accessible to ATP. Additional phosphorylation also makes NBD2 accessible to ATP. When ATP binds to NBD1 and is subsequently hydrolyzed, the channel opens, but then it rapidly closes once the adenosine diphosphate and phosphate dissociate (“flickery opening”). However, if a second ATP binds to NBD2, the channel is stabilized in its open state (“long opening”). ATP hydrolysis at NBD2 terminates the long opening and is thus necessary for CFTR to return to its closed state. Dephosphorylation of the R domain by protein phosphatases returns CFTR to its resting state. The control of CFTR by ATP hydrolysis is reminiscent of the control of G protein activity by GTP hydrolysis (see p. 54 of the text).

The R domain of CFTR can also be phosphorylated by PKC. PKC enhances the stimulatory effect of PKA on CFTR Cl transport, but alone it appears to have little direct effect on CFTR function.

image

The figure shows a widely accepted model of how ATP regulates CFTR both by phosphorylation and by ATP hydrolysis. The channel is closed in the three channel states in the top row (nothing bound to the nucleotide-binding domains). The channel is in a “flickery” open state as it makes the transition from the top row to the middle row (NBD1 occupied). Finally, the channel is in a stable or “long” open state in the third row (NBD1 and NBD2 occupied). ADP, adenosine monophosphate; ATP, adenosine triphosphate; CFTR, cystic fibrosis transmembrane conductance regulator; MSD, membrane-spanning domain; NBD, nucleotide-binding domain. (Data from Gadsby DC, Dousmanis AG, and Nairn AC: ATP hydrolysis cycles the gating of CFTR Cl channels. Acta Physiol Scand Suppl 643:247–256, 1998.)

Contributed by Emile Boulpaep and Walter Boron

Maximal Glucose Gradient Achievable by SGLT1 and -2

SGLT2. As noted in the text on p. 125 (see Equation 5–17), SGLT2—the Na+/glucose cotransporter with a 1:1 stoichiometry of Na+ to glucose—is in equilibrium when

Equation 1

image

where image is the electrochemical energy difference across the cell membrane for Na+, and image is the chemical energy difference for glucose (because glucose has no charge, the electrical energy difference for glucose across the membrane is zero). Starting from the definition of electrochemical energy difference in Equation 5–6 in the text (p. 111), we can express image in terms of the Na+concentrations and membrane potential:

Equation 2

image

Similarly, we can express image in terms of the glucose concentrations:

Equation 3

image

If we substitute these last two expressions into Equation 1, we obtain the following equation, which describes the relationships between the Na+ and glucose concentrations when SGLT2 is in equilibrium:

Equation 4

image

SGLT1. As noted in the textbook on p. 125 (see Equation 5–19), SGLT1—the Na+/glucose cotransporter with a 2:1 stoichiometry of Na+ to glucose—is in equilibrium when

Equation 5

image

If we substitute Equations 2 and 3 into Equation 5, we obtain the following equation, which describes the relationships between the Na+ and glucose concentrations when SGLT1 is in equilibrium:

Equation 6

image

We can use Equation 4 (for SGLT2) and Equation 6 (for SGLT1) to compute the maximum achievable glucose gradients. Simply insert the values for [Na+]i, [Na+]o, and Vm as discussed on p. 125.

Contributed by Emile Boulpaep and Walter Boron

image Transporters in the SLC4 Family

So far, investigators have identified ten human genes in the SLC4 family of solute carriers. These genes include three that encode Cl–HCO3 exchanger (the so-called anion exchangers, or AE1, AE2, and AE3), and five that encode Na+-coupled HCO3 transporters. In addition, one gene encodes an Na/borate cotransporter, and another gene encodes a protein—termed AE4—of controversial function. For a discussion of these subjects, consult the review by Romero et al.

The five Na+-coupled HCO3 transporters include the two electrogenic Na/HCO3 cotransporters (NBCe1 and NBCe2), two electroneutral Na/HCO3 cotransporters (NBCn1 and NBCn2), and a single Na+-driven Cl–HCO3 exchanger (NDCBE).

NBCe1 and NBCe1 appear to be able to transport Na+ and HCO3in an Na+:HCO3 stoichiometry of either 1:3 (as in the renal proximal tubule; see p. 859 and Fig. 39–4 on p. 858 in the text) or 1:2 (as in most other cells, including the pancreatic duct; see p. 918 and Fig. 43–6 on p. 919). Preliminary evidence from the laboratory of Boron suggests that NBCe1 and NBCe2—at least when operating with a stoichiometry of 1:2—in fact transport image rather than HCO3. Of course, image arises from HCO3 in the reaction HCO3image image + H+, which has a pK of approximately 10.3.

The Na+-driven Cl–HCO3 exchanger appears to move 1 Na+ and 2 HCO3ions into the cell in exchange for 1 Cl (which moves out of the cell). Extensive kinetic data are consistent with the hypothesis that the Na+-driven Cl–HCO3exchanger from the squid axon in fact transports either Na+ plus image (in exchange for Cl) or perhaps the NaCO3 ion pair (in exchange for Cl). The NaCO3 forms rapidly, and reversibly, from Na+ and image: Na+ + image NaCO3.

Work on NBCn2 (Parker et al., 2008) is consistent with the hypothesis that this electroneutral Na/HCO3 cotransporter—which appears to transport 1 Na+ and 1 HCO3 into the cell—may in fact mediate the uptake of 1 Na+ and 1 image in exchange for 1 intracellular HCO3. The net effect of exchanging 1 extracellular image for 1 intracellular HCO3 would be the uptake of 1 HCO3. In fact, it is intriguing to speculate that all members of the SLC4 family are in fact exchangers, and that the proteins that appear to mediate cotransport in fact mediate an exchange that “nets out” as apparent cotransport.

In addition to the SLC4 family, several members of the SLC26 family can also carry HCO3, although these SLC26 proteins tend to be less selective in the anions that they transport. For a review of this gene family, consult Mount and Romero.

REFERENCE

Boron WF: Intracellular-pH-regulating mechanism of the squid axon: Relation between the external Na+ and HCO3 dependences. J Gen Physiol 85:325–345, 1985.

Boron WF, and De Weer P: Intracellular pH transients in squid giant axons caused by CO2, NH3, and metabolic inhibitors. J Gen Physiol 67:91–112, 1976.

Boron WF, and Knakal RC: Intracellular pH-regulating mechanism of the squid axon: Interaction between DNDS and extracellular Na+ and HCO3J Gen Physiol 93:123–150, 1989.

Boron WF, and Knakal RC: Intracellular pH-regulating mechanism of the squid axon. Dependence on extracellular pH. J Gen Physiol 99:817–837, 1992.

Boron WF, and Russell JM: Stoichiometry and ion dependencies of the intracellular-pH-regulating mechanism in squid giant axons. J Gen Physiol 81:373–399, 1983.

Hogan EM, Cohen MA, and Boron WF: K+- and HCO3-dependent acid–base transport in squid giant axons: Base efflux. J Gen Physiol 106:821–844, 1995.

Hogan EM, Cohen MA, and Boron WF: K+-and HCO3-dependent acid–base transport in squid giant axons: Base influx. J Gen Physiol 106:845–862, 1995.

Mount DB, and Romero MF: The SLC26 gene family of multifunctional anion exchangers. Pflügers Arch 447:710–721, 2004.

Parker MD, Musa-Aziz R, Rojas JD, Choi I, Daly CM, and Boron WF: Characterization of human SLC4A10 as an electroneutral Na/HCO3 cotransporter (NBCn2) with Cl self-exchange activity. J Biol Chem283:12777–12788, 2008.

Romero MF, Fulton CM, and Boron WF: The SLC4 family of HCO3 transporters. Pflügers Arch 447:495–509, 2004.

Contributed by Emile Boulpaep and Walter Boron

Using Membrane Vesicles to Study Glucose Transport

We describe the membrane-vesicle technique in WebNote 0757c--In Vitro Preparations for Studying Renal Function in the Research LaboratoryFigure 5-12 on p. 127 in the text illustrates the use of this technique to explore how the Na+ gradient affects glucose uptake. The vesicles are made from brush-border membrane vesicles (i.e., made from the apical membrane of the proximal tubule). In the absence of Na+ in the experimental medium, glucose enters renal brush border membrane vesicles slowly until reaching an equilibrium value (green curve in the central graph of Figure 5-12). At this point, internal and external glucose concentrations are identical. The slow increase in intravesicular [glucose] occurs by diffusion in the absence of Na+. In contrast, adding Na+ to the external medium establishes a steep inwardly directed Na gradient, thereby dramatically accelerating glucose uptake (red curve in the central graph of Figure 5-12). The result is a transient “overshoot” during which glucose accumulates above the equilibrium level. Thus, in the presence of Na+, the vesicle clearly transports glucose uphill. Similar gradients of other cations, such as K+, have no effect on glucose movement, beyond that expected from diffusion alone.

A negative cell voltage can also drive Na/glucose cotransport, even when there is no Na+ gradient. In experiments in which the internal and external Na+ concentrations are the same, making the inside of the vesicles electrically negative accelerates glucose uptake (not shown).

In vesicle experiments performed on vesicles made from the basolateral membrane, the overshoot in intravesicular [glucose] does not occur, even in the presence of an inward Na+ gradient. Thus, the Na/glucose cotransporter is restricted to the apical membrane.

Contributed by Emile Boulpaep and Walter Boron

The Na–H Exchangers (NHEs)

Consult the review by Orlowski and Grinstein for an overview of the NHE family of exchangers (also known as the SLC9 family of “solute linked carriers”). Note, however, that the SLC9 family contains one more confirmed member (i.e., a total of nine) than at the time the Orlowski–Grinstein review was published.

REFERENCE

Orlowski J, and Grinstein S: Diversity of the mammalian sodium/proton exchanger SLC9 gene family. Pflügers Arch 447:549–565, 2004.

Contributed by Emile Boulpaep and Walter Boron

image Transporters in the SLC4 Family

So far, investigators have identified ten human genes in the SLC4 family of solute carriers. These genes include three that encode Cl–HCO3 exchanger (the so-called anion exchangers, or AE1, AE2, and AE3) and five that encode Na+-coupled HCO3 transporters. In addition, one gene encodes an Na/borate cotransporter, and another gene encodes a protein—termed AE4—of controversial function. For a discussion of these subjects, consult the review by Romero et al.

The five Na+-coupled HCO3 transporters include the two electrogenic Na/HCO3 cotransporters (NBCe1 and NBCe2), two electroneutral Na/HCO3 cotransporters (NBCn1 and NBCn2), and a single Na+-driven Cl–HCO3 exchanger (NDCBE).

NBCe1 and NBCe1 appear to be able to transport Na+ and HCO3in an Na+:HCO3 stoichiometry of either 1:3 (as in the renal proximal tubule; see p. 859 and Fig. 39–4 on p. 858 in the text) or 1:2 (as in most other cells, including the pancreatic duct; see p. 918 and Fig. 43–6 on p. 919). Preliminary evidence from the laboratory of Boron suggests that NBCe1 and NBCe2—at least when operating with a stoichiometry of 1:2—in fact transport image rather than HCO3. Of course, image arises from HCO3 in the reaction HCO3imageimage + H+, which has a pK of approximately 10.3.

The Na+-driven Cl–HCO3 exchanger appears to move 1 Na+ and 2 HCO3 ions into the cell in exchange for 1 Cl (which moves out of the cell). Extensive kinetic data are consistent with the hypothesis that the Na+-driven Cl–HCO3exchanger from the squid axon in fact transports either Na+ plus image (in exchange for Cl) or perhaps the NaCO3 ion pair (in exchange for Cl). The NaCO3 forms rapidly, and reversibly, from Na+ and image: Na+ + image NaCO3.

Recent work on NBCn2 (Parker et al.) is consistent with the hypothesis that this electroneutral Na/HCO3 cotransporter—which appears to transport 1 Na+ and 1 HCO3 into the cell—may in fact mediate the uptake of 1 Na+ and 1 image in exchange for 1 intracellular HCO3. The net effect of exchanging 1 extracellular image for 1 intracellular HCO3 would be the uptake of 1 HCO3. In fact, it is intriguing to speculate that all members of the SLC4 family are in fact exchangers, and that the proteins that appear to mediate cotransport in fact mediate an exchange that “nets out” as apparent cotransport.

In addition to the SLC4 family, several members of the SLC26 family can also carry HCO3, although these SLC26 proteins tend to be less selective in the anions that they transport. For a review of this gene family, consult Mount and Romero.

REFERENCE

Boron WF: Intracellular-pH-regulating mechanism of the squid axon: Relation between the external Na+ and HCO3 dependences. J Gen Physiol 85:325–345, 1985.

Boron WF, and De Weer P: Intracellular pH transients in squid giant axons caused by CO2, NH3, and metabolic inhibitors. J Gen Physiol 67:91–112, 1976.

Boron WF, and Knakal RC: Intracellular pH-regulating mechanism of the squid axon: Interaction between DNDS and extracellular Na+ and HCO3J Gen Physiol 93:123–150, 1989.

Boron WF, and Knakal RC: Intracellular pH-regulating mechanism of the squid axon. Dependence on extracellular pH. J Gen Physiol 99:817–837, 1992.

Boron WF, and Russell JM: Stoichiometry and ion dependencies of the intracellular-pH-regulating mechanism in squid giant axons. J Gen Physiol 81:373–399, 1983.

Hogan EM, Cohen MA, and Boron WF: K+- and HCO3-dependent acid–base transport in squid giant axons: Base efflux. J Gen Physiol 106:821–844, 1995.

Hogan EM, Cohen MA, and Boron WF: K+-and HCO3-dependent acid–base transport in squid giant axons: Base influx. J Gen Physiol 106:845–862, 1995.

Mount DB, and Romero MF: The SLC26 gene family of multifunctional anion exchangers. Pflügers Arch 447:710–721, 2004.

Parker MD, Musa-Aziz R, Rojas JD, Choi I, Daly CM, and Boron WF: Characterization of human SLC4A10 as an electroneutral Na/HCO3 cotransporter (NBCn2) with Cl self-exchange activity. J Biol Chem283:12777–12788, 2008.

Romero MF, Fulton CM, and Boron WF: The SLC4 family of HCO3 transporters. Pflügers Arch 447:495–509, 2004.

Contributed by Emile Boulpaep and Walter Boron

The Water Pump Controversy

Loo and colleagues have proposed that the Na/glucose cotransporter SGLT1 in the human small intestine cotransports not only Na+ and glucose but also water. In other words, with each “cycle,” SGLT1 would move 2 Na+ ions, 1 glucose molecule, and more than 200 water molecules. The authors envisage that the Na+ ions and glucose molecule—along with the water molecules—would diffuse from the extracellular fluid into a pore within the cotransporter protein. The cotransporter would then undergo a conformational change that would close an outer gate and thereby “occlude” these ions and molecules from the extracellular fluid. By opening an inner gate, the cotransporter would “deocclude” these particles and allow the 2 Na+ ions, the glucose molecule, and the 200+ water molecules to enter the cytoplasm of the intestinal cell (i.e., enterocyte). There is no controversy that this general model—minus the water—explains how SGLT1 works. The question is whether each cycle of the cotransporter also moves a fixed number of water molecules through the membrane protein along with the Na+ and glucose. Loo and colleagues suggest that the water pumped by SGLT1 would account for approximately half of the water taken up by the small intestine.

On the other hand, Lapointe and colleagues have challenged the conclusion of Loo and colleagues, suggesting that the data of Loo et al. can more easily be explained by the classical model. That is, as SGLT1 would cotransport Na+ and glucose from the extracellular to the intracellular fluid, water would follow osmotically.

REFERENCE

Lapointe J-Y, Gagnon M, Poirier S, and Bissonnette P: The presence of local osmotic gradients can account for the water flux driven by the Na+–glucose cotransporter. J Physiol 542:61–62, 2002.

Loo DDF, Zeuthen T, Chandy G, and Wright EM: Cotransport of water by the Na+/glucose cotransporter. Proc Natl Acad Sci USA 93:13367–13370, 1996.

Loo DDF, Wright EM, and Zeuthen T: Water pumps. J Physiol 542:53–60, 2002.

Contributed by Emile Boulpaep and Walter Boron

Osmolality versus Osmolarity

Osmolality is a measure of the number of osmotically active particles per kilogram of H2O. The number of particles is expressed in units of moles. Thus, 1 osmole (Osm) is 1 mole (mol) of osmotically active particles. Note that we express osmolality in terms of the mass of solvent (H2O), not the mass of the entire solution (i.e., solutes and solvent). Unfortunately, it is rather impractical to measure the mass of H2O in a solution (e.g., you could weigh the material before and after evaporating all the H2O). For that reason, chemists have introduced osmolarity, the number of osmotically active particles per liter of total solution. It is easy to determine this volume. For very dilute solutions, the osmolality and osmolarity are quantitatively almost identical. Even for interstitial fluid, osmolality and osmolarity differ by less than 1%. Thus, for all practical purposes, one could use these terms interchangeably. On the other hand, the osmometers used to determine the number of osmoles in body fluids are usually calibrated with standards that are labeled in terms of osmoles per kilogram H2O (i.e., osmolality). Therefore, in this text, we express the osmotic activity of solutions in terms of osmolality.

Blood plasma presents a special problem. Plasma proteins occupy approximately 7% of the total volume of plasma but cannot cross the capillary wall. The solution that equilibrates across the capillary wall is the protein-free part of the blood plasma, which clinicians refer to as “plasma H2O.” Therefore, osmolality of the interstitial fluid will be the same as the osmolality of the protein-free portion of blood plasma. This value is approximately 290 milliosmoles/kg or 290 mOsm. The osmolality of the total volume of the blood plasma (i.e., the protein-free portion plus the proteins) is only 291 mOsm. The extra 1 mOsm is the osmotic pressure of the plasma proteins. as discussed on p. 133 of the text, this extra 1 mOsm has a special name: colloid osmotic pressure or oncotic pressure. The reason the plasma proteins contribute so little is that although they have a large mass, they have a high molecular weight and thus represent very few particles.

Contributed by Peter Aronson, Emile Boulpaep, and Walter Boron

The Water Pump Controversy

Loo and colleagues have proposed that the Na/glucose cotransporter SGLT1 in the human small intestine cotransports not only Na+ and glucose but also water. In other words, with each “cycle,” SGLT1 would move 2 Na+ ions, 1 glucose molecule, and more than 200 water molecules. The authors envisage that the Na+ ions and glucose molecule—along with the water molecules—would diffuse from the extracellular fluid into a pore within the cotransporter protein. The cotransporter would then undergo a conformational change that would close an outer gate and thereby “occlude” these ions and molecules from the extracellular fluid. By opening an inner gate, the cotransporter would “deocclude” these particles and allow the 2 Na+ ions, the glucose molecule, and the 200+ water molecules to enter the cytoplasm of the intestinal cell (i.e., enterocyte). There is no controversy that this general model—minus the water—explains how SGLT1 works. The question is whether each cycle of the cotransporter also moves a fixed number of water molecules through the membrane protein along with the Na+ and glucose. Loo and colleagues suggest that the water pumped by SGLT1 would account for approximately half of the water taken up by the small intestine.

On the other hand, Lapointe and colleagues have challenged the conclusion of Loo and colleagues, suggesting that the data of Loo and colleagues can more easily be explained by the classical model. That is, as SGLT1 would cotransport Na+ and glucose from the extracellular to the intracellular fluid, water would follow osmotically.

REFERENCE

Lapointe J-Y, Gagnon M, Poirier S, and Bissonnette P: The presence of local osmotic gradients can account for the water flux driven by the Na+–glucose cotransporter. J Physiol 542:61–62, 2002.

Loo DDF, Zeuthen T, Chandy G, and Wright EM: Cotransport of water by the Na+/glucose cotransporter. Proc Natl Acad Sci USA 93:13367–13370, 1996.

Loo DDF, Wright EM, and Zeuthen T: Water pumps. J Physiol 542:53–60, 2002.

Contributed by Emile Boulpaep and Walter Boron

Coulomb’s Law

The attractive electrostatic force between two charged particles of opposite sign and the repulsive electrostatic force between two charged particles of the same sign are described by Coulomb’s law. The coulombic force between two interacting particles with charges of q1 and q2 is

image

This equation shows that the electrostatic force is directly proportional to the product of the charges and is inversely proportional to the square of the distance, r, between them, image0 is a physical constant called the permittivity of free space (or the vacuum permittivity) and is equal to 8.854 × 10–12 C2 J–1 m–1 he denominator of the equation also includes a dimensionless parameter called the dielectric constant (image). The dielectric constant of a vacuum is defined as 1.0. The dielectric constant is a property that depends on the polarizability of the medium surrounding the two charges. Polarizability refers to the ability of molecules of the medium to orient themselves around ions to reduce electrostatic interactions. Polar water molecules are able to effectively solvate ions by orienting themselves around ions in solutions, thereby reducing coulombic forces between neighboring ions. The dielectric constant of water is therefore relatively high and has a value of approximately 80. For a nonpolar hydrocarbon, such as decane or the alkyl-chain interior of a phospholipid bilayer, image is comparatively low and has a value of approximately 2.

Contributed by Ed Moczydlowski

Electrical Fields and Potentials

A useful way to represent the electrical force (F) acting on a charged particle is by the concept of an electrical field. The electrical field (E) is defined as the force that a particle with positive charge q0 would sense in the vicinity of a charge source. Forces are vector parameters that are described by a magnitude and a direction. The direction of an electrostatic force is defined by the direction that a positive charge would move, namely away from a positively charged source or toward a negatively charged source. Similarly, the direction of an electrical field is the direction that a positive test charge would move within the field. The definition of an electrical field is

image

Although the net charge of any bulk system must be equal to zero, other forms of energy, such as chemical energy, can be used to separate positive and negative charges. The electrical potential (Ψ) describes the potential energy that arises from such a separation of charge. The electrical potential difference (ΔΨ) is a measure of the work (W12) needed to move a test charge q0 between two points (1 and 2) in an electrical field:

image

The electrical potential difference (V) is measured in volts (i.e., joules per coulomb). Because work is also equal to force times distance, the electrical potential difference may also be expressed in terms of the magnitude of the force required to move a test charge (q0) over a distance (d, in cm), along the same direction as the force. With the help of the preceding two equations, we can therefore define the electrical potential difference in terms of the electrical field (volts/cm):

image

Thus, the voltage difference between two points is the product of electrical field and the distance between those points. Conversely, the electrical field is the voltage difference divided by the distance:

image

Contributed by Ed Moczydlowski

Methods for Recording Membrane Potential

In Figure 6-3 in the textbook, we discussed two major approaches for measuring membrane potential (Vm).

In part "A" of the figure, we illustrate the microelectrode method. Microelectrodes are made by heating the middle of a piece of a capillary glass and pulling the melted glass to form a very fine, hollow glass tip (diameter = ~0.5 µm). The microelectrode is filled with an electrolyte solution such as 3 M KCl. A silver wire plated with silver chloride is inserted into the 3 M KCl and connected to an amplifier that is designed to measure small voltages accurately.

In part "B" of Figure 6-3, we illustrate the fluorescent-dye method. Intracellular dye is excited by green light with a wavelength of ~520 nm. A dichroic mirror specifically reflects the fluorescent light, which has a wavelength of >610 nm, to a photodetector.

In part "C" of Figure 6-3, we compare Vm records obtained with the microelectrode and dye methods. The microelectrode and dye methods record action potentials of nearly identical shape in the same neuron. The two phases of the recorded action potential represent a rapid spike representing Na+ current, followed by a slower wave representing Ca2+ current. (Modified from Grinvald A: Annu Rev Neurosci 8:263-305, 1985.)

In part "D" of Figure 6-3, we show two fluorescence records, one obtained from the soma of one neuron, and another from thin processes of a second neuron. The shapes of the action potentials are similar in the two cell regions, but the action potential in the processes is delayed. (Modified from Grinvald A: Annu Rev Neurosci 8:263-305, 1985.)

An Impermeant Bilayer

If a totally impermeant bilayer were not separating the two solutions, the unequal concentrations of KCl would lead to diffusion of the salt in the direction of high to low [KCl]. However, by sealing the hole in the partition with a pure lipid bilayer having no permeability to K+ or Cl, we ensure that the system does not have any separation of charge, and therefore the measured transmembrane voltage is 0 mV.

Contributed by Ed Moczydlowski

Ionophores

We can create a perfectly K+-selective membrane by adding certain organic molecules, known as K+ ionophores, to a planar lipid bilayer. Examples are valinomycin and gramicidin. These molecules have the ability to partition into bilayers and catalyze the diffusion of K+ across phospholipid membranes. Valinomycin and gramicidin act by different mechanisms, but both allow a current of K+ ions to flow across membranes. Valinomycin, which is isolated from Streptomyces fulvissimus, is an example of a carrier molecule that binds K+ and literally ferries it across the lipid bilayer. On the other hand, gramicidincatalyzes K+ movement by the same basic mechanism that has been established for ion channel proteins in cell membranes. Gramicidin, a small, unusual peptide produced by Bacillus brevis, forms a water-filled pore across the membrane with a very small diameter (0.4 nm). The pore is small enough to permit only water molecules or K+ ions to move through in single file. Both gramicidin and valinomycin share another property of channel proteins, called ionic selectivity. These ionophores are strongly cation selective: They accept certain inorganic cations but not Cl or other anions.

Contributed by Ed Moczydlowski

Planar Lipid Bilayers

Planar bilayers can be readily formed by spreading a solution of phospholipids across a small hole in a thin plastic partition that separates two chambers filled with aqueous solution. The lipid solution seals the hole and spontaneously thins to produce a stable phospholipid bilayer. This artificial membrane, by itself, is structurally much like a cell membrane, except that it is completely devoid of protein. In this example, purified K+ channels have been incorporated into the membrane. Because of the large K+ gradient across this K+-permeable membrane, a transmembrane voltage of 92.4 mV (right-side negative) develops spontaneously across the membrane.

Contributed by Ed Moczydlowski

Electrical Fields and Potentials

A useful way to represent the electrical force (F) acting on a charged particle is by the concept of an electrical field. The electrical field (E) is defined as the force that a particle with positive charge q0 would sense in the vicinity of a charge source. Forces are vector parameters that are described by a magnitude and a direction. The direction of an electrostatic force is defined by the direction that a positive charge would move, namely away from a positively charged source or toward a negatively charged source. Similarly, the direction of an electrical field is the direction that a positive test charge would move within the field. The definition of an electrical field is

image

Although the net charge of any bulk system must be equal to zero, other forms of energy, such as chemical energy, can be used to separate positive and negative charges. The electrical potential (Ψ) describes the potential energy that arises from such a separation of charge. The electrical potential difference (Δμ) is a measure of the work (W12) needed to move a test charge q0 between two points (1 and 2) in an electrical field:

image

The electrical potential difference (V) is measured in volts (i.e., joules per coulomb). Because work is also equal to force times distance, the electrical potential difference may also be expressed in terms of the magnitude of the force required to move a test charge (q0) over a distance (d, in cm), along the same direction as the force. With the help of the preceding two equations, we can therefore define the electrical potential difference in terms of the electrical field (volts/cm):

image

Thus, the voltage difference between two points is the product of electrical field and the distance between those points. Conversely, the electrical field is the voltage difference divided by the distance:

image

Contributed by Ed Moczydlowski

Calculating an Ionic Current from an Ionic Flow

On p. 154 of the text, we pointed out that the current carried by ion X through the membrane (Ix) has the units of amperes, which is the same as coulombs per second (the coulomb, C, is the fundamental unit of charge). In order to compute how many moles per second of X are passing through the membrane, we need to convert from coulombs to moles. We can compute a macroscopic quantity of charge by using a conversion factor called the Faraday (F). The Faraday is the charge (in coulombs) of a mole of univalent ions. In other words, F is the product of the elementary charge (e0; see p. 147) and Avogadro’s number:

image

Thus, given an ionic current, we can easily compute the flow of the ion:

IX = F (flow of ion X)

Contributed by Ed Moczydlowski

Shape of the I–V Relationship

In the textbook, we introduced the GHK current equation as Equation 6–7 on p. 154:

image

In the nonphysiological case in which [K+]i and [K+]o are equal to [K+], the previous equation reduces to

image

In this case, the relationship between the K+ current (IK) and Vm should be a straight line that passes through the origin, as shown by the dashed line in Figure 6-7A on p. 154 in the textbook.

Similarly, in the nonphysiological case in which [Na+]i and [Na+]o are equal to [Na+], the GHK current equation reduces to

image

Again, the preceding equation predicts that the relationship between the Na+ current (INa) and Vm also should be a straight line, as shown by the dashed line in Figure 6-7B in the textbook. These relationships are “ohmic” because they follow Ohm’s law: ΔI = ΔV/R (see Web Note 0185a, Ohmic I–V Curve), where R in this equation represents resistance. Thus, the slope of the line is 1/R or the conductance:

Current = Conductance × Voltage

Comparing the previous equation with the two that precede it, we see that—for the special case in which the ion concentrations ([X]) are identical on both sides of the membrane—the conductance is

image

Thus, according to the GHK current equation, the membrane’s conductance to an ion is proportional to the membrane’s permeability and also depends on ion concentration.

What does the GHK current equation predict for more realistic examples in which [K+]i greatly exceeds [K+]o, or when [Na+]i is much lower than [Na+]o? The solid curve in Figure 6-7A in the textbook is the prediction of the GHK current equation for the normal internal (155 mM) and external (4.5 mM) concentrations of K+. By convention, a current of ions flowing into the cell (inward current) is defined in electrophysiology as a negative-going current, and a current flowing out of the cell (outward current) is defined as a positive current. (As in physics, the direction of current is always the direction of movement of positive charge. This means that an inward flow of Cl is an outward current.) The nonlinear behavior of the I–V relationship in Figure 6-7A in the text is solely due to the asymmetric internal and external concentrations of K+. Because K+ is more concentrated inside than outside, the outward K+currents will tend to be larger than the inward K+ currents. That is; the K+ current will tend to exhibit outward rectification, as shown by the solid IV curve in Figure 6-7A. Such IV rectification is known as Goldman rectification. It is due solely to asymmetric ion concentrations and does not reflect an asymmetric behavior of the channels through which the ion moves.

For the case of 155 mM K+ inside the cell and 4.5 mM K+ outside the cell, the GHK current equation predicts an inward current at voltages more negative than -95 mV and an outward current for voltages more positive than -95 mV. The value of-95 mV is called reversal potential (Vrev) because it is precisely at this voltage that the direction of current reverses (i.e., the net current equals zero). If we set IK equal to zero in the GHK current equation and solve for Vrev, we find that this rather complicated equation reduces to the Nernst equation for K+ (which is Equation 6–5 on p. 152 in the text):

image

Thus, the GHK current equation for an ion X predicts a reversal potential (Vrev) equal to the Nernst potential (EX) for that ion; that is, the current is zero when the ion is in electrochemical equilibrium. At voltages more negative than Vrev, the net driving force on a cation is inward; at voltages more positive than Vrev, the net driving force is outward.

Figure 6-7B in the text shows a similar treatment for Na+. Again, the dashed line that passes through the origin refers to the artificial situation in which [Na+]i and [Na+]o are each equal to 145 mM. This line describes an ohmic relationship. The solid curve in Figure 6-7B shows the IV relationship for a physiological set of Na+ concentrations: [Na+]o = 145 mM, [Na+]i 12 mM. The relationship is nonlinear solely because of the asymmetric internal and external concentrations of Na+. Because Na+ is more concentrated outside than inside, the inward Na+ currents will tend to be larger than the outward Na+ currents. That is, the Na+ current will tend to exhibit inward rectification. Again, such IV rectification is known as Goldman rectification.

Contributed by Ed Moczydlowski

Contribution of Ions to Membrane Potential

In the text, we introduced Equation 6–9 on p. 155:

image

and pointed out that the resting Vm depends mostly on the concentrations of the most permeant ion. This last statement is only true on the condition that the most permeant ion is also present at a reasonable concentration. It would be more precise to state that Vm depends on a series of permeability–concentration products. Thus, an ion contributes to Vm to the extent that its permeability–concentration product dominates the previous equation. An interesting example is the H+ ion. Although its permeability PH may be quite high in some cells, H+ concentrations on both sides of the membrane are usually extremely low (at a pH of 7, [H+] is 10-7 M). Thus, although PH may be large, the product PH × [H+] is usually negligibly small so that H+ usually does not contribute noticeably to Vm via a PH × [H+] term in the previous equation.

Contributed by Ed Moczydlowski

Electrical Units

Unit of resistance: Ohm. 1 ohm = 1 volt/amp.

Unit of conductance (the reciprocal of resistance): Siemens. 1 siemens = 1/ohm. In English, “Siemens”—named after Ernst von Siemens—is used both for the singular and for the plural.

Unit of charge: coulomb. 1 coulomb = the electrical charge separated by the plates of a 1-farad capacitor charged to 1 volt.

Unit of capacitance: Farad. 1 farad = 1 coulomb/volt. Thus, if we charge a 1-farad capacitor to 1 volt, the charge on each plate will be 1 coulomb.

Unit of electrical work: 1 joule = 1 volt × 1 coulomb.

Contributed by Ed Moczydlowski

Charge Carried by a Mole of Monovalent Ions

We can compute a macroscopic quantity of charge by using a conversion factor called the Faraday (F). The Faraday is the charge of a mole of univalent ions, or e0 times Avogadro’s number:

image

Contributed by Ed Moczydlowski

Electrical Units

Unit of resistance: Ohm. 1 ohm = 1 volt/amp.

Unit of conductance (the reciprocal of resistance): Siemens. 1 siemens = 1/ohm. In English, “Siemens”—named after Ernst von Siemens— is used both for the singular and for the plural.

Unit of charge: coulomb. 1 coulomb = the electrical charge separated by the plates of a 1-farad capacitor charged to 1 volt.

Unit of capacitance: Farad. 1 farad = 1 coulomb/volt. Thus, if we charge a 1-farad capacitor to 1 volt, the charge on each plate will be 1 coulomb.

Unit of electrical work: 1 joule = 1 volt × 1 coulomb.

Contributed by Ed Moczydlowski

Charge Separation Required to Generate the Membrane Potential

To generate a membrane potential, there must be a tiny separation of charge across the membrane. How large is that charge? Imagine that we have a spherical cell with a diameter of 10 μm. If [K+]i is 100 mM and [K+]o is 10 mM, the Vm according to the Nernst equation would be –61.5 mV (or 0.0615 V) for a perfectly K+-selective membrane at 37°C. What is the charge (Q) on 1 cm2 of the “plates” of the membrane capacitor? We assume that the specific capacitance is 1 μF/cm2. From Equation 6–13 on p. 157 in the text, we know that

Q = CV

where Q is measured in coulombs (C), C is in farads (F), and V is in volts (V). Thus,

Q = (1 × 10-6 F cm–2) × (0.0615 V)

= 61.5 × 10–9°C cm-2

As described in Web Note 0157a, Charge Carried by a Mole of Monovalent Ions, the Faraday is the charge of 1 mole of univalent ions—or 96,480°C. To determine how many moles of K+ we need to separate in order to achieve an electrical charge of 61.5 × 10–9 C cm–2 (i.e., the Q in the previous equation), we merely divide Q by the Faraday. Because Vm is negative, the cell needs to lose K+:

image

The surface area for a spherical cell with a diameter of 10 μm is 3.14 × 10–6 cm2. Therefore,

image

The volume of this cell is 0.52 × 10–12 L. Given a [K+]i of 100 mM,

Total K+ content of cell = (0.1 mole/L) × (0.52 × 10–12 L)

= 0.52 × 10–13 moles

What fraction of the cell’s total K+ content represents the charge separated by the membrane?

image

Thus, in the process of generating a Vm of –61.5 mV, our hypothetical cell needs to lose only 0.004% of its total K+ content to charge the capacitance of the cell membrane.

Contributed by Ed Moczydlowski

Electrochemical Driving Forces and Predicted Direction of Net Fluxes

For Na+ and Ca2+, the arrows—which indicate the driving force—point down, indicating that the driving force favors the passive influx of these ions. For K+, the arrow points up, indicating that the driving force favors the passive efflux of K+. For Cl in skeletal muscle cells, the arrow points up, indicating that the driving force favors a small passive influx. In other cells, the arrow for Cl points down, indicating that the driving force favors passive efflux.

Contributed by Ed Moczydlowski

Conductance Varies with Driving Force

In Web Note 0154b, Shape of the I–V Relationship, we pointed out that when [K+]i = [K+]o, the I–V relationship for K+ currents is linear and passes through the origin (see dashed line in Fig. 6–7A on p. 154 in the text). In this special case, the K+ conductance (GK) is simply the slope of the line because, according to Ohm’s law, IK = GK × Vm. In other words, GK = ΔIKVm.

In the aforementioned web note, we also pointed out that when [K+]i does not equal [K+]o, the I–V relationship is curvilinear (see the solid curve in Fig. 6–7A in the text) as described by the GHK current equation for K+ is:

Equation 1

image

This equation is identical to Equation 6–7 on p. 154 in the text, but with K+ replacing the generic ion “X.” Note that for K+, all of the z values are +1.

Because slope conductance for K+ (GK) is the change in K+ current (IK) divided by the change in membrane voltage (Vm), we could in principle derive an equation for GK by taking the derivative of Equation 1 with respect to Vm(i.e., GK = dIK/dVm). Because Vm appears three times in Equation 1 (and twice in an exponent), this derivative—that is, GK—turns out to be extremely complicated (not shown). Nevertheless, it is possible to show that, in general, GKincreases with increasing values of Vm. For the special case in which Vm = EK, the equation for GK simplifies to

Equation 2

image

It is clear from Equation 2 that GK increases as Vm becomes more positive. However, this relationship is not linear because as Vm increases, EK (the equilibrium potential for K+) must also increase, and thus the [K+]o and/or the [K+]iterms in Equation 2 must also change.

For Equation 6–7 in the text, Equation 2 describes GK at exactly one point—when Vm = EK at -95 mV. At other values of Vm, the appropriate expression for GK is far more complicated than Equation 2. Nevertheless, it is clear from the graph in Equation 6–7 that the slope of the I–V relationship (i.e., GK) increases with Vm. Thus, the slope of the curve in Equation 6–7 A is relatively shallow (i.e., low GK) for the inward currents at relatively negative Vm values (lower portion of the plot) and steeper (i.e., high GK) for outward currents at more positive Vm values (upper portion of the plot).

Contributed by Ed Moczydlowski

Units for the “Time Constant”

As described in Equation 6–17 on p. 158 in the text, the time constant (τ) is

τ = R C

where R is resistance (in ohms) and C is capacitance (in farads). The units of are thus

τ = R·C = ohm × farad

Because an ohm is a volt/ampere, and a farad is a coulomb per volt,

image

Because electrical current (in amps) is the number of charges (in coulombs) moving per unit time (in seconds), an amp is a coulomb per second:

image

Thus, the unit of the “time constant” is seconds.

Contributed by Emile Boulpaep and Walter Boron

Time Constant of Capacitative Current

In Figure 6-11 on p. 158 in the text, we saw that closing the switch (panel A) causes the voltage to decline exponentially with a time constant τ (panel B), and it causes a current to flow maximally at time zero and then to decay with the same time constant as voltage. In other words, the capacitative current flows only while voltage is changing. Why? Current is charge flowing per unit time. Thus, we can obtain the capacitative current (IC) by taking the derivative of charge (Q) in Equation 6–16 on p. 158 in the text with respect to time:

image

By definition, the derivative of charge with respect to time is current (i.e., IC = dQ/dt). Thus, if voltage is constant (i.e., dV/dt = 0), no capacitative current can flow. In Figure 16-11C on p. 158, IC is zero before the switch is closed, when the voltage is stable at V0, and again is zero at “infinite” time, when the voltage is stable at 0. On the other hand, when the voltage is changing, the previous equation indicates that ICis nonzero and is directly proportional to Cand to the rate at which the voltage is changing. Note, however, that V and IC relax with the same time constant. To understand the exponential time course, note that Ohm’s law can be used to express the current through the resistor in Figure 16-11A as V/R. If V/R is substituted for IC in the preceding equation, we have

image

We can rearrange the preceding differential equation to solve for V:

image

We can now solve this differential equation to obtain the time course of the decay in voltage:

image

The preceding equation is Equation 6–18 on p. 158 in the text. Thus, the voltage falls exponentially with time. We now return to the first equation and plug in our newly derived expression for V:

image

Thus, the capacitative current decays with the same time constant as does voltage. At time zero, the current is –V0/R, and at infinite time the current is zero.

Contributed by Ed Moczydlowski

Two-Electrode Voltage Clamping

Historically, the technique of two-electrode voltage clamping was first used to analyze the ionic currents in a preparation known as the perfused squid giant axon. Certain nerve fibers of the squid are so large that their intracellular contents can be extruded and the hollow fiber can be perfused with physiological solutions of various ionic composition. Electrodes in the form of thin wires can be inserted into the axon to clamp the axon membrane potential along its length and measure the current. This technique was used by Alan L. Hodgkin and Andrew F. Huxley in 1952 to deduce the nature of ionic conductance changes that underlie the nerve action potential. For this work, Hodgkin and Huxley shared with J. C. Eccles the Nobel Prize in Physiology or Medicine in 1963 (see Web Note 0183a, Alan L. Hodgkin and Andrew F. Huxley). The Hodgkin–Huxley analysis is discussed further in Chapter 7.

Another, more recent, application of the two-electrode voltage clamp technique is called oocyte recording (see Fig. 6–13A on p. 160 in the text). A large oocyte from the African clawed frog, Xenopus laevis, is simultaneously impaled with two micropipette electrodes that serve to clamp the voltage and record current. Native Xenopus oocytes have only small endogenous currents, but they can be induced to express new currents by preinjecting the cell with mRNA transcribed from an isolated gene that codes for an ion channel protein. The oocyte system can therefore be used to characterize the conductance behavior of a relatively pure population of ion channels that are expressed in the plasma membrane after protein translation of the injected mRNA by the oocyte. This approach has proven to be an invaluable assay system for isolating cDNA molecules coding for many different types of channels and electrogenic transporters (see Chapter 5). This approach also has become a standard technique used to study the molecular physiology and pharmacology of ion channels.

Contributed by Ed Moczydlowski

Voltage and Current Transients Due to Membrane Capacitance

In Figure 6-12A on p. 159 in the text (“current clamp”), we instruct the electronics to suddenly increase the current that we are injecting into the cell and to hold this new current at a constant value. The sudden increase in the current flowing through the membrane causes Vm to rise exponentially until we fully charge the membrane capacitance (Cm). Thus, Vm rises with a time constant (see Web Note 0158b, Units for the “Time Constant”) of Rm × Cm (Rm is membrane resistance). At infinite time, the charge on the capacitor is at its maximal value, and all the current flowing through the membrane flows through Rm, the “ohmic” membrane resistance.

In Figure 6-12B in the text (“voltage clamp”), we instruct the electronics to inject enough current into the cell to suddenly increase the membrane potential (Vm) of the cell. The current required to charge the membrane capacitance (Cm) is at first extremely large. However, as we charge the membrane capacitance, that current decays exponentially with a time constant (see Web Note 0158b, Units for the “Time Constant”Rm × Cm. At infinite time, the membrane capacitance is fully charged, and no current is required to hold the command voltage. However, this current decays exponentially, with a time course also determined by the R × C of the membrane.

Contributed by Ed Moczydlowski

Erwin Neher and Bert Sakmann

http://www.nobel.se/medicine/laureates/1991/index.html

Rosette Arrangement of Channel Subunits

The radial arrangement of subunits or domains around a central pore appears to be a common theme of channel structure. Figure 6-17 on p. 172 in the text illustrates that various membrane protein channels can be classified according to whether they are formed from 4, 5, or 6 separate subunits or from a number of subunit-like domains within a single polypeptide. An example of a channel composed of nonidentical subunits is the nicotinic ACh receptor channel. An example of a channel composed of identical subunits is the voltage-gated K+ channel. Thus, such K+ channels have a homotetrameric, symmetric subunit arrangement, whereas the gap junction has a homohexameric structure. Finally, the voltage-sensitive Na+ and Ca2+ channels are examples of channels formed by four internally homologous, nonidentical subunit-like domains within a single large approximately 250-kDa polypeptide α subunit. These latter channels are formed by a pseudo-symmetrical arrangement of four homologous domains, rather than distinct subunits. The voltage-sensitive cation channels are discussed in more detail in Chapter 7. Thus, the major families of channel proteins found in membranes have apparently solved the problem of how to get an ion across a membrane by forming a channel at the central interface of protein subunits or domains.

Contributed by Ed Moczydlowski

The Nicotinic Acetylcholine Receptor

The nicotinic acetylcholine receptors (AChRs), which are all ligand-gated ion channels, come in two major subtypes, N1 and N2. The N1 nicotinic AChRs are at the neuromuscular junction, whereas the N2AChRs are found in the autonomic nervous system (on the postsynaptic membrane of the postganglionic sympathetic and parasympathetic neurons) and in the central nervous system. Both N1 and N2 are ligand-gated ion channels activated by ACh or nicotine. However, whereas the N1 receptors at the neuromuscular junction are stimulated by decamethonium and preferentially blocked by d-tubocurarine and α-bungarotoxin, the autonomic N2 receptors are stimulated by tetramethylammonium, blocked by hexamethonium, but resistant to α-bungarotoxin. When activated, N1 and N2 receptors are both permeable to Na+and K+, with the entry of Na+ dominating. Thus, the nicotinic stimulation leads to rapid depolarization.

The nicotinic AChRs in skeletal muscle and autonomic ganglia are heteropentamers. That is, five nonidentical protein subunits surround a central pore, in a rosette fashion (see Web Note 0165, Rosette Arrangement of Channel Subunits). Because the five subunits are not identical, the structure exhibits pseudo-symmetry rather than true symmetry. There are at least 10 α subunits (α1–α10) and 4 β subunits (β1–β4). The basis for these differences is a difference in subunit composition.

The N1 receptors have different subunit compositions depending on location and developmental stage. The subunit composition of α2βγδ is found in fetal skeletal muscle as well as the nonjunctional regions of denervated adult skeletal muscle. The electric organ of the electric eel (Torpedo), from which the channel was first purified, has the same subunit composition. The subunit composition of α2βγδ is found at the neuromuscular junction of adult skeletal muscle. Here, the subunit replaces the subunit. In both α2βγδ and α2βγδ pentamers, the α subunits are of the α1 subtype and the β subunits are of the β1 subtype.

In the Torpedo N1 AChRs, the α, β, γ, and δ subunits have polypeptide lengths of 437–501 amino acids. The reconstructed longitudinal images of the receptor shown in Figure 6-19 on p. 174 in the text indicate that the whole ACh receptor molecule is approximately 12.5 nm in length. The extracellular end of the receptor appears to protrude approximately 6 nm above the surface of the membrane; there is a similar protrusion of 2 nm at the cytoplasmic side.

The N2 receptors in the nervous system, like those in muscle, are heteromers, probably heteropentamers. N2 receptors use α2–α10 and β2–β4.

Nicotinic receptors

Receptor Type

Agonists

Antagonists

N1 nicotinic ACh

ACh (nicotine decamethonium)

d-Tubocurarine, α-bungarotoxin

N2 nicotinic ACh

ACh (nicotine TMA)

Hexamethonium

Contributed by Ed Moczydlowski

Mutations in Connexin-32 That Cause Charcot–Marie–Tooth Disease

The protein folding diagram of Cx32 in the accompanying figure indicates the locations of six point mutations (in red), as well as a frameshift mutation, that have been observed in certain patients with this disease. (Mutations in other genes besides Cx32 can lead to Charcot–Marie–Tooth disease.)

image

Membrane folding of connexin-32, one of the gap junction proteins. (Data from Bergoffen J, Scherer SS, Wang S, et al.: Connexin mutations in X-linked Charcot–Marie–Tooth disease. Science 262:2039–2042, 1993.)

Contributed by Ed Moczydlowski

Genetic and Autoimmune Ion Channel Defects

Channel

Disease

Etiology

Voltage-gated K+ channels

   

KvLQT1 (old terminology) cardiac K+ channel, also known as KCNQ1

A form of long QT syndrome

Mutation of KCNQ gene on chromosome 11. See box on p. 203 of text.

Cardiac K+ channel (HERG)

A form of long QT syndrome

Mutation. See box on p. 203 of text.

Voltage-gated Na+ channels

   

Skeletal muscle Na+ channel (Nav 1.4)

A form of hyperkalemic periodic paralysis (HYPP)

Mutation of SCN4A gene located on human chromosome 17. See box on p. 195 of text.

Skeletal muscle Na+ channel (Nav 1.4)

Paramyotonia congenita (PC)

Mutation of SCN4A gene located on human chromosome 17. See box on p. 195 of text.

Cardiac muscle Na+ channel (Nav 1.5)

A form of long QT syndrome

Mutation of SCN5A gene located on human chromosome 17. See box on p. 195 of text.

Voltage-gated Ca2+ channels

   

α1S subunit (old terminology) of skeletal muscle L-type Ca2+ channel, also known as Cav 1.1

A form of muscular dysgenesis

Mutation of CACNA1S gene on chromosome 1. See box on p. 200 of text.

Presynaptic (i.e., on motor neuron) Ca2+ channels at neuromuscular junction

Lambert–Eaton syndrome

Autoimmune; most often seen in patients with certain types of cancer, such as small cell lung carcinoma. See box on p. 200 of text.

α1S subunit (old terminology) of skeletal muscle L-type Ca2+ channel, also known as Cav 1.1

A form of hypokalemic periodic paralysis

Mutation of CACNA1S gene on chromosome 1. See box on p. 200 of text.

α1A subunit (old terminology) of P/Q-type Ca2+ channel, also known as Cav 2.1

Familial hemiplegic migraine

Mutation of CACNA1A gene on chromosome 19. See box on p. 200 of text.

α1A subunit (old terminology) of P/Q-type Ca2+ channel, also known as Cav 2.1

Episodic ataxia type-2

Mutation of CACNA1A gene on chromosome 19. Ataxia originating from the cerebellum. See box on p. 200 of text.

Ligand-gated channels

   

N1 nicotinic acetylcholine receptor (nAChR)

Myasthenia gravis

Autoimmune disease attacking the junctional nAChR (α2βimageΔ pentamer (see Web Note 0174a, The Nicotinic Acetylcholine Receptor). See box on p. 231 of text.

Other channels

   

CX32 (Connexin—making up gap junction)

Charcot–Marie–Tooth

Mutation

CFTR

Cystic fibrosis

Mutation. See p. 124 of text for a discussion of the channel, and see box on p. 920 for a discussion of the disease.

β and/or γ subunit of ENaC epithelial Na+ channel

Liddle disease

Gain-of-function mutation due to defective endocytosis of ENaC channels on the apical membrane. See p. 786 of text for a discussion of the channel. For a discussion of the disease, see Web Note 0874, Liddle Disease.

Contributed by Ed Moczydlowski

Voltage-Gated Channels

Some families of channel proteins are so large and diverse that they are known as superfamilies. For example, the superfamily of voltage-gated channels consists of K+, Na+, and Ca2+ channels, respectively denoted KV, NaV, and CaV channels that have a common structural motif (see p. 189 in the text). These channels play a primary role in electrical signaling in the nervous system, where they underlie the voltage-dependent depolarization (NaV and CaV) and hyperpolarization (KV) of propagating action potentials (discussed in Chapter 7). The pore-forming complex of each of these channels consists of four subunits or domains, each of which contains six transmembrane segments denoted as S1–S6. Voltage-gated K+ channels are believed to represent an evolutionary precursor to NaV and CaV channels because their pore-forming subunit contains only one S1 through S6 domain (see Fig. 6–21B). Voltage-gated K+ channels are homotetramers or heterotetramers of monomer subunits. The pore-forming subunits of Na+and Ca2+ channels (Figs. 6–21J and 6–21K) both comprise four domains (I–IV), each of which contains the S1 through S6 structural motif that is homologous to the basic voltage-gated K+ channel subunit or monomer. Because domains I–IV of NaV and CaV channels are organized as four tandem repeats within the membrane, these domains are referred to as pseudosubunits. The molecular evolution of the four-repeat structure of NaV and CaV channels is believed to have occurred by a process involving consecutive gene duplication from a primordial gene containing S1 through S6. Members of the voltage-gated superfamily of channels are also recognized by a characteristic structure of the S4 transmembrane segment in which four to seven positively charged residues (lysine or arginine) are located at every third position. This unique S4 domain appears to function as the voltage-sensing element of voltage-gated ion channels (see p. 190 of the text).

Voltage-gated Ca2+ channels also illustrate another feature of some ion channels: They are multisubunit complexes consisting of accessory proteins in addition to the channel-forming subunits. For example, CaVchannels are composed of a large pseudotetrameric α1 subunit with domains I–IV that form the pore, plus four additional structurally unrelated subunits known as α2, β, γ, and Δ (see Fig. 6–21K). Like the homologous α subunit of NaV channels, the large 1 subunit of CaV channels specifies most of the basic channel functions, including ionic selectivity, voltage sensitivity, and the binding sites of various drugs. It appears that the β, γ, and δ subunits are important for modulating the activity of Ca2+ channels, but their exact functional roles are largely unknown. In some cases, accessory subunits modulate the gating activity and pharmacology of channel complexes, whereas in other cases such accessory subunits of channels may help target newly synthesized channels to their proper cellular locations.

Contributed by Ed Moczydlowski

Structure of ClC Channels

Rod MacKinnon and his group solved the X-ray structure of a ClC-type Cl channel from Escherichia coli and Salmonella (see first paper below), and they have also studied the basis for the channel’s Clselectivity (see second paper).

REFERENCE

Dutzler R, Campbell EB, Cadene M, Chait BT, and MacKinnon R: X-ray structure of a ClC chloride channel at 3.0 Å reveals the molecular basis of anion selectivity. Nature 415:287–294, 2002.

Dutzler R, Campbell EB, and MacKinnon R: Gating the selectivity filter in ClC chloride channels. Science 300:108–112, 2003.

Contributed by Emile Boulpaep and Walter Boron

Rheobase and Chronaxie

Figure 7-3A on p. 182 in the text shows a strength–duration curve for nerve or muscle. As the duration of a stimulus increases, the minimum intensity of stimulation required to elicit an action potential decreases. The rheobase is the minimum intensity of stimulation required to generate an action potential when the stimulation is of infinite duration (i.e., the horizontal dashed line in Fig. 7–3A). Stimuli greater than the rheobase require shorter times. When the stimulus is twice the rheobase, the minimum duration required to achieve an action potential is the chronaxie.

Contributed by Emile Boulpaep and Walter Boron

Alan L. Hodgkin and Andrew F. Huxley

http://www.nobel.se/medicine/laureates/1963/index.html

Two-Electrode Voltage Clamping

Historically, the technique of two-electrode voltage clamping was first used to analyze the ionic currents in a preparation known as the perfused squid giant axon. Certain nerve fibers of the squid are so large that their intracellular contents can be extruded and the hollow fiber can be perfused with physiological solutions of various ionic composition. Electrodes in the form of thin wires can be inserted into the axon to clamp the axon membrane potential along its length and measure the current. This technique was used by Alan L. Hodgkin and Andrew F. Huxley in 1952 to deduce the nature of ionic conductance changes that underlie the nerve action potential. For this work, Hodgkin and Huxley shared with J. C. Eccles the Nobel Prize in Physiology or Medicine in 1963 (see WebNote “2e-0183a--Alan L Hodgkin & Andrew F Huxley (1e-0176b).doc). The Hodgkin–Huxley analysis is discussed further in Chapter 7.

Another, more recent, application of the two-electrode voltage-clamp technique is called oocyte recording (Figure 6-13A on p. 160 in the text). A large oocyte from the African clawed frog, Xenopus laevis, is simultaneously impaled with two micropipette electrodes that serve to clamp the voltage and record current. Native Xenopus oocytes have only small endogenous currents, but they can be induced to express new currents by preinjecting the cell with mRNA transcribed from an isolated gene that codes for an ion channel protein. The oocyte system can therefore be used to characterize the conductance behavior of a relatively pure population of ion channels that are expressed in the plasma membrane after protein translation of the injected mRNA by the oocyte. This approach has proven to be an invaluable assay system for isolating cDNA molecules coding for many different types of channels and electrogenic transporters (Chapter 5). This approach also has become a standard technique used to study the molecular physiology and pharmacology of ion channels.

Contributed by Ed Moczydlowski

Ohmic I–V Curve

According to Ohm’s law (I = V/R), the I–V relationship is a straight line if 1/R (i.e., the conductance) is constant. The slope is positive. For a simple electrical circuit consisting of a resistor and a voltage source, the line passes through the origin (i.e., I = 0 when V = 0). However, if the Na+ current (INa) were ohmic (i.e., we assume that the [Na+] is the same on both sides of the membrane), INa is zero when the driving force (Vm – ENa) is zero (see Equation 7–2 on p. 185 of the text). Therefore, the I–V plot for a Na+ current passes through the x axis at the equilibrium potential for Na+ (ENa).

In real-life situations, the I–V curve for Na+ currents is much more complicated, following the GHK current equation, as discussed in Web Note 0154b, Shape of the I–V Relationship.

Contributed by Ed Moczydlowski

Boltzmann Distribution of Voltage-Dependent Gating for Ion Channel Proteins

If a channel can exist only in a closed or open conformation, the sum of the channel’s open probability (Po) and closed probability (Pc) must be 1 so that the equilibrium constant Keq is

Equation 1

image

The first two equalities in the above equation are the same as Equation 7–3 on p. 185 in the text.

According to statistical mechanics, the relative probability that the channel is in the open versus the closed state (Po/Pc) is determined by the difference in free energy (ΔG) between the open state (Go) and the closed state (Gc) of the channel. By applying the Boltzmann distribution law of physical chemistry, we find that

Equation 2

image

Here, kB is the Boltzmann constant (1.381 × 10-23 J K-1), and T is the absolute temperature. According to Equation 2, when half of the channels are open and half are closed (i.e., Po = 0.5 and Po/Pc = 1), ΔGmust be zero. In other words, if the energy of the open state is the same as the energy of the closed state, there should be an equal number of channels in each state. The free energy ΔG for opening a voltage-gated channel may be thought of as a sum of two terms, a chemical free energy difference (ΔGchem) and an electrical free energy difference (ΔGelec). The ΔGchem term describes the difference in free energy between the open and closed conformational states of a single channel protein in the absence of an applied electric field. The ΔGelec term describes the energy expended when an electrically charged portion of the channel protein molecule is moved by the electric field as the channel opens. Thus, the total change in free energy for opening a voltage-gated channel is the sum of the chemical and electrical terms:

Equation 3

image

Note that this equation is similar to Equation 5–6 on p. 111, which we introduced to describe the electrochemical potential difference (i.e., image) for a mole of ions X (see Web Note 0110, Electrochemical Potential). The difference is that, here, we are applying Equation 3 to a single channel molecule. We saw in Chapter 5 that the electrical term for a mole of X is the product z F Vm, where z is the valence and Fis the charge on a mole of particles. Likewise, the electrical term ΔGelec for a single molecule is the product of the valence (z) of the moving portion of the channel protein (the “voltage sensor”), the elementary charge (e0 = 1.602 × 1019 coulomb), and the applied membrane voltage, Vm. Thus,

Equation 4

image

Note that ze0Vm is the energy required to move the charge of the channel’s voltage sensor across the electric field of the whole membrane.

In deriving an expression for Po, it is helpful to express ΔGchem in electrical terms. As noted above, when half the channels are open and half are closed (i.e., Po = Pc = 0.5), ΔG is zero. Equation 4 thus becomes

Equation 5

image

Here, V0.5 is the voltage at which Po is 0.5. Combining Equation 4 and Equation 5, we have

Equation 6

image

Equation 6 may be substituted into Equation 2 and rearranged to yield the following expression for the dependence of opening probability on voltage:

Equation 7

image

The preceding equation appears in the textbook as the inset to Figure 7-7B on p. 188.

Contributed by Ed Moczydlowski

Classical Hodgkin–Huxley Model of the Action Potential

The Hodgkin–Huxley (HH) analysis follows basic principles similar to the simple two-state (i.e., closed–open) model of single-channel gating described in Equation 7–3 on p. 185 of the text. The HH analysis provides a description of macroscopic currents for Na+ (INa) and K+ (IK) but relates these macroscopic currents not to single-channel currents but to the maximal conductance of the membrane to Na+ (image) or K+ (image). In the single-channel/Boltzmann model (see Web Note 0185b, Boltzmann Distribution of V-Dependent Gating), these maximal conductances would be achieved when Po is 1. Thus, image or image would be the product of the single-channel conductance (gNa or gK) and the number of open channels (N). In the HH analysis, the probability of observing the maximal conductance is described by three empirical, voltage-sensitive parameters—m and h for the Na+ conductance and n for the K+conductance. Like Po in the single-channel/Boltzmann model, m, h, and n vary between 0 and 1. The original HH equations for macroscopic K+ and Na+ current are

Equation 1

image

Equation 2

image

Here, Vm is the membrane potential, EK is the equilibrium potential for K+, and ENa is the equilibrium potential for Na+.

Hodgkin and Huxley used the parameter n to describe the probability (which varies from 0 to 1) that an activating “particle” or gate is in a permissive configuration for K+ channel opening. However, they found it necessary to use the fourth power of n to account for the sigmoid-shaped time dependence (or lag phase) for K+ current activation. The molecular interpretation of this n4 dependence is that four independent activation (or gating) particles must be in a permissive state for a single channel to open.

Similarly, the m3 parameter in Equation 2 is the probability of Na+ channel opening. In molecular terms, this m3 dependence states that three independent gating particles must be in a permissive configuration for opening to occur. In order to account for the inactivation phase of the Na+ current, Hodgkin and Huxley proposed that the channel has a separate inactivation gate described by the parameter h in Equation 2. The h parameter is defined as the probability (from 0 to 1) that the channel is not inactivated. Thus, when m and h are both 1, the current is maximal.

The n, m, and h probability parameters of the HH model depend on Vm according to a Boltzmann distribution function such as that in Web Note 0185b, Boltzmann Distribution of V-Dependent Gating. The green curve in Figure 7-8A on p. 189 shows the steady-state dependence of the n parameter (which governs image) on Vm, as derived by Hodgkin and Huxley. Because this parameter is measured at infinite time, it is represented as nFigure 7-8B shows the same for the two steady-state parameters that govern imagem (blue curve) and h (red curve). The dependence of n and m on Vm determines the voltage range for activation of the K+ and Na+ currents, respectively. The hparameter for inactivation of the Na+ current spans a voltage range that is more negative than activation described by the m parameter. Thus, any voltage capable of activating the Na+ channel also promotes inactivation. The reason Na+ channels are able to open first, before closing, is that once a depolarization is initiated, activation occurs faster than inactivation. (Note that the m and h parameters describe m and h at infinite time and make no statement about how rapidly m reaches m or h reaches h.)

In their analysis of the squid axon action potential, Hodgkin and Huxley modeled the axon membrane as an equivalent electrical circuit that included image and image—which we have just discussed—as well as a leak component (image)—which corresponds to unspecified ohmic background conductance attributable to other types of K+ channels and Cl channels—and a membrane capacitance (Cm). The HH theory predicts that the total membrane current (Im) is a sum of the capacitative current and the various ionic currents (see Equation 6–19 on p. 159 in the text). For the HH model,

Equation 3

image

Hodgkin and Huxley used this equation to predict the shape of the action potential in the squid giant axon. A comparison of their prediction (see Fig. 7–8C) with an actual record of an action potential from the squid giant axon (see Fig. 7–8D) shows that their theory does a very good job of describing this phenomenon.

Contributed by Ed Moczydlowski

Evidence for Gating Currents

Two groups of investigators, working on two different preparations, nearly simultaneously discovered the gating currents predicted two decades earlier by Alan Hodgkin and Andrew Huxley. In a paper published in March 1973, Martin Schneider and W. Knox Chandler demonstrated the presence of a gating current for Na+ channels in frog skeletal muscle. In a paper published in April 1973, Clay Armstrong and Pancho Bezanilla demonstrated the presence of a gating current for Na+ channels in squid giant axons.

REFERENCE

Armstrong CM, and Bezanilla F: Currents related to movement of the gating particles of the sodium channels. Nature 242:459–461, 1973.

Schneider MF, and Chandler WK: Voltage dependent charge movement of skeletal muscle: A possible step in excitation-contraction coupling. Nature 242:244–246, 1973.

Contributed by Emile Boulpaep and Walter Boron

Electroplax Organ of the Electric Eel

The electroplax organ of the electric eel (Electrophorus electricus) is composed of specialized cells called electrocytes that are an evolutionary adaptation of skeletal -muscle cells. The innervated membrane face of the electrocytes contains a high density of both nicotinic acetylcholine receptors and voltage-gated Na+ channels. Thus, this tissue is a rich source of both proteins. Indeed, for both proteins, this tissue played a key role in the purification, biochemical characterization, reconstitution into lipid membranes, and physiological characterization.

Contributed by Ed Moczydlowski

Roderick MacKinnon

http://nobelprize.org/chemistry/laureates/2003/index.html

Crystal Structure of the KcsA K+ Channel

In 1998, the laboratory of Roderick MacKinnon at Rockefeller University used X-ray diffraction to solve the three-dimensional crystal structure of a membrane protein known as KcsA. KcsA is the protein product of a gene from the actinomycete bacterium Streptomyces livdans. KcsA is homologous to the S5-P-S6 region of the Shaker K+ channel and is known to function as a K+ channel in planar bilayer membranes. KcsA lacks the S1–S4 voltage-sensing region, and it consists of a pore-forming domain equivalent to that of the vertebrate inward rectifier K+ channel gene family (KIR). As is the case for the Shaker-type K+ channels, KcsA is a homotetramer. The P-region sequence of KcsA is very similar to the P region of the Shaker K+ channel, which contains amino acid residues critical for K+ selectivity, as well as extracellular sensitivity to blockade by tetraethylammonium and charybdotoxin. The accompanying Figure 1 shows a ribbon diagram representation of the structure of KcsA, in one view looking down from the top of the membrane (Fig. 1A) and in a second view looking from the side (Fig. 1B). Each of the four monomer subunits of the protein is shown in a different color. Starting from the intracellular N-terminus, the first transmembrane span (“outer helix,” corresponding to Shaker S5) forms an helix that serves as the periphery of the channel. After crossing the membrane to the extracellular side, the peptide backbone then forms a loop that corresponds to the P region. The first half of this loop is a short helix that folds back a short distance into the plane of the membrane and then immediately exits the extracellular side of the membrane. In the tetrameric complex that constitutes the channel protein, this latter portion of the P loop forms a narrow tunnel-like region called the ion selectivity filter. After exiting the extracellular face of the membrane, the peptide backbone turns again to form a third helix (“inner helix,” corresponding to Shaker S6) that crosses the membrane to the intracellular side. The four inner helices of the tetramer form the scaffold of the ion channel pore. These four inner helices are tilted in a remarkable flower-like configuration that has also been compared to four poles of an inverted teepee tent dwelling.

The KcsA structure reveals the molecular basis for K+ selectivity of K+ channel pores. The selectivity filter region is lined not by the side chains of amino acids but, rather, by four rings of carbonyl oxygen atoms contributed by the peptide backbone of four amino acid residues in the P region. K+ ions in the 12 Å long selectivity filter (near the extracellular surface of the channel) are bound in a cage by coordination to oxygen atoms contributed by each of the four subunits. The size of this cage is just the right size for a K+ ion. A smaller Na+ ion would fit too loosely, so its binding in the cage would not be energetically favorable in comparison to its binding to water in its normal hydrated state. Figure 1C is a cutaway surface view of the pore showing the location of three K+ ions in the crystal structure. Up to seven distinct binding sites for K+ have been identified in high-resolution studies of the KcsA pore. The presence of multiple K+ ions in the pore is consistent with the results of many electrophysiologic studies, which suggested that multiple K+ ions move through the channel in single file.

For his work on the structural biology of ion channels, Roderick MacKinnon shared the 2003 Nobel Prize in Chemistry.

image

Figure 1. Structure of the Streptomyces K+ channel (KcsA). A, KcsA is a homotetramer. Each monomer is represented in a different color and contains only two membrane-spanning elements, which is analogous to the S5-P-S6 portion of Shaker-type K+ channels. B, This view more clearly shows the P region, which is very similar to the P region of the Shaker K+ channel. The P region appears to form the selectivity filter of the channel. C, This is a cutaway view of the pore that shows three K+ ions. The top two K+ ions are bound in a tight cage that is formed by the peptide backbones of the P regions of each of the four channel subunits. (Data from Doyle DA, Morais Cabral J, Pfuetzner RA, et al.: The structure of the potassium channel: Molecular basis of K+ conduction and selectivity. Science 280:69–77, 1998.)

Contributed by Ed Moczydlowski

Effects of μ-Conotoxin

μ-Conotoxin is a specific blocker of the subtype of voltage-gated Na+ channels that are present in adult skeletal muscle. This conclusion can be verified by performing a simple electrophysiological experiment on a “nerve–muscle” preparation consisting of a motor nerve and the attached skeletal muscle fibers. The approach is to record the membrane potential of a muscle fiber membrane while artificially stimulating the preparation with a brief electrical depolarization applied either to the nerve or directly to the muscle. In a normal preparation, either stimulus is able to evoke a muscle action potential. However, in a preparation exposed to μ-conotoxin, one observes no response when stimulating the muscle fiber directly but observes a graded postsynaptic potential in the endplate region when stimulating the nerve directly. This latter response demonstrates that μ-conotoxin does not affect either the motor nerve or the neuromuscular junction (e.g., the nicotinic acetylcholine receptor at the motor endplate).

Contributed by Ed Moczydlowski

Erythromelalgia

Certain defects in human gene SCN9A, which encodes the peripheral nerve Na+ channel Nav1.7, result in a variety of syndromes that alter pain perception. The absence of functional expression of this channel by nonsense mutation results in complete insensitivity to pain. Various single amino acid replacements due to missense mutations of the channel gene result in gain-of-function syndromes that result in heightened and severe sensitivity to pain known as primary erythromelalgia (from the Greek erythros [red] + melos [limb] + algos [pain]; see http://en.wikipedia.org/wiki/Erythromelalgia) and paroxysmal extreme pain disorder. These findings suggest that Nav1.7 may be a good target for discovery of new drugs in the treatment of pain.

REFERENCE

Drenth JPH, and Waxman SG: Mutations in sodium-channel gene SCN9A cause a spectrum of human genetic pain disorders. J Clin Invest 117:3606–3609, 2007.

Fischer TZ, Gilmore ES, Estacion M, Eastman E, Taylor S, Melanson M, Dib-Hajj SD, and Waxman SG: A novel Nav1.7 mutation producing carbemazepine-responsive erythromelalgia. Ann Neurol 65:733–741, 2009.

Contributed by Ed Moczydlowski

Hyperpolarization by Activation of GIRKs

Although Kir channels pass current better in the inward than the outward direction, the membrane potential (Vm) is typically never more negative than EK. Thus, net inward K+ current does not occur physiologically. As a result, the activation of GIRK channels hyperpolarizes cardiac cells by increasing K+ conductance or outward K+ current.

Contributed by Ed Moczydlowski

Charge Separation Required to Generate the Membrane Potential

To generate a membrane potential, there must be a tiny separation of charge across the membrane. How large is that charge? Imagine that we have a spherical cell with a diameter of 10 μm. If [K+]i is 100 mM and [K+]o is 10 mM, the Vm according to the Nernst equation would be –61.5 mV (or 0.0615 V) for a perfectly K+-selective membrane at 37°C. What is the charge (Q) on 1 cm2 of the “plates” of the membrane capacitor? We assume that the specific capacitance is 1 μF/cm2. From Equation 6–13 on p. 157 in the text, we know that

Q = CV

where Q is measured in coulombs (C), C is in farads (F), and V is in volts (V). Thus,

Q = (1 × 10-6 F cm–2) × (0.0615 V)

= 61.5 × 10–9 C cm-2

As described in Web Note 0157a, Charge Carried by a Mole of Monovalent Ions, the Faraday is the charge of 1 mole of univalent ions—or 96,480 C. To determine how many moles of K+ we need to separate in order to achieve an electrical charge of 61.5 × 10–9 C cm–2 (i.e., the Q in the previous equation), we merely divide Q by the Faraday. Because Vm is negative, the cell needs to lose K+:

image

The surface area for a spherical cell with a diameter of 10 μm is 3.14 × 10–6 cm2. Therefore,

image

The volume of this cell is 0.52 × 10–12 L. Given a [K+]i of 100 mM,

Total K+ content of cell = (0.1 mole/L) × (0.52 × 10–12 L)

= 0.52 × 10–13 moles

What fraction of the cell’s total K+ content represents the charge separated by the membrane?

image

Thus, in the process of generating a Vm of –61.5 mV, our hypothetical cell needs to lose only 0.004% of its total K+ content to charge the capacitance of the cell membrane.

Contributed by Ed Moczydlowski

Resistance and Capacitance Units for Cable Properties

The purpose of this web note is to justify the units given in the first four rows of Table 7–3 on p. 210 of the text. Our approach is to present these four electrical units per unit length of axon and then to show how these units make sense when we calculate the resistance or capacitance of an entire axon.

The longitudinal resistances of the intracellular fluid (ro) and extracellular fluids (ri) are expressed in units of ohm/cm. In each case, we can think of the total resistance of either the intra- or extracellular fluid as being the resistance of a stack of resistors in series—each resistor representing 1 cm of fluid length along the axis of the cable. Thus, the total resistance of either the intra- or extracellular fluid (ohm) increases in proportion to increasing fiber length (cm), and the proportionality factor is the longitudinal resistance of each of the N segments (in ohm/cm):

Total Resistance = (Individual Resistance) × N

Because each N is in fact 1 cm,

image

The transverse membrane resistance (rm) is expressed in the units ohm × cm. We can think of the total resistance of the membrane as being the resistance of a stack of resistors in parallel—each resistor representing the membrane resistance of a segment of axon that is 1 cm long. Because the N resistors are arranged in parallel,

image

Rearranging,

image

Finally, inserting the units for the individual resistance, and realizing that each N is in fact 1 cm,

image

One way to think of this is that a longer section of axon membrane has more channels, a greater total conductance, and thus a lower total resistance.

The membrane capacitance (cm) has units μF/cm. We can think of the total capacitance of the membrane as being the capacitance of a stack of capacitors in parallel—each capacitor representing the membrane capacitance of a segment of axon that is 1 cm long. Because the N capacitors are arranged in parallel,

Total Capacitance = (Individual Capacitance) × N

Because each N is in fact 1 cm,

image

Thus, just as longitudinal resistances in series summate, membrane capacitances in parallel summate; both are thus expressed per unit length.

Contributed by Emile Boulpaep and Walter Boron

Units of “Length Constant”

In our discussion of cable properties in the textbook, we presented Table 7–3 on p. 210, which summarizes the units of cable parameters in two ways: (1) resistance per unit length (top three rows in Table 7–3) and (2) specific resistance (rows 5 and 6 in Table 7–3).

Resistance per unit length. In the textbook, we presented Equation 7–6 on p. 210:

image

This equation uses resistance per unit length. If we substitute the appropriate units from Table 7–3 into this equation, we obtain

image

Thus, the length constant has units of distance (cm).

Specific resistance. In the textbook, we presented Equation 7–8 on p. 210:

image

This equation uses specific resistance. If we substitute the appropriate units from Table 7–3 into the preceding equation, we obtain

image

Thus, the length constant again has units of distance (cm).

Contributed by Emile Boulpaep and Walter Boron

Sir Henry H. Dale and Otto Loewi

http://www.nobel.se/medicine/laureates/1936/index.html

Tubocurarine

See the following link:

http://www.portfolio.mvm.ed.ac.uk/studentwebs/session2/group12/tubocura.htm

Two-Electrode Voltage Clamping

Historically, the technique of two-electrode voltage clamping was first used to analyze the ionic currents in a preparation known as the perfused squid giant axon. Certain nerve fibers of the squid are so large that their intracellular contents can be extruded and the hollow fiber can be perfused with physiological solutions of various ionic composition. Electrodes in the form of thin wires can be inserted into the axon to clamp the axon membrane potential along its length and measure the current. This technique was used by Alan L. Hodgkin and Andrew F. Huxley in 1952 to deduce the nature of ionic conductance changes that underlie the nerve action potential. For this work, Hodgkin and Huxley shared with J. C. Eccles the Nobel Prize in Physiology or Medicine in 1963 (see Web Note 0183a, Alan L. Hodgkin and Andrew F. Huxley). The Hodgkin–Huxley analysis is discussed further in Chapter 7.

Another, more recent, application of the two-electrode voltage clamp technique is called oocyte recording (see Fig. 6–13A on p. 160 in the text). A large oocyte from the African clawed frog, Xenopus laevis, is simultaneously impaled with two micropipette electrodes that serve to clamp the voltage and record current. Native Xenopus oocytes have only small endogenous currents, but they can be induced to express new currents by preinjecting the cell with mRNA transcribed from an isolated gene that codes for an ion channel protein. The oocyte system can therefore be used to characterize the conductance behavior of a relatively pure population of ion channels that are expressed in the plasma membrane after protein translation of the injected mRNA by the oocyte. This approach has proven to be an invaluable assay system for isolating cDNA molecules coding for many different types of channels and electrogenic transporters (see Chapter 5). This approach also has become a standard technique used to study the molecular physiology and pharmacology of ion channels.

Contributed by Ed Moczydlowski

Contribution of Ca2+ to the Resting Membrane Potential

Equation 6–9 on p. 155 of the text is the Goldman–Hodgkin–Katz voltage equation, which we reproduce here:

image

Of course, we could insert additional terms for other cations besides K+ and Na+. For example, if we included Ca2+, the equation would look something like the following:*

image

A typical value for [Ca2+]i would be 10–7 M or 0.0001 mM, and a typical value for [Ca2+]o would be 1.2 mM. Thus, even though the concentration ratio for Ca2+ across the plasma membrane is large, this ratio per se has no bearing on the GHK equation. What counts here are the magnitudes of the product PCa[Ca2+], which are generally small compared to the other terms in both the numerator and the denominator. Thus, Ca2+ makes very little contribution to Vmin the resting state. However, if we were to reduce the size of the other terms in either the numerator or the denominator, the Ca2+ would begin to matter.

Inspired by Dr. Jack Rose, Idaho State University

Contributed by Emile Boulpaep and Walter Boron

* The GHK equation has dropped the z (valence) term, as if all ions were monovalent. In order to insert Ca2+ into this simple equation, we treat the ion as if it were monovalent, which is clearly not the case. Thus, this equation merely serves to make the point that Ca2+ contributes very little to Vm because of the small magnitude of the product of permeability and concentration.

Ligand Binding Sites of the Nicotinic Acetylcholine Receptors

New insight into the molecular details of the extracellular agonist-binding domain of AChR has been obtained from the X-ray crystal structure of an acetylcholine binding protein (AChBP) from Lymnaea stagnalis, a freshwater snail. AChBP is a soluble protein of 229 residues that is homologous to the amino-terminal region of nicotinic AChR and other members of the pentameric ligand-gated channel superfamily. As shown in Figure 3 of the paper by Brejc et al., the crystal structure shows that AChBP is formed as a radially symmetric homopentamer of the monomer subunit with the agonist binding site located between the five subunit interfaces. The tertiary structure of a single monomer subunit of AChBP features 10 β strands folded into a β sandwich. The snail AChBP specifically binds many of the same agonist and antagonist and antagonist molecules as AChR, including ACh, carbamylcholine, nicotine, d-tubocurarine, and α-bungarotoxin. AChBP serves as a particularly good homology model for the structure of nicotinic receptors in the mammalian nervous system that are formed as homopentamers of-subunits.

REFERENCES

Brejc K, van Dijk, WJ, Klaassen, RV, Schuurmans M., van der Oost J, Smit AB, and Sixma TK: Crystal structure of an ACh-binding protein reveals the ligand-binding domain of nicotinic receptors. Nature411:269–276, 2001.

Celie PHN, van Rossum-Fikkert SE, van Dijk WJ, Brejc K, Smit AB, and Sixma TK: Nicotine and carbamylcholine binding to nicotinic acetylcholine receptors as studied in AChBP crystal structures. Neuron41:907–914, 2004.

Contributed by Ed Moczydlowski

Quantal Nature of Transmitter Release

The quantal nature of transmitter release can be expressed quantitatively by postulating that a nerve terminal contains a population of N quanta or vesicles, and that each has a finite probability (P) of releasing under any given set of conditions. Thus, the mean number (m) of quanta released after any single nerve impulse is

Equation 1

image

No. of quanta (x)

No. of events observed (nx)

Probability observed

Probability predicted

0

18

0.091

0.100

1

44

0.222

0.231

2

55

0.278

0.265

3

36

0.182

0.203

4

25

0.126

0.117

5

12

0.061

0.054

6

5

0.025

0.021

7

2

0.010

0.007

8

1

0.005

0.002

Figure 8-12B on p. 225 in the textbook illustrates the results of an experiment very similar to that shown in Figure 8-12A, except that the investigators—Boyd and Martin—repeated the nerve stimulation 198 times, rather than the 7 times in Figure 8-12A. In each case, Boyd and Martin recorded the magnitude of the MEPP and placed it into a “bin” that was 0.1 mV wide. Thus, if they observed a MEPP of 1.23 mV, they placed it into the 1.2 bin. Figure 8-12B, a histogram summarizing the results of the 198 nerve evoked responses, shows a series of peaks. The peak at 0 mV corresponds to the 18 trials in which the nerve stimulus evoked no end plate potential. The peaks labeled I, II, III, etc. correspond to MEPPs that are multiples of the unit event—which is 0.4 mV—at amplitudes of 0.4, 0.8, 1.2 mV, etc. Thus, peak I corresponds to 1 quantum released, peak II corresponds to 2 quanta released, and so on.

If we sum up all the MEPPs in the 198 trials, we see that the total change in Vm was 184 mV. Dividing by 198 produces the mean amplitude of the MEPPs, 0.93 mV. If we assume a unitary response of 0.4 mV, 0.93 mV corresponds to 2.3 quanta, which is the m in Equation 1. Thus, on average, a nerve impulse produces a MEPP of 0.93 mV, which corresponds to the release of 2.3 quanta. However, in any given nerve impulse, the actual MEPP—if we could measure it with perfect accuracy—must correspond to an integral number of quanta released (x = 0, 1, 2, 3, …). Of course, because of noise and inaccuracies in the measuring system, Boyd and Martin also measured MEPPs that corresponded to nonintegral numbers of quanta. The y axis in Figure 8-12B gives the number of times Boyd and Martin observed a given MEPP out of the total of 198 observations. The seven bell-shaped or Gaussian curves in Figure 8-12B represent the probability of releasing 1–7 quanta.

Because each bin is 0.1 mV wide, and because the unitary MEPP is 0.4 mV, Boyd and Martin added up 0.4/0.1 or four consecutive bins to obtain the number of observations (nX) corresponding to the release of x quanta, out of the total of 198 observations (ntotal). For example, for x = 0 quanta, n0 was 18; for x = 1 quantum, n1 was 44; the second column in Table 1 in this Web Note gives the number of events observed (nx) for each number of quanta “x” (listed in the first column). The probability (px) that we saw x quanta being released after a single nerve impulse is

Equation 2

image

Thus, for x = 0, p0 would be 18/198 or 0.091; for x = 1, p1 would be 44/198 or 0.222; the other values are given in column 3 of Table 1.

How do these observed values agree with those predicted by probability theory? Probability theory predicts that pX should follow a Poisson distribution:

Equation 3

image

Note that m in this equation is once again the mean number of quanta released per nerve impulse—2.3 in our example. This theory assumes that the underlying probability of vesicle release (P in Equation 1) is very small and that the population of replenishable vesicles (N in Equation 1) is very large. The last column of Table 1 shows that the pX predicted by Equation 3 is very nearly the same as the observed pX for each number of quanta.

We can also check the agreement of the data with the theory by testing whether the observed number of blank records (0-mV events) can predict the mean number (m) of quanta released after any single nerve impulse. According to Equation 3, when x = 0,

Equation 4

image

or

In p0 = -m

Because p0 is 18/198 or 0.091, the m value that we compute from Equation 4 is 2.4 quanta. This value is very close to the measured mean of 2.3 quanta. Findings such as these have provided strong support for the quantal theory of neurotransmitter release at the neuromuscular junction.

REFERENCE

Boyd IA, and Martin AR: The end-plate potential in mammalian muscle. J Physiol 132:74–91, 1956.

Contributed by Ed Moczydlowski

Sir Bernard Katz

http://www.nobel.se/medicine/laureates/1970/index.html

Modulation of Quantal Release

As discussed in Web Note 0224a, Quantal Nature of Transmitter Release, the quantal nature of transmitter release can be expressed quantitatively by postulating that a nerve terminal contains a population of Nquanta or vesicles, and that each has a finite probability (P) of releasing under any given set of conditions. Thus, the mean number (m) of quanta released after any single nerve impulse is

Equation 1

image

As noted in the textbook, facilitation is a short-lived enhancement of the postsynaptic potential in response to a brief increase in the frequency of nerve stimulation. One way facilitation may occur is by a transient increase in the mean number of quanta per nerve stimulus, corresponding to an increase in the m parameter of Equation 1.

Potentiation is a long-lived and pronounced increase in transmitter release that occurs after a long period of high-frequency nerve stimulation. This effect can last for minutes after the conditioning stimulus. Potentiation may be caused by a period of intense nerve firing, which increases [Ca2+]i in the presynaptic terminal and thus increases the probability of exocytosis (the P parameter in Equation 1).

Synaptic depression is a transient decrease in the efficiency of transmitter release and, consequently, a reduction in the postsynaptic potential, in response to a period of frequent nerve stimulation. Depression may result from a temporary depletion of transmitter-loaded vesicles from the presynaptic terminal—that is, a reduction in the number of available quanta, corresponding to the parameter N in Equation 1.

Thus, these three temporal changes in synaptic strength and efficiency appear to reflect changes at different steps of synaptic transmission. Similar modulation of synaptic strength in the central nervous system provides a mechanistic paradigm for understanding how individual nerve terminals may “learn.”

Contributed by Ed Moczydlowski

“SNAP” Nomenclature

Unfortunately, SNAP means different things to different people: “SNAP” in SNAP-25 means “synaptosomes associated protein 25,” and “SNAP” in α-SNAP means “soluble NSF-attachment protein.”

Contributed by Emile Boulpaep and Walter Boron

“SNAP” Nomenclature

Unfortunately, SNAP means different things to different people: “SNAP” in SNAP-25 means “synaptosomes associated protein 25,” and “SNAP” in α-SNAP means “soluble NSF-attachment protein.”

Contributed by Emile Boulpaep and Walter Boron

Acetylcholinesterase

The acetylcholinesterase enzyme is an ellipsoidal globular protein, approximately 4.5 × 6.0 × 6.5 nm. It includes a central 12-stranded β-sheet surrounded by 14--helical segments. The active site of the enzyme is composed of three residues (Ser200, His440, and Glu327) located on different loops. These residues are analogous to the Ser-His-Asp catalytic triad of serine proteases such as trypsin and chymotrypsin. This similarity is an example of convergent evolution, inasmuch as there is little structural similarity between the two types of enzymes. A unique aspect of the structure of AChE is that the active site of ACh hydrolysis is located at the bottom of a 2.0-nm-deep gorge (the active site gorge) that the substrate must enter by diffusion from the surface of the protein. The three-dimensional structure of the catalytic subunit of AChE from the electric ray, Torpedo californica, has been solved by X-ray crystallography.

In the first step of the enzymatic reaction (see Equation 8–5 on p. 230 of the text), the H from the hydroxyl of Ser200 becomes attached to the oxygen in the ester linkage of ACh, resulting in the formation of choline and a tetrahedral acyl-enzyme intermediate at Ser200.

In the second step of Equation 8–5, the hydrolysis of the acyl-enzyme yields acetate and the free enzyme.

Contributed by Ed Moczydlowski

Blockade of Muscle Na+ Channels

An action potential is not only the first but also the last step in transmission at the neuromuscular junction: The production of an action potential in the muscle fiber membrane signals the successful completion of synaptic transmission. Action potentials, including those in muscle, can be blocked by TTX and STX. Selective blockade of the muscle action potential can be achieved with a unique toxin called μ-conotoxin (see p. 194 of the text), which is obtained from a marine snail (Conus geographus). μ-Conotoxin is a 22-residue, basic peptide with a discoidal, starlike three-dimensional structure that is stabilized by three disulfide bonds. It is an especially potent blocker of the particular isoform of the voltage-dependent Na+ channel that is present in adult mammalian skeletal muscle, but it has little effect on the Na+channel isoforms of nerve or heart. If an intact nerve–muscle preparation is exposed to μ-conotoxin, stimulation of the nerve still evokes the release of ACh, but the muscle action potential is completely eliminated.

Contributed by Ed Moczydlowski

Tubocurarine

See the following link:

http://www.portfolio.mvm.ed.ac.uk/studentwebs/session2/group12/tubocura.htm

Depolarization Blockade

Acetylcholinesterase inhibitors lead to an accumulation of acetylcholine in the synaptic cleft, causing a sustained activation of the nicotinic acetylcholine receptor, and thus a sustained depolarization of the postsynaptic membrane. Although the initial depolarization would lead to an action potential and muscle contraction, the sustained depolarization would prevent voltage-gated Na+ channels from recovering from inactivation. The result is a flaccid muscle paralysis.

Contributed by Ed Moczydlowski

Tropomyosin–Troponin Interactions: The “Functional Group” of the Thin Filament

As discussed in the textbook, troponin (which consists of troponin T, C, and I) interacts with one tropomyosin molecule, which in turn interacts with seven actin monomers (see Fig. 9–6 on p. 244 and pp. 242–244 of the text). The region along a thin filament that falls under the control of a single troponin molecule has been referred to as a functional group. However, overlap of troponin T onto more than one tropomyosin molecule (recall that the tropomyosin molecules stack end to end to create a nearly continuous filament) may allow a single troponin complex to control a functional group of 14 or more actin molecules.

Contributed by Ed Moczydlowski

SERCA Isoforms

SERCA is an acronym for sarcoplasmic and endoplasmic reticulum calcium ATPase. The energy for Ca2+ pumping comes from the hydrolysis of ATP. As discussed on p. 122 in the text (also see Web Note 0122a, Crystal Structure of SERCA1), the Ca2+-transporting protein is an E1–E2 (or P-type) ATPase that has a molecular weight of 110 kDa. Three different SERCA isoforms are known.

All of the SERCA isoforms (SERCA1, -2, and-3) are Ca–H exchange pumps. The SERCA2 isoform may be expressed as two alternatively spliced variants. The SERCA1 isoform is expressed in fast-twitch skeletal muscle, which is a subtype of skeletal muscle fibers that contract rapidly (see p. 260 in the text). The SERCA2a isoform is found in slow-twitch skeletal muscle as well as in cardiac and smooth muscle. The SERCA2b isoform is found in smooth muscle cells; it is also heavily expressed in the endoplasmic reticulum of nonmuscle cells. Table 9–2 on p. 261 summarizes the distribution of the SERCA isoforms among muscle types.

Note that all of the SR Ca2+ pumps (i.e., SERCAs) are distinct from the Ca2+ pumps in the plasma membrane, which are known as PMCAs (see p. 122).

Contributed by Emile Boulpaep and Walter Boron

Store-Operated Ca2+ Channels (SOCs)

Receptor-operated and store-operated Ca2+ channels are defined not by the structure of the channel but by their apparent physiological regulation.

Receptor-operated Ca2+ channels (ROCs)—also called “second messenger-operated channels”—mediate Ca2+ entry in response to stimulation of a Gq protein-coupled receptor (see p. 53 of text as well as Table 3–2 on the same page) or a receptor tyrosine kinase (see p. 69) and subsequent increase in the activity of phospholipase C (see p. 59), such as PLCβ or PLCγ.

Store-operated Ca2+ channels (SOCs) mediate “capacitative” Ca2+ entry that is triggered by depletion of Ca2+ inside the endoplasmic reticulum. Thapsigargin, a specific inhibitor of the endoplasmic reticulum Ca2+ pump or SERCA, can cause depletion of the internal Ca2+ pool.

Ca2+ release from ROCs, together with the entry of Ca2+ via SOCs, provides the Ca2+ that underlies one form of pharmacomechanical coupling. By this pathway, drugs, excitatory neurotransmitters, and hormones can induce smooth muscle contraction that is independent of action potential generation, as discussed in the text on p. 258.

Store-operated Ca2+ channels are particularly important in the cellular physiology of various nonexcitable cells such as secretory epithelia, mast cells, and lymphocytes. In these latter cells, depletion of Ca2+ in storage compartments of the endoplasmic reticulum (ER) results in activation of Ca2+ influx through the plasma membrane. Electrophysiologists have termed this latter Ca2+ current ICRAC, which denotes the Ca2+-release-activated Ca2+current. The ICRAC current serves an important function of helping to replenish emptied stores of intracellular Ca2+.

Recent work has elucidated the molecular basis of SOCs in lymphocytes, partially based on identification of a gene called ORAI. Missense mutations in the human ORAA1 gene result in a severe combined immunodeficiency syndrome (SCID). The lymphocytes of the affected individuals lack the ICRAC current, which plays a vital role in lymphocyte activation. The ORAI gene encodes a membrane protein with four transmembrane segments that functions as a multimeric low-conductance Ca2+ channel in the plasma membrane (see Fig. 6–21T on p. 177 of the text, as well as p. 178). Figure 3 from the paper by Hewavitharana et al. illustrates how Ca2+ depletion in the ER is coupled to activation of the ORAI channel by direct interaction with a STIM protein in the ER membrane. STIM is believed to sense the Ca2+concentration in the ER.

Although the ORAI channel and STIM proteins comprise a potential candidate for voltage-independent activation of SOC in smooth muscle, evidence suggests that the Ca2+-permeable TRP channels (see Fig. 6–21I on p. 176 of the text, as well as pp. 177–178)—TRPC1 and TRPC5—may function as SOCs in mammalian portal vein myocytes. Activation of these latter TRP channels in portal vein smooth muscle appears to be coupled to IP3-mediated release of internal Ca2+ via mechanisms involving α1-adrenergic receptor activation of a phospholipase C pathway that includes IP3, diacylglycerol, protein kinase C, and calmodulin. Further work is clearly needed to investigate the molecular basis of SOC channels in smooth muscle and the physiological functions of human ORAI channels.

REFERENCE

Albert AP, Saleh SN, Peppiatt-Wildman CM, and Large WA: Multiple activation mechanisms of store-operated TRP channels in smooth muscle cells. J Physiol 583:25–36, 2007.

Hewavitharana T, Deng X, Soboloff J, and Gill DL: Role of STIM and Orai proteins in the store-operated calcium signaling pathway. Cell Calcium 42:173–182, 2007.

Yildirim E, Kawasaki BT, and Birnbaumer L: Molecular cloning of TRPC3a, an N-terminally extended, store-operated variant of the human C3 transient receptor potential channel. Proc Natl Acad Sci USA102:3307–3311, 2005.

Contributed by Emile Boulpaep and Walter Boron

Nitric Oxide (NO)

For more information on the chemistry and physiology of NO, consult the following web sites:

http://users.rcn.com/jkimball.ma.ultranet/BiologyPages/N/NO.html

http://herkules.oulu.fi/isbn9514268512/html/i231674.html

Santiago Ramón y Cajal

http://www.nobel.se/medicine/laureates/1906/index.html

Sir Charles Scott Sherrington

http://www.nobel.se/medicine/laureates/1932/index.html

Stem Cells

The general rule that neurons are created only during embryonic development and are never replaced is valid in a practical sense for all parts of the mammalian central nervous system except for the olfactory bulb and the dentate gyrus of the hippocampus, which may retain a population of true stem cells. Stem cells are cells that have the ability to

1. Proliferate

2. Renew themselves over the life of the organism

3. Create fully differentiated cells through progenitor cells

4. Retain their multilineage potential throughout life

5. Replace cells lost to injury or disease

These stem cells create mature brain cells by engaging in asymmetric cell division, which yields one stem cell and one cell that begins on the path to terminal differentiation. This latter cell is called a progenitor cell. It may continue to divide, but its progeny are committed to a particular line of cell differentiation (e.g., neurons or astrocytes, but not both). Stem cells can also engage in symmetrical division and simply create two new stem cells.

The stem cells of the nervous system are capable of generating neurons, astrocytes, and oligodendrocytes. A slowly dividing population of presumed stem cells resides in the subependymal area of the lateral ventricles (i.e., analogous to the germinal matrix of the fetal brain; see p. 267 of the text). These cells are apparently the source for the olfactory neurons that are continually renewed during life. Adult stem cells from the brain proliferate in response to epidermal growth factor. It is not understood how to make these cells produce progenitor cells for neurons or glial cells. It is hoped that by sending stem cells the right sequence of signals, it might eventually be possible to replace neurons lost to injury or disease.

Contributed by Bruce Ransom

Stem Cells

The general rule that neurons are created only during embryonic development and are never replaced is valid in a practical sense for all parts of the mammalian central nervous system except for the olfactory bulb and the dentate gyrus of the hippocampus, which may retain a population of true stem cells. Stem cells are cells that have the ability to

1. Proliferate

2. Renew themselves over the life of the organism

3. Create fully differentiated cells through progenitor cells

4. Retain their multilineage potential throughout life

5. Replace cells lost to injury or disease

These stem cells create mature brain cells by engaging in asymmetric cell division, which yields one stem cell and one cell that begins on the path to terminal differentiation. This latter cell is called a progenitor cell. It may continue to divide, but its progeny are committed to a particular line of cell differentiation (e.g., neurons or astrocytes, but not both). Stem cells can also engage in symmetrical division and simply create two new stem cells.

The stem cells of the nervous system are capable of generating neurons, astrocytes, and oligodendrocytes. A slowly dividing population of presumed stem cells resides in the subependymal area of the lateral ventricles (i.e., analogous to the germinal matrix of the fetal brain; see p. 267 of the text). These cells are apparently the source for the olfactory neurons that are continually renewed during life. Adult stem cells from the brain proliferate in response to epidermal growth factor. It is not understood how to make these cells produce progenitor cells for neurons or glial cells. It is hoped that by sending stem cells the right sequence of signals, it might eventually be possible to replace neurons lost to injury or disease.

Contributed by Bruce Ransom

Heinrich Quincke

http://www.whonamedit.com/doctor.cfm/504.html

http://www.uic.edu/depts/mcne/founders/page0075.html

System L Amino Acid Transporters in Brain Capillary Endothelial Cells

Large neutral amino acids (i.e., phenylalanine, tyrosine, and leucine) are selectively transported into the brain by System L. As outlined in Table 36–1 on p. 803 of the text, the system L protein is a heterodimer of SLC7A8 and SLC3A2. It has broad substrate specificity and transports across the blood–brain barrier several important drugs that act on the brain, including levodopa (for Parkinson disease), baclofen (to reduce spasticity), and gabapentin (for chronic pain and epilepsy).

Contributed by Bruce Ransom

Glial Modulation of Neuronal Excitability via Extracellular K+ and pH

Chesler and Ransom proposed a model (see the accompanying figure) that integrates our knowledge of acid–base transporters in neurons and astrocytes, the pH sensitivity of neuronal ion channels, and a wealth of data on changes in the composition of brain extracellular fluid (BECF) during neuronal activity (e.g., increased [K+]o that occurs as the result of a train of action potentials). Neural activity (step 1 in the figure) leads to a rise in [K+]BECF (step 2), which would depolarize astrocytes (step 3). As first described by Siebens in renal proximal tubule cells, this depolarization would promote electrogenic Na/HCO3influx (step 4), which simultaneously raises pHi and lowers pHBECF (step 5). The low pHBECF would inhibit the neuronal Na+-driven Cl–HCO3 exchanger (step 6), causing neuronal pHi to fall (step 7). The decreases in both pHBECF and neuronal pHi complete the feedback loop by inhibiting voltage-gated channels and ligand-gated changes, thereby decreasing neuronal excitability (step 7). Indeed, low pH appears to reduce neuronal activity in experimental models of epilepsy.

Glial Modulation of Neuronal Excitability

image

REFERENCE

Chesler M: The regulation and modulation of pH in the nervous system. Prog Neurobiol 34:401–427, 1990.

Ransom BR: Glial modulation of neural excitability mediated by extracellular pH: A hypothesis. Prog Brain Res 94:37–46, 1992.

Siebens AW, and Boron WF: Depolarization-induced alkalinization in proximal tubules: I. Characteristics and dependence on Na+Am J Physiol 25:F342–F353, 1989.

Siebens AW, and Boron WF: Depolarization-induced alkalinization in proximal tubules: II. Effects of lactate and SITS. Am J Physiol 25:F354–F365, 1989.

Astrocytomas

As pointed out in the text, malignant astrocyte tumors (i.e., astrocytomas) lack gap junctions. One theory is that growth-limiting factors pass among coupled cells to regulate proliferation. Thus, if gap junctions are lost, cells with minimal intrinsic production of these factors would be more prone to escape from normal regulation and become tumor clones.

Contributed by Bruce Ransom

K+ Siphoning by Muller Cells

An additional specialization that contributes to spatial buffering is a nonuniform distribution of K+ channels on a single cell. The density of K+ channels on the cell membrane of retinal Müller cells (panel A of the accompanying figure), which are specialized astrocytes, is highest on the cell’s endfoot. Thus, focal increases in [K+]o at the endfoot cause greater depolarization than if they occur elsewhere along the cell’s membrane (panel B of the accompanying figure). Because the endfoot of the Müller cell, which abuts the vitreous humor of the eye, has the highest density of K+ channels, excess extracellular K+ is preferentially transported to the vitreous, which acts as a disposal site. It is not known whether nonuniform K+ channel distribution is a general feature of astrocytes.

image

Role of Müller cells in spatial buffering. A, The Müller cells are the predominant glial cell of the retina. B, In this experiment on an isolated Müller cell from a salamander retina, the investigator monitored membrane potential from the soma of the cell while ejecting K+ from a second pipette at different points along the Müller cell. These ejections, which raise local [K+]o, produced the largest depolarizations when K+ was ejected at the endfoot and microvilli.

Contributed by Bruce Ransom

Shapes of Action Potentials in Various Neurons

The accompanying figure shows a range of shapes of action potentials.

image

Shapes of action potentials in various neurons.

Contributed by Barry Connors

Sir John Carew Eccles

http://www.nobel.se/medicine/laureates/1963/index.html

Temperature Dependence of Axonal Conduction

Temperature dependence of axonal conduction. (Data from Sears TA, and Bostock H: Conduction failure in demyelination: Is it inevitable? Adv Neurol 31:357–375, 1981.)

image

Contributed by Barry Connors

Sir Charles Scott Sherrington

http://www.nobel.se/medicine/laureates/1932/index.html

Santiago Ramón y Cajal

http://www.nobel.se/medicine/laureates/1906/index.html

Steps in Synaptic Transmission

image

A chemical synapse between neurons. In A, the resting state before the arrival of an action potential is shown. In B, the arrival of the action potential in the presynaptic neuron triggers a series of seven events.

Contributed by Barry Connors

NO as a Neurotransmitter in the CNS

image

Nitric oxide (NO) synthesis in a central neuron. Presynaptic glutamate release triggers the entry of Ca2+ through NMDA glutamate receptor channels or voltage-gated Ca2+ channels. Via calmodulin (CaM), Ca2+ stimulates nitric oxide synthase (NOS; see p. 69 of the text). NO diffuses out and through cells to affect presynaptic and postsynaptic elements of the same synapse or of nearby synapses. NADPH, nicotinamide adenine dinucleotide phosphate; NMDA, N-methyl-D-aspartate.

Contributed by Barry Connors

Pyroglutamate and C-Terminal Amides

Figure 13-9 on p. 333 shows several examples of neuroactive peptides in which the N-terminal residue is pyroglutamate (indicated by a p in the structure shown in the textbook). Similarly, the figure shows several examples in which the C-terminal residue has an amide.

Pyroglutamate. Figure 58-2 on p. 1215 of the textbook shows the peptide backbone of a generic protein. Imagine that the leftmost (i.e., N-terminal) residue in this figure is the side chain for glutamate (see Table 2–1 on p. 16 in the textbook for a listing of side chains). A reaction of the carboxyl group on the glutamate side chain with the terminal amino group results in the creation of an amide derivative in the form of a five-membered ring. For example, for thyrotropin-releasing hormone (TRH), the structure would be:

This posttranslational modification of a glutamate residue is called a pyroglutamate residue. In the figure, the peptide bonds are shown in red. The pyroglutamate is the magenta ring structure at the right.

C-terminal amide. Figure 58-2 on p. 1215 shows the peptide backbone of a protein. Notice that the rightmost (i.e., C-terminal) residue in this figure has a free carboxyl group. If this carboxyl group undergoes a reaction that transfers an –NH2, the result is an amide group (in the carboxyterminal residue of Figure 58-2, replace the O group with NH2). In the above figure, this amide is the magenta “–NH2” at the right.

For comparison, a hypothetical tripeptide without the pyroglutamate at the N terminus and with the C-terminal amide would be as follows:

Contributed by Emile Boulpaep and Walter Boron, with George Farr providing the chemical structures

The Membrane-Delimited Pathway for the Activation of Ion Channels by G Proteins

The first evidence for a membrane-delimited pathway came from patch-clamp experiments on inside-out patches containing a muscarinic acetylcholine receptor (M2), the Gs heterotrimeric G protein, and a K+channel capable of being activated by G proteins. These experiments showed that the G protein’s βγ subunits—which remains attached to the membrane—are necessary for activating the K+ channel. Thus, everything that is required for the signal-transduction process to work is present in the small patch of membrane. Some authors have voiced a lingering doubt that the βγ subunits can directly interact with ion channels. An alternative to a direct coupling between G protein βγ subunits and channel is that some lipid-soluble, “second messenger”—which is also in the plane of the membrane—mediates the interaction between the G protein βγ subunits and the K+ channel. However, whether the G protein–channel linkage is direct or occurs via some local membrane messenger, receptors and channels must be quite close for the membrane-delimited pathway to work.

REFERENCE

Clapham DE: Direct G protein activation of ion channels? Annu Rev Neurosci 17:441–464, 1994.

Contributed by Barry Connors

Compartmentalization of Second Messenger Effects

In the textbook, we referred only to whole-cell levels of intracellular second messengers (e.g., cAMP), as if these messengers were uniformly distributed throughout the cell. However, some cell physiologists and cell biologists believe that local effects of intracellular second messengers may be extremely important in governing how signal transduction processes work. One piece of evidence for such local effects is that the receptors for hormones and other extracellular agonists often are a part of macromolecular clusters of proteins that share a common physiological role. For example, a hormone receptor, its downstream heterotrimeric G protein, an amplifying enzyme (e.g., adenylyl cyclase) that generates the intracellular second messenger (e.g., cAMP), other proteins (e.g., the A kinase anchoring protein [AKAP]), and the effector molecule (e.g., protein kinase A) may all reside in a microdomain at the cell membrane. Thus, it is possible that a particular hormone could act by locally raising [cAMP]i to levels much higher than in neighboring areas so that—of all the cellular proteins potentially sensitive to cAMP—the newly formed cAMP may only activate a local subset of these targets.

A second piece of evidence for the local effects of cAMP is the wide distribution of phosphodiesterases, which would be expected to break down cAMP and limit its ability to spread throughout the cell.

Contributed by Laurie Roman

Differential Ca2+ Permeabilities of AMPA- and NMDA-Type Glutamate Receptors

If the AMPA-type and NMDA-type glutamate receptor channels are so closely related phylogenetically, how is it that they have such different Ca2+ permeabilities? Most of the AMPA-type glutamate receptor channels have a relatively low Ca2+ permeability because they include at least one GluR2 subunit. GluR2 (but not GluR1, -3, or-4) has a positively charged arginine residue at a particular site within the channel-forming domain. The arginine in GluR2 is critical for the low Ca2+ permeability of the native AMPA-type receptor channel. GluR1, -3, and-4 all have a neutral glutamine in place of the arginine. Indeed, if one constructs a complete AMPA-gated channel in which none of the four subunits has the arginine at the critical site, this channel will have an unnaturally high Ca2+ permeability. Starting from such a channel lacking the critically placed arginines, re-introducing a single arginine into any of the four subunits restores the low Ca2+ permeability.

Because the NMDA-gated channel is naturally permeable to Ca2+, you can guess that it follows the same structural rules as the AMPA-gated channel. Indeed, if you locate the homologous amino acid residue where the neutral arginine would be in the AMPA-gated channel, you will find a neutral asparagine in all subunits of the NMDA-gated channel. Predictably, these neutral asparagines—like glutamines at the homologous sites in the mutant subunits of the AMPA-gated channel—allow Ca2+ to pass through the pore of NMDA-gated channels.

Contributed by Barry Connors

Short-Term Synaptic Plasticity

See the following Web Notes:

Quantal Nature of Transmitter Release

The quantal nature of transmitter release can be expressed quantitatively by postulating that a nerve terminal contains a population of N quanta or vesicles, and that each has a finite probability (P) of releasing under any given set of conditions. Thus, the mean number (m) of quanta released after any single nerve impulse is

Equation 1

image

Figure 8-12B on p. 225 of the textbook illustrates the results of an experiment very similar to that shown in Figure 8-12A, except that the investigators—Boyd and Martin—repeated the nerve stimulation 198 times rather than the 7 times in Figure 8-12A. In each case, Boyd and Martin recorded the magnitude of the MEPP and placed it into a “bin” that was 0.1 mV wide. Thus, if they observed a MEPP of 1.23 mV, they placed it into the 1.2 bin. Figure 8-12B, a histogram summarizing the results of the 198 nerve evoked responses, shows a series of peaks. The peak at 0 mV corresponds to the 18 trials in which the nerve stimulus evoked no end plate potential. The peaks labeled I, II, III, etc. correspond to MEPPs that are multiples of the unit event—which is 0.4 mV—at amplitudes of 0.4, 0.8, 1.2 mV, etc. Thus, peak I corresponds to 1 quantum released, peak II corresponds to 2 quanta released, and so on.

If we sum up all the MEPPs in the 198 trials, we see that the total change in Vm was 184 mV. Dividing by 198 produces the mean amplitude of the MEPPs, 0.93 mV. If we assume a unitary response of 0.4 mV, 0.93 mV corresponds to 2.3 quanta, which is the m in Equation 1. Thus, on average, a nerve impulse produces a MEPP of 0.93 mV, which corresponds to the release of 2.3 quanta. However, in any given nerve impulse, the actual MEPP—if we could measure it with perfect accuracy—must correspond to an integral number of quanta released (x = 0, 1, 2, 3, …). Of course, because of noise and inaccuracies in the measuring system, Boyd and Martin also measured MEPPs that corresponded to nonintegral numbers of quanta. The y axis in Figure 8-12B gives the number of times Boyd and Martin observed a given MEPP out of the total of 198 observations. The seven bell-shaped or Gaussian curves in Figure 8-12B represent the probability of releasing 1–7 quanta.

Table 1. Poisson distribution of quanta released during nerve stimulation

No. of quanta (x)

No of events observed (nx)

Probability observed

Probability predicted

0

18

0.091

0.100

1

44

0.222

0.231

2

55

0.278

0.265

3

36

0.182

0.203

4

25

0.126

0.117

5

12

0.061

0.054

6

5

0.025

0.021

7

2

0.010

0.007

8

1

0.005

0.002

Because each bin is 0.1 mV wide, and because the unitary MEPP is 0.4 mV, Boyd and Martin added up 0.4/0.1 or four consecutive bins to obtain the number of observations (nX) corresponding to the release of x quanta, out of the total of 198 observations (ntotal). For example, for x = 0 quanta, n0 was 18; for x = 1 quantum, n1 was 44; the second column in Table 1 in this Web Note gives the number of events observed (nx) for each number of quanta “x” (listed in the first column). The probability (px) that we saw x quanta being released after a single nerve impulse is

Equation 2

image

Thus, for x = 0, p0 would be 18/198 or 0.091; for x = 1, p1 would be 44/198 or 0.222; the other values are given in column 3 of Table 1.

How do these observed values agree with those predicted by probability theory? Probability theory predicts that pX should follow a Poisson distribution:

Equation 3

image

Note that m in this equation is once again the mean number of quanta released per nerve impulse—2.3 in our example. This theory assumes that the underlying probability of vesicle release (P in Equation 1) is very small and that the population of replenishable vesicles (N in Equation 1) is very large. The last column of Table 1 shows that the pX predicted by Equation 3 is very nearly the same as the observed pX for each number of quanta.

We can also check the agreement of the data with the theory by testing whether the observed number of blank records (0-mV events) can predict the mean number (m) of quanta released after any single nerve impulse. According to Equation 3, when x = 0,

Equation 4

image

or

In p0 = -m

Because p0 is 18/198 or 0.091, the m value that we compute from Equation 4 is 2.4 quanta. This value is very close to the measured mean of 2.3 quanta. Findings such as these have provided strong support for the quantal theory of neurotransmitter release at the neuromuscular junction.

REFERENCE

Boyd IA, and Martin AR: The end-plate potential in mammalian muscle. J Physiol 132:74–91, 1956.

Contributed by Ed Moczydlowski

Modulation of Quantal Release

As discussed in Web Note 0224a, Quantal Nature of Transmitter Release, the quantal nature of transmitter release can be expressed quantitatively by postulating that a nerve terminal contains a population of Nquanta or vesicles, and that each has a finite probability (P) of releasing under any given set of conditions. Thus, the mean number (m) of quanta released after any single nerve impulse is

Equation 1

image

As noted in the textbook, facilitation is a short-lived enhancement of the postsynaptic potential in response to a brief increase in the frequency of nerve stimulation. One way facilitation may occur is by a transient increase in the mean number of quanta per nerve stimulus, corresponding to an increase in the m parameter of Equation 1.

Potentiation is a long-lived and pronounced increase in transmitter release that occurs after a long period of high-frequency nerve stimulation. This effect can last for minutes after the conditioning stimulus. Potentiation may be caused by a period of intense nerve firing, which increases [Ca2+]i in the presynaptic terminal, and thus increases the probability of exocytosis (the P parameter in Equation 1).

Synaptic depression is a transient decrease in the efficiency of transmitter release and, consequently, a reduction in the postsynaptic potential, in response to a period of frequent nerve stimulation. Depression may result from a temporary depletion of transmitter-loaded vesicles from the presynaptic terminal—that is, a reduction in the number of available quanta, corresponding to the parameter N in Equation 1.

Thus, these three temporal changes in synaptic strength and efficiency appear to reflect changes at different steps of synaptic transmission. Similar modulation of synaptic strength in the central nervous system provides a mechanistic paradigm for understanding how individual nerve terminals may “learn.”

Contributed by Ed Moczydlowski

Sir Bernard Katz

http://www.nobel.se/medicine/laureates/1970/index.html

Contributed by Emile Boulpaep and Walter Boron

Eric R. Kandel

http://www.nobel.se/medicine/laureates/2000/index.html

Tracing of Nerve Tracts Using Pseudorabies Virus

The central nervous system neuroanatomy of autonomic control has been difficult to define experimentally. However, a technique developed by Arthur Loewy and colleagues, tracing nerve tracts with the pseudorabies virus, has helped to define more clearly the central pathways for autonomic control. For example, if axons of preganglionic sympathetic neurons are exposed to pseudorabies virus, the virus is transported back into the cell bodies, where they replicate. After a delay of several days, neurons that make synapses with these preganglionic neurons (i.e., “premotor” neurons) become infected and the virus is transported to their cell bodies. After longer periods of incubation, neurons farther upstream are also infected. Histological staining can then be used at different time points to visualize neurons that contain the virus at each level upstream.

REFERENCE

Jansen ASP, van Nguyen X, Karpitskiy V, Mettenleiter TC, and Loewy AD: Central command neurons of the sympathetic nervous system: Basis of the fight-or-flight response. Science 270:644–646, 1995.

Contributed by George Richerson

Phox2b

At one time, scientists searched for “master genes” responsible for directing the development of each group of neurons that share a common function (e.g., all motor neurons or all neurons that contain GABA). This search has largely been fruitless, except for Phox2b, which is the closest example of a master gene in that it is expressed almost uniquely and nearly ubiquitously in neurons of the visceral control system. The implication is that these neurons are so closely related to each other in their function that they are bound together by a common developmental program. This common bond is so primitive that a homologue of Phox2b is even found in neurons of Ciona, a urochordate that is a marine animal made up primarily of an intestine that filters seawater.

Contributed by George Richerson

Muscarinic Receptors

Muscarinic receptors are found both presynaptically and postsynaptically throughout the autonomic nervous system. Many smooth muscles co-express multiple muscarinic subtypes, each of which may play different roles in neurotransmission. Thus, it is sometimes difficult to predict the effects of applying ACh to a particular tissue.

Contributed by George Richerson

Cholinergic Sympathetic Neurons

Using antibodies directed against choline acetyltransferase (i.e., the enzyme that catalyzes the conversion of acetyl CoA and choline into acetylcholine; see Fig. 13–8B on p. 332 and also p. 217 of the text) and the vesicular acetylcholine transporter (which transports acetylcholine from the cytoplasm of the nerve terminal into the synaptic vesicles; see Fig. 8–15 on p. 228 of the text), Schafer et al. confirmed the cholinergic nature of the terminals of sudomotor and some vasomotor nerve fibers. In addition, these investigators studied the developmental biology of postganglionic sympathetic neurons. They found that a small minority of sympathetic neurons have a cholinergic phenotype even during early embryonic development—even before the neurons innervate sweat glands. Thus, a true postganglionic sympathetic neuron—postganglionic in both the gross anatomic and the physiological sense of the word—can be cholinergic. In other words, a preganglionic sympathetic “first” neuron, with its cell body in the intermediolateral column, may synapse in a sympathetic ganglion with a postganglionic sympathetic “second” neuron that releases acetylcholine at its nerve terminals.

REFERENCE

Schafer MK, Schutz B, Weihe E, and Eiden LE: Target-independent cholinergic differentiation in the rat sympathetic nervous system. Proc Natl Acad Sci USA 94:4149–4154, 1997.

Schafer MK, Eiden LE, and Weihe E: Cholinergic neurons and terminal fields revealed by immunohistochemistry for the vesicular acetylcholine receptor: II. The peripheral nervous system. Neuroscience84:361–376, 1998.

Contributed by Emile Boulpaep and Walter Boron

Sir Henry H. Dale

http://www.nobel.se/medicine/laureates/1936/index.html

Walter B. Cannon

http://www.the-aps.org/about/pres/introwbc.htm

Fight or Flight Response

Walter B. Cannon (http://www.the-aps.org/about/pres/introwbc.htm) described this response for the first time in 1929.

REFERENCE

Cannon W: Bodily Changes in Pain, Hunger, Fear, and Rage. New York: Appleton, 1929.

Contributed by Emile Boulpaep and Walter Boron

Hierarchical Reflex Loops in the Autonomic Nervous System

image

Hierarchical reflex loops in the autonomic nervous system. CNS, central nervous system; ENS, enteric nervous system.

Contributed by George Richerson

Richard Axel and Linda Buck

http://nobelprize.org/nobel_prizes/medicine/laureates/2004/

Importance of Pupil Size for Depth of Focus

Imagine that a photographer focuses a camera on an object by adjusting the focal power of the camera lens (see Equation 15–1 on p. 379 in the text). In principle, only objects at a particular distance from the camera will be in sharp focus. However, if the photographer stops down the diaphragm (to high F values) behind the lens of a camera, only fairly parallel rays of light can enter the camera so that the depth of focus is very broad. In other words, because the camera is receiving very little information concerning the distance to an object, objects at rather different distances from the camera may all appear to be more or less in focus.

Just the opposite happens when the photographer opens up the diaphragm (to very low F values). In this case, the depth of focus is very shallow so that the only objects that are in sharp focus are those at a particular distance from the camera. Other objects that are closer or further from the camera will appear blurred to varying extents, depending on their distance from the point of optimal focus.

Turning now to the eye, miosis (pupillary constriction) is the equivalent of a stopped-down diaphragm (high F value), whereas mydriasis (pupillary dilation) is the equivalent of a fully open diaphragm (low F value). Thus, under conditions of mydriasis (e.g., with sympathetic stimulation or in response to low light levels), the depth of focus can be very shallow, which can cause close object to appear blurred if the lens is unable to sufficiently accommodate (i.e., to increase its focal power). Blurring is especially problematic with increasing age (e.g., >40 years), when accommodation becomes progressively limited—a condition known as presbyopia.

Contributed by Barry Connors

Vestibulo-Ocular Reflexes

Through vestibulospinal reflexes, the vestibular system influences body posture, which is essential for balancing one’s body, preventing it from falling, and—when falling—lifting one’s head to prevent it from impact injury. Furthermore, through vestibulo-ocular reflexes, the vestibular system influences movements of the eyes, which stabilize images on retinas during head movements.

Because visual processing in the retina is relatively slow, it is necessary to stabilize the images of the world on the retina. Stabilizing reflexes, collectively called vestibular–ocular reflexes, enable you to read this text while shaking your head. Note that it is much more difficult to read while shaking the book. The vestibular system measures head movements and elicits compensatory movements of the eyes (see accompanying figure). The position of each eye is controlled by three pairs of muscles that control horizontal, vertical, and rotational eye movements. Vestibular–ocular reflexes are linked to all five vestibular organs to enable compensatory eye movements in every direction. Muscles that control horizontal eye movements are linked to the horizontal semicircular canals and the utricle. Muscles that control vertical eye movements are linked to the anterior and posterior semicircular canals and the saccule. Finally, muscles that control rotational eye movements are linked to the anterior and posterior semicircular canals and the utricle. Vestibular–ocular reflexes can be suppressed during the observation of moving targets—for example, watching a bird or a ball flying by.

During large rotations—for example, during spinning—eye movements required for stabilizing an image on the retina exceed the limits of the orbit. Under these conditions, vestibular–ocular reflexes elicit fast reset movements of the eyes. Alterations between slow movements of the eyes intended to stabilize images on the retina and fast reset motions are called nystagmus (from the Greek nystagmos [tired or sleepy, like the nodding movement of the head just before falling asleep]). Nystagmus exist in all directions and are named by the direction of the fast reset phase (e.g., rightward nystagmus). Lesions to the vestibular system—for example, in head trauma or stroke—can lead to a spontaneous nystagmus when altered neuronal activity is falsely interpreted as head movements. Nystagmi induced by body rotations or by a caloric test are used clinically to evaluate vestibular function as lesions alter or eliminate nystagmi. The caloric test consists of introducing cold (30°C) or warm (40°CC) water into the external ear canal. Temperature changes induce convective movements of endolymph that are interpreted as head rotations. Comparisons of the caloric responses of the left and right ear can be used to localize lesions.

image

An example of a vestibular–ocular reflex. A, Head rotation to the left causes endolymph to push and pull on the cupulae of the left and right horizontal canals, respectively. B, Movement of the cupula tilts hair bundles in the ampulla of the left horizontal canal in the stimulatory direction, leading to excitation of afferent dendrites and an increase in the frequency of action potentials. Conversely, movement of cupula tilts hair bundles in the ampulla of the right horizontal canal in the inhibitory direction, which leads to a cessation of afferent stimulation and a decrease in the frequency of action potentials. C, Head rotations have a linear component that results from centrifugal forces against gravity. Centrifugal forces move the otolith membranes of the left and right macula utricle to the left. Displacements of the otolith membranes cause stimulation and inhibition of afferent activity depending on the orientation of the hair bundles. Note that the simple left head movement is coded by an intricate pattern of increased and decreased neuronal activity. The pattern is analyzed by the vestibular nuclei and used to elicit compensatory movements of the eyes to ensure that images remain stable on the retina during head movements.

Contributed by Philine Wangemann

Spatial Orientation

Proprioceptors in the skin, tendons, muscles, and joints provide information about posture, and the visual system provides clues from one’s surrounding. Although the vestibular system contributes to one’s conscious perception of motion and body position, vestibular information is mostly processed subconsciously. Through vestibulospinal reflexes, the vestibular system influences body posture, which is essential for balancing one’s body, preventing it from falling, and—when falling—lifting one’s head to prevent it from impact injury. Furthermore, through vestibulo-ocular reflexes (see Web Note 0389, Vestibulo-Ocular Reflexes), the vestibular system influences movements of the eyes, which stabilize images on one’s retinas during head movements.

Contributed by Philine Wangemann

Vestibular Innervation

The vestibular system is innervated by the vestibular nerve, which is a branch of CN VIII. The vestibular nerve is composed of afferent and efferent fibers.

Afferent fibers consist of dendrites of nerve cells from Scarpa’s ganglion housed within the temporal bone. Afferent dendrites contact multiple hair cells within small regions of a macula or crista. Integration over several sensory cells increases the signal-to-noise ratio of the sensory information. Axons of Scarpa’s ganglion cells contact the ipsilateral vestibular nuclei brainstem. Vestibular nuclei analyze information from the labyrinths on both sides of the head and control oculomotor and postural reflexes.

Efferent innervation of the vestibular labyrinth originates from cell bodies that are located lateral to the facial genu in the brainstem. Bilateral axons to the left and right vestibular system synapse onto afferent calyces of type I hair cells and onto type II vestibular hair cells. Vestibular efferent innervation has been hypothesized to maintain long-term calibration of afferent activity between the two vestibular labyrinths.

Contributed by Philine Wangemann

Head Rotation and the Vestibular-Ocular Reflex Vestibulo-Ocular Reflexes

Through vestibulospinal reflexes, the vestibular system influences body posture, which is essential for balancing one’s body, preventing it from falling, and—when falling—lifting one’s head to prevent it from impact injury. Furthermore, through vestibulo-ocular reflexes, the vestibular system influences movements of the eyes, which stabilize images on retinas during head movements.

Because visual processing in the retina is relatively slow, it is necessary to stabilize the images of the world on the retina. Stabilizing reflexes, collectively called vestibular–ocular reflexes, enable you to read this text while shaking your head. Note that it is much more difficult to read while shaking the book. The vestibular system measures head movements and elicits compensatory movements of the eyes (see accompanying figure). The position of each eye is controlled by three pairs of muscles that control horizontal, vertical, and rotational eye movements. Vestibular–ocular reflexes are linked to all five vestibular organs to enable compensatory eye movements in every direction. Muscles that control horizontal eye movements are linked to the horizontal semicircular canals and the utricle. Muscles that control vertical eye movements are linked to the anterior and posterior semicircular canals and the saccule. Finally, muscles that control rotational eye movements are linked to the anterior and posterior semicircular canals and the utricle. Vestibular–ocular reflexes can be suppressed during the observation of moving targets—for example, watching a bird or a ball flying by.

During large rotations—for example, during spinning—eye movements required for stabilizing an image on the retina exceed the limits of the orbit. Under these conditions, vestibular–ocular reflexes elicit fast reset movements of the eyes. Alterations between slow movements of the eyes intended to stabilize images on the retina and fast reset motions are called nystagmus (from the Greek nystagmos [tired or sleepy, like the nodding movement of the head just before falling asleep]). Nystagmus exist in all directions and are named by the direction of the fast reset phase (e.g., rightward nystagmus). Lesions to the vestibular system—for example, in head trauma or stroke—can lead to a spontaneous nystagmus when altered neuronal activity is falsely interpreted as head movements. Nystagmi induced by body rotations or by a caloric test are used clinically to evaluate vestibular function as lesions alter or eliminate nystagmi. The caloric test consists of introducing cold (30°C) or warm (40°CC) water into the external ear canal. Temperature changes induce convective movements of endolymph that are interpreted as head rotations. Comparisons of the caloric responses of the left and right ear can be used to localize lesions.

image

An example of a vestibular-ocular reflex. A, Head rotation to the left causes endolymph to push and pull on the cupulae of the left and right horizontal canals, respectively. B, Movement of the cupula tilts hair bundles in the ampulla of the left horizontal canal in the stimulatory direction, leading to excitation of afferent dendrites and an increase in the frequency of action potentials. Conversely, movement of cupula tilts hair bundles in the ampulla of the right horizontal canal in the inhibitory direction, which leads to a cessation of afferent stimulation and a decrease in the frequency of action potentials. C, Head rotations have a linear component that results from centrifugal forces against gravity. Centrifugal forces move the otolith membranes of the left and right macula utricle to the left. Displacements of the otolith membranes cause stimulation and inhibition of afferent activity depending on the orientation of the hair bundles. Note that the simple left head movement is coded by an intricate pattern of increased and decreased neuronal activity. The pattern is analyzed by the vestibular nuclei and used to elicit compensatory movements of the eyes to ensure that images remain stable on the retina during head movements.

Contributed by Philine Wangemann

Sound Waveforms

image

Waveforms of a pure tone, a sound, and noise. A pure tone (left) consists of a sine wave of only one single frequency. Noise (right) does not contain any recognizable periodic elements. Other sounds (middle) have a notable periodic pattern and consist of multiple superimposed waves.

Contributed by Philine Wangemann

Phon Scale

Sounds that have identical sound pressure levels (dB SPL) are not perceived as equally loud at all frequencies. The phon scale, which accounts for these differences in perception, has been developed by asking a number of human subjects to adjust intensities of test tones to equal loudness with reference tones at 1000 Hz (see the accompanying figure). The normal hearing threshold is approximately 4 phon, discomfort is perceived at 110 phon, and the pain threshold is 130 phon. Industrial noise levels are often given in the units dB (A). The dB (A) scale is a weighted scale that approximates human perception.

image

Diagram of the relationship between sound pressure level (dB SPL) and frequency (Hz). Sound pressure levels that are perceived as equally loud are graphed as equal loudness-level contours. The human ear is most sensitive between 1000 and 5000 Hz. Equal loudness-level contours from 4 and 80 phon are based on ISO226:2003, and equal loudness-level contours of 110 and 130 phon are based on ISO226:1987.

Contributed by Philine Wangemann

Acoustic Impedance

Acoustic impedance is defined as the ratio of sound pressure to volume velocity. Air has a low acoustic impedance. Consider what happens when the membrane of a loudspeaker is displaced in air. Because the air is very compressible, the displacement of the loudspeaker membrane does not increase air pressure very much, but it does impart a high-volume velocity to the air. On the other hand, the acoustic impedance of water is approximately 10,000 times higher than that of air because water is highly incompressible and dense. Consider what happens when we submerge a watertight loudspeaker in water. If we were able to displace the loudspeaker membrane to the same extent and just as fast as we did when the loudspeaker was in air, we would find that the resulting pressure wave would be far greater. (The way we set up this thought experiment, the volume velocities would be identical in the two cases.)

In the case of the ear—which takes advantage of (1) the area difference between the tympanic membrane versus the oval window and (2) the lever action of the ossicles—the pressure amplification occurs at the expense of volume velocity, thereby conserving energy.

Contributed by Barry Connors

Alfonso Giacomo Gaspare Corti

While working in the laboratory of Albert von Kölliker in Würzburg (Germany), Corti (1822–1876) developed novel histological staining techniques that allowed him to distinguish individual—and previously unidentified—elements within the cochlea. It was he who first identified the sensory organ that now bears his name, the organ of Corti.

http://en.wikipedia.org/wiki/Organ_of_corti

http://en.wikipedia.org/wiki/Koelliker

Contributed by Emile Boulpaep and Walter Boron

Otoacoustic Emissions

Amplification by the outer hair cells evokes vibrations of the basilar membrane that travel through the middle ear, set the tympanic membrane in motion, and produce a sound that comes out of the ear canal. Clinically most relevant are transient otoacoustic emissions and distortion product otoacoustic emissions. Transient otoacoustic emissions are sounds that are detected in the ear canal milliseconds after a very brief stimulus. Amplification by the outer hair cells is nonlinear, which means that the cochlea produces and emits distortion products. Distortion products in response to two pure tones at nearby frequencies (f1 and f2) relate to these stimuli by simple math—for example, 2f1– f2 or 2f2 – f1. Transient otoacoustic emissions and distortion product otoacoustic emissions provide useful clues for the evaluation of outer hair cell function.

Contributed by Philine Wangemann

Auditory Frequency Range

Our auditory frequency range is well adapted to the perception of speech, which encompasses frequencies between 60 and 12,000 Hz. We can comfortably hear sounds with amplitudes from 0 to 120 dB SPL. Higher sound pressure levels cause pain and destruction of the ear (see Web Note 0394b, The Phon Scale). Typical sound pressure levels are whispering at 20 dB SPL, normal conversation at 60 dB SPL, loud traffic at 80 dB SPL, and a nearby train horn at 120 dB SPL.

Contributed by Philine Wangemann

Rate Coding

Amplitude information is transmitted by rate coding. Rate coding refers to the principle that increases in sound amplitude result in an increase in the rate of action potentials. Cooperation between neurons is required to code the full range of sound pressure level from 0 to 120 dB SPL.

Contributed by Philine Wangemann

Georg von Békésy

http://www.nobel.se/medicine/laureates/1961/index.html

Sharpening of Cochlear Tuning

Outer hair cells express the motor protein prestin along the lateral cell wall, which is responsible for electromotility. Transduction-mediated depolarization of outer hair cells during upward movements of the basilar membrane causes prestin to contract, which shortens the hair cell body and increases the upward movement of the basilar membrane (see Fig. 15–23 on p. 397 in the text). Conversely, hyperpolarization during downward movements of the basilar membrane expands prestin, elongates the outer hair cells, and enlarges the downward movement of the basilar membrane. This electromotility, which amplifies and sharpens the peak of the sound-induced traveling wave, is a prerequisite for the sensitivity of hearing and the ability to sharply discriminate frequencies (see Fig. 15–25 on p. 400 in the text).

Contributed by Philine Wangemann

Central Processing of Auditory Patterns

Auditory patterns are analyzed in the medial geniculate and the auditory cortex. Neurons in these areas are often highly specialized and respond only to a specific frequency and intensity pattern. Interpretation of sound elements requires cortical input beyond the auditory cortex.

Central processing is clinically evaluated by auditory brainstem recordings. The coordinated firing of groups of neurons in responses to brief stimuli (clicks or tone pips) produces transient voltage fluctuations that can be detected with surface electrodes. Distinctive voltage fluctuations occur 2–12 ms after the stimulus and can be associated with neuronal activity in the auditory pathway, including the cochlear nerve, cochlear nucleus, and superior olivary complex.

Contributed by Philine Wangemann

Conductive Hearing Loss

Conductive hearing losses are diseases that compromise the conduction of sound through the external ear, tympanic membrane, or middle ear. Pressure differences across the tympanic membrane can rupture the “eardrum.” Accumulations of fluid in the middle ear can lead to conductive hearing losses that are particularly often seen in children suffering from middle ear infections (otitis media). With proper treatment, the hearing loss due to otitis media is usually self-limited. Otosclerosis, which stiffens the ossicular chain, is another common cause of conductive hearing loss.

Treatments of conductive hearing loss encompass a palette of devices, including hearing aids and middle ear implants. Hearing aids amplify the sound in the external ear canal. Prosthetic devices can replace the tympanic membrane and the ossicular chain. Middle ear implants are clamped onto the incus and enhance the vibrations of the ossicular chain.

Contributed by Philine Wangemann

Also see the following web site:

http://en.wikipedia.org/wiki/Conductive_hearing_loss

Cochlear Implants

See the following web sites:

http://www.nidcd.nih.gov/health/hearing/coch.htm

http://www.utdallas.edu/~loizou/cimplants/tutorial/

Levels of Organization of the Nervous System

image

Data from Shepherd GM: Neurobiology, 3rd ed. New York: Oxford University Press, 1994.

Contributed by Barry Connors

Sir Charles Scott Sherrington

http://www.nobel.se/medicine/laureates/1932/index.html

David Hubel & Torsten Wiesel

David H. Hubel and Torsten N. Wiesel shared the 1981 Nobel Prize in Physiology or Medicine with Roger W. Sperry. Hubel and Wiesel were cited for their discoveries of “information processing in the visual system.”

http://nobelprize.org/nobel_prizes/medicine/laureates/1981/

Cardiac Output of the Left Heart and the Right Heart

As shown on the right side of Figure 17-3 on p. 432, the bronchial circulation—which carries approximately 2% of the cardiac output or approximately 100 mL/min at rest—originates from the aorta (i.e., the output of the left heart). After passing through bronchial capillaries, approximately half of this bronchial blood empties into the azygos vein (see p. 718) and returns to the right atrium, and approximately half enters pulmonary venules (i.e., the input to the left heart). In other words, approximately 1% or 50 mL/min of the blood leaving the left ventricle reenters the left atrium, thus bypassing the right heart (i.e., a right-to-left shunt). Thus, although we generally say that the outputs of the left and right hearts are identical in the steady state, in fact, the cardiac output of the left heart exceeds the cardiac output of the right heart by approximately 1% or 50 mL/min at rest.

The Hagen–Poiseuille Law

Jean Léonard Marie Poiseuille (1797–1869) was a French physician. (For more information, see http://www.cartage.org.lb/en/themes/Biographies/MainBiographies/P/Poiseuille/1.html.) Gotthilf Heinrich Ludwig Hagen (1797–1884) was a German physicist. (For more information, see http://www.wikipedia.org/wiki/Gotthilf_Heinrich_Ludwig_Hagen.)

The Hagen–Poiseuille law describes the laminar flow of a viscous liquid through a cylindrical tube (see Figure 17-5B on p. 435). The viscous resistance reflects the frictional interaction between adjacent layers of fluid, each of which moves at a different velocity. This resistance does not reflect the friction between the outermost layer of fluid, which is stationary, and the wall of the tube.

In the Hagen–Poiseuille law (Equation 17–9 on p. 434),

Equation 1

image

F is the flow (ml • s-1), ΔP is the pressure difference (dynes • cm–2), r is the inner radius of the tube (cm), l is the length of the tube (cm), and η is the dynamic viscosity (dynes • s • cm–2 = poise). The unit of dynamic viscosity, the poise, is named after Poiseuille.

REFERENCES:

Pappenheimer JR: Contributions to microvascular research of Jean Léonard Marie Poiseuille. In Handbook of Physiology Sect 2. The Cardiovascular System. Vol. IV, Parts 1 and 2, pp. 1–10. Bethesda, MD: American Physiological Society, 1984.

http://www.wikipedia.org/wiki/Poiseuille’s_law.

Viscous Resistance

The Hagen–Poiseuille law describes the laminar flow of a viscous liquid through a cylindrical tube (see Figure 17-5B on p. 435). The viscous resistance reflects the frictional interaction between adjacent layers of fluid, each of which moves at a different velocity. This resistance does not reflect the friction between the outermost layer of fluid, which is stationary, and the wall of the tube. (In other words, Hagen and Poiseuille assumed that the outer edge of fluid does not move. It sticks to the wall!) Rather, viscous resistance depends on the fluid’s viscosity and shape.

In Equation 17–11 on p. 434, we define the viscous resistance as

image

Here, the resistance term R has the fundamental dimensions (mass) • (length)–4 • (time)–4. If the length (l) and the radius (r) are given in centimeters, and if the dynamic viscosity (η) is given in poise (or dynes • s • cm–2), then resistance is in the units dynes • cm–5 • s–1.

If one instead expresses the dynamic viscosity (η) not in poise but, rather, in the units g cm–1 s–1 (remembering that because force = mass × acceleration, the dyne has the units g • cm s–2), then the units of resistance become g cm–4s–1.

Note that if the vessel is not straight, rigid, cylindrical (implying a smooth internal surface), and unbranched, other nonviscous parameters will sum with the viscous resistance to make up the total resistance of the system (R) that appears in Ohm’s law of hydrodynamics (Equation 17–1 on p. 431). Such nonviscous resistances can arise from contributions from rough vessel walls and obstructions in the path of fluid flow—qualities of the container.

Contributed by Ridder Emile Boulpaep

Viscous Resistance

The Hagen–Poiseuille law describes the laminar flow of a viscous liquid through a cylindrical tube (see Figure 17-5B on p. 435). The viscous resistance reflects the frictional interaction between adjacent layers of fluid, each of which moves at a different velocity. This resistance does not reflect the friction between the outermost layer of fluid, which is stationary, and the wall of the tube. (In other words, Hagen and Poiseuille assumed that the outer edge of fluid does not move. It sticks to the wall!) Rather, viscous resistance depends on the fluid’s viscosity and shape.

In Equation 17–11 on p. 434, we define the viscous resistance as

image

Here, the resistance term R has the fundamental dimensions (mass) • (length)–4 • (time)–4. If the length (l) and the radius (r) are given in centimeters, and if the dynamic viscosity (η) is given in poise (or dynes • s • cm–2), then resistance is in the units dynes • cm–5 • s–1.

If one instead expresses the dynamic viscosity (η) not in poise but, rather, in the units g cm–1 s–1 (remembering that because force = mass × acceleration, the dyne has the units g • cm s–2), then the units of resistance become g cm–4s–1.

Note that if the vessel is not straight, rigid, cylindrical (implying a smooth internal surface), and unbranched, other nonviscous parameters will sum with the viscous resistance to make up the total resistance of the system (R) that appears in Ohm’s law of hydrodynamics (Equation 17–1 on p. 431). Such nonviscous resistances can arise from contributions from rough vessel walls and obstructions in the path of fluid flow—qualities of the container.

Contributed by Ridder Emile Boulpaep

Reynolds Number

In Equation 17–13 in the textbook,

Equation 1

image

the mean linear velocity (image) is expressed in cm • s-1, the radius (r) in centimeters, the density (ρ) in g • cm–3, and the viscosity in poise. When the equation is written as above—with the term 2r or diameter in the numerator—blood flow is laminar when Re is below ~2000.

You may also encounter a similar equation with r, rather than 2r, in the numerator:

Equation 2

image

When the equation is written in terms of radius rather than diameter, blood flow is laminar when Re is below ~1000. In the first and second printings of the first edition of the textbook, the number 1160 was used assuming the “radius” convention in Equation 2.

Regardless of which version of the equation we use, the terms in the numerator reflect disruptive forces produced by the inertial momentum in the liquid, because of both the velocity term and the product r × ρ, which is related to the mass of the moving fluid. In other words, a high inertial momentum predisposes to turbulence. The term in the denominator reflects the cohesive forces in the liquid—that is, the viscosity that tends to keep the layers of fluid together.

One way of looking at the previous equations is that at low Re, flow is laminar and a tiny volume of fluid in one layer in Figure 17-5B tends to stay in that layer. When Re is sufficiently high, flow is turbulent and that tiny volume may leave its original layer and become part of a neighboring layer—that is, it participates in eddy formation.

Another way of looking at the equations is that a tiny volume of fluid has a certain probability of deviating course and leaving its original layer. This tendency to stray from its original layer is enhanced when velocity (image) and/or density (ρ) is high (which raises inertial momentum) but is counteracted by the viscosity (which tends to hold it in the layer). The tendency to stray is also counteracted by a small radius, which reduces the number of layers and brings the average layer closer to a constraining wall—channeling the fluid.

REFERENCE:

http://www-gap.dcs.st-and.ac.uk/~history/Mathematicians/Reynolds.html

http://www.voltaicpower.com/Biographies/ReynoldsBio.htm

Mechanical Impedance of Blood Flow

We began this chapter by drawing an analogy between the flow of blood and electrical current, as described by Ohm’s law of hydrodynamics: ΔP = F × R. We now know that there are other factors that influence pressure. In addition to the flow resistance R (electrical analogy = ohmic resistor), we must also consider the compliance C (electrical analogy = capacitance) as well as the inertiance L (electrical analogy = inductance). A similar problem is faced in electricity when dealing with alternating (as opposed to direct) currents. In Ohm’s law for alternating currents, E = I × Z, where Z is a complex quantity called the impedance. Z depends on the electrical resistance R, the electrical capacitance C, and the electrical inductance L. Similarly, for blood flow, we can write ΔP = F × Z, where Z is also a complex quantity, called mechanical impedance, that includes

Compliant impedance that opposes volume change (compliance of the vessel);

Viscous (or resistive) impedance that opposes flow (shearing forces in the liquid). This term is the “R” of Ohm’s law of hydrodynamics: ΔP = F × R (Equation 17–1 on p. 431); and

Inertial impedance that opposes a change of flow (kinetic energy of fluid and vessels).

Considering all these sources of pressure, we can state that the total pressure difference at any point in time, instead of being given by Ohm’s law, is

Equation 1

image

The Pgravity term is discussed on p. 437 in the Section titled “Gravity Causes a Hydrostatic Pressure Difference When There Is a Difference in Height.”

99mTc Scanning

Several compounds labeled with technetium-99m (99mTc)—for instance, 99mTc-sestamibi and 99mTc-tetrofosmin—have been introduced for imaging myocardial perfusion. The 99mTc label emits gamma radiation at 140 keV by an isomeric transition (indicated by the “m” in 99m); it has a half-life of 6 hours. Following injection, the initial distribution of these agents in the myocardium is proportional to the relative distribution of myocardial blood flow. The radiochemical enters cardiac myocytes passively in such a way that approximately 30–40% of the chemical is extracted by the myocardium. Extraction may be enhanced by administering nitrates prior to injection. Because the radiochemical leaves the myocyte rather slowly (over several hours), one can perform the imaging with the gamma camera over a time period of hours. Note that absolute measurements of myocardial blood flow would require positron emission tomography, which can quantitate counts per unit volume of tissue.

It is possible to use 99mTc-labeled compounds not only for assessing myocardial perfusion but also for assessing myocardial function. In single-photon emission computed tomography, the computer acquires imaging data synchronized with the R wave of the electrocardiogram (see Figure 21-7 on p. 515). This gated imaging allows one to display end-diastolic and end-systolic images along various axes of the heart. These end-diastolic and end-systolic dimensions can then be compared to assess ejection fraction, stroke volume, regional wall motion, and regional wall thickening.

Ventricular Volume from M-Mode Echocardiography

As shown in Figure 17-17B on p. 446, the left ventricle is often assumed to be a prolate ellipse, with a long axis L and two short axes D1 and D2. To simplify the calculation, and to allow ventricular volume to be computed from a single measurement, it is sometimes assumed that D1 and D2 are identical, and that D1 is half of L. Unfortunately, using this algorithm and just a single dimension, as provided by M-mode echocardiography, often yields grossly erroneous volumes.

One can obtain a more accurate estimate of ventricular volume by including an independent measurement of a second dimension, as is done in two-dimensional echocardiography. For example, one could obtain the long axis (L) in addition to the short axes (D1 and D2, which are assumed to be the same in the simple calculation). However, the ventricle often does not resemble a prolate ellipse, certainly not in pathological states. Thus, cardiologists have used more complex geometric models (e.g., bullet shape).

Plasma Proteins*

Protein

Conventional Units

International Units

Protein, total Electrophoresis

6.4–8.3 g/dL

Albumin: 3.5–5.0 g/dL

α1-Globulin: 0.1–0.3 g/dL

α2-Globulin: 0.6–1.0 g/dL

β-Globulin: 0.7–1.1 g/dL

γ-Globulin: 0.8–1.6 g/dL

64.0–83.0 g/L

35–50 g/L

1–3 g/L

6–10 g/L

7–11 g/L

8–16 g/L

Acid phosphatase

 

M: 2.5–11.7 U/L

F: 0.3–9.2 U/L

Alanine aminotransferase (ALT, SGPT)

M: 10–40 U/L

F: 7–35 U/L

0.17–0.68 μKat/L

0.12–0.60 μKat/L

Albumin

3.4–4.8 g/dL

34–48 g/L

Alkaline phosphatase

25–100 U/L

Adult (>20 y) 0.43–1.70 μKat/L

Amylase

27–131 U/L

0.46–2.23 μKat/L

Angiotensin I

<25 pg/mL

<25 ng/L

Angiotensin II

10–60 pg/mL

10–60 ng/L

α1-Antitrypsin

78–200 mg/dL

0.78–2 g/L

Aspartate aminotransferase (AST)

10–30 U/L

0.17–0.51 μKat/L

Ceruloplasmin

18–45 mg/dL

180–450 mg/L

Chorionic gonadotropin, β-subunit (β-HCG)

M and nonpregnant F: <5.0 mIU/mL

<5.0 IU/L

C-peptide

0.78–1.89 ng/mL

0.26–0.62 nmol/L

C-reactive protein

68–8200 ng/mL

68–8200 μg/L

Creatine kinase (CK)

 

M: 38–174 U/L

F: 26–140 U/L

Erythropoietin

 

5–36 U/L

Ferritin

M: 20–250 ng/mL

20–250 μg/L

F: 10–120 ng/mL

10–120 μg/L

α1-Fetoprotein

<10 ng/mL

<10 μg/L

Fibrin degradation products

<10 μg/mL

<10 mg/L

Fibrinogen

200–400 mg/dL

2.00–4.00 g/L

Follitropin (FSH)

M: 4–25 mIU/mL

F: Follicular phase: 1–9 mIU/L

Ovulatory peak: 6–26 mIU/mL

Luteal phase: 1–9 mIU/mL

Postmenopausal: 30–118 mIU/mL

4–25 IU/L

1–9 IU/L

6–26 IU/L

1–9 IU/L

30–118 IU/L

Gastrin

25–90 pg/mL

25–90 ng/L

γ-Glutamyltransferase (GGT)

M: 2–30 U/L

0.03–0.51 μKat/L

Growth hormone (hGH, somatotropin)

Adult, M: 0–4 ng/mL

Adult, F: 0–18 ng/mL

>60 y, M: 1–9 ng/mL

>60 y, F: 1–16 ng/mL

0–4 μg/L

0–18 μg/L

1–9 μg/L

1–16 μg/L

Immunoglobulin A (IgA)

40–350 mg/dL

400–3500 mg/L

Immunoglobulin D (IgD)

0–8 mg/dL

0–80 mg/L

Immunoglobulin E (IgE)

0–380 IU/mL

0–380 kIU/L

Immunoglobulin G (IgG)

650–1600 mg/dL

6.5–16 g/L

Immunoglobulin M (IgM)

55–300 mg/dL

550–3000 mg/L

Insulin (12-hr fasting), immunoreactive

0.7–9.0 μIU/mL

5–63 pmol/L

Lactate dehydrogenase (LDH)

 

208–378 U/L

Lipase

31–186 U/L

0.5–3.2 μKat/L

Lutropin (LH)

M: 1–8 mU/mL

F: Follicular phase: 1–2 mU/mL

F: Midcycle: 16–104 mU/mL

F: Luteal: 1–12 mU/mL

F: Postmenopausal: 16–66 mU/mL

1–8 U/L

1–12 U/L

16–104 U/L

1–12 U/L

16–66 U/L

Lysozyme

0.4–1.3 mg/dL

4–13 mg/L

Myoglobin

 

M: 19–92 μg/L

F: 12–76 μg/L

Parathyroid hormone (PTH)

(Varies with laboratory) N-terminal 8–24 pg/mL

C-terminal 50–330 pg/mL

Intact 10–65 pg/mL

8–24 ng/L

50–330 ng/L

10–65 ng/L

Prostate-specific antigen (PSA)

M: <4 ng/mL

<4 μg/L

Renin (normal diet)

Supine: 0.2–1.6 ng/mL/hr

Standing: 0.7–3.3 ng/mL/hr

0.2–1.6 μg/L/hr

0.7–3.3 μg/L/hr

Thyroglobulin (Tg)

3–42 ng/mL

3–42 μg/L

Thyrotropin (hTSH)

0.4–4.2 μU/mL

0.4–4.2 mU/L

Thyrotropin-releasing hormone (TRH)

5–60 pg/mL

5–60 ng/L

Thyroxine-binding globulin or thyroid-binding globulin (TBG)

15.0–34.0 μg/mL

15.0–34.0 mg/L

Transcortin or corticosteroid-binding globulin (CBG)

M: 18.8–25.2 mg/L

F: 14.9–22.9 mg/L

323–433 nmol/L

256–393 nmol/L

Transferrin

200–400 mg/dL

>60 y: 180–380 mg/dL

2.0–4.0 g/L

1.80–3.80 g/L

Transthyretin (thyroxine-binding prealbumin)

10–40 mg/dL

100–400 mg/L

Troponin-I

 

<10 μg/L

Troponin-T

 

0–0.1 μg/L

*Adapted from Cecil Textbook of Medicine, 22nd ed., Table 478–2.

Erythropoietin

Erythropoietin (EPO) is an approximately 34-kDa glycoprotein made mainly in the kidney by fibroblast-like type I interstitial cells in the cortex and outer medulla (p. 757). EPO is a growth factor related to other cytokines, and it acts through a tyrosine kinase-associated receptor (p. 70) to stimulate the production of proerythroblasts in the bone marrow, as well as the development of red cells from their progenitor cells. In fetal life, the liver, rather than the kidney, produces EPO. Even in the adult, Kupffer cells in the liver produce some EPO.

Four lines of evidence indicate that the stimulus for EPO synthesis is a decrease in local PO2. First, EPO synthesis increases with anemia. Second, EPO production increases with lowered renal blood flow. Third, EPO synthesis increases with central hypoxia (i.e., low arterial PO2), such as may occur with pulmonary disease or with living at high altitude (p. 1275). In all three of these cases, local PO2 falls as tissues respond to a fall in O2 delivery by extracting more O2 from each volume of blood that passes through the kidney. Finally, EPO production increases when Hb has a high O2 affinity. Here, the renal cells must lower PO2 substantially before O2 dissociates from Hb. Thus, mutant hemoglobins with high O2 affinities, stored blood (which has low 2,3-DPG levels), and alkaline blood all lead to increased EPO production.

Besides local hypoxia, several hormones and other agents stimulate EPO production. For example, prostaglandin E2 and adenosine appear to stimulate EPO synthesis by increasing intracellular levels of cyclic adenosine monophosphate. Norepinephrine and thyroid hormone also stimulate EPO release. Finally, androgens stimulate—whereas estrogens inhibit—EPO synthesis, explaining at least in part why women in their childbearing years have lower hematocrit levels than do men.

Because the kidneys are the major source of EPO, renal failure leads to reduced EPO levels and anemia. The development of recombinant EPO has had a major impact in ameliorating the anemia of chronic renal failure.

Contributed by Walter Boron

Carbonic Anhydrases

Overview

The carbonic anhydrases (CAs) are a family of zinc-containing enzymes with at least 16 members among mammals; Table 1 lists some of these isoforms. Physiologically, the CAs catalyze the interconversion of CO2 and HCO3, although they can also cleave aliphatic and aromatic ester linkages. Carbonic anhydrase I (CA I) is present mainly in the cytoplasm of erythrocytes. CA II is a ubiquitous cytoplasmic enzyme. CA IV is a GPI-linked enzyme (p. 14) found, for example, on the outer surface of the apical membrane of the renal proximal tubule (p. 858). A hallmark of many CAs is their inhibition by sulfonamides (e.g., acetazolamide).

Reaction Catalyzed by CAs

Before considering the action of carbonic anhydrase, it is instructive to examine the interconversion of CO2 and HCO3 in the absence of enzyme. When [CO2] increases,

Equation 1

image

CO2 can also form HCO3 by directly combining with OH, a reaction that becomes important at high pH values, when [OH] is also high:

Equation 2

image

Because the dissociation of H2O replenishes the consumed OH, the two mechanistically distinct pathways for HCO3 formation are functionally equivalent. Of course, both reaction sequences are reversible. However, in the absence of CA, the overall speed of the interconversion between CO2 and HCO3 is slow at physiological pH. In fact, it is possible to exploit this slowness experimentally to generate and CO2/HCO3 solutions that are temporarily “out of equilibrium” (see webnote Out-of-Equilibrium CO2HCO3 Solutions). Unlike normal (i.e., equilibrated) solutions, such out-of-equilibrium solutions can have virtually any combination of [CO2], [HCO3], and pH in the physiological range.

Structural biologists have solved the crystal structures of several CAs. At the reaction site, three histidines coordinate a zinc atom that, along with a threonine, plays a critical role in binding CO2 and HCO3. In CA II, the fastest of the CAs, a fourth histidine acts as a proton acceptor/donor. Extensive site-directed mutagenesis studies have provided considerable insight into the mechanism of the CA reaction. The CAs have the effect of catalyzing the slow CO2hydration in Equation 1. Actually, these enzymes catalyze the top reaction in Equation 2, the direct combination of CO2 with OH to form HCO3. CA II catalyzes both reactions in Equation 2: [AUTHOR: PLEASE INDICATE WHAT THE SQUARE BOXES SHOULD BE. ARROWS?]

Equation 3

image

CA II has one of the highest turnover numbers of any known enzyme: Each second, one CA II molecule can convert more than 1 million CO2 molecules to HCO3 ions. In the erythrocyte, this rapid reaction is important for the carriage of CO2 from the peripheral blood vessels to the lungs (p. 680). In the average cell, CAs are important for allowing the rapid buffering of H+ by the CO2/HCO3 buffer pair.

Another role of CAs may be in minimizing the pH changes that occur on membrane surfaces that contain transporters that move H+ or image. For example, the extrusion of H+ from the cell by an Na-H exchanger would generate a low pH at the outer surface of the cell. CA IV, with its extracellular catalytic domain, would consume much of the extruded H+

Equation 4

image

and thereby minimize the fall in surface pH.

Preliminary data suggest that the electrogenic Na/HCO3 cotransporters (NBCe1 and NBCe2; see p. 127), and perhaps the other Na+-coupled “HCO3” transporters (the electroneutral NBCs NBCn1 and NBCn2, and the Na+-driven Cl-HCO3 exchanger NDCBE; see p. 129), actually move image. As image enters the cell, the following reaction would not only replenish the image but also generate H+ on the outer surface of the cell:

Equation 5

image

The consequence would be a buildup of H+ on the extracellular surface, as in the case of an Na-H exchanger. An extracellular CA such as CA IV would consume this newly generated H+:

Equation 6

image

The net reaction (summing Equation 5 and Equation 6) would be

Equation 7

image

Thus, when a transporter such as NBCe1 appears to transport two HCO3 into the cell, what is really happening is that one image is being transported by the NBCe1, and one CO2 and one H2O enter the cell by another mechanism. CA enzymes on both the extra- and intracellular surfaces of the cell would minimize pH changes (by consuming or generating H+, as necessary) generated by NBCs and H+ transporters.

CA Deficiency in Humans

In humans, the homozygous absence of normal CA II causes CA II deficiency syndrome, characterized by osteopetrosis, renal tubular acidosis, and cerebral calcification. At least seven different mutations can cause genetic defects. The mutation that is common in patients of Arabic descent causes mental retardation but less severe osteopetrosis. Other patients may carry two different mutations. Indeed, the first three patients described with CA II deficiency syndrome, sisters in the same family, were compound heterozygotes, having received one mutation from their mother and a second from their father.

Although CA I deficiency exists, the homozygous condition has no obvious consequences because CA I and CA II normally contribute about equally to the CA activity in red blood cells.

Nontraditional CAs

Three soluble CAs—VIII, X, and XI—are unusual in that they lack one or more of the three homologous His residues that enzymatically active CAs use to coordinate Zn2+. In addition, two receptor tyrosine phosphatases—RPTPβ and RPTP —have nontraditional CA domains at the location of the ligand binding site. It is likely that these RPTPs are CO2 and/or HCO3 sensors.

Table 1

Some Human Carbonic Anhydrases*

ACZ, acetazolamide; GPI, glycosyl phosphatidylinositol; RBC, red blood cell.

image

*Several additional carbonic anhydrases have been cloned. In some cases, they have not been functionally characterized.

Integral membrane protein with one membrane-spanning segment.

REFERENCE:

Purkerson JM and Schwartz GJ: The role of carbonic anhydrases in renal physiology. Kidney Int. 71:103–115, 2007.

Contributed by Walter Boron

Effect of Fibrinogen on Blood Viscosity

As shown by Figure 18-7, at very low shear rates (i.e., x-axis), the viscosity of whole blood (the value of shear stress divided the shear rate for the red curve) is higher than at high shear rates because of the non-Newtonian nature of whole blood. The “yield shear stress” (the intercept at the y-axis) is the minimum force (i.e., shear stress) that one needs to apply to achieve any blood flow (i.e., shearing) at all.

The yield shear stress increases with the square of the fibrinogen concentration. Fibrinogen is a large glycoprotein (MW ≅ 340 kDa) that is a hexamer which is in turn composed of a dimer of three chains—and a.

All known congenital fibrinogen disorders cause fibrinogen levels to be low. Congenital afibrinogenemia is a rare autosomal-recessive disorder that leads to severely impaired hemostasis. As you would expect, because of the lack of fibrinogen, this disease is associated with near-Newtonian behavior of whole-blood viscosity. Congenital hypofibrinogenemia is a rare genetic condition caused by mutations in one of the three fibrinogen chain genes (α, β, and γ). As a result, the heterozygotes exhibit poor assembly and secretion of mature fibrinogen by the liver.

Acquired alterations in fibrinogen levels include both hypofibrinogenemia and hyperfbrinogenemia. Hypofibrinogenemia can result from liver failure. Elevated fibrinogen levels are part of the acute phase reaction during inflammation. Higher fibrinogen levels are associated with higher risk of ischemic heart disease, although there is not necessarily a cause-and-effect relationship.

Contributed by Emile Boulpaep

von Willebrand’s Disease

The disease is named for the Finnish internist Erik Adolf von Willebrand (1870–1949). In 1925, von Willebrand saw a 5-year-old patient from the Åland Islands in the Sea of Bothnia between Finland and Sweden. Four of her siblings had died from bleeding at an early age, and both her mother and her father came from families with histories of bleeding. Von Willebrand went to the Åland Islands and found 23 of 66 family members had bleeding problems. In his report of the family in 1926, von Willebrand concluded that this was an unknown form of hemophilia. He called it pseudohemophilia. It is also known as vascular hemophilia and angiohemophilia.

Contributed by Emile Boulpaep and Walter Boron

Hemophilias

Deficiencies of certain factors will affect coagulation. Hemophilia A (the most frequent form of hemophilia) is caused by a deficiency in factor VIII:C. The gene for factor VIII is located on the X chromosome, explaining why females are carriers of hemophilia A, whereas males present with the disease.

Hemophilia B or Christmas disease is caused by a deficiency in factor IX.

The very mild Hemophilia C is caused by a deficiency in factor XI. However, a genetic deficiency of a particular factor does not always result in a clotting defect. For instance, factor V as a component of the prothrombinase complex is a procoagulant factor. However, factor V also participates in the inactivation of activated factor VIII (FVIIIa). As a result, mutations in the factor V gene may produce either hemorrhagic or thrombotic phenotypes. The most common thrombophilic mutation is the factor V Leiden mutation that is resistant to degradation by activated protein C. The mutation is associated with increased risk of venous thromboembolism.

Contributed by Emile Boulpaep

Relative Resistance of Arterioles vs Capillaries

In Chapter 17, we introduced the concept of how to compute the aggregate resistance of a group of blood vessels (or resistors) arranged in parallel. We used Equation 17–3 on p. 431, which we reproduce here:

Equation 1

image

If we assume that each of N parallel branches has the same resistance Ri (i.e., Ri = R1 = R2 = R3 = R4 = …), then the overall resistance is

Equation 2

image

Thus,

Equation 3

image

If the aorta gives rise to 107 arterioles (N in the previous equations), each with a resistance (Ri) of 15 × 107 resistance units, then the total resistance of all the capillaries would be 15 resistance units:

Equation 4

image

In Table 19–4 on p. 471 of the textbook, the resistance units were dynes  s  cm–5.

If the same aorta gives rise to 3000 × 107 capillaries (N), each with a resistance (Ri) of 1 × 1010 resistance units, then the total resistance of all the capillaries would be 3 resistance units:

Equation 5

image

Thus, because the capillaries vastly outnumber the arterioles, their aggregate resistance is less, even though their unit resistance is considerably greater.

Contributed by Emile Boulpaep

Derivation of Equation for Mid-Capillary Pressure

On p. 471 of the text, we show Equation 19–3,

Equation 1

image

which we here renumber as Equation 1.

The capillary pressure (Pc) depends on arteriolar pressure (Pa), venular pressure (Pv), the precapillary resistance upstream of the capillary bed (Rpre), and the postcapillary resistance downstream of the capillary (Rpost). This equation describes the hydrodynamic equivalent of the electrical voltage drop (“voltage divider”) across each of two resistances in series, such as the pair of resistors shown in Figure 19-4A.

Returning to our blood vessels, because of conservation of flow along the circuit, the flow (F) across Rpre and Rpost is, by definition, the same. For each of the two resistive elements, Ohm’s law of hydrodynamics (Equation 17–1) states that

Equation 2

image

Equation 3

image

Thus, because F is identical in Equation 2 and Equation 3,

Equation 4

image

This last equation is a simple rearrangement of Equation 1.

image

Contributed by Emile Boulpaep

Nonlinear Relationships among Pressure, Flow, and Resistance

In Figure 19-7A, the broken line shows the theoretical pressure-flow relationship for a rigid tube—flow is directly proportional to driving pressure. For a real vascular bed (red curve), the relationship is nonlinear. First, the curve does not pass through the origin (i.e., flow is zero until driving pressure exceeds critical closing pressure). Second, the curve bends upward because increased transmural pressure widens the vessels. Increasing the vasomotor tone (blue and green curves) has two effects, shifting the critical closing pressure to the right and decreasing the slope (i.e., increasing the resistance once the vessel is open).

In Figure 19-7B, the three curves describe the resistance for the like-colored curves in panel A. Under control conditions (no sympathetic stimulation—red curve), the resistance is infinitely high at pressures below the critical closing pressure because the baseline active tension causes the vessel to collapse. Higher driving pressures cause the vessel to dilate, lowering resistance with the fourth power of radius. Thus, the resistance falls dramatically with increasing driving pressure. Increasing the vasomotor tone (blue and green curves) shifts the pressure–resistance relationships to the right (reflecting the increased critical closing pressures) and up (reflecting the higher resistance throughout).

Contributed by Emile Boulpaep and Walter Boron

Changes in Vessel Volume

The volume (V) of a vessel is the product of its mean cross-sectional area and length (l). Thus, for a cylindrical vessel with a radius of r:

V = πr2 l

Changes in the volume (ΔV) of a vessel—changes such as those that occur during the cardiac cycle or respiratory cycle—generally are due to changes in radius, rather than in length. During the cardiac cycle, the ejection during systole of a stroke volume of 70 ml of blood causes a substantial increase in the radius of the thoracic aorta, but causes the length of the thoracic aorta to increase by only ~1%. Moreover, a 1% decrease in the length of the abdominalaorta compensates for this increase in the length of the thoracic aorta.

In the case of coiled vessels, an increase in vessel length may make a larger contribution to the volume change. We will discuss two examples, vessels in the uterus and in “apical” skin.

(1) The arteries that supply the uterus form arcuate arteries inside the myometrium, from which arise radial arteries oriented towards the lumen of the uterus. As the radial arteries enter the endometrium, they become coiled spiral arteries. These spiral arteries undergo dramatic changes as the endometrium grows during the endometrial cycle (p. 1165 in textbook). During the proliferative phase of the cycle, the spiral arteries grow toward the lumen of the uterus together with the endometrium. During the luteal/secretory phase, the spiral arteries increase their coiling. On page 1178, we discuss the role of these spiral arteries in the maternal blood flow during pregnancy. See also Figure 56-6on page 1179, which shows an unlabelled spiral artery that branches off from the “Maternal artery.”

(2) Another example of coiled vessels is the arteriovenous anastomoses (glomus bodies) in apical skin (see p. 591 in the textbook). These vessels act as shunts between arterioles and venules in the dermis, and play a role in the control of cutaneous blood flow, and thus heat flow from the “core” and the skin (see p. 1244 in the textbook).

In the case of pulmonary vessels, increases in lung volume stretch the blood vessels within the parenchyma of the lung, thereby increasing their length. Imagine that lung volume increases from residual volume (1.5 – 1.9 L as shown in Fig. 26–8 on p. 625) to total lung capacity (4.9–6.4 L as shown in Fig. 26–8), resulting in a 3.4-fold increase in lung volume. If that volume increase represents a uniform increase in all three axes of the lung, it would correspond to a ~50% increase along each dimension.

Contributed by Emile Boulpaep and Walter Boron

Young’s Modulus

The elastic modulus used in Equation 19–7 on page 476 in the textbook is the elastic modulus measured in an experiment in which one stretches an object. The tensile elastic modulus also called Young’s elastic modulus is expressed by the term Y (for Young). Y is a measure of the force needed to stretch a material. If the material that we stretch has a uniform cross-sectional area A, the stress is the force we apply, normalized to the cross-sectional area (F / A). Stress is given in units of force/area, such as dyne/cm2 or newton/m2. One pascal (Pa) is 1 N/m2. Because 1 newton = 105 dynes and 1 m2 = 104 cm2, 1 pascal is 10 dyne/cm2.

The elongation that results from the stress that we apply is expressed as a strain or the change in length of the material normalized to its initial length ([L – L0] / L0). The relationship between stress and strain is given by Equation 19–7 on page 476 in the textbook:

image

Because strain is dimensionless (i.e., length divided by length), the coefficient Y has the same units as stress, dyne/ cm2 or newton/m2 = pascal (Pa).

Table 19–5 on page 476 in the textbook gives the elastic moduli in dyne/cm2, whereas in engineering elastic moduli are often given in pascal. For further comparison, the elastic modulus of cortical long bone, such that of the femur, is 2 × 1010 Pa or 2 × 1011 dyne/cm2, and that of most types steel is only an order of magnitude larger, ~ 2 × 1011 Pa = 2 × 1012 dyne/cm2.

Finally, the elastic modulus of materials can also be obtained by measuring the degree of bending of a material under a given weight. For example, one could suspend a beam between two fixed points at either end of the beam, with the weight placed in the middle. The deflection of the beam is described by an equation analogous to Equation 19–7 (which is only valid for the tensile elastic modulus).

Contributed by Emile Boulpaep and Walter Boron

Axes of Vessel Deformation

Figure 19-10 on page 477 in the textbook shows the three axes along which deformation can occur during the filling of a blood vessel: circumferential (θ), longitudinal (x), and radial (r). Therefore, as a blood vessel is distended by blood filling its lumen, we can consider three stresses and three strains, each with a different orientation. The three strains are:

(i) an elongation of the circumference (Δθ = Δ 2πr), where r is the average of the vessel’s inner radius (r1 as shown in Fig. 17–4 on p. 433) and outer radius (r2)

(ii) an elongation of the length of the vessel (Δx)

(iii) a compression of the thickness of the vessel wall (Δh) in the direction of the radius, that is, a change in the difference between outer and inner radii, Δ(r2 – r1)

As noted in WebNote Changes in Vessel Volume, blood vessels actually change little in length during distension, and therefore we can disregard the strain-stress along the axis x of Figure 19-10. Although thinning of the wall does occur during blood vessel distension, the radial stress from wall compression is usually far less than the circumferential stress; therefore, we will also ignore the strain-stress along the axis r. Thus, we are left to consider only the strain-stress relationship along the circumferential axis (θ), which is given by Laplace’s law in Equation 19–8 on page 477 in the textbook:

T = ΔP • r

Note that in the above equation, stress (i.e., force per unit area) is replaced by tension (i.e., force per unit length).

Contributed by Emile Boulpaep and Walter Boron

Laplace’s Law

In WebNote Axes of Vessel Deformation, we pointed out that, although one could consider as many as three axes of stress-strain relationships for a blood vessel, the most important is the circumferential stress-strain relationship. Laplace’s law illustrates how the circumferential geometry of an elastic tube depends on the balance of the distending force, which is generated by the transmural pressure (ΔP) that pushes the wall outward, and the constricting forcefrom elastic components within the wall that pulls the wall inward. We can compute the distending force acting on a vessel (vessel length = L) from ΔP. For a blood vessel, the ΔP is the transmural pressure, which is the difference between the intravascular pressure and the tissue pressure (see the inset of Fig. 17–4 on p. 433). The pressure is simply the force (F) divided by the inner surface area of the vessel wall, which is (Asurface), 2 • r • L. Because we disregard the changes in thickness of the wall, the present treatment assumes a single radius (r), which is roughly equivalent to the mid-wall radius. Thus,

Equation 1

image

If we normalize this distending force per unit length of vessel, F/L (in dyne/cm), we have:

Equation 2

image

The constricting force that balances the distending force is the circumferential stress in the wall of the vessel. This stress is the force that must be applied to bring together the two edges of an imaginary slit of length L that has been cut through the vessel wall, along the longitudinal axis of the vessel wall (see Fig. 19–11 on p. 477 in the textbook). You can imagine that, as we cut through the vessel wall, we see that the cross-sectional area cut through the wall (Aslit) is Aslit = h • x, where h is the thickness of the wall. This cross-sectional area is highlighted in yellow in Figure 19-10 on page 477 and is labeled “Aslit.” The circumferential stress is the force acting over the area Aslit. However, because we lack information about thickness of the wall, and thus about Aslit, we will ignore the dimension of thickness and instead will focus on the constricting force per unit length of the slit rather than per unit area. Thus, instead of working with the circumferential stress (F / Aslit) the of vessel, we will instead work with the circumferential tension (F / L, in dyne/cm):

Equation 3

image

In order for the system to be in equilibrium, the work done by the distending force must balance the work done by the constricting force. Work is force times displacement. The work done by the distending force (Equation 2) is done over a displacement in the radial axis (Δr), as shown in Figure 19-10 on page 477 of the textbook:

Equation 4

image

The work done by the constricting force (Equation 3) is done over a displacement in the circumferential axis and has the magnitude 2π• Δr:

Equation 5

image

Based on the principles of virtual work and conservation of energy, we conclude that—at equilibrium—the distending work (Equation 4) is the same as the constricting work (Equation 5):

Equation 6

image

Simplifying this equation yields the law of Young/Laplace for a cylinder:

Equation 7

image

or

image

As we shall see on page 637, Equation 27–6 describes Laplace’s law for a sphere, such as a balloon. In this case, the equation of Young and Laplace becomes:

Equation 8

ΔP = 2 T / r

Here, ΔP is the pressure distending the balloon (i.e., the difference between the internal and external pressures), T is the tension within the wall of the balloon, and r is the radius of the balloon. If the sphere were instead a soap bubble, T would be the surface tension.

Contributed by Emile Boulpaep and Walter Boron

Length-Tension vs Strain-Stress Diagrams

In Figure 19-12C on page 478 of the text, we plot the wall tension of a cylindrical blood vessel against its radius (r, in mm). This wall tension is the force per unit length (T, in dyne/cm) of an imaginary slit in the wall of the blood vessel (see Figure 19-10 on p. 477). The radius in Figure 19-12C is related by a constant (2π) to the length of the circumference of the vessel (2πr). Thus, the x-axis is really a length, so that Figure 19-12C is really a length-tensiondiagram similar to that shown for passive tension in muscle (see Figure 9-9C on p. 248 in text). Note, however, that in Figure 9-9C, what we plotted on the y-axis was the unnormalized force (F, in dynes), not the wall tension (in which the force is normalized to the length of an imaginary slit in the vessel).

In contrast, an engineer studying the elastic properties of a solid would use a strain-stress diagram, as shown in Figure 19-9B on page 476, which differs from a length-tension diagram on both the y -and x-axes. On the y-axis of a strain-stress diagram, we plot the force, normalized to the cross-sectional area of the material—we define this parameter as stress (dyne/cm2). On the x-axis, we plot the fractional change in the length of the material—we define this dimensionless parameter as the strain. The following equation (Equation 19–7 on p. 476 of the text) shows that the relationship between stress and strain is linear: Equation 1

image

Note that the proportionality constant in this equation is Young’s elastic modulus (Y), which is a characteristic of a particular material, as shown in Table 19–5 on page 476.

It would be advantageous to convert the length-tension diagram in Figure 19-12C into a true strain-stress diagram because that would allow us to estimate the Young’s elastic modulus for the blood-vessel wall, which in turn would give us insight into the material that makes up the wall. This conversion requires that we convert (1) the y-axis from wall tension (dynes/cm) to stress (dynes/cm2), and (2) the x-axis from absolute length (cm) to fractional change in length (dimensionless). Starting from the definition of stress,

Equation 2

image

We see that we can obtain the stress by dividing wall tension (y-axis in Figure 19-12C) by the wall thickness. Note that the experimental data of Figure 19-12C were obtained on vessels of an experimental animal with vessels diameters that were about half those of the human aorta or vena cava. Assuming that wall thickness of both the aorta and vena cava in the experimental animal were 0.1 cm, we can convert the y-axis of Figure 19-12C to units of stress (dyne/cm2) simply by dividing the wall tension by 0.1 cm. We will perform this conversion separately for the aorta and vena cava and, in the process, compute Young’s elastic modulus for the materials that constitute the wall of the aorta and vena cava.

Aorta: Because the length-tension diagram in Figure 19-12C was not linear, the resulting strain-stress diagram will also be nonlinear. Therefore, we will analyze the relationship between strain and stress at two different points along the curve (i.e., at two different degrees of elongation of the circumference of the vessel wall).

For an elongation of the vessel-wall circumference from a radius of 3.15 mm (the intersection of the curve with the x-axis) to a radius 4 mm, the fractional change in length is (L – L0)/L0= (4 – 3.15)/3.15 = 0.27, or a change of 27%. Achieving this elongation requires that we increase the wall tension from zero to 21,500 dyne/cm. Viewed another way, assuming a wall thickness of 0.1 cm, we must increase the stress from zero to (21,500 dyne/cm)/(0.1 cm) or 215,000 dyne/cm2. Inserting the preceding values into Equation 1 yields an elastic modulus (Y) of ~ 800,000 dyne/cm2. Referring to Table 19–5 on page 476, we see that this value is intermediate between the elastic modulus of smooth muscle and that of elastin, suggesting that both smooth muscle and elastin contribute to the elastic properties of the vessel wall in this low range of elongation of the vessel-wall circumference.

For an elongation of the vessel-wall circumference from a radius of 6 mm (the red point on the red curve in Figure 19-12C) to a radius of 6.1 mm, the fractional change in length is (6.1 – 6.0)/6.0 = 0.017, or a change of 1.7%. Achieving this elongation requires that we increase the wall tension from 120,000 dyne/cm to 140,000 dyne/cm, an increase in wall tension of 20,000 dyne/cm. Viewed another way, and assuming a wall thickness of 0.1 cm, we must increase the stress by (20,000 dyne/cm)/(0.1 cm) or 200,000 dyne/cm2. Inserting the preceding values into Equation 1 yields an elastic modulus (Y) of ~ 12,000,000 dyne/cm2. This estimated elastic modulus somewhat exceeds the typical elastic modulus of elastin, indicating the likely recruitment—in this range of elongation—of some material with a higher elastic modulus (i.e., collagen).

This analysis confirms the conclusion that we reached on page 478 in the text. Thus, depending on the degree of stretch, different materials of different elastic modulus contribute to the overall elastic diagramof the aorta.

Vena cava: For an elongation of the vessel-wall circumference from a radius of 3 mm to a radius of 6 mm, the fractional change in length is (L – L0)/L0= (6 – 3)/3 = 1, or a change of 100%. Achieving this elongation requires that we increase the wall tension from zero to ~1000 dyne/cm. Assuming a wall thickness of 0.1 cm, we must increase the stress from zero to (1000 dyne/cm)/(0.1 cm) or 10,000 dyne/cm2. Inserting the preceding values into Equation 1 yields an elastic modulus (Y) of ~100,000 dyne/cm2, which is in the range of the elastic modulus for pure smooth muscle (see Table 19–5). However, because smooth muscle is arranged in parallel with elastin, it is impossible to pull on one without pulling on the other. Thus, the elastic modulus of ~100,000 dyne/cm2 is unrealistically low. In fact, the stress that we are applying in this range of elongation does not place any increased strain on the smooth muscle and elastic fibers of the vessel wall. Rather, the small increase in wall stress is merely that required to change the geometry of the vena cava from ellipsoidal (i.e., collapsed) to circular (i.e., fully rounded), as discussed at the left/top of page 476 of the textbook.

For an elongation of the vessel-wall circumference from a radius of 6.8 mm (the blue point on the blue curve in Figure 19-12C) to a radius of 6.9 mm, the fractional change in length is (6.9 – 6.8)/6.8 = 0.015, or a change of 1.5%. Achieving this elongation requires that we increase the wall tension from 20,000 dyne/cm to 40,000 dyne/cm, an increase in wall tension of 20,000 dyne/cm. Assuming a wall thickness of 0.1 cm, we must increase the stress by (20,000 dyne/cm)/(0.1 cm) or 200,000 dyne/cm2. Inserting the preceding values into Equation 1 yields an elastic modulus (Y) of ~ 13,600,000 dyne/cm2. The estimated elastic modulus of the vena cava in this range of elongation of the circumference somewhat exceeds the typical elastic modulus of elastin, indicating—as in the case of the aorta—the recruitment of a material with a higher elastic modulus (i.e., collagen).

Contributed by Emile Boulpaep and Walter Boron

Stability of Vessels with Combined Active and Passive Tension

Figure 19-15 on page 480 of the textbook shows that total vascular wall tension from active and passive elements (red curve) is a rising function of relative radius (i.e., length). We can compare the active, passive, and total tensions of a blood-vessel wall with those of skeletal muscle, which are shown in Figure 9-9C on page 248. Active tensions in both skeletal muscle and vascular smooth-muscle cells (VSMCs) plotted against length exhibit a maximum, as shown for skeletal muscle in Figure 9-9D and for VSMCs by the blue curve in Figure 19-15. However, note that the plot of the total tension of skeletal muscle against length (orange curve in Figure 9-9C) exhibits a plateau or a maximum, whereas the plot of total tension of VSMCs against length rises monotonically throughout (red curve in Figure 19-15). The latter phenomenon is due to the increasingly large passive tension component (green curve in Figure 19-15), which rises very steeply as one stretches the wall of the blood vessel.

The absence of a plateau in the total-tension vs radius curve for a blood-vessel wall is of great benefit for the stability of a blood vessel over a wide range of transmural pressures. We can make this point more clearly by considering a length-tension diagram similar to the red curve in Figure 19-15, but in which we plot the absolute radius on the x-axis. The solid red curve in Figure 19-12C is just such a plot. Here, the dashed red line represents the particular transmural pressure of 150 mm Hg that satisfies the physical equilibrium of that vessel at a wall tension of 120,000 dynes/cm and a radius of 6 mm. We could draw a family of dashed lines in Figure 19-15—each one representing one transmural pressure, and passing through the origin (zero tension and zero radius) and intersecting various points on the rising red curve. Each of these dashed lines would represent one of a wide range of transmural pressures that can be in physical equilibrium, each with its own wall tension and vessel radius.

We now return to the red curve in Figure 19-15, which represents a vessel whose VSMCs have been maximally stimulated by norepinephrine. Note that in this plot, the x-axis starts with “100%,” rather than zero. This 100% represents the “unloaded” diameter in which the transmural pressure is zero. This is also the minimum radius that the vessel can achieve under the current conditions of norepinephrine stimulation. Now let us assume that we extend the x-axis of Figure 19-15 to the left to “0%” to obtain the true origin of a diagram such as that in Figure 19-12 (tension = 0, radius 0). Because we have drawn Figure 19-15 for an artery of an experimental animal, we will assume that the 100% radius corresponds to 3 mm = 0.3 cm.

Just as we introduced the concept of drawing a family of dashed lines in Figure 19-12C, we can draw a family of dashed lines in Figure 19-15, with its x-axis artificially extended to the left to 0%. The table below shows the coordinates of the endpoints of just such a family of dashed lines. In each row we show the coordinates of the origin (columns 1 and 2), the coordinates of the intersection of the “dashed line” with the red curve (columns 3 and 4), and finally the appropriate equilibrium pressure in two different units (columns 5 and 6) computed from Laplace’s law (i.e., P = T / r). For example, the first row of data pertains to the unloaded condition. Here, the dashed line is horizontal and connects the new origin at 0% with 100% (i.e., the old origin). Note that because the slope is the transmural pressure, which is zero. Another example is the last row of data, which corresponds to a radius of 200%, or twice the initial radius of 100%. Here, the dashed line has a slope of 275 mm Hg, which is the transmural pressure necessary for the physical equilibrium between the radius of 200% and wall tension of 220,000 dynes/cm. Thus, the table shows that the system can be in equilibrium for transmural pressures ranging from zero to 275 mm Hg, and even beyond.

Coordinates of the origin

Coordinates of intersection of the “dashed line” with red curve

Equilibrium pressure = slope of the dashed line = T / r

Tension

(dynes/cm
)

radius

T (dynes/cm)

radius

P (dyne/cm2)

P (mm Hg)

0

0 % = 0 cm

0

100 % = 0.3 cm

0

0 mm Hg

0

0 % = 0 cm

10,000

120 % = 0.36 cm

28,000

20 mm Hg

0

0 % = 0 cm

30,000

140 % = 0.42 cm

71,000

54 mm Hg

0

0 % = 0 cm

68,000

160 % = 0.48 cm

142,000

106 mm Hg

0

0 % = 0 cm

120,000

180 % = 0.54 cm

222,000

167 mm Hg

0

0 % = 0 cm

220,000

200 % = 0.6 cm

367,000

275 mm Hg

We will now use two examples to illustrate why it is important for blood vessels to contain elastic material with a reasonably high elastic modulus. That is, the green curve in Figure 19-15 must be reasonably steep.

First, consider the hypothetical case in which the active tension of smooth muscle (analogous to the blue curve in Figure 19-15) peaks at a wall tension of 100,000 dynes/cm at a radius of 190% = 0.57 cm, and then falls very steeply to a wall tension of zero at a radius of 195%. If we now sum this new hypothetical blue curve and the existing green curve in Figure 19-15, we would obtain a red curve with a maximum total wall tension of ~150,000 dynes/cm at a radius of 190%, and then falls off at higher radii. At the maximum wall tension, the transmural pressure (P) would be 197 mm Hg. Any transmural pressure in excess of 197 mmHg (i.e., a pressure of P + ΔP) would further dilate the vessel to a radius in excess of 190% (i.e., a radius of r + Δr). The total wall tension required for equilibrium, according to Laplace’s law, would be Trequired = (P + ΔP) × (r +Δr), which would have to be >150,000 dynes/cm. In fact, the actual tension (Tactual) has already passed its peak of 150,000 dynes/cm. Accordingly, Trequired = (P + ΔP) × (r +Δr) > Tactual and a blowout would result (see Figure 19-16B, condition #2 on p. 481).

Second, consider another hypothetical case in which smooth-muscle tension was perfectly constant. That is, the blue curve for active tension (analogous to the blue curve in Figure 19-15) would be a flat horizontal line that might have a wall tension, for example, of 100,000 dynes/cm, irrespective the size of the vessel. If we now sum this new hypothetical blue curve and the existing green curve in Figure 19-15, we would obtain a red curve that would be the same as the green curve, but upwardly displaced by 100,000 dynes/cm. Thus, this new red curve would be flat between a radius of 0% and a radius of 140%. Beyond a radius of 140%, this new red curve would rise with the same slope as the green curve. Let us now assume a starting radius of 140% (0.42 cm) and a wall tension of 100,000 dynes/cm, which would be in physical equilibrium—according to Laplace’s law—at a transmural pressure of 178 mm Hg. If the transmural pressure now falls below 178 mm Hg (i.e., a pressure of P – ΔP), the vessel would tend to narrow below a radius 140% (i.e., a radius of r – Δr). The total wall tension required for equilibrium, according to Laplace’s law, would be Trequired = (P – ΔP) × (r – Δr), which would have to be < 100,000 dynes/cm. In fact, the actual tension (Tactual) is 100,000 dynes/cm. Accordingly, Trequired = (P – ΔP) × (r – Δr) < Tactual and a complete vessel collapse would result (see Figure 19-16B, condition #3 on p. 481).

Limitations of Krogh’s Tissue-Cylinder Model

Krogh’s tissue-cylinder model (shown in Figure 20-4A on p. 485), which describes O2 and CO2 exchange between the capillary and surrounding tissue, is based on several simplifying—but critical—assumptions.

1. The model assumes that the capillary displays cylindrical symmetry around a central axis so that only two spatial dimensions must be considered (i.e., x and r in Figure 20-4A).

2. The model is only correct for the idealized case of capillaries that run in parallel, start and end in the same plane, and carry blood in the same direction.

3. It neglects any longitudinal diffusion of gas along the x-axis within the tissue and the blood. In other words, Krogh assumes that blood flow is the sole mode for gas to move along the x-axis.

4. The model requires that the capillary wall itself does not constitute a rate-limiting barrier to O2 or CO2 transport; that is, the permeability of the endothelial membranes to these gases is similar to the diffusion properties of the bulk phase. In other words, as stated in the textbook under point 4 on p. 484, the radial diffusion coefficient (Dr) is uniform within the blood vessel, the vessel wall, and the surrounding tissue.

5. Krogh assumes that there is no O2 flow into or out of the tissue cylinder across the cylinder’s outer boundary (i.e., beyond the radius, rt). In a regular array of identical tissue cylinders, each neighboring tissue cylinder would have the same PO2 at its outer boundary (Figure 20-4C). Therefore, there would be no PO2 difference to drive O2 diffusion from one tissue cylinder to another.

6. The model assumes a steady state. There are no transients; PO2 is a function of position, not of time.

7. The O2 consumption of the tissue must be constant.

8. The upstream PO2 in the capillary must be constant.

Investigators have generated more complicated models that include different geometries of capillary distribution and also incorporate (1) the effects of pH and PCO2 changes on the O2 affinity of hemoglobin (see pp. 677–678, as well as Figure 29-5 on p. 678), (2) the effects of changes in oxygen solubility on the O2 content of the blood, and (3) the effects of changes in the amount of hemoglobin and its affinity for O2, which even more strongly affects the O2content of the blood.

Contributed by Emile Boulpaep

Fick’s Law

The passive movement of a small solute (X) across any surface can be described by Fick’s law:

Equation 1

image

where JX is the flux of solute (units: moles cm–2 s–1), assuming a positive JX in the direction of increasing distance z. D is the diffusion coefficient in cm2 s–1, and ∂[X]/∂z is the concentration gradient of X (units: moles cm–3 cm–1) along the z-axis. In the case of a solute crossing a capillary wall (see Figure 20-5 on p. 486 of the textbook), we assume that the concentration of the solute in the bulk phase of the capillary ([X]c), as well as in the bulk phase of the interstitial fluid ([X]if), is constant and uniform. We also assume that the diffusion distance along the axis of diffusion (z) is equal to the thickness of the capillary wall (a). We can then rewrite Fick’s law as

Equation 2

image

Because the wall thickness (a) is difficult to determine, one often combines the terms DX and a into a single permeability coefficient P (units: cm s–1), defined as PX = DX/a. The permeability coefficient is an expression of the ease with which a solute crosses a membrane, driven by the concentration difference. Therefore, the flux of a solute becomes

Equation 3

image

This last equation is the same as Equation 20–4 on p. 486 of the textbook.

Contributed by Emile Boulpaep

Effect of Inflammation on Capillary Leakiness

Endothelial tight junctions are regulated by a wide variety of signaling mechanisms, including cytokines; extracellular [Ca2+]; G-proteins; intracellular [cAMP] and [Ca2+]; serine, threonine, and tyrosine kinases; and proteases. The increased endothelial permeability induced by the inflammatory response can result from two general mechanisms. First, increased tension caused by actomyosin/cytoskeletal contractility can change the shape of cells and pull individual endothelial cells apart. Second, intercellular adhesion can be decreased by breakdown or modulation of the intercellular junctions.

Histamine increases vascular permeability by causing transitory gaps of 100–400 nm between adjacent endothelial cells. These gaps occur without any detectable increased tension within the cells. Instead, histamine alters the adhering junctions between endothelial cells, particularly the adhesions that are based on vascular–endothelial cadherin (VE-cadherin). Among the cell–cell adhesion molecules (see p. 18in the textbook), the type I cadherins (i.e., E-, N-, and P-cadherin) associate with cortical actin filaments via α and β catenin, whereas VE-cadherin is a type II cadherin that is linked not only to cortical actin by α and β catenin but also to the intermediate filament protein vimentin (see p. 24 in the textbook) via γ catenin and desmoplakin. Endothelial cells respond to histamine with an increase in intracellular [Ca2+], thereby stimulating the tyrosine phosphorylation of VE-cadherin and γ catenin. How these phosphorylation events affect the link of VE-cadherin with the vimentin cytoskeleton is not known.

CADHERIN TERMINOLOGY:

E-cadherin (in epithelial cells)

N-cadherin (in nerve and muscle cells)

P-cadherin (in placental and epidermal cells)

VE-cadherin (in vascular endothelial cells)

Contributed by Emile Boulpaep

Pore Theory

The “pore theory” has been the main model of capillary permeability for a long time. Many studies have attempted to relate the permeability of solutes of various molecular weights to the geometry of hypothetical fluid-filled transendothelial channels, clefts, fenestrations, and gaps (see p. 483 in the textbook). Investigators have used the whole-organ extraction of molecular probes to estimate the size of a pore that would be necessary to allow movement of these probes at the observed rates. The result can then be used to estimate the number or density of pores, assuming that they have a fixed size and geometry. However, structural studies of capillary endothelial cells of various organs have failed to corroborate the initial formulation of the pore theory. Electron microscopic examination reveals that in tissues such as muscle, transendothelial channels and the junctions between endothelial cells would allow the passage of substances of a molecular radius of 5 nm, exceeding that of inulin. The fenestrae in other tissues—such as the intestine, the kidney, and some glands—have even wider openings, 60–80 nm in diameter. However, except in glomerular capillaries, these openings are mostly covered by a thin diaphragm (see p. 754 in the textbook). Thus, the diverse overall geometry, size, and number of the transendothelial channels, clefts, and fenestrae in endothelia do not agree with the limited sets of pores that have been postulated based on pore theory. On the other hand, investigators measuring solute exchange at the level of a single perfused capillary—which is a far simpler system than a whole organ—are beginning to resolve the discrepancy between whole-organ permeability measurements and the images obtained by electron microscopy.

REFERENCE

Pappenheimer JR: Passage of molecules through capillary walls. Physiol Rev 33:387–423, 1953.

Pappenheimer JR, Renkin EM, and Borrero LM: Filtration, diffusion and molecular sieving through peripheral capillary membranes. A contribution to the pore theory of capillary permeability. Am J Physiol167:13–46, 1951.

Contributed by Emile Boulpaep

Stokes–Einstein Radius

The radius of a spherical molecule that would have a diffusion coefficient equivalent to that of the lipid-insoluble substance (which itself may not be spherical).

Contributed by Emile Boulpaep

Fast vs Slow Pathways for Exchange of Macromolecules across Capillary Walls

Classical transcytosis provides a relatively slow pathway. A fast pathway is provided by the infrequent, transient chains of fused vesicles that happen to span the full width of the endothelial cell. Any degree of differential diffusion through this fast pathway will manifest itself as sieving.

Contributed by Emile Boulpaep

Ernest Henry Starling

Ernest Starling (1866–1927) was born in London and educated at Guy’s Hospital Medical School (M.B., 1889). Upon graduation, he became a demonstrator in physiology at Guys. In 1890, he began part-time work at University College, London, where he soon began a lifelong association with Sir William M. Bayliss.

Starling was Professor of Physiology at University College, London, where he did pioneering work in two cardiovascular areas, the heart and the microcirculation. His name is attached to “Starling’s law of the heart,” which describes the dependence of stroke volume on end diastolic volume (see p. 547 in the textbook), and “the Starling equation,” which describes the movement of fluid across the capillary wall (see p. 489). In addition, Starling and Bayliss together coined the term and introduced the concept of a “hormone” as part of their discovery of secretin, the first hormone. He and Bayliss also showed that intestinal peristalsis is a ganglionic reflex.

His textbook Principles of Human Physiology (1912; 14th ed. with Sir Charles A. Evans, 1968) was a standard physiology textbook in the first half of the 20th century.

REFERENCE

http://www.whonamedit.com/doctor.cfm/1188.html.

Contributed by Emile Boulpaep

Hydraulic Conductivity vs Water Permeability Coefficient

The hydraulic conductivity (Lp) is the coefficient that relates water flux Jv(units: cm3 cm–2 s–1) to the net driving force in units of pressure (ΔP and/or Δπ; units: mm Hg):

image

Thus, the units of Lp are cm s–1(mm Hg)–1. These are terms used in Equation 20–8 and in Table 20–4 on p. 489 of the textbook.

The water permeability coefficient or osmotic permeability coefficient or filtration coefficient (Pf) is the coefficient that relates water flux (Jv; units: moles cm –2 s–1) to the net driving force of water in units of concentration difference (Δ[X]; units: moles cm–3):

Jv = Pf Δ[X]

Thus, the units of Pf are in cm s–1.

What is the relationship between the two proportionality factors Lp and Pf? It can be shown that

image

Here, R is the universal gas constant (0.082055 atm • liter • mole–1 • K–1) = 62.4 mm Hg • liter • mole–1 • K–1), T is the absolute temperature, and Vw is the partial molar volume of water (0.018 liter • mole–1). Note that the PfLpconversion factor depends on temperature. At 37°C,

image

Thus, at 37°C,

Pf= (1,074,667 mm Hg) Lp

This conversion makes sense because multiplying Lp, which is in units of cm s–1(mm Hg)–1, by (mm Hg) yields cm s–1, which are the units of Pf.

Contributed by Emile Boulpaep

Hydraulic Conductivity vs Water Permeability Coefficient

The hydraulic conductivity (Lp) is the coefficient that relates water flux Jv(units: cm3 cm–2 s–1) to the net driving force in units of pressure (ΔP and/or Δπ; units: mm Hg):

image

Thus, the units of Lp are cm s–1(mm Hg)–1. These are terms used in Equation 20–8 and in Table 20–4 on p. 489 of the textbook.

The water permeability coefficient or osmotic permeability coefficient or filtration coefficient (Pf) is the coefficient that relates water flux (Jv; units: moles cm –2 s–1) to the net driving force of water in units of concentration difference (Δ[X]; units: moles cm–3):

Jv = Pf Δ[X]

Thus, the units of Pf are in cm s–1.

What is the relationship between the two proportionality factors Lp and Pf? It can be shown that

image

Here, R is the universal gas constant (0.082055 atm • liter • mole–1 • K–1) = 62.4 mm Hg • liter • mole–1 • K–1), T is the absolute temperature, and Vw is the partial molar volume of water (0.018 liter • mole–1). Note that the PfLpconversion factor depends on temperature. At 37°C,

image

Thus, at 37°C,

Pf= (1,074,667 mm Hg) Lp

This conversion makes sense because multiplying Lp, which is in units of cm s–1(mm Hg)–1, by (mm Hg) yields cm s–1, which are the units of Pf.

Contributed by Emile Boulpaep

Reflection Coefficient Lest we forget … she is still here!

If a semipermeable membrane excludes a solute (Xperfectly, then a concentration difference of the solute X (Δ[X]) generates an osmotic pressure difference that is exactly the same as the theoretically predicted value (see Equation 20–9 on p. 489 of the textbook):

Equation 1

image

Here, R is the gas constant (0.082055 atm • liter • mole–1 • K–1), and T the absolute temperature (K). Equation 1 is known as van’t Hoff’s law. Because RT at 37°C equals 25.4 atm • liter • mole–1 or 19,332 mm Hg •liter • mole–1, an osmotic pressure difference of 1 mM should exert an ideal osmotic pressure (Δπtheor) of 19.3 mm Hg (also see left column on p. 133 in the textbook).

If, on the other hand, the membrane excludes the solute imperfectly, the observed osmotic pressure (Δπobs) is less than the ideal. The reflection coefficient (X) is the ratio of the observed over predicted osmotic pressures:

Equation 2

image

The reflection coefficient is the property of a semipermeable membrane that causes the observed osmotic pressure (πobs)—generated by a concentration difference Δ[X]—to be less than the theoretical osmotic pressure for an ideal membrane (πtheor). The reflection coefficient is dimensionless and ranges between 0 and 1. When = 1, the membrane excludes the solute perfectly and is an ideal osmometer. When = 0, the membrane treats the solute the same as water, and the solute generates no osmotic pressure.

Because the capillary endothelium has multiple “permeability” pathways for macromolecules, and because the permeability is different for different macromolecules, the σ in Equation 20–8 on p. 489 in the textbook (reproduced here)

image

is actually the average reflection coefficient of proteins by the capillary wall.

Contributed by Emile Boulpaep

Null-Point Technique for Measuring Interstitial Pressure

As pointed out in the textbook on p. 491, measuring interstitial pressure (Pif) is technically challenging. If one measures Pif by inserting a small needle percutaneously and immediately records the pressure needed to force fluid out of the needle and into the interstitial fluid, one obtains values of +1 to +5 mm Hg. However, this approach suffers from some weaknesses. First, the very act of pushing fluid out of the needle distorts the narrow interstitial spaces during this acute measurement. Second, the interstitial fluid is actually in several microcompartments that are separated by connective tissue; the fluid injected cannot communicate freely among all of these microcompartments. As a result, the experimenter would have to wait a very long time for the distortions to dissipate.

A “null-point” method overcomes some of the aforementioned difficulties. In this case, the experimenter makes upward and downward adjustments to the pressure inside the probe in an effort to avoid any net movement of fluid into or out of the interstitial fluid (i.e., out of or into the needle). In acute experiments, this null-point method for measuring Pif (as outlined for capillary pressure in the right column of p. 490) yields values of +1 to +2 mm Hg. However, during the next 4 or 5 hours, the measured value drops to –1 to –2 mm Hg. Thus, the acute measurements of Pif—even those using a null-point method—are intrinsically flawed. As outlined in the textbook, Guyton overcame these shortcomings by obtaining a chronic record of Pif.

Total Osmotic Pressure vs Colloid Osmotic Pressure of Plasma

The total osmotic pressure of blood plasma that contains ~290 mOsm/L of solutes can be computed from the van’t Hoff equation (Equation 20–9 on p. 489 of the textbook):

image

As described in webnote “Reflection coefficient”, RT can be expressed as 19,332 mm Hg •liter • mole–1. Thus, for a Δ[X] of 0.29 moles per liter (i.e., 290 mOsm),

image

This pressure of 5597 mm Hg corresponds to 7.4 atm. If distilled water were on the opposite side of the capillary endothelium, and if the capillary wall would reflect all of the solutes in the blood plasma (i.e., if the wall were perfectly impermeable to all solutes but permeable to water), then the osmotic pressure difference across the capillary wall would be 7.4 atm. However, these conditions are not valid. First, most of the solutes in blood plasma are also in the interstitial fluid at approximately the same concentrations. Second, even when small concentration differences exist across the capillary wall for these small solutes such as Na+ or Cl (sometimes called crystalloids), these solutes do not exert any effective osmotic pressure across the capillary wall because they pass with great ease through the capillary wall. That is, these crystalloids have a reflection coefficient σ see webnote Reflection coefficient[CE80]”) of zero.

As stated in the textbook (p. 491), the colloid osmotic pressure (πc) of blood plasma is only 25 mm Hg, which is minuscule compared to the total osmotic pressure (5597 mm Hg). The colloid osmotic pressure is generated solely by concentration difference across the capillary wall of solutes with a reflection coefficient of ~1—that is, the proteins in the blood plasma. The concentration difference for these proteins is ~1.3 mM. Thus,

πc = RT Δ[X]

= (19.3 mm Hg/mM) × (1.3 mM)

= 25 mm Hg

Contributed by Emile Boulpaep

Effects of Changes in Plasma H2O on Colloid Osmotic Pressure

The curves in Figure 20-8 on p. 492 of the textbook exhibit a nonlinear dependence of colloid osmotic pressure on the concentration of plasma proteins. The nonlinearity of the curve becomes clinically significant when a gain or loss of plasma water alters the plasma protein concentration. As expected, identical increases or decreases in plasma H2O—caused by gain or loss in extracellular fluid—exert changes in colloid osmotic pressure that are of opposite sign. However, the changes in colloid osmotic pressure are not identical in magnitude.

For instance, if we assume a normal plasma volume of 3000 mL and plasma protein concentration of 7.0 g/dL, then a 300-mL loss of plasma H2O will increase plasma protein concentration to 7.78 g/dL (a gain of 0.78 g/dL), whereas a 300-mL gain of plasma H2O will decrease plasma protein concentration to 6.36 g/dL (a loss of 0.64 g/dL). These two identical changes in plasma H2O do not result in the same change in colloid osmotic pressure. First, the absolute change in plasma protein concentration is less for 300 mL of overhydration than for 300 mL of dehydration. Second, because the curve in Figure 20-8 is nonlinear, the change in colloid osmotic is larger in the direction of increased protein concentration (i.e., during dehydration, when the curves in Figure 20-8 become steeper) than in the direction of decreased protein concentration (i.e., during an equivalent overhydration).

Contributed by Emile Boulpaep

Donnan Effects across the Capillary Wall

Plasma proteins do more than act as osmotic agents. They also carry net negative charges. Thus, albumin and other plasma proteins can act as the counterbalancing anion for some of the cations in blood plasma. Because the endothelium is relatively impermeable to proteins, the protein concentration of the interstitial fluid is lower than in the capillary. The result is a “Donnan effect” (see pp. 108–109 in the textbook) across the endothelial wall so that at equilibrium the composition of cations and anions in the interstitial fluid is not identical to that in the protein-free plasma of the capillary (see Table 5–2 on p. 108). If we make the simplifying assumption that the capillary wall excludes all proteins from the interstitial fluid, the equilibrium concentration ratios for monovalent cations and anions are

image

Thus, the Donnan effect causes the capillary lumen to contain higher concentrations of cations and lower concentrations of anions than the protein-free solution of the interstitium.

As noted on p. 134, it is a general property of a Gibbs–Donnan equilibrium that after the permeant ions achieve the predicted electrochemical equilibrium across a barrier separating two compartments, the compartment containing the impermeant ions has a higher osmolality than the compartment from which the impermeant ions are excluded (see Figure 5-15 on p. 134). Thus, just as the presence of impermeant proteins in the cytoplasm leads to cell swelling because of Donnan forces, the presence of impermeant anions in the capillary lumen leads to the movement of water from the interstitium into the capillary lumen.

Note that the water movement we have chosen to discuss so far is not due to the osmotic pressure exerted by the plasma proteins per se. Rather, we are considering the osmotic pressure difference that arises from the unequal distribution of Na+ and Cl between capillary lumen (c) and interstitial fluid (if). By analogy to the calculation shown in Equation 5–31 on p. 134, we can calculate the theoretically predicted osmotic force (Δπtheor) caused by the difference in the osmolalities of small, permeant ions (ΔOsm):

ΔπtheorRT ΔOsm

Of course, it was the Gibbs–Donnan equilibrium that set up this difference in total osmolality across the capillary wall. Because the major small ions on either side of the capillary wall are Na+ and Cl,

Δπtheor = RT [([Na+]c + [CI]c) - ([Na+]if + [CI]if)]

Using the values of Table 5–2 on p. 108 for protein-free plasma and interstitial fluid, we have

Δπtheor = RT[([153mM]c + [110mM])c) - ([145mM]if + [116mM]if)]

Δπtheor = RT[2mM]

Because RT at 37°C equals 19,332 mm Hg/M, an osmolality difference of 1 mM exerts an ideal osmotic pressure of 19.332 mm Hg. Thus, the Gibbs–Donnan equilibrium for Na+ and Cl causes a theoretical osmotic pressure difference of

Δπtheor = 38.7 mm Hg (due to Na+ and Cl)

Physiologically, the osmotic difference of 38.7 mm Hg caused by the unequal distribution of small ions is of no consequence for water movement across the capillary wall because the capillary does not reflectNa+ or Cl (i.e., Na = Cl = 0), and therefore these solutes generate no effective osmotic pressure. See webnote for a discussion of reflection coefficients (σ).

As introduced on p. 133, and discussed more fully on p. 490, the only effective osmotic pressure difference across the capillary wall is that caused directly by the plasma proteins acting as solutes. This effective osmotic pressure difference is the colloid osmotic pressure, which tends to pull water into the capillary lumen:

ΔColloid = (c – (if 25 mm Hg (due to colloids)

As shown in Table 20–6 on p. 492, the physiological force opposing the colloid osmotic pressure (Δπ) is the difference between the capillary hydrostatic pressure (Pc) and the interstitial hydrostatic fluid pressure (Pif).

In the preceding paragraph, we saw that because the capillary wall is freely permeable to Na+ and Cl, the only transmural concentration differences that count are those for the colloids. What would happen if the capillary wall were an ideal osmotic membrane, permeable to water but not to any solutes (i.e., neither ions nor proteins)? In such a hypothetical case, the total osmotic pressure difference across the capillary wall would be the sum of the Δtheor (or 38.7 mm Hg) caused by the small ions and the ΔColloid (or 25 mm Hg) caused by the colloids, which totals ~64 mm Hg. Of course, the hydrostatic pressure difference (Pc – Pif) would never be large enough to prevent the net movement of water into the lumen of the typical capillary.

Contributed by Emile Boulpaep

Transcapillary Refill

The opposite of the changes responsible for interstitial edema occurs when there is significant hemorrhage. During severe hemorrhagic hypotension, capillary pressure drops and fluid moves from the tissue space into the vascular space, as discussed on p. 607 in the textbook. This fluid movement—known as transcapillary refill—helps replace the fluid lost in the hemorrhage and thereby serves as a compensatory mechanism for blood loss. The amount of fluid that can be replaced from the interstitium of the skeletal muscle is significant. Because this fluid is cell free, it lowers the hematocrit of the blood, a condition known as hemodilution.

Contributed by Emile Boulpaep

Assumptions of Landis and Pappenheimer

Direct measurements of the four parameters of the Starling equation (PcPifπc, and πif) in organs with low lymph flow such as skeletal muscle indicate that Pc > [Pif + (πc – πif)] throughout the length of the capillary. These values would predict unrealistically high net filtration rates that are incompatible with the observed low lymph flow.

Landis and Pappenheimer estimated only 2–4 L of net total-body filtration (excluding renal glomerular filtration), which agreed well with total lymph flow because of the particular values that they used in the classical Starling equation:

1. Landis and Pappenheimer used arterial and venous values of Pc that can only be correct at the level of the heart. As shown in Figure 17-8 on p. 438 in the text, gravity can add 95 mm Hg to the transmural pressure in feed arteries of the dependent limb and could raise Pc to 90–100 mm Hg, predicting filtration throughout the length of the capillary.

2. Landis and Pappenheimer ignored dynamic changes in Pc. Vasomotion causes Pc to cycle between high and low values, creating alternating periods of filtration and reabsorption.

3. Landis and Pappenheimer assumed low arterial values of πif.

4. Landis and Pappenheimer assumed that values of Pif and πif were clamped in time, whereas the rate of filtration determines Pif and πif. At high filtration rates, Pif would tend to rise, opposing further filtration. At high filtration rates, πif would tend to fall, also opposing further filtration.

In reality, as noted on p. 495, net total-body filtration (excluding renal glomerular filtration) is much less than the 2–4 L estimated by Landis and Pappenheimer because the endothelial barrier is not a single membrane separating two well-stirred clamped compartments and the barrier effectively exhibits osmotic asymmetry. Placing the protein osmotic barrier at the glycocalyx and considering a dynamic range of subglycocalyx colloid osmotic pressures (πsg) independent of bulk πif carries important implications. First, the net filtration pressure is far less than expected from the Starling equation, and this explains why actual lymph flows are less than the net filtration rates postulated from bulk values of PcPifπc, and πif. Second, during reversal of flow (i.e., absorption), protein in the subcalyx fluid should quickly concentrate to prevent all absorption. Thus, overall fluid balance of the interstitium is not primarily maintained by venous absorption but, rather, by lymphatic function.

REFERENCE

Landis EM: Capillary pressure in frog mesentery as determined by microinjection methods. Am J Physiol 75:548–570, 1925–1926.

Landis EM: The capillary blood pressure in mammalian mesentery as determined by the micro-injection method. Am J Physiol 93:353–362, 1930.

Landis EM and Pappenheimer JR: Exchange of substances through the capillary walls. In Handbook of Physiology: Circulation (WF Hamilton and P Dow, eds.), Section 2, Vol. 2, pp. 961–1034. Washington, DC: American Physiological Society, 1963.

Levick JR: Revision of the Starling principle: New views of tissue fluid balance. J Physiol 557:704, 2004.

Pappenheimer JR and Soto-Rivera A: Effective osmotic pressure of the plasma proteins and other quantities associated with the capillary circulation in the hindlimbs of cats and dogs. Am J Physiol 152:471–491, 1948.

Contributed by Ridder Emile Boulpaep

Vasodilation Caused by Increases in [K+]o

Why does the transient increase in [K+]o cause a transient, paradoxical hyperpolarization rather than the depolarization that one might expect from the Nernst equation (Equation 6–5 on p. 152 of the text)?

First, the effect is transient because the increase in [K+]o is short-lived because the ensuing vasodilation will wash away the excess extracellular K+.

Second, the rise in [K+]o causes Vm to become more negative (a hyperpolarization) even though EK (the equilibrium potential for K+) becomes more positive (Equation 6–5 on p. 152). The reason is that the K+conductance of vascular smooth muscle cells depends largely on inwardly rectifying K+ channels (Kir; see Figure 7-20 on p. 206). A peculiar property of Kir channels is that an increase in [K+]o not only causes EK to shift to more positive values but also increases the slope conductance (i.e., the slope of the I-V relationship at EK). Vascular smooth muscle cells normally do not live at EK but, rather, at more positive voltages (–30 to –40 mV), reflecting the contributions from other conductances (e.g., Na+) with more positive equilibrium potentials. In the text, we introduced Equation 6–12, which we reproduce here:

image

Here, GKGNaGCaGCl, etc. represent membrane conductances for each ion, whereas Gm represents the total membrane conductance. Thus, GK/Gm represents the fractional conductance for K+. Therefore, the equation tells us that Vm not only depends on the various equilibrium potentials but also on their respective fractional conductances. Thus, if an increase in [K+]o simultaneously causes (1) a slight decrease in the absolute value of EK and (2) a larger increase in GK, the absolute value of the product (GK/Gm)EK will be larger. Because (GK/Gm)EK is a negative number, the net effect is that the computed value of Vm is more negative (i.e., a hyperpolarization).

In principle, a second phenomenon can contribute to the hyperpolarization. The increase in [K+]o will enhance the activity of the electrogenic Na-K pump, resulting in an increase in the pump’s outward current and therefore a hyperpolarization.

Contributed by Emile Boulpaep

Delayed [Ca2+]i Increase in Response to Endothelin

ET may mediate the second, delayed phase of [Ca2+]i increase through multiple pathways, including Ca2+ channels, nonselective cation channels, kinases, and other second messenger systems.

Contributed by Emile Boulpaep

Angiogenin

Although initially identified in the media of cultured tumor cells, angiogenin is present in normal plasma and it is a mitogen for normal endothelial cells. Angiogenin—a soluble 14-kDa protein—mediates a number of functions in addition to angiogenesis. For example, angiogenin is a microbicidal agent that plays a role in innate immunity.

Angiogenin belongs to a superfamily of ribonucleases (RNases; see p. 102 in the text). Ribonuclease A is the prototype of that family, and angiogenin has been classified as RNase 5. Critical structural differences between angiogenin and the other RNases are apparent in the ribonucleolytic site and the receptor binding site. The ribonucleolytic activity and angiogenic activity of angiogenin can be separated because the protein can be modified and, as a result, retain its ribonucleolytic activity but lose its angiogenic activity.

Angiogenin-responsive endothelial cells express a specific receptor on the cell membrane. After binding to the receptor, some angiogenin is rapidly endocytosed and translocated to the nucleus. Indeed, angiogenin contains a specific nuclear localization sequence. In addition, another portion of the angiogenin bound to its receptor may trigger a number of intracellular signaling cascades. Both pathways lead to cell growth and neovascularization. Angiogenin plays a role in vascularization not only of malignancies but also in nonmalignant pathologies (e.g., in diabetic retinopathy).

Contributed by Emile Boulpaep

Cardiac Currents Carried by Electrogenic Transporters

In addition to the channels summarized in Table 21–1 in the text, numerous other channels are present in heart muscle. The distribution of this large array of time- and voltage-dependent membrane currents (Table 21–1) differs in each of the different cardiac cell types. In addition, there are yet other membrane channels (not summarized in Table 21–1) that are responsible for “background” currents that we have not discussed that are not gated by voltage and not time dependent. These background currents can be modulated by diverse factors and help to shape the action potential.

In addition to all of the channels, cardiac cells have two electrogenic transporters that also carry current across the plasma membranes: the Na-Ca exchanger and the Na-K pump.

The Na-Ca exchanger (NCX; see p. 131) is an electrogenic transporter that normally moves three Na+ ions into the cell in order to extrude one Ca2+ ion, using the electrochemical gradient for Na+ as an energy source for transport. Under these conditions, the Na-Ca exchanger produces an inward or depolarizing current (i.e., a net inward movement of positive charge). However, if this electrochemical gradient reverses, as it transiently does early during the cardiac action potential (due to the positive Vm), the Na-Ca exchanger may be able to reverse and mediate entry of Ca2+ and a net outward current. Later during the cardiac action potential, the Na-Ca exchanger returns to its original direction of operation (i.e., Ca2+ extrusion and inward current). During the plateau phase of the action potential, the inward current mediated by the Na-Ca exchanger tends to prolong the action potential.

The Na-K pump is also an electrogenic transporter, normally moving two K+ ions into the cell for every three Na+ ions that it transports out of the cell, using ATP as an energy source (see p. 119). Therefore, this pump produces an outward or hyperpolarizing current. Cardiotonic steroids (e.g., digoxin and ouabain) inhibit the Na-K pump and thereby cause an increase in [Na+]i. This inhibition also reduces the outward current carried by the pump and therefore depolarizes the cell.

Contributed by W. Jonathan Lederer

Cardiac Currents Carried by Electrogenic Transporters

In addition to the channels summarized in Table 21–1 in the text, numerous other channels are present in heart muscle. The distribution of this large array of time- and voltage-dependent membrane currents (Table 21–1) differs in each of the different cardiac cell types. In addition, there are yet other membrane channels (not summarized in Table 21–1) that are responsible for “background” currents that we have not discussed that are not gated by voltage and not time dependent. These background currents can be modulated by diverse factors and help to shape the action potential.

In addition to all of the channels, cardiac cells have two electrogenic transporters that also carry current across the plasma membranes: the Na-Ca exchanger and the Na-K pump.

The Na-Ca exchanger (NCX; see p. 131) is an electrogenic transporter that normally moves three Na+ ions into the cell in order to extrude one Ca2+ ion, using the electrochemical gradient for Na+ as an energy source for transport. Under these conditions, the Na-Ca exchanger produces an inward or depolarizing current (i.e., a net inward movement of positive charge). However, if this electrochemical gradient reverses, as it transiently does early during the cardiac action potential (due to the positive Vm), the Na-Ca exchanger may be able to reverse and mediate entry of Ca2+ and a net outward current. Later during the cardiac action potential, the Na-Ca exchanger returns to its original direction of operation (i.e., Ca2+ extrusion and inward current). During the plateau phase of the action potential, the inward current mediated by the Na-Ca exchanger tends to prolong the action potential.

The Na-K pump is also an electrogenic transporter, normally moving two K+ ions into the cell for every three Na+ ions that it transports out of the cell, using ATP as an energy source (see p. 119). Therefore, this pump produces an outward or hyperpolarizing current. Cardiotonic steroids (e.g., digoxin and ouabain) inhibit the Na-K pump and thereby cause an increase in [Na+]i. This inhibition also reduces the outward current carried by the pump and therefore depolarizes the cell.

Contributed by W. Jonathan Lederer

Cardiac Na+ Channels

The channel that underlies INa is a classic voltage-gated Na+ channel, with both β1 and subunit (see p. 194 and Figure 7-12A on p. 193 in the text). The cardiac α subunit differs from the brain subunit in having a long cytoplasmic loop connecting the first and second repeats of its six membrane-spanning segments. This long loop has several phosphorylation sites, and it conveys a unique quality to the cardiac channel: Phosphorylation by cAMP-dependent protein kinase (i.e., PKA; see p. 58) stimulates the cardiac channel but inhibits the brain channel.

Contributed by W. Jonathan Lederer, Emile Boulpaep, and Walter Boron

Time Course of Ca2+ Current in Ventricular Muscle

Please refer to Figure 21-4B on p. 508 of the text. The lower panel (red trace) illustrates the time course of the Ca2+ current during an action potential in a ventricular myocyte.

During phase 4, at rest, where Vm is maximally negative, the Ca2+ channels are mostly closed and ICa is a very small inward current. Following the depolarization produced by the very fast Na+ channel during phase 0, the Ca2+channels activate (in ~1 ms), producing the rapid downstroke of the red ICa record in Figure 21-4B.

Next, by a completely separate and time-dependent process, the Ca2+ channels inactivate at positive potentials (half time, 10–20 ms), producing the slower decay of inward current toward the end of phase 1 in Figure 21-4B. Along with the inactivation of the Na+ channels and the opening of the Kv4.3 channels that underlie Ito, the inactivation of Ca2+ channels contributes to the small repolarization that defines phase 1 (see Figure 21-4B). Note that for both activation and inactivation, the cardiac Ca2+ channels are approximately an order of magnitude slower than cardiac Na+ channels.

During phase 2 of the action potential, a small ICa remains, helping to prolong the plateau. This phase is represented by the flat portion of the red ICa record—displaced below the dashed zero-current line in Figure 21-4B.

During phase 3, as Vm returns to negative potentials, two things happen to Ca2+ channels. First, the still-active Ca2+ channels (which were activated by positive Vm values) will go through a process of deactivation (caused by negative Vm values). Second, the Ca2+ channels that had been inactivated during phase 2 now begin to recover from inactivation. The net effect is that a minuscule Ca2+ current remains during phase 4, which takes us back to the beginning of this discussion.

Cardiac K+ Currents

On p. 508 of the text, refer to Table 21–1, which lists five K+ currents:

• IKR, the rapid repolarizing K+ current, is the current arising from heteromultimeric channels composed of HERG and minK subunits.

• IKS, the slow repolarizing K+ current, arises from different heteromultimeric channels composed of KvLQT1 and minK subunits. In older terminology, the “delayed rectifier K+ current” is the sum of IKR and IKS.

• Ito, the transient outward current, occurs during phase 1 of the action potential. Along with the inactivation of the Na+ channels and (slightly later) the inactivation of Ca2+ channels, Ito contributes to the small repolarization that defines phase 1 (see Figure 21-4B). The Shaker-type K+ channel (see p. 201) Kv4.3 carries Ito.

• GIRK—the G-protein–activated, inwardly rectifying K+ channels (part of the IR family of K+ channels; see p. 205)—open in response to acetylcholine. Like many K+ channels, the GIRK channels are composed of two different GIRK subunits clustered as tetramers.

• KATP—the K+ channels inhibited by intracellular ATP (like GIRKs, part of the IR family of K+ channels: see p. 205)—contribute to the background K+ current. The KATP channel is a tetramer composed of two different subunits, as is the case for the GIRK K+ channels and the channels that give rise to the IKR and IKS currents.

Contributed by W. Jonathan Lederer, Emile Boulpaep, and Walter Boron

Contribution of Ionic Currents to Action Potential

Equation 21–2 on p. 509 of the text gives Vm in terms of the weighted conductances of the various ions. Another, less general, way of expressing this concept is the Goldman–Hodgkin–Katz (GHK) equation, which was introduced in Chapter 6. The GHK equation relates Vm to the cellular permeability to different ions (PNaPK, and PCl), as well as to the intra- and extracellular concentration of these ions (see Equation 6–9 on p. 155):

image

Several assumptions underlie the GHK equation, including that (1) the voltage varies linearly with distance through the membrane (constant-field assumption), (2) the ions move independently of one another, (3) the ions are driven only by their electrochemical gradients, (4) the permeabilities are constant, and (5) the total membrane current is zero (i.e., the individual ionic currents sum to zero and Vm is constant). Although we derived this GHK equation with these assumptions—which are not strictly true during the action potential—the equation nevertheless embodies the notion that changes in permeabilities and concentrations of specific ions will affect the shape of the action potential.

The Action Potential of the SA Node

Figure 21-4A illustrates the phases of the SA node action potential and the underlying currents.

During phase 0 of the action potential, ICa activates regeneratively (red record in bottom panel, specifically the rapid downstroke), producing a rapid upstroke of Vm. Underlying ICa are both T-type and L-type Ca2+ channels.

At the transition between phases 0 and 3, ICa then begins to inactivate, a feature that begins the repolarization process. Note that phases 1 and 2 are not seen in the SA node because the inactivation of ICacombines with the slow activation of IK to bring about the phase 3 repolarization of the action potential.

As Vm approaches the maximum diastolic potential at the beginning of phase 4, three slow changes in membrane current take place that underlie phase 4 pacemaker activity:

1. IK deactivates slowly with time (over hundreds of milliseconds), producing a decreasing outward current (see green record in middle panel, specifically the slow decline of outward current during phase 4).

2. ICa contributes inward (i.e., depolarizing) current in the following way. Although Vm has become more negative at the end of phase 3, Vm is still positive enough to keep ICa partially activated (albeit to only a small extent) from the previous action potential. In addition, at the end of phase 3, Vm is still negative enough to cause ICa to recover slowly from inactivation (remember that recovery from inactivation and activation of ICa are independent processes). Thus, as ICa recovers from inactivation over hundreds of milliseconds, there is a small, increasingly inward ICa that tends to depolarize the SA nodal cells during phase 4 (see red record in lower panel, specifically the slow downstroke of inward current during phase 4).

3. If slowly activates as Vm becomes sufficiently negative at the end of phase 3. The result is a slowly growing, inward (i.e., depolarizing) current (see orange record in middle panel, specifically the rapid downstroke of inward current during phase 4).

Thus, during phase 4, the sum of a decreasing outward current (IK) and two increasing inward currents (ICa and If) produces the slow pacemaker depolarization associated with the SA node.

As Vm rises from approximately –65 mV toward the threshold of approximately –55 mV during the pacemaker depolarization, ICa becomes increasingly activated and eventually becomes regenerative, producing the rapid upstroke of the action potential, which takes us back to the beginning of this discussion. Note that the turning off of If tends to oppose the rapid upstroke of Vm during phase 0. However, the activation of ICa overwhelms the turning off of If.

The Action Potential of the Purkinje Fiber

As pointed out in the text, the action potential of the Purkinje fibers depends on four time- and voltage-dependent membrane currents:

• INa (not present in the SA and AV nodal cells)

• ICa

• IK

• If

As in ventricular muscle, the maximum diastolic potential of Purkinje fibers (–80 mV) is sufficiently negative that little, if any, INa remains active during phase 4 of the action potential (see orange curve in Figure 21-4B for ventricular muscle).

In contrast to the SA and AV nodes, the maximum diastolic potential of Purkinje fibers is also sufficiently negative that little, if any, ICa remains active during phase 4 of the action potential (see red curve in Figure 21-4A for the SA node).

Also in contrast to the SA and AV nodal cells, IK deactivates quickly and does not appear to contribute to pacemaker depolarization during phase 4 of the action potential (see green curve in Figure 21-4A for the SA node).

However, at the more negative values of Vm prevailing in Purkinje fiber cells, If activates more fully than in SA or AV nodal cells during phase 4 of the action potential (see blue curve in Figure 21-4A for the SA node). The time-dependent activation of If produces an inward (i.e., depolarizing) current that underlies the depolarization of pacemaker activity. However, this pacemaking happens at a very low rate so that the pacemaker activity of the Purkinje cells does not normally determine the “heart rate” of the ventricles.

Normally, the Purkinje fiber cells are activated by the conducted action potential that passes through the AV node. The rapid upstroke (phase 0) is mediated by INa and ICa. The rapid repolarization (phase 1) occurs because of the inactivation of INa and the activation of Ito (see Table 21–1 on p. 508 of the textbook, and also see p. 506). The plateau (phase 2) mainly reflects a small maintained inward current via INaand ICa. Finally, the repolarization (phase 3) begins with the activation of IK.

As is the case for the other pacemaker tissues in the heart, the intrinsic rhythmicity of the Purkinje fibers is the target of therapeutic agents, neurohormones, and physiologic changes (e.g., changes in heart rate).

Contributed by W. Jonathan Lederer

The Action Potential of the Purkinje Fiber

As pointed out in the text, the action potential of the Purkinje fibers depends on four time- and voltage-dependent membrane currents:

• INa (not present in the SA and AV nodal cells)

• ICa

• IK

• If

As in ventricular muscle, the maximum diastolic potential of Purkinje fibers (–80 mV) is sufficiently negative that little, if any, INa remains active during phase 4 of the action potential (see orange curve in Figure 21-4B for ventricular muscle).

In contrast to the SA and AV nodes, the maximum diastolic potential of Purkinje fibers also is sufficiently negative that little, if any, ICa remains active during phase 4 of the action potential (see red curve in Figure 21-4A for the SA node).

Also in contrast to the SA and AV nodal cells, IK deactivates quickly and does not appear to contribute to pacemaker depolarization during phase 4 of the action potential (see green curve in Figure 21-4A for the SA node).

However, at the more negative values of Vm prevailing in Purkinje fiber cells, If activates more fully than in SA or AV nodal cells during phase 4 of the action potential (see blue curve in Figure 21-4A for the SA node). The time-dependent activation of If produces an inward (i.e., depolarizing) current that underlies the depolarization of pacemaker activity. However, this pacemaking happens at a very low rate so that the pacemaker activity of the Purkinje cells does not normally determine the “heart rate” of the ventricles.

Normally, the Purkinje-fiber cells are activated by the conducted action potential that passes through the AV node. The rapid upstroke (phase 0) is mediated by INa and ICa. The rapid repolarization (phase 1) occurs because of the inactivation of INa and the activation of Ito (see Table 21–1 on p. 508 of the textbook, and also see p. 506). The plateau (phase 2) mainly reflects a small maintained inward current via INaand ICa. Finally, the repolarization (phase 3) begins with the activation of IK.

As is the case for the other pacemaker tissues in the heart, the intrinsic rhythmicity of the Purkinje fibers is the target of therapeutic agents, neurohormones, and physiologic changes (e.g., changes in heart rate).

Contributed by W. Jonathan Lederer

Effect of Acetylcholine on Purkinje Fiber Conduction Velocity

As noted in the text, acetylcholine slows conduction in both the SA and AV nodes. Purkinje fibers are the third (and slowest) group of cells in the heart with intrinsic pacemaker activity. Reports suggest that acetylcholine also decreases the intrinsic activity of Purkinje fibers, presumably via a reduction of If.

Contributed by W. Jonathan Lederer

Nomenclature and Durations of ECG Waves

The various waves of the ECG are named P, Q, R, S, T, and U:

• P wave: a small, usually positive, deflection before the QRS complex

• QRS complex: a group of waves that may include a Q wave, an R wave, and an S wave; note, however, that not every QRS complex consists of all three waves

• Q wave: the initial negative wave of the QRS complex

• R wave: the first positive wave of the QRS complex, or the single wave if the entire complex is positive

• S wave: the negative wave following the R wave

• QS wave: the single wave if the entire complex is negative

• R’ wave: extra positive wave, if the entire complex contains more than two or three deflections

• S’ wave: extra negative wave, if the entire complex contains more than two or three deflections

• T wave: a deflection that occurs after the QRS complex and the following isoelectric segment (i.e., the ST segment that we define later)

• U wave: a small deflection sometimes seen after the T wave (usually of same sign as the T wave)

In addition to the totally qualitative wave designations defined previously, cardiologists may use upper- and lowercase letters as a gauge of the amplitude of Q, R, and S waves:

• Capital letters Q, R, S are used for deflections of relatively large amplitude.

• Lowercase letters q, r, s are used for deflections of relatively small amplitude. For instance: an rS complex indicates a small R wave followed by a large S wave.

The various intervals are

• PR interval: measured from the beginning of the P wave to the beginning of the QRS complex; normal duration is 0.12 and 0.2 s (three to five small boxes on the recording)

• QRS interval: measured from the beginning to the end of the QRS complex, as defined previously; normal duration is <0.12 s

• QT interval: measured from the beginning of the QRS complex to the end of the T wave; the QT interval is an index of the length of the overall ventricular action potential; duration depends on heart rate because the action potential shortens with increased heart rate

• RR interval: the interval between two consecutive QRS complexes; duration is equal to the duration of the cardiac cycle

• ST segment: from the end of the QRS complex to the beginning of the T wave

Contributed by Emile Boulpaep (and requested by Walter Boron)

Willem Einthoven

See http://www.nobel.se/medicine/laureates/1924/index.html.

How Does Digitalis Increase Vagal Tone?

The effect of digitalis drugs to increase vagal tone is probably indirect. Digitalis compounds increases myocardial contractility (see p. 552 in the text), which increases cardiac output. The resulting increase in effective circulating volume (see p. 575) relieves high-pressure (see p. 555) and low-pressure baroreceptor reflexes (p. 567), thereby increasing parasympathetic tone and having the opposite effect on sympathetic tone.

Contributed by Emile Boulpaep and Walter Boron

ECG Rhythm Strip

image

Determining the “rhythm,” as discussed in the box on p. 519, requires an observation over a longer time interval than for the ECG shown in Figure 21-11. This rhythm strip shows leads V1, II, and V5, obtained simultaneously for an extended period. (We thank the Division of Cardiology, University of Maryland School of Medicine, for obtaining this ECG recording from the author.)

Contributed by W. Jonathan Lederer

Triggered Activity

Both the early afterdepolarizations (EADs; mentioned in the text on p. 527) and the delayed afterdepolarizations (DADs; mentioned in the text on p. 528) are the impetus for a form of arrhythmia called triggered activity, which is a spontaneous, abnormal beat or series of beats.

The natural automaticity generated by pacemaker cells (e.g., in the SA node) can occur without any preceding action potentials. In contrast, triggered activity requires at least one preceding action potential. Thus, if an afterdepolarization occurs but does not reach threshold, the cell will eventually return to its resting potential and no triggered activity will occur. If, however, an afterdepolarization reaches threshold, it can generate an unusual action potential from which another afterdepolarization may or may not arise. Thus, it is possible to generate a train of spontaneous depolarizations before the cell finally returns to its resting potential. In the case of a single unusual action potential, the electrical activity can generate an extrasystole. In the case of a train of depolarizations, the electrical activity can generate a run of extrasystoles.

The difference between EADs and DADs is that the additional depolarization in an EAD occurs during phase 2 or 3. On the other hand, with a DAD, the additional depolarization takes place during phase 4. The ventricular tachyarrhythmias seen in long Q-T syndrome are an example of arrhythmias caused by EADs. Some digitalis-induced arrhythmias are examples of arrhythmias caused by DADs.

Contributed by W. Jonathan Lederer

Cardiac Currents Carried by Electrogenic Transporters

In addition to the channels summarized in Table 21–1, numerous other channels are present in heart muscle. The distribution of this large array of time- and voltage-dependent membrane currents (Table 21–1) differs in each of the different cardiac cell types. In addition, there are yet other membrane channels (not summarized in Table 21–1) that are responsible for “background” currents that we have not discussed that are not gated by voltage and not time dependent. These background currents can be modulated by diverse factors and help to shape the action potential.

In addition to all of the channels, cardiac cells have two electrogenic transporters that also carry current across the plasma membranes: the Na-Ca exchanger and the Na-K pump.

The Na-Ca exchanger (NCX; see p. 131 in the text) is an electrogenic transporter that normally moves three Na+ ions into the cell in order to extrude one Ca2+ ion, using the electrochemical gradient for Na+ as an energy source for transport. Under these conditions, the Na-Ca exchanger produces an inward or depolarizing current (i.e., a net inward movement of positive charge). However, if this electrochemical gradient reverses, as it transiently does early during the cardiac action potential (due to the positive Vm), the Na-Ca exchanger may be able to reverse and mediate entry of Ca2+ and a net outward current. Later during the cardiac action potential, the Na-Ca exchanger returns to its original direction of operation (i.e., Ca2+ extrusion and inward current). During the plateau phase of the action potential, the inward current mediated by the Na-Ca exchanger tends to prolong the action potential.

The Na-K pump is also an electrogenic transporter, normally moving two K+ ions into the cell for every three Na+ ions that it transports out of the cell, using ATP as an energy source (see p. 119). Therefore, this pump produces an outward or hyperpolarizing current. Cardiotonic steroids (e.g., digoxin and ouabain) inhibit the Na-K pump and thereby cause an increase in [Na+]i. This inhibition also reduces the outward current carried by the pump and therefore depolarizes the cell.

Contributed by W. Jonathan Lederer

Triggered Activity

Both the early afterdepolarizations (EADs; mentioned in the text on p. 527) and the delayed afterdepolarizations (DADs; mentioned in the text on p. 528) are the impetus for a form of arrhythmia called triggered activity, which is a spontaneous, abnormal beat or series of beats.

The natural automaticity generated by pacemaker cells (e.g., in the SA node) can occur without any preceding action potentials. In contrast, triggered activity requires at least one preceding action potential. Thus, if an afterdepolarization occurs but does not reach threshold, the cell will eventually return to its resting potential and no triggered activity will occur. If, however, an afterdepolarization reaches threshold, it can generate an unusual action potential from which another afterdepolarization may or may not arise. Thus, it is possible to generate a train of spontaneous depolarizations before the cell finally returns to its resting potential. In the case of a single unusual action potential, the electrical activity can generate an extrasystole. In the case of a train of depolarizations, the electrical activity can generate a run of extrasystoles.

The difference between EADs and DADs is that the additional depolarization in an EAD occurs during phase 2 or 3. On the other hand, with a DAD, the additional depolarization takes place during phase 4. The ventricular tachyarrhythmias seen in long Q-T syndrome are an example of arrhythmias caused by EADs. Some digitalis-induced arrhythmias are examples of arrhythmias caused by DADs.

Contributed by W. Jonathan Lederer

Inertial Component of Flow in the Aorta

As discussed in webnote 2e-0437--Impedance of Blood Flow (1e-0436).doc, when pressure and flow fluctuate, the simple Ohm’s lawlike relationship ΔP = F × R should be replaced by ΔP = F × Z, where Z is a complex mechanical impedance. Within the impedance term are components that describe compliant impedance, viscous (or resistive) impedance, and inertial impedance.

In Figure 22-1B on p. 531 in the text (and also in the top panel of Figure 22-2 on p. 533), the pressure curves for the left ventricle (blue curve) and the aorta (red curve) cross over in the middle of the ejection phase. Yet, the aortic valve does not close at that instant, despite the apparent reversal of the pressure gradient. The flow curve in the aorta (black curve in the second panel of Figure 22-2) is further proof that the aortic valve remains open: Even after the apparent pressure gradient reverses just past the peak ejection, blood flow remains positive during the remainder of the ejection phase.

Blood flow in the aorta is a good example in which the flow dynamics is primarily inertial in character. During ejection, the aorta receives the entire stroke volume of the left ventricle at a high linear velocity. Thus, the kinetic energy (½ mv2) is large because aortic flow carries a large mass of blood (m) at a high velocity (v). The compliance term (mostly radial compliance) within the complex impedance of the aorta is not as important because axial flow is much more important than radial flow. Finally, the viscous resistance term within the complex impedance of the aorta is minimal because the radius of the aorta is large and resistance is inversely proportional to r4 (see Equation 17–11 on p. 434). Thus, in the aorta, the inertial impedance becomes the major determinant of the overall impedance Z.

The dominance of the inertial impedance is illustrated by the finding that the aortic valve does not close despite a reversal of the pressure gradient between the left ventricle and the aortic arch as recorded by indwelling catheters with side openings. As shown in Figure 17-11 (see p. 440), the “side pressure” measurement does not take into account the kinetic momentum (i.e., Bernouilli forces) along the axis of blood flow. If we had included the inertial component in our measurement of ΔP—by measuring pressure with catheters whose face upstream, as shown by the uppermost catheter in Figure 17-11—we would observe no reversal of the pressure. Thus, there is no violation of the principle that ΔP = F × Z; that is, blood is still flowing down an energy gradient.

Contributed by Emile Boulpaep

Mechanical Impedance of Blood Flow

We began this chapter drawing an analogy between the flow of blood and electrical current, as described by Ohm’s law of hydrodynamics: ΔP = F × R. We now know that there are other factors that influence pressure. In addition to the flow resistance R (electrical analogy = ohmic resistor), we must also consider the compliance C (electrical analogy = capacitance) as well as the inertiance L (electrical analogy = inductance). A similar problem is faced in electricity when dealing with alternating (as opposed to direct) currents. In Ohm’s law for alternating currents, E = I × Z, where Z is a complex quantity called the impedance. Z depends on the electrical resistance R, the electrical capacitance C, and the electrical inductance L. Similarly, for blood flow, we can write ΔP = F × Z, where Z is also a complex quantity, called mechanical impedance, that includes

Compliant impedance that opposes volume change (compliance of the vessel);

Viscous (or resistive) impedance that opposes flow (shearing forces in the liquid). This term is the “R” of Ohm’s law of hydrodynamics: ΔP = F × R (Equation 17–1 on p. 431); and

Inertial impedance that opposes a change of flow (kinetic energy of fluid and vessels).

Considering all these sources of pressure, we can state that the total pressure difference at any point in time, instead of being given by Ohm’s law, is

Equation 1

image

The Pgravity term in the previous equation is discussed on p. 437 in the Section titled “Gravity Causes a Hydrostatic Pressure Difference When There Is a Difference in Height.”

Distortion of Propagated Waves

The peak of the arterial pressure profile gets taller and sharper as we move away from the heart (see Figure 22-6A on p. 538 of text). There are three major reasons for this:

1. The higher frequency components of the wave travel faster. The pressure wave in the arch of the aorta is far more complex than a simple sine or cosine wave. Nevertheless, we can think of the complex waveform in the aortic arch as being the algebraic sum of many individual sine and cosine waves, each with its own amplitude, frequency, and phase (i.e., how much the wave’s peak is shifted left or right along the time axis). The precise mathematical method by which complex waveforms are broken down into simpler components is called Fourier analysis. Waves of higher frequency propagate with a greater velocity than waves of lower frequency. Thus, the farther the high-and low-frequency waves travel down the vessel, the more separated they become from one another (a process termed dispersion; see Figure 22-6A). Also, even if we examine a single sine wave—which, of course, has a single frequency—the position of the peak will shift backwards as the wave travels down the vessel (this is called a phase shift). The magnitude of the phase shift increases with increasing frequency. Furthermore, the blood vessels produce more damping on the peaks of higher frequency waves than on those of low-frequency waves (see Figure 22-6A). When we summate these various effects on the sine wave and cosine wave components downstream, the reconstructed pressure wave has a different (i.e., distorted) shape than the original wave.

2. The vessels become stiffer toward the periphery, increasing wave velocity, especially for higher frequency components. Vessel walls become stiffer progressing down the vascular tree. The smaller peripheral vessels have a thicker wall relative to their luminal diameter. Waves propagate faster in stiff vessels than in compliant ones. Thus, pressure waves travel faster in smaller arteries. Increased stiffness speeds up high-frequency waves more than low-frequency ones (see Figure 22-6A).

3. The pressure waves bounce off the end of the arterial tree and reflect back up the vessels. The vascular circuit is not infinite, nor does the end of the vasculature have a device that completely absorbs a transmitted pressure wave. Therefore, some of the wave must reflect back up the artery and summate with the waves traveling in the forward direction. By themselves, reflected waves are not large enough to explain the large distortions in the arterial pressure profile. Moreover, if the wave distortions were due only to reflections, then the reflections at any one point in the vascular tree would have to be stable with time (i.e., the reflections would have to create a “standing wave”). However, the vascular tree is far too short to create standing waves of the appropriate frequencies. In addition, to create a standing wave, the heart would have to beat with an absolutely invariant rhythm, which, of course, is not the case. Thus, reflections make only a small contribution to the distortion.

Contributed by Emile Boulpaep

Distortion of Propagated Waves

The peak of the arterial pressure profile gets taller and sharper as we move away from the heart (see Figure 22-6A on p. 538 of text). There are three major reasons for this:

1. The higher frequency components of the wave travel faster. The pressure wave in the arch of the aorta is far more complex than a simple sine or cosine wave. Nevertheless, we can think of the complex waveform in the aortic arch as being the algebraic sum of many individual sine and cosine waves, each with its own amplitude, frequency, and phase (i.e., how much the wave’s peak is shifted left or right along the time axis). The precise mathematical method by which complex waveforms are broken down into simpler components is called Fourier analysis. Waves of higher frequency propagate with a greater velocity than waves of lower frequency. Thus, the farther the high-and low-frequency waves travel down the vessel, the more separated they become from one another (a process termed dispersion; see Figure 22-6A). Also, even if we examine a single sine wave—which, of course, has a single frequency—the position of the peak will shift backwards as the wave travels down the vessel (this is called a phase shift). The magnitude of the phase shift increases with increasing frequency. Furthermore, the blood vessels produce more damping on the peaks of higher frequency waves than on those of low-frequency waves (see Figure 22-6A). When we summate these various effects on the sine wave and cosine wave components downstream, the reconstructed pressure wave has a different (i.e., distorted) shape than the original wave.

2. The vessels become stiffer toward the periphery, increasing wave velocity, especially for higher frequency components. Vessel walls become stiffer progressing down the vascular tree. The smaller peripheral vessels have a thicker wall relative to their luminal diameter. Waves propagate faster in stiff vessels than in compliant ones. Thus, pressure waves travel faster in smaller arteries. Increased stiffness speeds up high-frequency waves more than low-frequency ones (see Figure 22-6A).

3. The pressure waves bounce off the end of the arterial tree and reflect back up the vessels. The vascular circuit is not infinite, nor does the end of the vasculature have a device that completely absorbs a transmitted pressure wave. Therefore, some of the wave must reflect back up the artery and summate with the waves traveling in the forward direction. By themselves, reflected waves are not large enough to explain the large distortions in the arterial pressure profile. Moreover, if the wave distortions were due only to reflections, then the reflections at any one point in the vascular tree would have to be stable with time (i.e., the reflections would have to create a “standing wave”). However, the vascular tree is far too short to create standing waves of the appropriate frequencies. In addition, to create a standing wave, the heart would have to beat with an absolutely invariant rhythm, which, of course, is not the case. Thus, reflections make only a small contribution to the distortion.

Contributed by Emile Boulpaep

“Pumping Work” Done by the Heart

In applying Equation 22–4 (on p. 543 of the text)

W = P · ΔV

to the external work done by the heart, we assumed that the left ventricle pumps against a constant aortic pressure. In reality, of course, the aortic pressure is not constant. Thus, in Equation 22–4 we also should have included a V· ΔP term to take into account the changing aortic pressure so that Equation 22–4 becomes

W = P · ΔV + ΔP · V

Nevertheless, our calculation of work using the area of the loop in Figure 22-10C (p. 543) does take this extra term into account.

Contributed by Emile Boulpaep

Carl J Wiggers (1883–1963)

Wiggers was the Chair of the Department of Physiology at Western Reserve University in Cleveland (1918–1953)—following John Macleod (1903–1918) in that position (see WebNote on Frederick Banting and Charles Best). He was the mentor of several dozen renown physiologists, one of whom was Corneille Heymans (see WebNote on Corneille Jean Francois Heymans).

Wiggers made numerous contributions to the field of cardiovascular physiology, one of which was the development of the pressure-volume loop, also known as the Wiggers Diagram.

REFERENCES:

http://physiology.case.edu/pdf/CASEhistory.pdf

http://en.wikipedia.org/wiki/Carl_J._Wiggers

http://www.the-aps.org/about/pres/introcjw.htm

Contributed by Walter Boron

Tension Heat

From the physical sciences, we know that we can define external mechanical work as the product of force and displacement. In the case of the heart, the external mechanical work is the product of the changes in pressure (i.e., force per unit area) and volume (i.e., displacement in three dimensions):

W = P · ΔV + ΔP · V

This is the equation we introduced in webnote 2e-0543--Pumping Work Done by the Heart (1e-0524a).doc. The first term is particularly important during isovolumetric contraction, and the second term is particularly important during the ejection phase. However, as we noted on p. 544, the heart consumes more energy than we can account for by the external mechanical work in the previous equation.

Imagine that the left ventricle had to maintain itself for some time at point D in Figure 22-9. Here, there is neither a change in pressure nor a change in volume so that the previous equation would tell us that the heart is performing no external mechanical work. Maintaining this isometric tension is like an extended arm holding a weight without lifting it: We do no external mechanical work, yet we burn ATP—tension heat. Moreover, this tension heat is proportional not only to the mass of the weight but also to how long we hold it. In contrast, if we transferred the weight from our arm to a nail in the wall, the nail could hold that weight for an indefinite period without consuming any energy.

If the path DEF in Figure 22-9 (i.e., ejection) were perfectly horizontal (a volume decrease at constant pressure), the external mechanical work would be P ΔV (i.e., the second term in the previous equation). However, merely maintaining this constant pressure during the period of ejection requires energy—tension heat. Moreover, just as in our analogy with the extended arm holding the weight, the tension heat of the heart is proportional to the pressure (i.e., the tension) and the time the pressure is maintained, as described by the third term in Equation 22–6 on p. 544. Returning to Figure 22-9, we can increase the tension heat by elevating the path DEF (i.e., raising the pressure) and/or by increasing the time interval (Δt) between D and F (i.e., slowing the ejection of the same volume). In practice, the Δt for each ejection might increase with aortic stenosis, which increases the ejection time. Alternatively, cumulative Δt (i.e., the aggregate Δt over a minute’s time) will increase with a high heart rate. Thus, performing the same external work at a high heart rate requires more total energy consumption that performing the same work at a low heart rate.

Contributed by Emile Boulpaep

Phospholamban

Phospholamban (PLN or PLB) is a 6-kDa integral membrane protein with 52 amino acids and a single transmembrane domain. The protein kinases that can phosphorylate phospholamban include protein kinase A, sarcoplasmic reticulum CaM kinase (SRCaM kinase—a distinct Ca2+-calmodulin-dependent protein kinase), and a cGMP-dependent kinase (see p. 69 in the text for a discussion of soluble guanylyl cyclases).

As noted in the text, the phosphorylated PLN can exist as a homopentamer that may function in the SR as an ion channel. Structural biology studies of PLN indicate that at its narrowest point, the pore radius is 1.8 Å.

Contributed by Emile Boulpaep

Cardiac Currents Carried by Electrogenic Transporters

In addition to the channels summarized in Table 21–1, numerous other channels are present in heart muscle. The distribution of this large array of time- and voltage-dependent membrane currents (Table 21–1) differs in each of the different cardiac cell types. In addition, there are yet other membrane channels (not summarized in Table 21–1) that are responsible for “background” currents that we have not discussed that are not gated by voltage and not time dependent. These background currents can be modulated by diverse factors and help to shape the action potential.

In addition to all of the channels, cardiac cells have two electrogenic transporters that also carry current across the plasma membranes: the Na-Ca exchanger and the Na-K pump.

The Na-Ca exchanger (NCX; see p. 131 of the text) is an electrogenic transporter that normally moves three Na+ ions into the cell in order to extrude one Ca2+ ion, using the electrochemical gradient for Na+ as an energy source for transport. Under these conditions, the Na-Ca exchanger produces an inward or depolarizing current (i.e., a net inward movement of positive charge). However, if this electrochemical gradient reverses, as it transiently does early during the cardiac action potential (due to the positive Vm), the Na-Ca exchanger may be able to reverse and mediate entry of Ca2+ and a net outward current. Later during the cardiac action potential, the Na-Ca exchanger returns to its original direction of operation (i.e., Ca2+ extrusion and inward current). During the plateau phase of the action potential, the inward current mediated by the Na-Ca exchanger tends to prolong the action potential.

The Na-K pump is also an electrogenic transporter, normally moving two K+ ions into the cell for every three Na+ ions that it transports out of the cell, using ATP as an energy source (see p. 119). Therefore, this pump produces an outward or hyperpolarizing current. Cardiotonic steroids (e.g., digoxin and ouabain) inhibit the Na-K pump and thereby cause an increase in [Na+]i. This inhibition also reduces the outward current carried by the pump and therefore depolarizes the cell.

Contributed by W. Jonathan Lederer

Contractility in Patients

For two reasons, it is not practical to assess cardiac performance in a patient by using the approaches outlined in Figures 22–11 and 22–12. First, with patients, we do not deal with isolated muscles in vitro. Second, the aforementioned figures require that we study the muscle under the artificial conditions of only isometric (i.e., preloaded) or only isotonic (i.e., afterloaded) contractions. During a full cardiac cycle, of course, these conditions alternate.

Contributed by Emile Boulpaep

Using ESPVR in Lieu of an Isometric Starling Curve

The end-systolic pressure–volume relation (ESPVR) is a load-insensitive index of left ventricular contractility. This relation has been measured in small animal species using a conductance–catheter technique—whereby several electrodes along a catheter are used to compute the electrical conductance, which can be converted to absolute ventricular volume—and indwelling pressure gauges. Sato et al. (1998) tested the ESPVR under different contractility states: baseline condition, after sympathectomy, and after β-blockade in rats. The general slope of the curve decreased with decreasing contractility—that is, modestly after sympathectomy and strongly after β-blockade. The curve was not always perfectly straight. The ESPVR was slightly convex toward the pressure axis under baseline conditions, linear under sympathectomized conditions, and slightly concave toward the pressure axis under β-blockade conditions.

REFERENCE

Feldman MD, Mao Y, Valvano JW, Pearce JA, and Freeman GL: Development of a multifrequency conductance catheter-based system to determine LV function in mice. Am J Physiol Heart Circ Physiol279:H1411–H1420, 2000.

Georgakopoulos D and Kass DA: Estimation of parallel conductance by dual-frequency conductance catheter in mice. Am J Physiol Heart Circ Physiol 279:H443–H450, 2000.

Ito H, Takaki M, Yamaguchi H, Tachibana H, and Suga H: Left ventricular volumetric conductance catheter for rats. Am J Physiol Heart Circ Physiol 270:H1509–H1514, 1996.

Kubota T, Mahler CM, McTiernan CF, Wu CC, Feldman MD, and Feldman AM: End-systolic pressure–dimension relationship of in situ mouse left ventricle. J Mol Cell Cardiol 30:357–363, 1998.

Sato T, Shishido T, Kawada T, et al.: ESPVR of in situ rat left ventricle shows contractility-dependent curvilinearity. Am J Physiol Heart Circ Physiol 274:H1429–H1434, 1998.

Uemura K, Kawada T, Sugimachi M, et al.: A self-calibrating telemetry system for measurement of ventricular pressure–volume relations in conscious, freely moving rats. Am J Physiol Heart Circ Physiol287:H2906–H2913, 2004.

Triggered Activity

Both the early afterdepolarizations (EADs; mentioned in the text on p. 527) and the delayed afterdepolarizations (DADs; mentioned in the text on p. 528) are the impetus for a form of arrhythmia called triggered activity, which is a spontaneous, abnormal beat or series of beats.

The natural automaticity generated by pacemaker cells (e.g., in the SA node) can occur without any preceding action potentials. In contrast, triggered activity requires at least one preceding action potential. Thus, if an afterdepolarization occurs but does not reach threshold, the cell will eventually return to its resting potential and no triggered activity will occur. If, however, an afterdepolarization reaches threshold, it can generate an unusual action potential from which another afterdepolarization may or may not arise. Thus, it is possible to generate a train of spontaneous depolarizations before the cell finally returns to its resting potential. In the case of a single unusual action potential, the electrical activity can generate an extrasystole. In the case of a train of depolarizations, the electrical activity can generate a run of extrasystoles.

The difference between EADs and DADs is that the additional depolarization in an EAD occurs during phase 2 or 3. On the other hand, with a DAD, the additional depolarization takes place during phase 4. The ventricular tachyarrhythmias seen in long Q-T syndrome are an example of arrhythmias caused by EADs. Some digitalis-induced arrhythmias are examples of arrhythmias caused by DADs.

Contributed by W. Jonathan Lederer

Élie de Cyon and Carl F. Ludwig

Élie de Cyon

Born into a Jewish community in Telsch, Lithuania (then a part of the Russian Empire), not far from the German border, Ila Faddevitch Tsion (1842–1910)—aka Élie de Cyon (French) or Elias Cyon (English)—was a tragic figure. He studied medicine in Warsaw and Kiev before moving to Berlin, where he received his doctorate in medicine and surgery. After Cyon joined the Medical–Surgical Academy in St. Petersburg and earned a second doctorate (in medicine) in 1865, the Ministry of Education in Russia sent him to Paris to study physiology, presumably with Claude Bernard. Afterwards, Cyon moved to Leipzig to work with Carl Ludwig. There, he developed the isolated, perfused, working frog heart and with Ludwig discovered the baroreflex. In 1866, Cyon described the inhibitory effect of the vagus nerve on cardiac muscle. The branch of the vagus that innervates the heart is known as the nerve of Ludwig–Cyon. With his brother M. Cyon, Cyon in 1867 discovered the nerve that stimulates the heart. Cyon observed, but did not document, the response of the heart to increased filling pressure, thereby anticipating by a few years the Frank–Starling mechanism.

In 1867, Cyon again journeyed to St. Petersburg, and he was Professor of Physiology at Saint Petersburg University from 1868 to 1872. During this time, he was a mentor of and had a major influence on I.P. Pavlov (1849–1936), who mastered surgical techniques and began his studies of circulation and digestion with Cyon. In 1974—against the will of the faculty—he was appointed Professor and Chair of Physiology at the Medical–Surgical Academy of St. Petersburg. However, majority nihilist students demanded Cyon’s removal, chaos erupted, troops were called in, and the academy was closed. Cyon requested and received a transfer to Leipzig, but he was dismissed from Russian service in 1875. He received an invitation from Claude Bernard to move to France, where Cyon performed his research and obtained his third doctorate. However, after Bernard’s death in 1878, Cyon fell out of favor, left science, and became involved in a wide range of activities, including newspaper work and an effort to unite French and Russian interests against Germany. He moved in high social circles and died in Paris in 1919, never having returned to Russia.

Carl F. Ludwig

Ludwig (1816–1895) was born in Witzenhausen, Germany, and obtained his doctorate in medicine in Marburg in 1839. In 1865, he became the inaugural professor of physiology at Leipzig, a position that he held until his death. Along with a few contemporaries—von Helmholtz, von Brücke, and de Bois-Reymond—Ludwig rejected the view that special biological laws applied to animals, and instead he championed the view that the laws of physics and chemistry applied also to animals—a philosophy necessary for the further development of physiology as a science. Ludwig invented the kymograph for recording changes in blood pressure—the first graphical output in the field of physiology. His research touched many areas of physiology, his institute became a center of physiological research, and he trained a large number of investigators from throughout Europe. The papers from his institute usually bear only the name of his pupils!

REFERENCE

http://www.speedylook.com/%C3%89lie_de_Cyon.html

http://en.wikipedia.org/wiki/Carl_Ludwig

Shilinis IuA: I. P. Pavlov’s teacher of physiology I. F. Tsion (1842–1912). Zh Vyssh Nerv Deiat Im I P Pavlova 49:576–588, 1999. [Article in Russian, abstract in English]

Contributed by Walter Boron

Corneille Heymans

Corneille Jean François Heymans (1892–1968) was born in Ghent, Belgium. He obtained his doctorate in medicine at the University of Ghent in 1920. Afterwards, he worked with E. Gley at the Collège de France in Paris, M. Arthus in Lausanne, H. Meyer in Vienna, E. H. Starling in University College London, and C.F. Wiggers at Western Reserve University in Cleveland. In 1922, Heymans returned to Ghent to become a Lecturer in Pharmacodynamics, and in 1930 he succeed his father as Professor of Pharmacology.

For his work on the carotid and aortic bodies and their role in the regulation of respiration, he received the 1938 Nobel Prize in Physiology or Medicine.

REFERENCE

http://nobelprize.org/nobel_prizes/medicine/laureates/1938.

Contributed by Walter Boron

Receptor Potential of Baroreceptors

As noted in the text, increased intraluminal pressure (actually an increase in tension in the vessel wall) triggers an inward current that generates a depolarization (i.e., receptor potential). The inward current that underlies the receptor potential is not sensitive to blockers of voltage-gated Na+, K+, or Ca2+ channels but is blocked by Gd3+. The channels inhibited by Gd3+ may be the mechanoelectrical transducers in baroreceptor nerve endings. TRPC1, -3,-4,-5,-6, and-7 channels are present in the plasma membrane of the cell bodies of the aortic baroreceptor neurons in the nodose ganglion. Although these channels are stretch sensitive, the cell body presumably is not subject to stretch. On the other hand, TRPC1 and TRPC3 are present in the fine nerve endings of myelinated A-type fibers that are tonically active in the normal range of arterial blood pressures. Thus, these channels could be responsible for sensory transduction. An alternate view is that such TRPC channels may set the sensitivity of the baroreceptor.

On the other hand, several types of K+ channels modulate the sensitivity of the baroreceptor nerve endings to stretch. By patch clamping the cell bodies of the aortic arch baroreceptors neurons, investigators have found that these K+ currents include Ca2+-activated K+ currents (KCa channels; see p. 203 in the text) and A currents (Kv channels sensitive to 4-aminopyridine; see p. 201). The various types of K+channels found at the cell bodies may also be functional at the peripheral sensory endings. Agents that block these K+ channels cause a sustained depolarization of the baroreceptor endings, decreasing the pressure sensitivity of the baroreceptors, presumably by inactivating other voltage-gated channels.

REFERENCE

Glazebrook PA, Schilling WP, and Kunze DL: TRPC channels as signal transducers. Pflügers Arch 451:125–130, 2005.

Contributed by Emile Boulpaep

Identifying the Medullary Cardiovascular Control Center

Investigators have established the overall importance of the medullary cardiovascular center in cardiovascular control using a variety of technical approaches:

1. Successive transections of the brain and spinal cord. Transecting the brain stem at the level of the pons does not affect the maintenance of normal blood pressure. However, transecting the medulla below the level of the facial colliculus (Figure 23-4A on p. 559 of the text) causes blood pressure to fall. Lower sections produce even deeper drops in pressure, down to ~40 mm Hg. The lowest pressures occur after transection at the level of the first cervical segment (i.e., spinal shock).

2. Stimulation of the bulbopontine region. Stimulating random cells in the medulla or pons can produce either pressor (i.e., increased blood pressure) or depressor responses. In general, the pressor areas extend more rostrally and more laterally than the depressor areas.

3. Recording from single neurons. Some neurons in medullary nuclei or other medullary areas exhibit electrical activity that is synchronous with the pulse. However, it is difficult to trace the activity of a specific neuron to a specific sensory input (e.g., a specific carotid baroreceptor) or to the control of a specific effector (e.g., the smooth muscle of a particular blood vessel). These recordings have not revealed any somatotopic organization (p. 418).

4. Labeling of pathways. Following the microinjection of radiolabeled amino acids into neurons of the NTS, the anterograde transport of the label allows tracking of the efferent pathway by autoradiography. Conversely, by exposing the cut central end of the carotid sinus nerve to horseradish peroxidase, it is possible—by exploiting the retrograde transport of the marker—to trace the course of the fibers to the NTS.

Contributed by Emile Boulpaep

The Vasomotor Area

The vasomotor area includes the A1 or C1 areas in the rostral ventrolateral medulla, as well as the inferior olivary complex and other nuclei (i.e., the nucleus gigantocellularis lateralis, lateral reticular nucleus, and medullary raphe).

The C1 area also includes some adrenergic neurons, identified by the presence of the enzyme phenylethanolamine-N-methyltransferase (see Figure 13-8C on p. 332 of text), which converts norepinephrine to epinephrine. Multiple brain stem neurons synapse with C1-area neurons and release acetylcholine, GABA, enkephalin, and substance P. As discussed on p. 565, the antihypertensive agent clonidine acts by binding to imidazole receptors on C1-area neurons.

Some of the baroreceptor afferent fibers project directly to the vasomotor area without interaction with the NTS.

Contributed by Emile Boulpaep

Cholinergic Sympathetic Neurons

From a macroscopic anatomic standpoint, there is no doubt that the cholinergic sympathetic nerve endings of sudomotor nerves (i.e., the nerves that cause sweat secretion) and some vasomotor nerves are distal to the sympathetic ganglia. In this sense, these fibers are clearly “postganglionic.” Indeed, these rare cholinergic sympathetic fibers run together from the sympathetic ganglion to the target organ along with the majority of adrenergic fibers.

From a physiological standpoint, all of the sympathetic neurons that reach the adrenal medulla (see p. 360 in the textbook) are “preganglionic.” That is, these fibers derive from neuron cell bodies that lie in the intermediolateral cell column of the spinal cord. Their axons then transit through the paravertebral ganglia of the sympathetic trunk (see Figure 14-4 on p. 355) without synapsing and then follow along the splanchnic nerves. Most of these axons then go directly to the adrenal medulla, where they synapse on their targets, the chromaffin cells. However, some axons transit through the celiac ganglion—again without synapsing—before reaching their target chromaffin cells in the adrenal medulla. Thus, all sympathetic fibers that synapse on chromaffin cells are physiologically preganglionic: A single neuron carries information from the spinal cord to the target cell. However, the sympathetic neurons that traverse the celiac ganglion before reaching the adrenal medulla could—from a macroscopic anatomical standpoint—be regarded as postganglionic.

Investigators in the 1960s and 1970s suggested that cholinergic sympathetic fibers that innervate the sweat glands (see pp. 360 and 592) and some of the vascular smooth muscle in skeletal muscle (p. 560) derive from neuronal cell bodies in the spinal cord. This situation would be analogous to that of the cholinergic sympathetic innervation of the adrenal medulla. If this were true, then one could regard these cholinergic sympathetic sudomotor/vasomotor fibers—physiologically—as being preganglionic. However, recent experiments suggest that these cholinergic sympathetic fibers can arise from neuron cell bodies located in sympathetic ganglia, and that these neurons develop from neural crest cells (see p. 274). Using antibodies directed against the vesicular acetylcholine transporter (VAChT; which transports acetylcholine from the cytoplasm of the nerve terminal into the synaptic vesicles; see Figure 8-15 on p. 228), Schäfer et al. (1997) demonstrated that VAChT-positive “principal ganglionic cells” (i.e., postganglionic neurons) are present in paravertebral sympathetic ganglia at all levels of the thoracolumbar paravertebral chain. These observations are consistent with the idea that sudomotor nerve fibers and some vasomotor nerve fibers (e.g., skeletal microvasculature) are cholinergic postganglionic sympathetic neurons. These authors also demonstrated VAChT-positive principal ganglionic cells in two other sympathetic ganglia: the stellate and superior cervical ganglia.

Schäfer et al. (1998) also studied the developmental biology of postganglionic sympathetic neurons. They found that a small minority of sympathetic neurons have a cholinergic phenotype even during early embryonic development—even before the neurons innervate sweat glands.

Thus, a true postganglionic sympathetic neuron—postganglionic in both the gross anatomic and the physiological sense of the word—can be cholinergic. In other words, a preganglionic sympathetic “first” neuron, with its cell body in the intermediolateral column, may synapse in a sympathetic ganglion with a postganglionic sympathetic “second” neuron that releases acetylcholine at its nerve terminals. Thus, it is no longer necessary to assume that cholinergic sympathetic sudomotor/vasomotor neurons are, in fact, preganglionic fibers that traversed the sympathetic ganglion without synapsing.

REFERENCE

Schäfer MK, Eiden LE, and Weihe E: Cholinergic neurons and terminal fields revealed by immunohistochemistry for the vesicular acetylcholine receptor: II. The peripheral nervous system. Neuroscience84:361–376, 1998.

Schäfer MK, Schutz B, Weihe E, and Eiden LE: Target-independent cholinergic differentiation in the rat sympathetic nervous system. Proc Natl Acad Sci USA 94:4149–4154, 1997.

The Action Potential of the SA Node

Figure 21-4A illustrates the phases of the SA-node action potential and the underlying currents.

During phase 0 of the action potential, ICa activates regeneratively (Figure 21-4A, red record in bottom panel, specifically the rapid downstroke), producing a rapid upstroke of Vm. Underlying ICa are both T-type and L-type Ca2+channels.

At the transition between phases 0 and 3, ICa then begins to inactivate, a feature that begins the repolarization process. Note that phases 1 and 2 are not seen in the SA node because the inactivation of ICacombines with the slow activation of IK to bring about the phase 3 repolarization of the action potential.

As Vm approaches the maximum diastolic potential at the beginning of phase 4, three slow changes in membrane current take place that underlie phase 4 pacemaker activity:

1. IK deactivates slowly with time (over hundreds of milliseconds), producing a decreasing outward current (Figure 21-4A, green record in middle panel, specifically the slow decline of outward current during phase 4).

2. ICa contributes inward (i.e., depolarizing) current in the following way. Although Vm has become more negative at the end of phase 3, Vm is still positive enough to keep ICa partially activated (albeit to only a small extent) from the previous action potential. In addition, at the end of phase 3, Vm is still negative enough to cause ICa to recover slowly from inactivation (remember that recovery from inactivation and activation of ICa are independent processes). Thus, as ICa recovers from inactivation over hundreds of milliseconds, there is a small, increasingly inward ICa that tends to depolarize the SA nodal cells during phase 4 (Figure 21-4A, red record in lower panel, specifically the slow downstroke of inward current during phase 4).

3. If slowly activates as Vm becomes sufficiently negative at the end of phase 3. The result is a slowly growing, inward (i.e., depolarizing) current (Figure 21-4A, orange record in middle panel, specifically the rather rapid downstroke of inward current during phase 4).

Thus, during phase 4, the sum of a decreasing outward current (IK) and two increasing inward currents (ICa and If) produces the slow pacemaker depolarization associated with the SA node.

As Vm rises from approximately -65 mV toward the threshold of approximately-55 mV during the pacemaker depolarization, ICa becomes increasingly activated and eventually becomes regenerative, producing the rapid upstroke of the action potential, which takes us back to the beginning of this discussion. Note that the turning off of If tends to oppose the rapid upstroke of Vm during phase 0. However, the activation of ICa overwhelms the turning off of If.

Vasodilation in Salivary and Sweat Glands

1. Salivary glands: For a discussion of the physiology of vasodilator kinins, see point 5 on p. 575 of the text.

2. Sweat glands: See the top left column on p. 592 of the text for a discussion of the mechanisms whereby cholinergic sympathetic neurons cause vasodilation in nonapical skin.

Contributed by Emile Boulpaep

Peripheral Chemoreceptors

Progress on the physiology of glomus cells has largely been a result of the ability to study glomus cells in culture and in the isolated carotid body in vitro.

In the model of Figure 32-11, there is some controversy—which may reflect species differences—about which K+ channel is the target of hypoxia. Some evidence favors the charybdotoxin-sensitive, Ca2+-activated K+ channel. Other data point to a Ca2+-insensitive, voltage-gated K+ channel and a voltage-insensitive “resting” K+ channel.

Contributed by George B. Richerson and Walter Boron

Atrial Natriuretic Peptide

Granular inclusions in atrial myocytes, called Palade bodies, contain proANP, the precursor of atrial natriuretic peptide (ANP; also called atrial natriuretic factor). ProANP, comprising 126 amino acids, is derived from the precursor known as pre-pro-ANP (151 residues in humans). The converting enzyme corin—a cardiac transmembrane serine protease—cleaves the proANP during or after release from the atria, yielding the inactive N-terminal fragment of 98 residues and the active C-terminal 28-amino acid peptide called ANP. Release is primarily caused by stretch of the atrial myocytes. Hormones such as angiotensin, endothelins, arginine vasopressin, and glucocorticoid modulate ANP expression and release. It is noteworthy that expression of corin is reduced in heart failure, which blunts the release of ANP in the failing heart. This blunting might contribute to the inappropriate increase of extracellular fluid volume in heart failure.

ANP is a member of the NP (natriuretic peptide) family of peptides. The biological effects of ANP are potent vasodilation, diuresis, natriuresis, and kaliuresis, as well as inhibition of the renin–angiotensin–aldosterone system.

At least three types of natriuretic peptide receptors (NPRs) exist: NPR-A (also called GC-A; GC, guanylyl cyclase), NPR-B (also called GC-B), and NPR-C. NPR-A and NPR-B are receptors with a single transmembrane domain coupled to a cytosolic guanylyl cyclase (see pp. 68–69 of the text). Activation of NPR-A or NPR-B leads to the intracellular generation of cGMP. In smooth muscle, intracellular cGMP activates the cGMP-dependent protein kinase that phosphorylates myosin light-chain kinase (MLCK). Phosphorylation of MLCK inactivates MLCK, leading to the dephosphorylation of myosin light chains, allowing muscle relaxation.

The ANP C-type receptor NPR-C is not coupled to a messenger system but serves mainly to clear the natriuretic peptides from the circulation.

The heart, brain, pituitary, and lung synthesize an ANP-like compound termed BNP, originally known as brain natriuretic peptide (32 residues in humans). The biological actions of BNP are similar to those of ANP.

The hypothalamus, pituitary, and kidney synthesize C-type natriuretic peptide (CNP), which is highly homologous to ANP and BNP. CNP binds only to NPR-B and is only a weak natriuretic but a strong vasodilator.

The kidney also synthesizes an ANP-like natriuretic compound known as urodilatin (URO). URO has four additional amino acids compared to ANP and binds also to the ANP A-type receptor. Its biologic effect in the target tissue is also transduced by cGMP.

Contributed by Emile Boulpaep

The Monotonic Dependence of Cardiac Output on Effective Circulating Volume

Starting from a volume-contracted state (change in effective circulating volume = -30 ml/kg in Figure 23-8 on p. 569), a gradual increase in effective circulating volume causes the cardiac output to increase monotonically (Figure 23-8, lower left portion of red curve) because the rising stroke volume (Starling’s law, steepened by baroreceptor response, as indicated by the lower left portion of the blue curve) more than counterbalances the falling heart rate (baroreceptor reflex, as indicated by the falling phase of the orange curve).

Continuing now from a normal volume state (change in effective circulating volume = 0 ml/kg in Figure 23-8), an additional increase in effective circulating volume causes a further monotonic increase in cardiac output because a rising heart rate (Bainbridge reflex, as indicated by the rising phase of the orange curve) combines with the flat stroke–volume curve (Starling relationship—normally flattening at high degrees of stretch—is further flattened by the baroreceptor reflex).

Contributed by Emile Boulpaep

How Does Cardiac Output Determine Right Atrial Pressure?

Imagine that we replace the right heart, the pulmonary circulation, and the left heart with a single pump (Figure 23-9A on p. 570 of the text), similar to the heart–lung machine used for cardiopulmonary bypass during open heart surgery. In explaining the shape of the vascular function curve in Figure 23-9C, we can stress either that large veins have a high compliance or that they have a low resistance.

High Venous Compliance Model

In this model, we ignore the small axial pressure gradient along the lumen of the venous reservoir that is a result of the small viscous resistance between the large veins and right atrium. Instead, we assume that the central venous pressure is the same as the right atrial pressure (RAP), and that we can lump the compliance of all large capacitance veins into a single compliance (CV). The model in Figure 23-9A has two reservoirs—an aortic and a venous reservoir—separated by the peripheral resistance of the microcirculation. As noted in our discussion of the “Windkessel” function of the aorta (see Figure 22-4C on p. 536), the compliance of the aorta (CA) is far less than that of the large veins (CV). During normal pumping of the heart, the aortic pressure (PA) is much higher than the central venous pressure (PV). Let us consider what happens immediately after a cardiac arrest. At that moment, PA still exceeds PV, and blood continues to flow from the aortic reservoir to the venous reservoir until PA and PV both become equal to the mean systemic filling pressure (MSFP). How much blood volume shifts from the aortic to the venous reservoir depends on the relative compliances of the two reservoirs. For the aorta,

Equation 1

image

and for the veins,

Equation 2

image

CV is approximately 20 times larger than CA. In the equilibrium state, all the blood lost by the aorta ends up in the veins (i.e., ΔVV = -ΔVA). Therefore, because CV is approximately 20 times larger than CA, and because the magnitudes of the volume changes are identical, the fall in the aortic pressure (ΔPA) must be approximately 20-fold greater than the rise in venous pressure (ΔPV). Thus, at equilibrium, when all the pressures are the same, we must end up at a pressure (MSFP = ~7 mm Hg) that is much closer to the physiologic central venous pressure (CVP = ~2 mm Hg) than the original mean aortic pressure (PA = ~95 mm Hg).

When the heart starts to pump again, it depletes the volume in the highly distensible venous reservoir so that PV progressively falls to the original steady-state value of 2 mm Hg. At this point, cardiac output and venous return are once again matched.

Low-Resistance Model

In this model, we ignore the capacitance of the veins and instead focus on the resistance between the large veins and right atrium. The hydrodynamic equivalent of Ohm’s law states that the driving pressure equals flow times resistance:

Equation 3

image

Because the venous return equals F, it should depend on the axial pressure gradient (ΔP) between the central venous pressure upstream and the right atrial pressure downstream. According to this model, RAP is the force that opposes flow into the atria. Venous return should also depend on the resistance to blood flow between the large systemic (i.e., “central”) veins that serve as the blood reservoir, on the one hand, and the right atrium, on the other hand. This resistance to venous return (RVR) resides mostly in these large-capacitance veins. From Ohm’s law, the venous return depends on CVP, RAP, and RVR:

Equation 4

image

RVR is usually considered to be the reciprocal of the slope of the linear portion of the vascular function curve in Figure 23-9C. However, this line is not really a plot of Ohm’s law. Ohm’s law should be a plot of the venous return versus the driving pressure (ΔP), as suggested by Equation 4. Instead, in Figure 23-9C, we plot the venous return versus RAP, which is not quite the same as ΔP. Changes in RAP in Figure 23-9C represent ΔP only if the “upstream pressure” (i.e., CVP) remains constant, which can only be true over a limited range of flows. The CVP remains constant only as long as sufficient blood is present on the venous side of the circulation. If flow increases too much, not enough blood can enter the veins, CVP falls, and the change in RAP is no longer equal to the change in the driving pressure ΔP. Despite this caveat, cardiovascular physiologists often take the reciprocal of the linear portion of Figure 23-9C as RVR.

According to this model, the negative intravascular pressures at high venous return (i.e., at high cardiac output) cause the large intrathoracic veins to collapse, which effectively increases the RVR to infinity. Hence, the curve plateaus.

Conclusions

Although both the high-capacitance and low-resistance models provide an intuitive understanding of the vascular function curve in Figure 23-9C, both compliance and viscous resistive properties of the venous system affect the relationship between pressure and flow.

Contributed by Emile Boulpaep

The Metabolism of the Angiotensins

The liver synthesizes and releases into the blood the α2-globulin angiotensinogen (Agt), which is a plasma glycoprotein that consists of 452 amino acids. Its molecular weight ranges from 52 to 60 kDa, depending on the degree of glycosylation. Angiotensinogen belongs to the serpin (serine protease inhibitor) superfamily of proteins, which also includes antithrombin III (see page 463 as well as Tables 18–4and 18–5). The liver contains only small stores of angiotensinogen, which it constitutively secretes. Production by the liver is greatly increased during the acute phase response (see box on p. 456). Angiotensinogen is synthesized in several tissues other than liver. In addition to the 52- to 60-kDa form of angiotensinogen, a high-molecular-weight angiotensinogen complex of 450–500 kDa is also present in plasma. Polymorphisms within the angiotensinogen gene may contribute to normal variations in arterial blood pressure and a tendency to develop hypertension.

The juxtaglomerular cells of the kidney—also called granular cells (see p. 754)—are specialized smooth muscle cells of the afferent arteriole that synthesize and release both the glycoprotein renin (37–40 kDa)—pronounced “ree-nin”—and its inactive precursor prorenin, which is the major circulating form. Prorenin-activating enzymes on endothelial cells convert this prorenin to renin. The kidney is the major source of circulating prorenin/renin, and the liver is responsible for removing renin from the circulation. The half-life of renin in plasma is 10–20 minutes. Renin is an aspartyl proteinase that cleaves a leucine–valine bond near the amino-terminus of angiotensinogen to release a decapeptide called angiotensin I (ANG I), which is not biologically active. By an alternative pathway, nonrenin proteases can also produce ANG I. The full sequence of ANG I is Asp-Arg-Val-Tyr-Ile-His-Pro-Phe-His-Leu:

Equation 1

image

Angiotensin converting enzyme (ACE; ~200 kDa) is produced by and attached to endothelial cells. ACE is a dipeptidyl-carboxypeptidase (a zinc peptidase) that cleaves angiotensin I by removing the carboxy-terminal dipeptide histidine–leucine and producing the octapeptide angiotensin II (ANG II). The ACE cleavage site is a phenylalanine–histidine bond. The sequence of ANG II is Asp-Arg-Val-Tyr-Ile-His-Pro-Phe:

Equation 2

image

ANG II has a half-life in blood of 1–3 minutes, indicating that a large fraction is removed in a single pass through the circulation. ANG II acts on G-protein–coupled receptors known as AT1 and AT2. In addition, two other receptors are less well characterized: AT3 and AT4. ANG IV can bind to AT4 receptors.

By an alternative pathway, non-ACE proteases can also convert ANG I to ANG II. Conversely, note that ANG I is not a specific substrate for ACE, which can cleave other peptides, including bradykinin (p. 575), enkephalins, and substance P.

Aminopeptidase A (also called angiotensinase A or glutamyl aminopeptidase) further cleaves the aspartate–arginine bond on angiotensin II to produce the heptapeptide angiotensin III (ANG III, also called Ang 2-8), which has the sequence Arg-Val-Tyr-Ile-His-Pro-Phe. ANG III, like ANG II, can also bind to AT receptors.

Aminopeptidase B (also called angiotensinase B or arginyl aminopeptidase) finally cleaves an arginine–valine bond on angiotensin III to produce the hexapeptide angiotensin IV (ANG IV, also called Ang 3-8). The sequence of ANG IV is Val-Tyr-Ile-His-Pro-Phe. This metabolite is inactive.

Finally, another angiotensin metabolite has received attention in recent years. ANG-(1-7) consists only of the first seven amino acids of ANG I: Asp-Arg-Val-Tyr-Ile-His-Pro. [ANG-(1–7) is not to be confused with another heptapeptide metabolite of ANG II, namely ANG III—also known as ANG-(2-8). ANG III has actions similar to those of ANG II but is weaker (see p. 574 in the text).] This heptapeptide can arise from ANG I by at least three routes:

Equation 3

image

Note that by the previous nomenclature, ANG I is ANG-(1-10), and ANG II is ANG-(1-8). The first and third pathways involve a new enzyme called ACE2. The second is catalyzed by any in a family of enzymes called neutral endopeptidases. ANG-(1–7) can bind to a G-protein–coupled receptor called the Mas receptor and—when acting on the cardiovascular system—can elicit effects opposite those of ANG II.

REFERENCE

Donoghue M, Hsieh F, Baronas E, et al.: A novel angiotensin-converting enzyme-related carboxypeptidase (ACE2) converts angiotensin I to angiotensin 1-9. Circ Res 87:E1–E9, 2000.

Ferrario CM and Chappell MC: Novel angiotensin peptides. Cell Mol Life Sci 61:2720–2727, 2004.

Gurley SB, Allred A, Le TH, et al.: Altered blood pressure responses and normal cardiac phenotype in ACE2-null mice. J Clin Invest 116:2218–2225, 2006.

Yagil Y and Yagil C: Hypothesis: ACE2 modulates blood pressure in the mammalian organism. Hypertension 41:871–873, 2003.

Contributed by Emile Boulpaep and Walter Boron

Crosstalk between ANP and Endothelin

ANP is involved in an intriguing feedback loop involving endothelin (ET). ANP stimulates endothelin formation by endothelial cells, but endothelin is itself a secretagogue for the atrial myocytes, causing them to release ANP. Thus, a vasodilator (ANP) promotes the release of a vasoconstrictor (ET), which in turn promotes the release of the original vasodilator.

Contributed by Emile Boulpaep

Liddle Disease

Liddle disease is caused by a gain-of-function mutation in the β or γ subunits of the epithelial Na+ channel (ENaC). For example, the critical regions in the subunit are important for endocytosis or proteosomal degradation of the channel. Thus, mutations result in an overabundance of ENaC at the apical membrane, resulting in excessive Na+ reabsorption, an increase in effective circulating volume, and hypertension. The disease is readily diagnosed by determining if the hypertension is reversed by the drug amiloride, which antagonizes ENaC. Indeed, amiloride is an effective therapy for Liddle disease.

For a description of ENaC, see Table 6–2 on p. 169 of the text.

REFERENCE

Hansson JH, Nelson-Williams C, Suzuki H, et al.: Hypertension caused by a truncated epithelial sodium channel gamma subunit: Genetic heterogeneity of Liddle syndrome. Nat Genet 11:76–82, 1995.

Liddle GW, Bledsoe T, and Coppage WS: A familial renal disorder simulating primary aldosteronism but with negligible aldosterone secretion. Trans Assoc Am Physicians 76:199–213, 1963.

Schild L, Canessa CM, Shimkets RA, et al.: A mutation in the epithelial sodium channel causing Liddle disease increases channel activity in the Xenopus laevis oocyte expression system. Proc Natl Acad Sci USA 92:5699–5703, 1995.

Shimkets RA, Warnock DG, Bositis CM, et al.: Liddle’s syndrome: Heritable human hypertension caused by mutations in the beta subunit of the epithelial sodium channel. Cell 79:407–414, 1994.

Contributed by Emile Boulpaep and Walter Boron

Brain Metabolism

As noted in Chapter 11 (see p. 289 and p. 302), the brain has rather limited glycogen stores (~10% of the amount stored in the liver), and virtually all of these stores are in the astrocytes, which have mechanisms for transferring the energy to the neurons. As noted in the text on p. 578, the glucose consumption by the brain alone is capable of exhausting the liver’s entire store of glycogen in only 1 day. When food is not eaten for more than 24 hours, the brain must either rely on glucose derived from gluconeogenesis (largely from the breakdown of muscle protein) or utilize an alternative fuel. For example, as ketone bodies rise in the bloodstream during fasting, the enzymes required for their oxidation are induced in brain cells, thereby enabling an alternative substrate for energy production and conserving lean body mass.

The text addresses related issues (1) on p. 289 in Chapter 11, (2) on pp. 302–303 (including Figure 11-10), and (3) in Chapter 58 on metabolism.

Contributed by Emile Boulpaep & Walter Boron

Emissary Veins

The emissary veins traverse the skull, carrying blood from the sinuses (e.g., superior sagittal sinus), which are surrounded by the dura mater inside the skull, to branches of the superficial temporal veins that are external to the skull. The emissary veins are typically responsible for little venous drainage from the brain.

Contributed by Steve Segal

Axon Reflex

Axon reflexes are thought to occur when a nerve ending is depolarized by local factors (e.g., irritation, pressure, seizures, altered pH, high [K+]o, or other chemical signals), triggering an action potential that travels anterograde along the axon to a branch point, where the action potential propagates back down another branch. Thus, an axon reflex is a local reflex arc that only involves the distal/peripheral part of a motor or sensory neuron.

In the case of a motor neuron, the stimulus would trigger an action potential that would move retrograde up the fiber to the branch point and then orthograde down to a terminal that would release its normal complement of neurotransmitters. Of course, when responding to its normal “central” stimuli, this motor neuron would function in the usual orthograde manner.

In the case of a sensory fiber, the stimulus would travel orthograde along the axon to a branch point and then travel retrograde to other nerve endings. If these endings have release machinery, they could activate an effector. Varicosities on sensory fibers may contain substance P (SP) and calcitonin gene–related peptide (CGRP), which the processes release in response to a local stimulus. Both SP and CGRP are vasodilatory neurotransmitters.

Another example of an afferent fiber that can release a neurotransmitter is the CN IX sensory neurons that innervate the glomus cells of the carotid body. As discussed on pp. 736–737 in the text, this is an example of a bidirectional synapse. The glomus cells can trigger an action potential in the sensory neuron, and the sensory neuron can apparently release neurotransmitters that may modulate the glomus cell.

Axon reflexes can also occur in neurons of the central nervous system—for example, from one part of the cortex to another.

Revised by George Richerson

Vasodilatory Effect of Hypoxia in the Brain

A fall in the blood and tissue PO2—from hypoxemia or impaired blood flow to the brain—may also contribute to vasodilation in the brain, although the effects are less dramatic than those produced by arterial hypercapnia. Several mediators may underlie the effect of hypoxia:

1. Adenosine: Levels of adenosine increase with hypoxia, reflecting the breakdown of ATP. Virtually any condition that increases brain O2 consumption will result in adenosine production and release within seconds. Because adenosine is a potent vasodilator (see Table 20–7 on p. 500 of the text and Table 20–8 on p. 501), increased adenosine levels tend to enhance blood flow and correct the hypoxia.

2. High [K+]: Hypoxia, seizures, or electrical stimulation all elevate [K+] in the BECF. Increased [K+]o leads to vasodilation (see Table 20–8 on p. 501; also see webnote 0501), which in turn tends to wash away the excess K+. Thus, elevated [K+]o may be involved only in the early portion of a hyperemic response.

3. Nitric oxide: Both brain vascular endothelial cells and neurons contain nitric oxide synthase (see p. 69 and also see the passage beginning on the right column of p. 499) and thus can generate the highly permeable NO, which readily dilates the brain’s resistance vessels.

4. Direct effects of low PO2: A mechanism receiving increasing attention is the effect of O2 on the K+ conductance of the VSMC membrane: A fall in PO2 increases K+ conductance, promoting VSMC relaxation.

Contributed by Steve Segal, Emile Boulpaep, and Walter Boron

Adverse Effects of Tachycardia on Left Coronary Perfusion

As shown in Figure 24-4 on p. 582 in the text, most of the blood flow to the left coronary artery occurs during diastole. During bradycardia, a greater proportion of time is spent in diastole. Although this effect promotes left coronary blood flow, the total requirement for blood flow declines. During tachycardia, the diastolic interval shortens relatively more than the systolic interval. Thus, if we were to sum up all the diastolic intervals that occur over the course of a minute, we would see that less total time is available for left coronary perfusion during diastole—even though the metabolic requirements of the left ventricle are much higher during tachycardia.

Contributed by Steve Segal and Emile Boulpaep

Vasodilation Caused by Increases in [K+]o

Why does the transient increase in [K+]o cause a transient, paradoxical hyperpolarization rather than the depolarization that one might expect from the Nernst equation (Equation 6–5 on p. 152 in the text)?

First, the effect is transient because the increase in [K+]o is short lived since the ensuing vasodilation will wash away the excess extracellular K+.

Second, the rise in [K+]o causes Vm to become more negative (a hyperpolarization) even though EK (the equilibrium potential for K+) becomes more positive (Equation 6–5 on p. 152). The reason is that the K+conductance of vascular smooth muscle cells depends largely on inwardly rectifying K+ channels (Kir; see Figure 7-20 on p. 206). A peculiar property of Kir channels is that an increase in [K+]o not only causes EK to shift to more positive values but also increases the slope conductance (i.e., the slope of the I–V relationship at EK). Vascular smooth muscle cells normally do not live at EK but, rather, at more positive voltages (-30 to -40 mV), reflecting the contributions from other conductances (e.g., Na+) with more positive equilibrium potentials. In the text, we introduced Equation 6–12, which we reproduce here:

image

Here, GKGNaGCaGCl, etc. represent membrane conductances for each ion, whereas Gm represents the total membrane conductance. Thus, GK/Gm represents the fractional conductance for K+. Therefore, the equation tells us that Vm depends not only on the various equilibrium potentials but also on their respective fractional conductances. Thus, if an increase in [K+]o simultaneously causes (1) a slight decrease in the absolute value of EK and (2) a larger increase in GK, the absolute value of the product (GK/Gm)EK will be larger. Because (GK/Gm)EK is a negative number, the net effect is that the computed value of Vm is more negative (i.e., a hyperpolarization).

In principle, a second phenomenon can contribute to the hyperpolarization. The increase in [K+]o will enhance the activity of the electrogenic Na-K pump, resulting in an increase in the pump’s outward current and therefore a hyperpolarization.

Contributed by Emile Boulpaep

Vasoactive Enteric Hormones

As noted in the text, the cholecystokinin and neurotensin released by the gastrointestinal tract may reach high enough concentrations in the local circulation to promote intestinal blood flow. However, these substances do not affect blood flow in other vascular beds because these hormones are too dilute, because other vascular beds lack appropriate receptors, or possibly because the hormones are destroyed as they pass through the liver. The intestinal mucosa releases additional peptide hormones (e.g., vasoactive intestinal peptide, gastrin, and secretin), but their effect on blood flow under physiologic conditions is questionable.

In addition to the vasoactive hormones released by the gastrointestinal tract, the carbohydrates and amino acids absorbed by the small intestine increase local osmolality, which in turn leads to an increase in blood flow. It has been suggested that amino acids may cause vasodilation independent of the osmolality effect.

The Spleen as a Blood Reservoir

In aerobic animals such as dogs and horses, and in diving animals such as seals, the spleen serves as an important reservoir of blood; it contains up to 10% of the total blood volume with a hematocrit that is approximately 10% higher than that in the systemic circulation. Sympathetic stimulation in these animals causes the capsule of the spleen to contract, ejecting this hemoconcentrated blood into the systemic circulation. In humans and cats, the spleen is principally a reticuloendothelial organ, having little role as a blood reservoir.

Contributed by Steven Segal

Axon Reflexes

Axon reflexes are thought to occur when a nerve ending is depolarized by local factors (e.g., irritation, pressure, seizures, altered pH, high [K+]o, or other chemical signals), triggering an action potential that travels anterograde along the axon to a branch point, where the action potential propagates back down another branch. Thus, an axon reflex is a local reflex arc that only involves the distal/peripheral part of a motor or sensory neuron.

In the case of a motor neuron, the stimulus would trigger an action potential that would move retrograde up the fiber to the branch point and then orthograde down to a terminal that would release its normal complement of neurotransmitters. Of course, when responding to its normal “central” stimuli, this motor neuron would function in the usual orthograde manner.

In the case of a sensory fiber, the stimulus would travel orthograde along the axon to a branch point and then travel retrograde to other nerve endings. If these endings have release machinery, they could activate an effector. Varicosities on sensory fibers may contain substance P (SP) and calcitonin gene–related peptide (CGRP), which the processes release in response to a local stimulus. Both SP and CGRP are vasodilatory neurotransmitters.

Another example of an afferent fiber that can release a neurotransmitter is the CN IX sensory neurons that innervate the glomus cells of the carotid body. As noted on pp. 736–737 in the text, this is an example of a bidirectional synapse. The glomus cells can trigger an action potential in the sensory neuron, and the sensory neuron can apparently release neurotransmitters that may modulate the glomus cell.

Axon reflexes can also occur in neurons of the central nervous system—for example, from one part of the cortex to another.

Revised by George Richerson

Calculation of Distension in an Upright Cylinder

Equation 19–4 on p. 475 in the text and the identical Equation 25–1 on p. 596 both describe how the “relative” or “normalized” distensibility depends on the relative change in volume (ΔV/Vo) and the pressure difference (ΔP):

Equation 1

image

We can now solve for the relative change in volume:

Equation 2

image

For a very thin disk of fluid (height h) in the upright vessel, the change in volume (ΔV) is due solely to a change in vessel radius. In other words, because V = 2, ΔV = r)2. Thus, we can rewrite Equation 2 as

Equation 3

image

In order to compute the shape of the upright vessel in Figure 25-3, the only other thing we need to know is how ΔP varies with the height in the upright vessel. For a hydrostatic column, the pressure increases linearly as we descend to greater depths, as described by Equation 17–4 on p. 432. We reproduce this equation here:

Equation 4

image

Here, ρ is the density of the liquid, g is the gravitational constant, and h is the height of the column. We could use this equation to compute the pressure in dynes/cm2 or pascals. However, physiologists tend to express pressures in “cm of H2O” or “mm Hg.” For example, in Figure 25-3B on p. 596, the pressure at the bottom of the 100-cm column is equivalent to 100 cm H2O, which is also (knowing the density of mercury) 73.5 mm Hg.

Now we can compute the relative distension at the bottom of the upright cylinder, which is under a pressure of 75.5 mm Hg. Rearranging Equation 3 and solving for Δr (the change in radius), we have

Equation 5

image

Because the initial radius (ro) of the horizontal cylinder in Figure 25-3A was everywhere 3 cm, the distended radius at the bottom of the upright column has increased by 3.6 cm for a total radius of 6.6 cm. In other words, the radius has more than doubled, and the volume has more than quadrupled (i.e., increased by a factor of 4.8).

If the relative distensibility were less (e.g., 0.01/mm Hg in Figure 25-3C), then the Δr would also be less at the bottom of the upright cylinder. On the other hand, because the Δr is less at each height, the column of water would have to be higher to accommodate the volume. Thus, the pressure at the bottom of the column would be greater (i.e., 130 cm H2O or 95.6 mm Hg in the example of Figure 25-3C). As in Equation 5, we can compute the relative distension at the bottom of the upright cylinder, which this time is under a pressure of 95.6 mm Hg:

Equation 6

image

In other words, uniformly reducing the relative distensibility by a factor of 2 still results in a near doubling of the radius and a near quadrupling of the volume (i.e., increasing by a factor of 3.8).

Contributed by Emile Boulpaep

Hypothetical Volume of Pooled Blood during Orthostasis

In the example shown in Figure 25-3B in the text, the column of blood would reach a height of 100 cm. Because the horizontal cylinder in Figure 25-3A had a length of 180 cm, turning the vessel upright reduced the length of the column by 80 cm. How much volume moved into the lower part of the distensible, upright vessel? The answer is the volume at the top of the white region in Fig. 25–3B, which is the product of the 80-cm length, cross-sectional area:

Hypothetical pooled volume = (80 cm) · π (3 cm)2 = 2262 cm2 = ~2.2 L

Contributed by Emile Boulpaep

Calculation of Distension in an Upright Cylinder

Equation 19–4 on p. 475 of the text—and the identical Equation 25–1 on p. 596—both describe how the “relative” or “normalized” distensibility depends on the relative change in volume (ΔV/Vo) and the pressure difference (ΔP):

Equation 1

image

We can now solve for the relative change in volume:

Equation 2

image

For a very thin disk of fluid (height h) in the upright vessel, the change in volume (ΔV) is due solely to a change in vessel radius. In other words, because V = hπr2, ΔV = hπ(Δr)2. Thus, we can rewrite Equation 2 as:

Equation 3

image

In order to compute the shape of the upright vessel in Figure 25-3, the only other thing we need to know is how ΔP varies with the height in the upright vessel. For a hydrostatic column, the pressure increases linearly as we descend to greater depths, as described by Equation 17–4 on p. 432. We reproduce this equation here:

Equation 4

image

Here, ρ is the density of the liquid, g is the gravitational constant, and h is the height of the column. We could use this equation to compute the pressure in dynes/cm2 or pascals. However, physiologists tend to express pressures in “cm of H2O” or “mm Hg.” For example, in Fig. 25–3B on p. 596, the pressure at the bottom of the 100-cm column is equivalent to 100 cm H2O, which is also (knowing the density of mercury) 73.5 mm Hg.

Now we can compute the relative distension at the bottom of the upright cylinder, which is under a pressure of 75.5 mm Hg. Rearranging Equation 3 and solving for Δr (the change in radius), we have:

Equation 5

image

Because initial radius (ro) of the horizontal cylinder in Fig. 25–3A was everywhere 3 cm, the distended radius at the bottom of the upright column has increased by 3.6 cm for a total radius of 6.6 cm—in other words, the radius has more than doubled, and the volume has more than quadrupled (i.e., increased by a factor of 4.8).

If the relative distensibility were less (e.g., 0.01/mm Hg in Fig. 25–3C), then the Δr would also be less at the bottom of the upright cylinder. On the other hand, because the Δr is less at each height, the column of water would have to be higher to accommodate the volume. Thus, the pressure at the bottom of the column would be greater (i.e., 130 cm H2O or 95.6 mm Hg in the example of Fig. 25–3C). As in Equation 5, we can compute the relative distension at the bottom of the upright cylinder, which this time is under a pressure of 95.6 mm Hg:

Equation 6

image

In other words, uniformly reducing the relative distensibility by a factor of 2 still results in a near doubling of the radius, and a near quadrupling of the volume (i.e., increasing by a factor of 3.8).

Contributed by Emile Boulpaep

Baroreceptor Responses in Orthostasis

As noted in the text (p. 597), orthostasis leads to the following sequence of events: Decreased venous return image fall in right atrial pressure (RAP) image decrease in stroke volume image decreased arterial pressure image response of high-pressure baroreceptors (p. 557image increased sympathetic output image generalized vasoconstriction and increased heart rate/contractility. Because RAP falls early in this sequence, you might wonder what role the atrial low-pressure baroreceptors play in the response. Reduced atrial stretch has little effect on heart rate (pp. 568–569) and causes an increase in sympathetic output only to the kidney (i.e., causing renal vasoconstriction). Therefore, the low-pressure baroreceptors make only a minor contribution to the overall orthostatic response (i.e., generalized vasoconstriction and increased heart rate/contractility).

Contributed by Emile Boulpaep

Effects of Temperature on Venous Pooling

As discussed on p. 586 of the text, the contraction of skeletal muscle in the legs (the “muscle pump”; see Figure 24-6 on p. 586) drives blood from the large veins in the lower limbs toward the heart. Conversely, each time these skeletal muscles relax, the vascular bed in the legs refills from the arterial side. Obviously, the arteriolar inflow resistance influences the rate at which the veins in the leg refill subsequent to the action of the muscle pump. When the lower limbs are at a high temperature, the arterioles dilate, lowering the inflow resistance and increasing the inflow of blood to the dependent vessels. Therefore, venous pooling worsens at high temperature, explaining why soldiers tend to faint under these conditions.

Contributed by Emile Boulpaep

Ocular Symptoms and Signs Associated with Fainting

On p. 601 of the text, it is noted that fainting may be associated with mydriasis (dilation of the pupil) and blurred vision. In addition, fainting may also be associated with dimmed vision.

The mydriasis that may occur during the loss of consciousness is not the direct consequence of the strong parasympathetic stimulation that underlies the fainting episode. Stimulation of the autonomic (parasympathetic) portion of CN III (see p. 353, as well as Figure 14-4 on p. 355) would lead to contraction of the sphincter muscle in the iris and therefore would lead to miosis (pupillary constriction). How does mydriasis arise? It is likely that the brain ischemia that leads to the altered mental status of the faint also causes a palsy of the preganglionic fibers that originate in the oculomotor (Edinger–Westphal) nucleus (see Figure 14-5 on p. 356), resulting in a relaxation of the iris’s sphincter muscle and therefore mydriasis. Note that the dilator muscle of the iris is innervated by postganglionic sympathetic fibers emanating from the superior cervical ganglion. Evidently, the brain hypoperfusion that triggers the faint has a lesser effect on the sympathetic system that causes dilation of the pupil.

Blurred vision before or after the loss of consciousness may be a direct consequence of strong parasympathetic stimulation. The ciliary zonule fibers are elastic elements that tend to stretch the lens of the eye in a radial direction and thus to flatten the lens. The ciliary muscle that encircles the lens is composed of smooth muscle fibers that are arranged both radially and circularly. The main effect of contraction of the ciliary muscle is to relax the radial tension exerted by elastic zonule fibers, thereby allowing the lens to become more curved. A higher curvature of the front surface of the lens increases its focal power (see Equation 15–1 on p. 379). It is possible that very strong parasympathetic stimulation could cause blurring by the following sequence of events. Preganglionic fibers in the oculomotor (Edinger–Westphal) nucleus synapse in the ciliary ganglion on postganglionic parasympathetic fibers that innervate the smooth muscle fibers of the ciliary muscle. Parasympathetic activation of this system would cause the lens to accommodate for objects very close to the eye. Therefore, the patient would experience blurred vision for any object further removed from the eye.

Dimming of vision may be part of the prodrome of fainting, presumably due to a loss of adequate retinal perfusion.

Contributed by Emile Boulpaep

Suppression of the Classical Baroreceptor Response in Vasovagal Syncope

In rare cases, certain chemicals can cause vasovagal syncope.

One hypothesis is that certain chemicals that stimulate TRPC channels of baroreceptors can activate the baroreceptors maximally, as if blood pressure had risen markedly. According to this view, vasovagal syncope is the appropriate response: decreased cardiac output and decreased peripheral resistance. Although blood pressure falls, vessels collapse, and stretch on the walls of the blood vessels wanes, the baroreceptors would still behave as if they were maximally stimulated.

Contributed by Emile Boulpaep

Central Commands for Exercise Originating Outside the Medulla

An increase in sympathetic output from the medullary cardiovascular center, by itself, would explain the immediate ventricular response during exercise. Increased sympathetic output from medullary centers would also explain the immediate vasoconstriction in inactive muscles and in the splanchnic, renal, and cutaneous circulations. However, sympathetic signals originating in the medulla cannot account for yet another immediate exercise response that occurs in dogs (although not in humans and other primates)—a rapid vasodilation that occurs only in active skeletal muscle. On the contrary, experimental stimulation of medullary centers would constrict all muscle beds.

Contributed by Emile Boulpaep

Joseph Black (1728–1799)

http://en.wikipedia.org/wiki/Joseph_Black

http://www.answers.com/topic/joseph-black

Henry Cavendish (1731–1810)

http://en.wikipedia.org/wiki/Henry_Cavendish

http://scienceworld.wolfram.com/biography/Cavendish.html

Joseph Priestley (1733–1804)

http://en.wikipedia.org/wiki/Joseph_Priestley

http://www.historyguide.org/intellect/priestley.html

http://www.woodrow.org/teachers/ci/1992/Priestley.html

Carl Scheele (1742–1786)

http://en.wikipedia.org/wiki/Carl_Wilhelm_Scheele

http://www.answers.com/topic/carl-wilhelm-scheele

Antoine Lavoisier (1743–1794)

http://en.wikipedia.org/wiki/Antoine_Lavoisier

http://www.antoine-lavoisier.com/

Lazzaro Spallanzani (1729–1799)

http://en.wikipedia.org/wiki/Lazzaro_Spallanzani

http://www.accessexcellence.org/RC/AB/BC/Spontaneous_Generation.php

http://www.newadvent.org/cathen/14209a.htm

Gas Laws

In the mid-17th century, Robert Boyle demonstrated that the relation between the pressure (P) and volume (V) of a real gas at a fixed temperature is essentially hyperbolic. Boyle’s law states that P and V for an ideal gas vary inversely:

Equation 1

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At the molecular level, the pressure exerted by a fixed number of gas molecules—the total force of gas per unit surface area of the container—reflects the number of collisions molecules make with the walls of the container. If we reduce the container’s volume by half, the number of collisions doubles for each square centimeter of the container’s walls and, therefore, pressure doubles.

A century after Boyle’s work, Jacques Charles found that the volume of a gas varies linearly with absolute temperature (T, in °K) if pressure is constant:

Equation 2

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At the molecular level, Charles’ law states that increasing the temperature increases the velocity of gas molecules, forcing the perfectly compliant container to increase in size.

Combining these two laws yields the so-called Boyle–Charles law:

Equation 3

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For an ideal gas, Constant #3 is nothing more than n ·R. where n is the number of moles and R is the universal gas constant. Incorporating n and R into Equation 60–3 yields the ideal gas law:

Equation 4

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If we compare the relationship among pressure, volume, and temperature for a fixed number of moles of the gas under two conditions, we see that

Equation 5

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With this simple equation, one better appreciates what happens when barometric pressure increases during diving or decreases during ascent to high altitude.

The barometric pressure (PB) is the sum of the partial pressures of the individual gases in the air mixture (Dalton’s law) (see box on “Partial Pressures and Henry’s Law” on p. 615 of the text). Thus, in the case of ordinary dry air (see Table 26–1), most of the sea-level PB of 760 mm Hg is due to N2 (~593 mm Hg) and O2 (~159 mm Hg), with smaller contributions from trace gases such as argon (~7 mm Hg) and CO2(~0.2 mm Hg). Thus, as PB increases during diving beneath the water, or as PB decreases during ascent to high altitude, the partial pressure of each constituent gas will change in proportion to the change in PB. This relationship is important for O2 delivery to tissues because a key variable that determines the O2 saturation of hemoglobin (Hb) is PO2 in the inspired air (see p. 706).

The conducting airways humidify inspired air so that it becomes fully saturated with H2O vapor at body temperature (see box on “Wet Gases” on p. 615). The H2O vapor then occupies part of the space in the lungs. At a body temperature of 37°C, PH2O is 47 mm Hg. If PB is 760 mm Hg, only 760 – 47 = 713 mm Hg is available for the sum of PO2, PN2, and PCO2. Because H2O readily evaporates from (or condenses into) liquid water, its partial pressure does not change with changes in PB.

Contributed by Walter Boron

Gas Laws

In the mid-17th century, Robert Boyle demonstrated that the relation between the pressure (P) and volume (V) of a real gas at a fixed temperature is essentially hyperbolic. Boyle’s law states that P and V for an ideal gas vary inversely:

Equation 1

image

At the molecular level, the pressure exerted by a fixed number of gas molecules—the total force of gas per unit surface area of the container—reflects the number of collisions molecules make with the walls of the container. If we reduce the container’s volume by half, the number of collisions doubles for each square centimeter of the container’s walls and, therefore, pressure doubles.

A century after Boyle’s work, Jacques Charles found that the volume of a gas varies linearly with absolute temperature (T, in °K) if pressure is constant:

Equation 2

image

At the molecular level, Charles’ law states that increasing the temperature increases the velocity of gas molecules, forcing the perfectly compliant container to increase in size.

Combining these two laws yields the so-called Boyle–Charles law:

Equation 3

image

For an ideal gas, Constant #3 is nothing more than n · R, where n is the number of moles and R is the universal gas constant. Incorporating n and R into Equation 60–3 yields the ideal gas law:

Equation 4

image

If we compare the relationship among pressure, volume, and temperature for a fixed number of moles of the gas under two conditions, we see that

Equation 5

image

With this simple equation, one better appreciates what happens when barometric pressure increases during diving or decreases during ascent to high altitude.

The barometric pressure (PB) is the sum of the partial pressures of the individual gases in the air mixture (Dalton’s law) (see box on “Partial Pressures and Henry’s Law” on p. 615 of the text). Thus, in the case of ordinary dry air (see Table 26–1), most of the sea-level PB of 760 mm Hg is due to N2 (~593 mm Hg) and O2 (~159 mm Hg), with smaller contributions from trace gases such as argon (~7 mm Hg) and CO2(~0.2 mm Hg). Thus, as PB increases during diving beneath the water, or as PB decreases during ascent to high altitude, the partial pressure of each constituent gas will change in proportion to the change in PB. This relationship is important for O2 delivery to tissues because a key variable that determines the O2 saturation of hemoglobin (Hb) is PO2 in the inspired air (see p. 706).

The conducting airways humidify inspired air so that it becomes fully saturated with H2O vapor at body temperature (see box on “Wet Gases” on p. 615). The H2O vapor then occupies part of the space in the lungs. At a body temperature of 37°C, PH2O is 47 mm Hg. If PB is 760 mm Hg, only 760 – 47 = 713 mm Hg is available for the sum of PO2, PN2, and PCO2. Because H2O readily evaporates from (or condenses into) liquid water, its partial pressure does not change with changes in PB.

Contributed by Walter Boron

Conversion from ΔVBTPS to ΔVATPS

The basis for our derivation is the ideal gas law:

Equation 1

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We are interested in following a portion of the total volume of gas in the lungs as this volume moves from the lungs—at body temperature and pressure, saturated (BTPS)—to a spirometer in equilibrium with liquid water—at ambient temperature and pressure, saturated (ATPS). In the lungs, the volume exiting is ΔVBTPS. We focus on the number of gas molecules in the volume ΔVBTPS:

Equation 2

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Let us assume that the pressure inside the lungs (PBTPS) is the same as barometric pressure (PB), which is true when no air is flowing and the glottis is open:

Equation 3

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The n in Equation 3 has two components: H2O and the dry gases (i.e., everything other than H2O). The number of dry gas molecules is proportional to the partial pressure of the dry gases. Thus,

Equation 4

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For example, if PB is 760 mm Hg and body temperature is 37°C, then the number of dry molecules is

Equation 5

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Now, what volume would these same dry gas molecules occupy after exhalation into a spirometer at ambient temperature (TATPS)? We assume that the ambient pressure is PB. Rearranging the ideal gas law,

Equation 6

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Substituting into Equation 6 the value for ndry from Equation 4,

Equation 7

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Canceling R and rearranging terms,

Equation 8

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For example, if PB is 760 mm Hg and ambient temperature is 25°C, then the volume occupied by the dry molecules exhaled from the lungs is

Equation 9

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In other words, if the dry gas molecules occupied 1 liter in the lungs, they would occupy only 902 ml in the spirometer.

However, this volume of dry gas molecules does not represent all of the gas that we exhaled: We also exhaled water vapor. What volume does the water vapor occupy after we exhale it into the spirometer? The answer to this question may sound a bit strange, but the volume (or number) of water molecules exhaled from the lungs does not determine the volume (or number) of water molecules in the spirometer. The reason is that the partial pressure of H2O in the spirometer—the gas phase of which is in equilibrium with liquid H2O—depends not on the amount of H2O vapor you exhale but only on ambient temperature. Consider four examples:

1. If body temperature is higher than ambient temperature (i.e., PH2O is higher in the body than in the spirometer), then some of the exhaled H2O molecules condense into the liquid of the spirometer. This is the usual case. Once in the spirometer, the dry gas molecules from the lungs are accompanied by fewer gaseous H2O molecules than had accompanied them in the lungs.

2. If the body temperature were the same as ambient temperature, then the number of H2O molecules that accompanied the exhaled dry gas in the lungs would be the same as the number of H2O molecules that accompany this exhaled dry gas in the spirometer. In other words, ΔVBTPS would be the same as ΔVATPS.

3. If the body temperature were lower than ambient temperature, then the exhaled H2O molecules would be joined in the gas phase of the spirometer by additional H2O molecules evaporating from the spirometer’s liquid water. In other words, once in the spirometer, the dry gas molecules from the lungs would be accompanied by more gaseous H2O molecules than they had been accompanied by in the lungs.

4. Finally, imagine that instead of exhaling into the spirometer a volume ΔV of BTPS air—consisting of both dry air and H2O vapor—we instead introduce into the spirometer only the dry air at body temperature contained within ΔVBTPS. This dry air will be joined in the gas phase of the spirometer by H2O molecules that evaporate from the spirometer’s liquid water, and the final ΔV in the spirometer will be the same as if we had exhaled BTPS (i.e., wet) air into the spirometer.

Thus, in computing the total change in spirometer volume (ΔVATPS) we do not need to consider the number of H2O molecules exhaled from the lungs: We only need to compute how many gaseous H2O molecules must accompany the exhaled dry gas molecules once these dry gas molecules are in the friendly confines of the spirometer. We will approach this problem by computing the ratio of dry to total gas molecules contained in ΔVATPS. Within the volume ΔVATPS—inside the spirometer—the ratio of number of gas molecules is the same as the ratio of their respective pressures:

Equation 10

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Because total pressure is PB, and because the partial pressure of the dry gases is the difference between PB and the vapor pressure of H2O,

Equation 11

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Because the volume occupied by the gases is proportional to the number of gas molecules,

Equation 12

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Solving for the total ΔVATPS,

Equation 13

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Equation 13 tells us that if we know the volume that the exhaled dry gases occupy once they are in the spirometer, we can easily compute the total volume occupied by these dry molecules and their obligated H2O molecules. Substituting into Equation 13 our expression for ΔV of the dry molecules at ATPS in Equation 8,

Equation 14

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Canceling PB terms,

Equation 15

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Thus, if PB is 760 mm Hg and ambient temperature is 25°C, then

Equation 16

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If we wish to convert back from ΔVATPS to ΔVBTPS, then the comparable equations are

Equation 17

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and

Equation 18

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This last portion of Equation 18 is the same as the equation under the heading “ATPS” in the Box on p. 617 of the text.

Contributed by Walter Boron

Conversion from ΔVBTPS to ΔVATPS

The basis for our derivation is the ideal gas law:

Equation 1

image

We are interested in following a portion of the total volume of gas in the lungs as this volume moves from the lungs—at body temperature and pressure, saturated (BTPS)—to a spirometer in equilibrium with liquid water—at ambient temperature and pressure, saturated (ATPS). In the lungs, the volume exiting is ΔVBTPS. We focus on the number of gas molecules in the volume ΔVBTPS:

Equation 2

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Let us assume that the pressure inside the lungs (PBTPS) is the same as barometric pressure (PB), which is true when no air is flowing and the glottis is open:

Equation 3

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The n in Equation 3 has two components: H2O and the dry gases (i.e., everything other than H2O). The number of dry gas molecules is proportional to the partial pressure of the dry gases. Thus,

Equation 4

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For example, if PB is 760 mm Hg and body temperature is 37°C, then the number of dry molecules is

Equation 5

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Up to this point, the discussion has been identical to that in Web Note 0617b, Conversion from ΔVBTPS to ΔVATPS, where we asked what volume this dry gas (as well as its obligated water vapor) would occupy ambient temperature and pressure, saturated (ATPS). In this Web Note, we instead ask what volume would these exhaled dry gas molecules occupy at standard temperature and standard pressure? The definitions are as follows:

Equation 6

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Equation 7

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Rearranging the ideal gas law,

Equation 8

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Substituting into Equation 8 the value for ndry from Equation 4,

Equation 9

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Canceling R and rearranging terms,

Equation 10

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For example, if PB is 760 mm Hg, then the volume occupied by the dry molecules exhaled from the lungs is

Equation 11

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In other words, if the dry gas molecules occupied 1 liter in the lungs, they would occupy only 826 ml n the spirometer.

If we wish to convert back from ΔVSTPD to ΔVBTPS, then the comparable equations are

Equation 12

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and

Equation 13

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This last portion of Equation 13 is the same as the equation under the heading “STPD” in the box on p. 617 of the text.

Contributed by Walter Boron

Flow versus Flux

On p. 618 of the text, we state that the flow of a gas across the blood–gas barrier is proportional to (1) the driving force—in this case the partial pressure gradient (ΔP) of the gas—across the barrier and (2) the area of the barrier. This concept is embodied in Equation 26–2 on p. 618 in the text:

Equation 1

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Not that flow has the units of mass per unit time—here, milliliters per minute. The flow per unit area is known as the flux, which in the context of the lung has the units of mL/[cm–2·s]). Thus, the area term does not appear in the equation that describes flux:

Equation 2

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Equation 2 is a restatement of Fick’s law, which we introduced in the text in Equation 5–13 on p. 112 and also Equation 20–4 on p. 486. For a more detailed discussion of Fick’s law, consult Web Note 0467, Fick’s Law.

In the case of the lung, pulmonary specialists do not work with flux values but, rather, with flow values because the surface area over which diffusion occurs is generally not known.

Contributed by Emile Boulpaep and Walter Boron

Hemocyanin

http://en.wikipedia.org/wiki/Hemocyanin

Hemerythrins

http://en.wikipedia.org/wiki/Hemerythrin

Pores of Kohn

The so-called pores of Kohn are named after HN Kohn, who in 1893 described pores through the alveolar wall in lungs from patients with pneumonia. He thought that these pores were pathological. However, nearly a half-century earlier, others had described alveolar pores in normal lungs. Kohn’s mentor later named the pores after his student, and the name stuck.

Modern ultrastructural work is consistent with the hypothesis that the pores of Kohn are fixation artifacts. If lungs are fixed by instilling the fixative into the trachea, one can observe small holes in the alveolar wall (Cordingley, 1972). However, if the lungs are fixed by perfusing the pulmonary blood vessels, the alveolar wall is continuous (i.e., no pores are to be seen).

Whether the pores are fixation artifacts or not, they are so small (about half the diameter of a pulmonary capillary) that it is unlikely that they play an important role in collateral ventilation, that is, the movement of air between adjacent alveoli.

For an excellent review, consult Mitzner’s chapter.

Reference

Cordingley JL: Pores of Kohn. Thorax 27:433–441, 1972.

Gil J, Weibel ER: Improvements in demonstration of lining layer of lung alveoli by electron microscopy, Respir Physiol 70:13–36, 1969.

Mitzner W: Collateral ventilation. In Crystal RG, West JB, et al., editors: The lung: scientific foundations, New York, 1991, Raven Press.

Parra SC, Gaddy LR, Takaro T: Ultrastructural studies of canine interalveolar pores (of Kohn). Lab Invest 38:8–13, 1978.

Contributed by Emile Boulpaep and Walter Boron

Helium Dilution Technique

In the text, we assumed that the spirometer volume (VS) at the time we opened the stopcock in Figure 26-9A on p. 627 was the same as the spirometer volume at the end of the experiment. We also implicitly assumed that the same was true of the lung volume (VL). However, this need not be true. At the instant we open the stopcock, the total volume of the system—that is, the sum of VS and VL—is in principle a constant. As the subject inhales, the VL increases but VS decreases, and vice versa. If the spirometer volume at the end of the experiment (VS,final) were different from the spirometer volume at the beginning (VS,initial), then Equation 26–3 on p. 626 in the text would be replaced by the following:

Equation 1

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Here, [He]initial is the initial concentration of helium in the spirometer, and [He]final is the final concentration of helium in the spirometer and in the lung’s airways. Thus, solving for final lung volume (VL,final),

Equation 2

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If we use the previous equation, it does not matter whether the initial and final spirometer volumes are the same. The computed VL,final is the lung volume at the instant we take a reading of VS,final. For example, even if the lungs were at FRC at the instant that the stopcock was opened (i.e., at the beginning of the experiment), if the lungs were at RV at the time we measure VL,final (i.e., at the end of the experiment) then Equation 2 will yield RV. In fact, VL,finalcan be anywhere between the RV and TLC.

If, at the end of the experiment, the subject adjusts his or her lung volume to be the same as at the beginning, then the initial and final spirometer volumes will also be the same (i.e., VS,initial = VS,final). In this case, Equation 2 simplifies to Equation 26–4 on p. 626 in the text:

Equation 3

image

Contributed by Emile Boulpaep and Walter Boron

Measurement of Intrapleural Pressure

Measuring intrapleural pressure (PIP) is intrinsically difficult because the space between the visceral and parietal pleuras is very thin (5–35 μm). The approaches include a pleural needle, a pleural catheter, esophageal balloon, pleural balloon, and a rib capsule (embedded in a rib) in direct contact with pleural fluid.

Each of these methods reports a vertical gradient in pleural pressure on the order of 0.5 cm H2O/cm in head-up dogs. This pressure gradient drives a downward viscous flow of pleural fluid, presumably along the flat surfaces of the ribs. According to a model, recirculation of pleural fluid would be achieved by an upward flow of fluid along the margins of adjacent lobes of the lungs (here, the fluid-filled space is larger, leading to a reduced resistance), energized by movements of the beating heart and ventilating lungs. Finally, a transverse flow of pleural fluid from these margins back to the flat portions of the ribs would complete the circuit.

REFERENCE

Lai-Fook SJ: Pleural mechanics and fluid exchange. Physiol Rev 84:385–410, 2004.

Contributed by Walter Boron

Actions of External and Internal Intercostal Muscles

Contrary to conventional wisdom, recent work shows that not all external intercostal muscles are inspiratory, and that not all internal intercostal muscles are expiratory. For an exhaustive analysis of this subject, consult the review by De Troyer et al.

REFERENCE

De Troyer A, Kirkwood PA, and Wilson TA: Respiratory action of the intercostal muscles. Physiol Rev 85:717–756, 2005.

Contributed by Walter Boron

Laplace’s Law for a Sphere

Imagine a soap bubble that is perfectly spherical. At equilibrium, the tendency of the transmural pressure (P) to expand the bubble exactly balances the tendency of the surface tension (T) to collapse the bubble. An infinitesimally small change in the radius of the sphere (dr) would produce infinitesimally small changes in both the area of the sphere (dA) and the volume of the sphere (dV). The infinitesimally small amount of pressure × volume work done in expanding the volume would equal the tension × area work done in expanding the surface area:

Equation 1

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Because the volume of a sphere is (4/3)πr3,

Equation 2

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Similarly, the area of a sphere is 4πr2. Thus,

Equation 3

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Substituting the expressions for dV (Equation 2) and dA (Equation 3) into Equation 1, we have

Equation 4

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Rearranging and solving for P, we have

Equation 5

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In our example of a soap bubble—and also in the hypothetical example of a perfectly spherical alveolus—T is a constant, r is the independent variable, and P is the dependent variable. Thus, a sphere with a smaller radius must have a larger transmural pressure to remain in equilibrium.

Prange discusses the limitations in applying Laplace’s law to alveoli. As noted in the text on p. 637, the alveoli are not perfect spheres of uniform spheres. Moreover, their interiors are interconnected, and individual alveoli often share walls with their adjacent neighbors (principle of interdependence).

REFERENCE

Prange HD: Laplace’s law and the alveolus: A misconception of anatomy and a misapplication of physics. Adv Physiol Educ 27:34–40, 2003.

Contributed by Emile Boulpaep and Walter Boron

The Role of Surfactant in the “Static” Pressure–Volume Loop

The classic, static pressure–volume loop exhibits considerable hysteresis (see large loop formed by purple and red curves in Fig. 27–4B on p. 633 of the text). This hysteresis is due in large part to the movement of surfactant into the air–water interface as the lung inflates from RV to TLC, and to the movement of surfactant out of the air–water interface as the lung deflates from TLC to RV.

During normal, quiet breathing, the pressure–volume loop (see small green loop, also in Fig. 27-4B) lies near the deflation limb of the “classic” blue loop. The quiet-breathing loop differs from the classic loop in three respects. First, the green quiet-breathing loop covers a much smaller range of pressures and volumes. Second, the green quiet-breathing loop exhibits very little hysteresis because relatively less surfactant moves into the air–water interface during inspiration and out of the air–water interface during expiration at these small tidal volumes. Third, at comparable lung volumes, the average compliance in the quiet-breathing loop (i.e., the slope of a line drawn between the two ends of the loop) is less than the static compliance of the classic loop’s deflation limb. Again, this difference arises because during quiet breathing, less surfactant is present at the air–water interface, causing the lungs to be stiffer.

During quiet breathing, the pool of surfactant available to move into and out of the air–water interface with each tidal volume gradually decreases as the result of the catabolism of surfactant (see Fig. 27–8Aon p. 639 of the text). As a result, the lungs gradually stiffen. In other words, the fall in compliance makes the lungs more difficult to inflate. In fact, some alveoli collapse, a condition termed atelectasis. This collapse is particularly prevalent in dependentregions of the lungs (e.g., the base of the lung in an upright individual), reflecting the relatively less negative PIP near the base of the lung (see Fig. 27–2 on p. 631) and thus the smaller degree of inflation. Fortunately, stretch receptors in the lung sense this atelectasis and trigger a large inspiratory effort to TLC—a sigh or a yawn (see box on p. 744 in the text). Sighing and, even more so, yawning are powerful stimuli for trafficking surfactant to the air–water interface, increasing compliance and reversing the atelectasis.

Contributed by Emile Boulpaep and Walter Boron

Aggregate Resistance of Small Airways

In the text, we point out that although each small airway has a high individual resistance compared to each large airway, there are so many of these small airways aligned in parallel that their aggregate resistance is very low.

In Chapter 17, we introduce the concept of how to compute the aggregate resistance of a group of blood vessels (or resistors) arranged in parallel. We used Equation 17–3 on p. 431, which we reproduce here:

Equation 1

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If we assume that each of N parallel branches has the same resistance Ri (i.e., Ri = R1 = R2 = R3 = R4 = …), then the overall resistance is

Equation 2

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Thus,

Equation 3

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As an example, let us compare the aggregate resistance at generations 10 and 16. At generation 10, the airway diameter may be approximately 1.2 mm (r = 0.6 mm), whereas at generation 16 the diameter might be 0.6 mm (r = 0.3 mm). Because the radius has fallen by a factor of 2 between generations 10 and 16, the fourth-power relationship between radius and resistance (Equation 27–8 on p. 640 of the text) tells us that the unitary resistance of each airway must increase by a factor of 16. However, there are 26-fold more airways at generation 16 than at generation 10. Thus, if we make the simplifying assumption that the airway length is the same for the two generations, we would conclude that the aggregate resistance falls to 16/64 or 25% of the initial value as we move from generation 10 to generation 16.

Contributed by Emile Boulpaep and Walter Boron

Effect of Increased Airway Resistance on Maximal Airflow

Beginning on p. 641 of the text, we presented an example in which chronic obstructive pulmonary disease (COPD) increased airway resistance (R) by a factor of 3.3 (from 1.5 to 5.0 respiratory resistance units of cm H2O/[L/s]; see Table 27–2 on p. 643). If the maximal ΔP that the subject can generate between atmosphere and alveoli (ΔPMax) were to remain normal, then the maximal airflow (V.Max—measured in liters/second) would also decrease by a factor of 3.3:

image

Although the relationship between V.max and the maximal amount of O2 taken up per minute (V.O2 max; see p. 1256 of the text) is not directly proportional, it is intuitively obvious that as V.max falls, V.O2maxmust also fall—and with it, the maximal amount of exercise that the individual can perform. Thus, if the healthy individual—running with maximal effort—were capable of jogging a kilometer in, for example, 5 minutes, then our COPD patient might at best be able to walk that distance over a much longer time. With further increases in R, the maximal exercise capacity of the COPD patient would gradually decline, and with sufficiently severe disease the patient might have difficulty even walking along a perfectly flat surface without aid of supplemental oxygen.

Contributed by Emile Boulpaep and Walter Boron

Airway Resistance

In the lower right panel of Figure 27-13 on p. 645 of the text, we have assumed that airway resistance (RAW) is constant during a respiratory cycle, so that the PA-V. curve is a straight line. However, RAWchanges with lung volume (see burgundy and teal curves in Fig. 27–12A on p. 645) and, as discussed on p. 650, airway collapse during expiration causes RAW to be greater during expiration than inspiration.

Contributed by Emile Boulpaep and Walter Boron

Model of the Respiratory Cycle

The four large graphs with gray backgrounds in Figure 27-14 on p. 647 of the text represent a hypothetical respiratory cycle. We generated the tracings using a rather simple computer model, making the following assumptions:

1. Throughout the respiratory cycle, the static compliance (C) was a constant 0.2 L/cm H2O.

2. Throughout the respiratory cycle, the resistance (R) was a constant 1 cm H2O/(L/s).

3. The initial lung volume (VL) was 3.2 L, corresponding to time zero in the graphs (i.e., point “a” in the four panels).

4. During inspiration, the subject shifted intrapleural pressure (PIP) from –5 cm H2O to –7.5 cm H2O with an exponential time course (time constant = 0.01 s). This value of τ for PIP results in τ for VL of approximately 0.2 s, consistent with the theoretical requirement that VL = R × C = 1 × 0.2 = 0.2 s. Thus, PIP is the prime mover, the parameter that our hypothetical subject controlled. A second consequence is that because (a) PIP changes by 2.5 cm H2O and (b) the compliance is 0.2 L/cm H2O, the total change in lung volume (ΔVL) was 0.5 L.

5. Expiration was the reverse of inspiration, with PIP shifting from –7.5 to –5.0 cm H2O with a time constant, once again, of 0.01 s. Again, the τ for VL was approximately 0.2 s.

In the actual modeling, we divided the inspiration and expiration into multiple 10-ms intervals. Each interval had two phases, one in which we allowed the change in PIP to change the lung volume, but with no airflow, and a second in which we allowed air to flow as dictated by the alveolar pressure and airway resistance.

First phase. At time zero (point a in the four panels), we imagined that we plugged the trachea with a cork and then allowed the subject to begin the inspiratory effort for a duration of 10 ms. PIP became slightly more negative according to the aforementioned exponential time course. At the end of the 10-ms period, we computed the new value of VL, knowing the current value of PIP and the compliance, and also assuming that the air molecules inside the lung obeyed the ideal gas law (PA VL = nRT). Keep in mind that because we plugged the trachea with a cork, the number of air molecules in the lung was fixed during the 10-ms period of inspiratory effort. Thus, we could compute the new value of PA. From this new value of PA and the current value of PIP, we could compute the transpulmonary pressure (PTP) after 10 ms. Thus, at the end of the first phase, we have new values for PIP, VL, PA, and PTP.

Second phase. Now that we determined the new value of PA, we removed our hypothetical cork for 10 ms and allowed air to flow into the lung, governed by the equation V = ΔP/R. Note that ΔP is the difference between barometric pressure (PB) and PA. At the end of 10 ms, we replaced the cork (the flow of air is far from complete). Knowing how many air molecules entered during the 10-ms interval, and assuming that PIP has not changed, we can now recompute all the relevant parameters and start the first phase of the second cycle.

Thus, although we assumed the time course of the green PIP-vs-time curve in the second gray panel of Figure 27-14 on p. 647, all of the other curves follow directly from the calculations and the assumed parameters. The time constant (τ) for VL that falls out of our computer simulation is approximately 0.2 s. As discussed in this Web Note, the theoretical time constant for a change in lung volume is the product R × C. In the model we have been discussing, R × C evaluates to a time constant of 0.2 s, which agrees well with our simulation. Note that the τ we assumed for the change in PIP was 0.01 s, which is considerably faster than the for the change in VL and thus is not rate limiting.

Contributed by Emile Boulpaep and Walter Boron

Calculating the Time Constant for a Change in Lung Volume

It should not be very surprising that the τ for the time course of VL is 0.2 s. Just as for electrical circuits, where the time constant of a resistor–capacitor network is R × C—where R is resistance and C is capacitance—the time constant for inflating a lung is the product of the airway resistance and the static compliance:

Equation 1

image

For healthy human lungs, we might assume that R is approximately 1 cm H2O/(L/s)—on p. 641 (left column) of the text we pointed out that normal values for R might range from 0.6 to 2.3 cm H2O/(L/s). We also might assume that C is approximately 0.2 L/cm H2O (see p. 615, left column). Thus, our predicted time constant is

Equation 2

image

If R increased fivefold from 1 to 5 cm H2O × s × L-1, the time constant would also quintuple:

Equation 3

image

Note that the time constant that we have computed is a theoretical minimum. The actual τ can only be as small as R× C if the individual making an inspiratory or expiratory effort decides to change PIP (or is capable of changing PIP) very rapidly compared to R× C. If the person decides to inhale or exhale slowly, then of course the actual time course with which VL changes can be far larger than R× C. As an extreme example, if an oboe player decides to exhale over a period of many tens of seconds, the time constant no longer depends on the mechanical properties of the lung but, rather, on the activity of the cerebral cortex.

Contributed by Emile Boulpaep and Walter Boron

Calculating the Time Constant for a Change in Lung Volume

It should not be very surprising that the τ for the time course of VL is 0.2 s. Just as for electrical circuits, where the time constant of a resistor–capacitor network is R × C—where R is resistance and C is capacitance—the time constant for inflating a lung is the product of the airway resistance and the static compliance:

Equation 1

image

For healthy human lungs, we might assume that R is approximately 1 cm H2O/(L/s)—on p. 641 (left column) of the text we pointed out that normal values for R might range from 0.6 to 2.3 cm H2O/(liter/s). We also might assume that C is approximately 0.2 L/cm H2O (see p. 615, left column). Thus, our predicted time constant is

Equation 2

image

If R increased fivefold from 1 to 5 cm H2O × s × L-1, the time constant would also quintuple:

Equation 3

image

Note that the time constant that we have computed is a theoretical minimum. The actual τ can only be as small as R× C if the individual making an inspiratory or expiratory effort decides to change PIP (or is capable of changing PIP) very rapidly compared to R× C. If the person decides to inhale or exhale slowly, then of course the actual time course with which VL changes can be far larger than R× C. As an extreme example, if an oboe player decides to exhale over a period of many tens of seconds, the time constant no longer depends on the mechanical properties of the lung but, rather, on the activity of the cerebral cortex.

Contributed by Emile Boulpaep and Walter Boron

Implications of High-Frequency Breathing in a Patient with a High Time Constant

As discussed in the text, a patient with increased airway resistance will require longer than normal to inflate the lungs by the expected tidal volume during an inspiratory effort (i.e., is increased) and will require longer than normal to deflate the lungs to the functional residual capacity during an expiratory effort (see Fig. 27–15A on p. 648 of the text). As a consequence, as such a patient breathes with ever-increasing respiratory frequencies, the effective tidal volume will fall (see Fig. 27–15C). The effect on the ventilation of alveoli is even more severe.

As discussed in Chapter 31, even in healthy lungs, not all of the tidal volume reaches the alveoli—a fixed amount (~150 mL per breath) is wasted ventilating the conducting airways (see the passage beginning on p. 700), which have no alveoli. Only the part of the tidal volume in excess of, for example, 150 mL actually reaches the alveoli. Thus, as the tidal volume gradually falls at increasing respiratory frequencies, the first volume to fall is the air ventilating the alveoli. The fall in tidal volume in a patient with increased airway resistance (i.e., an increased τ) can therefore cause alveolar ventilation to fall far more steeply than the total ventilation.

Contributed by Emile Boulpaep and Walter Boron

Hydrogen Ions in Aqueous Solutions

Hydrogen ions do not truly exist as “free” protons in aqueous solutions. Instead, a shell of water molecules surrounds a proton, forming an extended complex sometimes denoted as H3O+ (hydronium ion) or H9O4+. Nevertheless, for practical purposes, we will treat the proton as if it were free. Also—as we do elsewhere in this book—we shall refer to concentrations of H+, bicarbonate (HCO3), and other ions. Bear in mind, however, that it is more precise to work with ion activities (i.e., the effective concentrations of ions in realistic, nonideal solutions).

Contributed by Emile Boulpaep and Walter Boron

The Origin of the ‘p’ of pH

Although the conventional wisdom is that the ‘p’ of ‘pH’ stands for the power of 10, Norby’s analysis of Sørensen’s original papers reveals a far more accidental explanation.

Sørensen used ‘p’ and ‘q’ to represent two solutions in an electrometric experiment. He arbitrarily assigned the standard ‘q’ solution a [H+] of 1N (Normal). That is, his standard solution had a [H+] of 1N, which is Cq = 10q. His unknown, therefore, had an [H+] of Cp = 10p. Using this approach, Sørensen proposed the nomenclature p+H, and nowadays we use simply pH.

REFERENCE

Norby JG: The origin and the meaning of the little p in pH. TIBS 25:36–37, 2000.

Sørensen SPL: Études enzymatiques: II. Sur la mesure et l’importance de la concentration des ions hydrogène dans les réactions enzymatiques. Compt. rend. du Lab. de Carlsberg 8:1–168, 1909.

Sørensen SPL: Enzymstudien: II. Mitteilung. Über die Messung und die Bedeutung der Wasserstoffionenkoncentration bei enzymatischen Prozessen. Biochem Zeitschr 21:131–304, and 22:352–356, 1909.

We thank Christian Aalkjær of the University of Aarhus in Denmark for bringing Norby’s paper to our attention.

Contributed by Emile Boulpaep and Walter Boron

Buffering of H+

For each H+ buffered in Equation 28–6 on p. 653 of the text, one B(n) is consumed. For each OH buffered in Equation 28–7 on p. 653, one B(n) is formed. Because almost all of the added H+ or OH is buffered, the change in the concentration of the unprotonated form of the buffer (i.e., Δ[B(n)]) is a good index of the amount of strong acid or base added per liter of solution.

Contributed by Walter Boron

Out-of-Equilibrium CO2/HCO3 Solutions

As described in the text beginning on the left column of p. 654, adding carbon dioxide to an aqueous solution initiates a series of two reactions that, in the end, produce bicarbonate and protons:

Equation 1

image

In the absence of carbonic anhydrase (CA), the first reaction—the hydration of CO2 to form carbonic acid—is extremely slow. The second is extremely fast. At equilibrium, the overall rate of the two forward reactions must be the same as the overall rate of the reverse reactions:

Equation 2

image

The first of these reverse reactions is extremely rapid, whereas the second—the dehydration of H2CO3 to form CO2 and water—is extremely slow in the absence of CA. As noted in the text, we can treat the system as if only one reaction were involved:

Equation 3

image

Moreover, we can describe this pseudoreaction by a single equilibrium constant. As shown by Equation 28–15 on p. 654 of the text, we can describe the equilibrium condition in logarithmic form by the following equation:

Equation 4

image

In other words, considering only equilibrium conditions, it is impossible to change pH or [HCO3] or [CO2] one at a time. If we change one of the three parameters (e.g., pH), we must change at least one of the other two (i.e., [HCO3] or [CO2]). Unfortunately, there are many cases in which the addition of CO2 and HCO3 markedly enhances some process. For example, at identical values of intracellular pH, the activation of quiescent cells by mitogens is far more robust in the presence than in the absence of the physiological CO2/HCO3 buffer. Which buffer component is critical in this case, CO2 or HCO3? There are also many cases in which a stress such as respiratory acidosis or metabolic acidosis triggers a particular response. For example, respiratory acidosis stimulates HCO3 reabsorption by the kidney—a metabolic compensation to a respiratory acidosis, as discussed beginning on p. 665 in the text. Again, we can ask which altered parameter signals the kidney to increase its reabsorption of HCO3, the rise in [CO2] or the fall in pH?

image

In the 1990s, the laboratory of Walter Boron realized that it could exploit the slow equilibrium CO2 + H2image H2CO3 to create CO2/HCO3 solutions that are temporarily out of equilibrium. Figure 1A illustrates how one can make an out-of-equilibrium (OOE) “pure” CO2 solution that contains a physiological level of CO2, has a physiological pH, but contains virtually no HCO3. The approach is to use a dual syringe pump to rapidly mix the contents of two syringes, each flowing at the same rate. One syringe contains a double dose of CO2 at a pH (e.g., 10% CO2) that is so low (e.g., pH 5.40) that, given a pKof approximately 6.1, very little HCO3 is present. The other syringe contains a well-buffered, relatively alkaline solution that contains no CO2 or HCO3. The pH of this second solution is chosen so that at the instant of mixing at the “T,” the solution has a pH of 7.40. Of course, the [CO2] after mixing is 5% (which corresponds to a PCO2 of ~37 mm Hg), and the [HCO3] is virtually zero. The solutions flow so rapidly that they reach the cell of interest before any significant re-equilibration of the CO2 and HCO3. Moreover, a suction device continuously removes the solution. As a result, the cells are continuously exposed to a freshly generated, out-of-equilibrium solution.

Figure 1B illustrates how one could make the opposite solution—a “pure” HCO3 solution that has a physiological [HCO3] and pH but virtually no [CO2]. The OOE approach can be used to make solutions with virtually any combination of [CO2], [HCO3], and pH—at least for moderate pH values. At extremely alkaline pH values, the reaction CO2 + OH HCO3 generates HCO3 so fast that it effectively short-circuits the OOE approach. Conversely, at extremely acid pH values, the rapid reaction H+ + HCO3 H2CO3 creates relatively high levels of H2CO3 so that even the uncatalyzed reaction H2CO3 CO2 + H2O is high enough to short-circuit the OOE approach. Nevertheless, at almost any pH of interest to physiologists, OOE technology allows one to change [CO2], [HCO3], and pH one at a time.

Work on renal proximal tubules with OOE solutions has shown that proximal tubules have the ability to sense rapid shifts in the CO2 concentration of the basolateral (i.e., blood side) solution that surrounds the outside of the tubule. This work suggests that the tubule has a sensor for CO2 that is independent of any changes in pH or HCO3. The tubule uses this CO2-sensing mechanism in its response to respiratory acidosis (see p. 661 of the text). This metabolic compensation involves a rapid increase in the rate at which it transports HCO3 from the tubule lumen to the blood, and thus a partial correction of the acidosis.

Work on neurons cultured from the hippocampus suggests that certain neurons can detect rapid decreases in the extracellular HCO3 concentration ([HCO3]o), independent of any changes in pHo or [CO2]o. The cell may use this detection system to stabilize intracellular pH (pHi) during extracellular metabolic acidosis, which would otherwise lower pHi.

REFERENCE

Ganz MB, Boyarsky G, Sterzel RB, et al.: Arginine vasopressin enhances pHi regulation in the presence of HCO3 by stimulating three acid–base transport systems. Nature 337:648–651, 1989.

Ganz MB, Perfetto MC, and Boron WF: Effects of mitogens and other agents on mesangial cell proliferation, pH and Ca2+Am J Physiol 259:F269–F278, 1990.

Zhao J, Hogan EM, Bevensee MO, et al.: Out-of-equilibrium CO2/HCO3 solutions and their use in characterizing a novel K/HCO3 cotransporter. Nature 374:636–639, 1995.

Zhao J, Zhou Y, and Boron WF: Effect of isolated removal of either basolateral HCO3 or basolateral CO2 on HCO3 reabsorption by rabbit S2 proximal tubule. Am J Physiol Renal Physiol 285:F359–F369, 2003.

Contributed by Walter Boron

Carbonic Anhydrases

The carbonic anhydrases (CAs) are a family of zinc-containing enzymes with at least 16 members among mammals; Table 1 accompanying this Web Note lists some of these isoforms. Physiologically, the CAs catalyze the interconversion of CO2 and HCO3, although they can also cleave aliphatic and aromatic ester linkages. Carbonic anhydrase I (CA I) is present mainly in the cytoplasm of erythrocytes. CA II is a ubiquitous cytoplasmic enzyme. CA IV is a GPI-linked enzyme (see p. 18 of the text) found, for example, on the outer surface of the apical membrane of the renal proximal tubule (see Fig. 39–2A on p. 854). A hallmark of many CAs is their inhibition by sulfonamides (e.g., acetazolamide).

Before considering the action of CA, it is instructive to examine the interconversion of CO2 and HCO3 in the absence of enzyme. When [CO2] increases,

Equation 1

image

CO2 can also form HCO3 by directly combining with OH, a reaction that becomes important at high pH values, when [OH] is also high:

Equation 2

image

Because the dissociation of H2O replenishes the consumed OH, the two mechanistically distinct pathways for HCO3 formation are functionally equivalent. Of course, both reaction sequences are reversible. However, in the absence of CA, the overall speed of the interconversion between CO2 and HCO3 is slow at physiological pH. In fact, it is possible to exploit this slowness experimentally to generate and CO2/HCO3 solutions that are temporarily “out of equilibrium” (see Web Note 654a, Out-of-Equilibrium CO2HCO3 Solutions). Unlike normal (i.e., equilibrated) solutions, such out-of-equilibrium solutions can have virtually any combination of [CO2], [HCO3], and pH in the physiological range.

Structural biologists have solved the crystal structures of several CAs. At the reaction site, three histidines coordinate a zinc atom that, along with a threonine, plays a critical role in binding CO2 and HCO3. In CA II, the fastest of the CAs, a fourth histidine acts as a proton acceptor/donor. Extensive site-directed mutagenesis studies have provided considerable insight into the mechanism of the CA reaction. The CAs have the effect of catalyzing the slow CO2hydration in Equation A. Actually, these enzymes catalyze the top reaction in Equation B, the direct combination of CO2 with OH to form HCO3

CA II catalyzes both reactions in Equation B:

image

CA II has one of the highest turnover numbers of any known enzyme: Each second, one CA II molecule can convert more than 1 million CO2 molecules to HCO3 ions. In the erythrocyte, this rapid reaction is important for the carriage of CO2 from the peripheral blood vessels to the lungs (see p. 681). In the average cell, CAs are important for allowing the rapid buffering of H+ by the CO2/HCO3 buffer pair and probably also for minimizing pH gradients near membranes with transporters engaging in the transport of H+ and image.

In humans, the homozygous absence of normal CA II causes CA II deficiency syndrome, characterized by osteopetrosis, renal tubular acidosis, and cerebral calcification. At least seven different mutations can cause genetic defects. The mutation that is common in patients of Arabic descent causes mental retardation but less severe osteopetrosis. Other patients may carry two different mutations. Indeed, the first three patients described with CA II deficiency syndrome, sisters in the same family, were compound heterozygotes, having received one mutation from their mother and a second from their father.

Although CA I deficiency exists, the homozygous condition has no obvious consequences because CA I and CA II normally contribute approximately equally to the CA activity in red blood cells.

Table 1 Some Human Carbonic Anhydrasesa

Isoform

Molecular Mass (kDa)

Cellular Location

Tissue Distribution

Relative Activity (%)

Sensitivity to Sulfonamides (e.g., Acetazolamide)

I

29

Cytosol

RBCs and GI tract

15

High

II

29

Cytosol

Nearly ubiquitous

100

High

III

29

Cytosol

8% of soluble protein in slow-twitch (type I) muscle

1

Low

IV

35

Extracellular surface of membrane (GPI-linked)

Widely distributed, including acid-transporting epithelia

~100

Moderate

IX

54/58

Catalytic domain on extracellular surfaceb

Certain cancers

~100

High

XII

44

Catalytic domain on extracellular surfaceb

Certain cancers

~30

Binds ACZ with unknown affinity

XIV

54

Catalytic domain on extracellular surfaceb

Kidney, heart, skeletal muscle, brain

~100

?

aSeveral additional CAs have been cloned. In some cases, they have not been functionally characterized.

bIntegral membrane protein with one membrane-spanning segment.

ACZ, acetazolamide; GPI, glycosyl phosphatidylinositol; RBC, red blood cell.

REFERENCE

Purkerson JM, and Schwartz GJ: The role of carbonic anhydrases in renal physiology. Kidney Int 71:103–115, 2007.

Sly WS, and Hu PY: Human carbonic anhydrases and carbonic anhydrase deficiency. Annu Rev Biochem 64:375–401, 1995.

Wykoff CC, Beasley N, Watson PH, Campo L, Chia SK, English R, Pastorek J, Sly WS, Ratcliffe P, and Harris AL: Expression of the hypoxia-inducible and tumor-associated carbonic anhydrases in ductal carcinoma in situ of the breast. Am J Pathol 158:1011–1019, 2001.

Contributed by Emile Boulpaep and Walter Boron

Derivation of the Henderson–Hasselbalch Equation

As shown in Equation 28–13 on p. 654 of the text,

image

We can define a dissociation constant for this pseudo-equilibrium:

Equation 1

image

Factoring out [H2O], we can define an apparent equilibrium constant:

Equation 2

image

Equation 2 is Equation 28–14 in the text. K at 37°C is approximately 10–6.1 M or 10–3.1 mM. Taking the log (to the base 10) of each side of this equation, and remembering that log(a × b) = log(a) + log(b), we have

Equation 3

image

Remembering that log [H+] ≡ –pH and log K≡ –p K, we may insert these expressions into Equation 3 and rearrange to obtain

Equation 4

image

This expression is the same as Equation 28–15 in the text. Finally, we may express [CO2] in terms of PCO2, recalling from Henry’s law that [CO2] = s × PCO2:

Equation 5

image

This is the Henderson–Hasselbalch equation, a logarithmic restatement of the CO2/HCO3 equilibrium in Equation 1.

Contributed by Emile Boulpaep and Walter Boron

Derivation of Expressions for Buffering Power in Closed and Open Systems

How does buffering power, in either a closed or an open system, depend on pH?

Closed system. We start with a restatement of Equation 28–8 on p. 653 of the text, in which we define buffering power as the amount of strong base that we need to add (per liter of solution) in order to increase the pH by one pH unit. In differential form, this definition becomes

Equation 1

image

Second, because the change in the concentration of the unprotonated form of the buffer, [B(n)], is very nearly the same as the amount of strong base added (see p. 653, below Equation 28–7), Equation 1 becomes

Equation 2

image

The third step is to combine Equation 28–3 on p. 653 of the text, reproduced here,

Equation 3

image

and Equation 28–5, reproduced here,

Equation 4

image

to obtain an expression that describes how [B(n)] depends on the concentration of total buffer, [TB], and [H+]:

Equation 5

image

Finally, we obtain the closed-system buffering power by taking the derivative of [B(n)] in Equation 5 with respect to pH. If we hold [TB] constant while taking this derivative (i.e., if we assume that the buffer can neither enter nor leave the system), we obtain the expression for βclosed:

Equation 6

image

Open system. How doesopen depend on PCO2 and pH? The first two steps of this derivation are the same as for the open system, except that we recognize that for the CO2/HCO3 buffer pair, [B(n)] is [HCO3]:

Equation 7

image

For the open system, the third step is to rearrange the Henderson–Hasselbalch equation (Equation 28–16 on p. 654, reproduced here),

Equation 8

image

and rearrange it to solve for [HCO3]:

Equation 9

image

If we take the derivative of [HCO3] in Equation 9 with respect to pH, holding PCO2 constant, the result is β open:

Equation 10

image

Because Equation 9 tells us that everything after “2.3” in Equation 10 is, in fact, “[HCO3],” we obtain the final expression for open:

Equation 11

image

This is Equation 28–20 on p. 656 of the text.

Contributed by Emile Boulpaep and Walter Boron

Derivation of Expressions for Buffering Power in Closed and Open Systems

How does buffering power, in either a closed or an open system, depend on pH?

Closed system. We start with a restatement of Equation 28–8 on p. 653 of the text, in which we define buffering power as the amount of strong base that we need to add (per liter of solution) in order to increase the pH by one pH unit. In differential form, this definition becomes

Equation 1

image

Second, because the change in the concentration of the unprotonated form of the buffer, [B(n)], is very nearly the same as the amount of strong base added (see p. 653, below Equation 28–7), Equation 1 becomes

Equation 2

image

The third step is to combine Equation 28–3 on p. 653 of the text, reproduced here,

Equation 3

image

and Equation 28–5, reproduced here:

Equation 4

image

to obtain an expression that describes how [B(n)] depends on the concentration of total buffer, [TB], and [H+]:

Equation 5

image

Finally, we obtain the closed-system buffering power by taking the derivative of [B(n)] in Equation 5 with respect to pH. If we hold [TB] constant while taking this derivative (i.e., if we assume that the buffer can neither enter nor leave the system), we obtain the expression for βclosed:

Equation 6

image

Open system. How doesopen depend on PCO2 and pH? The first two steps of this derivation are the same as those for the open system, except that we recognize that for the CO2/HCO3 buffer pair, [B(n)] is [HCO3]:

Equation 7

image

For the open system, the third step is to rearrange the Henderson–Hasselbalch equation (Equation 28–16 on p. 654, reproduced here),

Equation 8

image

and rearrange it to solve for [HCO3]:

Equation 9

image

If we take the derivative of [HCO3] in Equation 9 with respect to pH, holding PCO2 constant, the result is open:

Equation 10

image

Because Equation 9 tells us that everything after “2.3” in Equation 10 is, in fact, “[HCO3],” we obtain the final expression for open:

Equation 11

image

This is Equation 28–20 on p. 656 of the text.

Contributed by Emile Boulpaep and Walter Boron

Metabolic Alkalosis Caused by Vomiting

Because the stomach secretes HCl into the lumen of the stomach, vomiting necessarily results in a net loss of HCl (see Web Note 0665, Equivalency of Adding HCO3, adding OH, or removing H), and this by itself causes some degree of metabolic alkalosis (see p. 659 of the text). In addition, the loss of Cl leads to volume contraction—that is, a decrease in effective circulating volume (see p. 575). The body’s multipronged response to this volume contraction (see p. 869) includes a stimulation of the renin–angiotensin–aldosterone axis, the endpoint of which is increased retention of NaCl and the osmotically obligated H2O. However, at the level of the renal proximal tubule, the increased levels of systemic [Ang II] lead not only to an increase in NaCl reabsorption but also to an increase in NaHCO3 reabsorption. Moreover, at the level of the distal nephron, the increased levels of aldosterone lead not only to an increase in NaCl reabsorption but also an increase in NaHCO3 reabsorption. The result is that the hormonal stimuli that represent the appropriate response to volume depletion lead, as a side effect, to a metabolic alkalosis. The proper treatment of this contraction alkalosis is not to infuse the patient with NaHCO3 but, rather, to replenish the lost volume by delivering “normal saline” intravenously. With effective circulating volume returned to normal, the stimulus to the renin–angiotensin–aldosterone axis is removed, and the acid–base disturbance resolves.

It is interesting to note that although volume depletion causes the kidney not only to retain NaCl but also to retain NaHCO3 inappropriately, the converse is not true. That is, respiratory or metabolic acidosis cause the kidney to retain NaHCO3 but to decrease the reabsorption of NaCl, so as to maintain a constant effective circulating volume.

What all this teaches us is that the defense of effective circulating volume trumps everything (including acid–base homeostasis). However, the body’s mechanisms for regulating acid–base balance are far more sophisticated than those for regulating effective circulating volume. Thus, the response to acidosis or alkalosis is precise and appropriate—and does not involve inappropriate changes in effective circulating volume that would otherwise lead to hyper- or hypotension.

Contributed by Walter Boron

Davenport Diagram: Constructing the Non-HCO3 Buffer Line

The non-HCO3 buffer line (the red line in Figs. 28–6B and 28–6C on p. 661 of the text) describes the buffering power of all buffers other than CO2/HCO3. In whole blood—here we refer to the line as the blood buffer line—hundreds of buffer groups may contribute to the overall non-HCO3 buffering power. Each of these buffer groups has its own pK and concentration, and thus its own bell-shaped curve—like the nine small curves in Figure 28-2B on p. 655—describing the pH dependence of its buffering power. Each of these buffer groups also has its own titration curve, as shown in Figure 28-6B on p. 661, and the sum of these titration curves (the red curve in this figure) is the combined titration curve of these buffers (βNon-HCO3). Notice that this red curve is nearly a straight line over the physiological pH range. In other words, in the physiological range, the slope of the red line is nearly constant, which is another way of stating that the non-HCO3 buffering power is nearly constant over this pH range—as illustrated in Figure 28-2B on p. 655.

We already know from Equation 28–8 on p. 653 (reproduced here as Equation 1) that we can define buffering power in terms of the amount of strong acid added to the solution:

Equation 1

image

From the perspective of the non-HCO3 buffers that are at work during respiratory acidosis, Δ[Strong Acid] is the H+ formed from CO2 and H2O as the result of the increase in PCO2 (see arrow from “Start” to point A in Fig. 28–6Con p. 661). Because respiratory acidosis produces HCO3 and H+ in a 1:1 ratio, the amount of bicarbonate formed during respiratory acidosis—that is, [HCO3]final – [HCO3]initial = Δ[HCO3]—is the same as the amount of H+ added (Δ[Strong Acid]). Thus, we can replace Δ[Strong acid] in Equation 1 with Δ[HCO3], and therefore somewhat paradoxically express the non-HCO3buffering power in terms of [HCO3]:

Equation 2

image

[HCO3]init and pHinit represent initial values (before increasing PCO2—that is, the point labeled “Start” in Fig. 27–6A), and [HCO3] and pH represent final values (after increasing PCO2—that is, the point labeled “A” in Fig. 28–6C). The equation describing the non-HCO3 buffer line is simply a rearrangement of Equation 2:

Equation 3

image

This equation describes a line whose slope is negative Non-HCO3. For whole blood, Non-HCO3 is 25 mM/pH unit so that the slope of the line is –25 mM/pH unit in Figure 27-6A. Note that because we assumed that the buffering power of the non-HCO3 buffers is constant over the pH range of interest, because this buffering power is represented by the slope of the non-HCO3 buffer curve in Figure 28-6C, the function describing this buffering power must be a straight line (i.e., a function with a constant slope).

We are now in a position to understand why, in Figure 28-6C, the non-HCO3 buffer line (Equation 3) shares the same y axis as the CO2 isopleth (e.g., the blue curve in Figure 28-6C), which is described by Equation 28–29 on p. 660, which we reproduce here:

Equation 4

image

In both the case of the line describing the non-HCO3 buffering power (Equation 3) and the exponential curve describing the open-system CO2 buffering power (Equation 4), the dependent variable is [HCO3].

The non-HCO3 buffer line passes through the point describing the initial conditions (pHinit, [HCO3]init). In Figure 28-6C, pHinit is 7.40 and [HCO3]init is 24 mM, as indicated by the point labeled “Start.” Because these initial conditions for the non-HCO3 buffers can change, we will see later in the text that the non-HCO3 buffer line can translate up and down on the Davenport diagram in metabolic alkalosis and metabolic acidosis. However, as long as β Non-HCO3 is constant, the slope of the line is always the same.

Contributed by Emile Boulpaep and Walter Boron

Equivalency of Adding HCO3, Adding OH, or Removing H+

Imagine that we start with 1 liter or an aqueous solution at 37°C. This solution mimics blood plasma: 5% CO2/24 mM HCO3 at pH 7.4, and the system that is “open” for CO2 (i.e., CO2 can freely enter and leave the aqueous solution so as to keep [CO2] constant). Moreover, this solution contains a non-HCO3 buffer (HB(n+1) H+ + B(n)) with a buffering power of 25 mM/pH unit.

Add NaHCO3. If we were to add 1 mM of NaHCO3 to this 1 L of solution, then [HCO3] would instantly increase by 1 mM. Of course, over time, subsequent reactions cause [HCO3] to gradually fall as the added HCO3 equilibrates with the preexisting CO2/HCO3 buffer according to the overall reactions:

Equation 1

image

Furthermore, because the consumption of HCO3 goes hand in hand with the consumption of H+, the pH will gradually rise, which in turn upsets the equilibrium of non-HCO3 buffers:

Equation 2

image

Thus, the rise in pH causes the HB(n + 1)/B(n) equilibrium to shift to the right, thereby increasing [B(n)]. As a result, the final Δ[HCO3] would be less than 1 mM. However, the changes in [HCO3] and [B(n)] would sum to very nearly 1 mM (i.e., the amount of NaHCO3 originally added):

Equation 3

image

We use “approximately equal” in Equation 3 because a tiny amount of the added HCO3 causes the pH to rise (i.e., it is not reflected in the Δ[B(n)]).

Add NaOH. Imagine that instead of adding NaHCO3, we add 1 mM of NaOH to our 1 L of solution. We can imagine that virtually all of the added OH would react with the CO2 to form an equivalent amount of HCO3:

Equation 4

image

(Note: This reaction is equivalent to CO2 + H2image HCO3 + H+.) Thus, [HCO3] would rise by very nearly 1 mM. We say “very nearly” because a tiny fraction of the added OH would equilibrate with H+and H2O, causing pH to rise:

Equation 5

image

This consumption of OH would cause pH to rise, which in turn would cause the HB(n+1)/B(n) equilibrium to shift to the right:

Equation 6

image

As a result [B(n)] would rise by a tiny amount. At the same time, however, the reaction CO2 + H2image HCO3 + H+ is out of equilibrium because the HCO3 that we formed in Equation 4 yields a [HCO3] far to high for the prevailing [H+]. Thus, Equation 4 would partially reverse, releasing more OH to react with H+ and leading to the formation of still more B(n). This reversal of Equation 4 (the secondary fall in [HCO3]) would continue until eventually the reactions in both Equation 4 and Equation 6 are in equilibrium. This process is illustrated by the panels on the right side of Figure 28-7 on p. 663 of the textbook. As a result, the final Δ[HCO3] would be less than the approximately 1 mM that we predicted in Equation 4. However, the changes in [HCO3] and [B(n)] would sum to very nearly 1 mM (i.e., the amount of NaOH added):

Equation 7

image

In fact, the values of Δ[HCO3] and Δ[B(n)] in Equation 7 (i.e., the example in which we added 1 mM NaOH) are precisely the same as those in Equation 3 (i.e., the example in which we added 1 mM NaHCO3).

Two provisos here. First, the reaction in Equation 4 would be very slow in the absence of added carbonic anhydrase (see Web Note 0654b, Carbonic Anhydrases). Nevertheless, even in the absence of carbonic anhydrase, this reaction would eventually come to equilibrium, and we could imagine that [HCO3] would eventually rise by very nearly 1 mM. Second, in this thought experiment, we are “imagining” that the added OH initially reacts only with CO2 to form approximately 1 mM HCO3, and that some of this HCO3 then dissociates to yield some CO2 and OH. In fact, a sizeable amount of the OH that we originally added will also react instantly with H+ (according to Equation 5), in turn leading to the formation of B(n) in Equation 6.

Remove HCl. Finally, imagine that we magically remove 1 mM of HCl from 1 L of our CO2/HCO3 solution. In real life, we could remove this H+ either by consuming it in a chemical (or biochemical) reaction or we could transport it out of some biological compartment (e.g., the cytosol). We could imagine that the HCl that we remove causes the CO2/HCO3 equilibrium to shift, thereby causing [HCO3] to rise by very nearly 1 mM:

Equation 8

image

The consumed CO2 would come from the atmosphere. A small amount of the H+ that we removed would lower pH:

Equation 9

image

However, the reaction in Equation 8 would be badly out of equilibrium because the rise in [HCO3] would be out of proportion to the fall in [H+]. Thus, the reaction in Equation 8 would begin to reverse, consuming some of the approximately 1 mM HCO3 that we initially formed. Moreover, the HB(n+1)/B(n) reaction would also be out of equilibrium because [H+] has fallen without any change in [B(n)] or [HB(n+1)]. As a result, the following will occur:

Equation 10

image

In fact, the reaction in Equation 8 would continue to reverse, releasing some HCO3 as well as an equal amount of H+ for consumption in Equation 10. Eventually, the reactions in both Equation 8 – Equation 10 would be in equilibrium. At this point,

Equation 11

image

In fact, the values of Δ[HCO3] and Δ[B(n)] in Equation 11 (i.e., this example in which we removed 1 mM HCl) are precisely the same as those in Equation 3 (i.e., the example in which we added 1 mM NaHCO3) and as those in Equation 7 (i.e., the example in which we added 1 mM NaOH).

Summary. Regardless of whether we add 1 mM of NaHCO3, add 1 mM of NaOH, or remove 1 mM of HCl, the result is the same. The CO2/HCO3 and the HB(n+1)/B(n) buffer systems will both end up being in equilibrium, and in each example [HCO3] will increase by the same amount, [B(n)] will increase by the same amount, and pH will increase by the same amount.

Contributed by Walter Boron

Acid Extruders and Acid Loaders in a Cell

Of the acid extruders that can produce this pHi recovery, the most widely distributed is the NHE1 isoform of the Na–H exchanger. However, mechanisms that mediate HCO3 uptake often co-exist with the Na–H exchanger in the same cell and are sometimes far more powerful than the Na–H exchanger. These HCO3 transporters include the Na+-driven Cl–HCO3 exchanger (or NDCBE, illustrated in Fig. 5–14, No. 17, on p. 130 of the text) and the Na/HCO3cotransporters with Na+:HCO3 stoichiometries of 1:2 (NBCe1 and NBCe2, the electrogenic Na/HCO3 cotransporters) and 1:1 (NBCn1, the electroneutral Na/HCO3cotransporter). Note that the electrogenic Na/HCO3 cotransporter that operates with an Na+:HCO3 stoichiometry of 1:3 (Fig. 5–14, No. 19) mediates net HCO3 efflux—reflecting the ionic and electrical gradients that govern its thermodynamic properties—and functions as an acid loader. However, the Na/HCO3 cotransporters with Na+:HCO3 stoichiometries of 1:2 and 1:1 both mediate the net uptake of HCO3 and function as acid extruders.

Other transporters that extrude acid from cells include the V-type H+ pump and the H–K exchange pump.

Other transport process that acid load cells include the passive influx of H+ as well as the efflux of HCO3 either through channels (e.g., GABA- or glycine-activated “Cl” channels) or through the K/HCO3cotransporter.

For a more detailed discussion of these transporters, see p. 132 of the text.

Contributed by Emile Boulpaep and Walter Boron

Acid Extruders and Acid Loaders in a Cell

Of the acid extruders that can produce this pHi recovery, the most widely distributed is the NHE1 isoform of the Na–H exchanger. However, mechanisms that mediate HCO3 uptake often co-exist with the Na–H exchanger in the same cell and are sometimes far more powerful than the Na–H exchanger. These HCO3 transporters include the Na+-driven Cl–HCO3 exchanger (or NDCBE, illustrated in Fig 5-14, No. 17, on p. 130 of the text) and the Na/HCO3cotransporters with Na+:HCO3 stoichiometries of 1:2 (NBCe1 and NBCe2, the electrogenic Na/HCO3 cotransporters) and 1:1 (NBCn1, the electroneutral Na/HCO3cotransporter). Note that the electrogenic Na/HCO3 cotransporter that operates with an Na+:HCO3 stoichiometry of 1:3 (Fig. 5–14, No. 19) mediates net HCO3 efflux—reflecting the ionic and electrical gradients that govern its thermodynamic properties—and functions as an acid loader. However, the Na/HCO3 cotransporters with Na+:HCO3 stoichiometries of 1:2 and 1:1 both mediate the net uptake of HCO3, and function as acid extruders.

Other transporters that extrude acid from cells include the V-type H+ pump and the H–K exchange pump.

Other transport process that acid load cells include the passive influx of H+ as well as the efflux of HCO3 either through channels (e.g., GABA- or glycine-activated “Cl” channels) or through the K/HCO3cotransporter.

For a more detailed discussion of these transporters, see p. 132 of the text.

Contributed by Emile Boulpaep and Walter Boron

Methemoglobinemia

An increase in the amount of hemoglobin (Hb) with its iron in the oxidized or Fe3+ (i.e., ferric) state is known as methemoglobinemia. As discussed on p. 673 of the text, the problem that arises is that with Fe3+in the porphyrin ring of Hb, O2 cannot bind, with a consequent reduction in the O2 carrying capacity of the blood. The Fe2+ (i.e., ferrous) iron of Hb spontaneously oxidizes to Fe3+, and a family of methemoglobin reductase enzymes normally returns the Hb to the ferrous state.

Methemoglobinemia can arise in three ways:

1. Mutant M forms of hemoglobin. Normally, the globin moiety of Hb cradles the porphyrin ring in such a way as to limit the accessibility of O2 to the Fe2+. In M forms of Hb (at least eight of which have been identified), point mutations in the or globin chains allow the O2 to approach the Fe2+ more closely and to oxidize—rather than to bind to—the Fe2+. This action shifts the balance between the normally slow rate of oxidation and reductase activity toward the formation of Fe3+.

2. Genetic deficiency (autosomal recessive) of one or both of the splice variants of methemoglobin reductase enzymes. The enzyme is reduced nicotinamide adenine dinucleotide (NADH)-cytochrome b5 reductase (cytb5: EC 1.6.2.2). Two splice variants, varying in the N-terminal region, are present: a soluble form with 275 amino acids and a membrane-bound form with 300 amino acids. The membrane-bound form is present mainly in the ER and mitochondrial outer membrane, where it is important for a variety of reactions (i.e., synthesis of fatty acids and cholesterol and also P450-mediated drug metabolism). A deficiency in the soluble form of RBCs—usually caused by missense mutations that reduce enzyme stability—causes type I methemoglobinemia, which is usually not severe. A deficiency in the membrane-bound form causes type II methemoglobinemia, which can cause severe mental retardation and neurological problems. The type I disease can be treated with the reducing agents ascorbic acid and methylene blue, either singly or together.

3. Toxin-induced oxidation of the Fe2+ in hemoglobin. Oxidation of the Fe2+ of hemoglobin to Fe3+ can occur by three routes: direct oxidation, promoted under hypoxic conditions; indirect oxidation in the presence of bound O2, a mechanism that is important in the methemoglobinemia produced by nitrite; and drug-induced oxidation, in which drug metabolites of compounds (e.g., amino-benzenes and nitro-benzenes) promote the oxidation.

REFERENCE

Percy MJ, McFerran NV, and Lappin TRJ: Disorders of oxidized haemoglobin. Blood Rev 19:61–68, 2005.

Prchal JT, Borgese N, Moore MR, Moreno H, Hegesh E, and Hall MK: Congenital methemoglobinemia due to methemoglobin reductase deficiency in two unrelated American black families. Am J Med89:516–522, 1990.

Contributed by Walter Boron

Erythropoietin

Erythropoietin (EPO) is an approximately 34-kDa glycoprotein made mainly in the kidney by fibroblast-like type I interstitial cells in the cortex and outer medulla (see p. 757 of the text). EPO is a growth factor related to other cytokines, and it acts through a tyrosine kinase-associated receptor (see p. 70) to stimulate the production of proerythroblasts in the bone marrow as well as the development of red cells from their progenitor cells. In fetal life, the liver, rather than the kidney, produces EPO. Even in the adult, Kupffer cells in the liver produce some EPO.

Four lines of evidence indicate that the stimulus for EPO synthesis is a decrease in local PO2. First, EPO synthesis increases with anemia. Second, EPO production increases with lowered renal blood flow. Third, EPO synthesis increases with central hypoxia (i.e., low arterial PO2), such as may occur with pulmonary disease or with living at high altitude (see p. 1275). In all three of these cases, local PO2 falls as tissues respond to a fall in O2 delivery by extracting more O2 from each volume of blood that passes through the kidney. Finally, EPO production increases when Hb has a high O2 affinity. Here, the renal cells must lower PO2 substantially before O2 dissociates from Hb. Thus, mutant hemoglobins with high O2 affinities, stored blood (which has low 2,3-DPG levels), and alkaline blood all lead to increased EPO production.

Besides local hypoxia, several hormones and other agents stimulate EPO production. For example, prostaglandin E2 and adenosine appear to stimulate EPO synthesis by increasing intracellular levels of cyclic adenosine monophosphate. Norepinephrine and thyroid hormone also stimulate EPO release. Finally, androgens stimulate, whereas estrogens inhibit, EPO synthesis, explaining at least in part why women in their childbearing years have lower hematocrit levels than do men.

Because the kidneys are the major source of EPO, renal failure leads to reduced EPO levels and anemia. The development of recombinant EPO has had a major impact in ameliorating the anemia of chronic renal failure.

Contributed by Walter Boron

Interactions of H+ with Hemoglobin

Like most proteins, hemoglobin has many titratable groups. However, the ones that are most important physiologically are the ones whose pK values are near the physiological pH. For a general discussion of buffers, consult the passage beginning on p. 652 of the text. Of particular interest is the passage dealing with buffers in a closed system (beginning on p. 655) and Figure 28-2B on p. 655.

Several titratable groups in the hemoglobin molecule contribute to the pH Bohr effect. The most important single group is the histidine at residue 146 of the β chains. When the hemoglobin molecule is fully deoxygenated (tensed state), the protonated His-146 forms a salt bridge with the negatively charged aspartate group at position 94 of the same β chain. This salt bridge stabilizes the protonated form of His-146 so that it has a high affinity for H+ (i.e., a relatively high pK value of ~8.0).

When the hemoglobin becomes fully oxygenated (relaxed state), the twisting of the hemoglobin molecule disrupts the salt bridge and thus destabilizes the protonated form of His-146 so that it has a low affinity for H+ and thus a relatively low pK value of approximately 7.1. This pK is roughly the same as the pH inside the red blood cell. According to Equation 27–5 on p. 634 of the text, the ratio [R-NH+3]/[R-NH2] must be 1:1 (so that in 50 out of every 100 hemoglobin molecules, this group is protonated).

Now let us fully deoxygenate this Hb and return the pK of His-146 to where it was at the beginning of this example—approximately 8.0. The pH inside the erythrocyte remains at 7.1. Equation 28–5 on p. 653 tells us that the ratio [R-NH+3]/[R-NH2] will be 8:1. That is, in 89 of every 100 hemoglobin molecules, this His-146 group is protonated. Thus, for every 100 hemoglobin molecules, 39 H+ ions have been taken up from the solution to titrate 39 R-NH2groups to form 39 additional R-NH+3 groups at His-146.

The preceding example is extreme because the hemoglobin does not become fully deoxygenated in the systemic capillaries. It is also a simplified example, inasmuch as multiple residues in hemoglobin contribute to the pH Bohr effect. Nevertheless, the example illustrates how deoxygenated Hb is better able to buffer excess protons.

In the previous paragraphs, we emphasized one side of the physiological coin: Deoxygenation makes hemoglobin a weaker acid (and thus causes hemoglobin to take up H+). However, as summarized by the reaction in Equation 29–9 on p. 677 of the text,

Equation 1

image

the converse is also true: The protonation of hemoglobin lowers hemoglobin’s affinity for O2.

Contributed by Emile Boulpaep and Walter Boron

Interactions of CO2 with Hemoglobin

As discussed on p. 678 of the text, CO2 can reversibly react with the four amino groups that constitute the four N termini of the globin chains—the two α chains and, especially, the two β chains. As shown by Equation 29–10 on p. 678 of the text, the interaction of CO2 with these amino termini causes the net charge on the residue to change from positive (Hb–NH+3) to negative (Hb–NH–COO–). A consequence is the formation of salt bridges—among several positively and negatively charged amino acid residues—that tend to stabilize the deoxygenated (or tensed) form of hemoglobin. Thus, in the systemic capillaries, the increased levels of CO2 favor the deoxygenated form of hemoglobin, which is tantamount to dumping O2. In other words, increased levels of CO2 cause the Hb–O2 dissociation curve to shift to the right (see Fig. 29–5C on p. 678 of the text).

In the lungs, the converse takes place as the binding of O2 to hemoglobin causes a twisting of the hemoglobin molecule as it shifts from the tensed to the relaxed state. This twisting disrupts the aforementioned salt bridges and destabilizes carbamino. As a result, the hemoglobin molecule dumps CO2, which exits the erythrocyte and diffuses into the alveolar airspace.

Contributed by Emile Boulpaep and Walter Boron

2,3-DPG

2,3-Diphosphoglycerate (2,3-DPG), also known as 2,3-bisphosphoglycerate (2,3-BPG), is an intermediate in one of the later reactions in glycolysis (see Fig. 58–6A on p. 1218 of the text). The overall reaction in question is 3-phosphoglycerate image 2-phosphoglycerate, catalyzed by phosphoglycerate mutase (PGM):

image

The actual mechanism is interesting. A specific kinase initially activates the PGM by transferring a phosphate group from the ‘2’ position of 2,3-diphosphoglycerate to a histidine residue of the enzyme, creating PGM-P and 3-phosphoglycerate (3-PG):

image

In the actual mutase reaction, this activated enzyme transfers the phosphate group to 2-PG, creating 2,3-DPG:

3-PG + PGM-P image 2,3-DPG + PGM

Finally, the enzyme can accept a phosphate group from 2,3-DPG, creating 3-PG:

2,3-DPG + PGM image 2-PG + PGM-P

Thus, 2,3-DPG is a cofactor in the mutase reaction. It is also continuously formed and consumed.

Contributed by Emile Boulpaep and Walter Boron

Other Gases That Bind to Hemoglobin

The text discusses in detail the interaction of O2 and CO2 with hemoglobin, briefly discusses the interaction of carbon monoxide (CO) with hemoglobin, and mentions the interactions of NO and H2S with hemoglobin.

Carbon monoxide. As noted in the text, the affinity of hemoglobin for CO is approximately 200-fold greater than for O2. Thus, when a fully oxygenated hemoglobin molecule, Hb(O2)4, is exposed to even a low level of CO, a CO molecule displaces one of the O2 molecules from some of the hemoglobin molecules, resulting in Hb(O2)3(CO). If the only effect of CO poisoning were to render ineffective one of the four O2 binding sites, then the symptoms would be no worse than reducing the hematocrit by 25% (e.g., from 40 to 30%) or perfusing the arteries with mixed venous blood (which also has an Hb–O2 saturation of 75%). In fact, if a single CO molecule binds to 40% of the hemoglobin molecules in the blood, the patient will experience symptoms, as outlined here. Why?

Basis of CO toxicity. CO is toxic for two reasons. First, it reduces the amount of binding sites available for O2 carriage. Second, the binding of CO stabilizes the hemoglobin molecule in its relaxed state, shifting the Hb–O2dissociation curve far to the left, making it more difficult for the Hb to release O2 in the systemic capillaries.

Calculating the CO saturation of Hb. To calculate the HbCO concentration, remember that when the Hb is exposed to CO, [HbCO] will equal the [HbO2] when the Hb is exposed to O2 at 210 times the [CO] in question. For example, Hb is 50% saturated with O2 (at equilibrium) when the PO2 is 28 torr. The 50% COHb concentration will be reached at equilibrium with 28/210 torr of CO, which would be only 0.133 torr of CO. Because 1 atmosphere of pressure is 760 torr, 0.133 torr of CO is equivalent to 0.133/760 or 0.000175 atm of CO, or 175 ppm of CO. A person exposed to this CO level for a long time would be severely incapacitated or killed. However, because it takes 4 hours to reach half the final equilibrated level of COHb, a 4-hour exposure to 175 ppm alveolar CO would lead to a COHb level of 50%/2 or 25% COHb. This level would give the person a headache and interfere with mental function. In 2 hours of exposure, the COHb would be one-fourth of 50% saturation or 12.5% COHb. This lower level would interfere with night vision and, because of some interference with O2 transport, raise the risk of angina in a person with limited coronary blood flow.

Symptoms and treatments. Symptoms of mild CO poisoning may begin when the CO saturation of hemoglobin reaches 10%—that is, when 40% of the hemoglobin molecules bind one CO (25% of sites on one Hb molecule × 40% of Hb molecules = 10% saturation). These symptoms, which are not very specific, may include headache, nausea, and vomiting.

For mild CO poisoning, the treatment is simply to remove the causative agent, which leaves the body with a half time of approximately 4 hours (i.e., CO dissociates very slowly from hemoglobin—it has a low off-rate).

For more severe CO poisoning, the recommended treatment is to have the patient breathe 100% O2, which increases the probability that O2 will displace CO from hemoglobin (i.e., it increases the off-rate), thereby speeding the washout of CO by approximately a factor of 4 (half-time ≈60 min).

When the CO saturation of hemoglobin reaches 20–25% (i.e., when, on average, 80–100% of hemoglobin molecules each bind one CO molecule), the symptoms are severe and include confusion, chest pain, and unconsciousness. The treatment is hyperbaric 100% O2—oxygen delivered at high pressure—which has two positive effects. First, the hyperbaric O2 (i.e., increased PO2) accelerates even further the displacement of CO from hemoglobin. Breathing hyperbaric 100% O2 at 2.5 atm of pressure reduces the half-time of washout to 20 minutes. Second, the hyperbaric O2 treatment can increase the concentration of dissolved O2 to such an extent that this dissolved O2 in the blood can deliver sufficient O2 to satisfy the body’s metabolic demands (see Equations 29–1 through 29–3 on p. 672 of the text).

Carbon monoxide reaches a lethal level at a hemoglobin saturation of approximately 50%.

Interestingly, hyperventilation is not an effective treatment for CO poisoning. One reason for this lack of effect may be that hyperventilation blows off CO2 and reduces the arterial PCO2 (see Equation 31–13 on p. 705 of the text). According to the Bohr effect, low levels of CO2 (e.g., caused by hyperventilation) would shift the Hb–O2 dissociation curve to the left, exacerbating the effect of the CO poisoning. In fact, Yandell Henderson showed that use of 5% CO2 in 95% O2 decreased plasma pH, which accelerated the displacement of CO from COHb as well as increased the tissue PO2 through the Bohr effect (communicated by Arthur Dubois).

Nitric oxide. Hb also binds NO. This interaction may help ensure that the effects of NO are paracrine rather than endocrine—that is, that the effects of NO are restricted to the sites of release. The physiological target of NO is soluble guanylyl cyclase (see p. 69 of the text), which binds NO through a heme group, just as does hemoglobin.

Contributed by Arthur DuBois, Emile Boulpaep, and Walter Boron

Total CO2

The following table complements Figure 29-8 in the textbook.

Table 1 Components of “Total CO2

 

Arterial Blood (PCO2= 40 mm Hg)

Mixed Venous Blood (PCO2= 46 mm Hg)

         

Component

Concentration

Contribution to Total CO2 (mL/dL)

Fraction of Total CO2(%)

Concentration

Contribution to Total CO2(mL/dL)

Fraction of Total CO2 (%)

 

Physically dissolved carbon dioxide

CO2

1.2 mM

2.4

5

1.4 mM

2.8

5.3

Carbonic acid

H2CO3

3 μM

~0

~0

~3.5 μM

~0

~0

Bicarbonate

 

24 mM

43.2

90

25.6 mM

46.0

88.5

Carbonate

CO32−

30 μM

~0

~0

30 μM

~0

~0

Carbamino compounds

R-NH-COO−

1.2 mM

2.4

5

1.6 mM

3.2

6.2

Total

26.4 mM

48

100

28.6 mM

52

100

 

Contributed by Emile Boulpaep and Walter Boron

Carbonic Anhydrases

The carbonic anhydrases (CAs) are a family of zinc-containing enzymes with at least 16 members among mammals; Table 1 accompanying this Web Note lists some of these isoforms. Physiologically, the CAs catalyze the interconversion of CO2 and HCO3, although they can also cleave aliphatic and aromatic ester linkages. Carbonic anhydrase I (CA I) is present mainly in the cytoplasm of erythrocytes. CA II is a ubiquitous cytoplasmic enzyme. CA IV is a GPI-linked enzyme (see p. 18 of the text) found, for example, on the outer surface of the apical membrane of the renal proximal tubule (see Fig. 39–2A on p. 854). A hallmark of many CAs is their inhibition by sulfonamides (e.g., acetazolamide).

Before considering the action of CA, it is instructive to examine the interconversion of CO2 and HCO3 in the absence of enzyme. When [CO2] increases,

Equation 1

image

CO2 can also form HCO3 by directly combining with OH, a reaction that becomes important at high pH values, when [OH] is also high:

Equation 2

image

Because the dissociation of H2O replenishes the consumed OH, the two mechanistically distinct pathways for HCO3 formation are functionally equivalent. Of course, both reaction sequences are reversible. However, in the absence of CA, the overall speed of the interconversion between CO2 and HCO3 is slow at physiological pH. In fact, it is possible to exploit this slowness experimentally to generate and CO2/HCO3 solutions that are temporarily “out of equilibrium” (see Web Note 654a, Out-of-Equilibrium CO2HCO3 Solutions). Unlike normal (i.e., equilibrated) solutions, such out-of-equilibrium solutions can have virtually any combination of [CO2], [HCO3], and pH in the physiological range.

Structural biologists have solved the crystal structures of several CAs. At the reaction site, three histidines coordinate a zinc atom that, along with a threonine, plays a critical role in binding CO2 and HCO3. In CA II, the fastest of the CAs, a fourth histidine acts as a proton acceptor/donor. Extensive site-directed mutagenesis studies have provided considerable insight into the mechanism of the CA reaction. The CAs have the effect of catalyzing the slow CO2hydration in Equation A. Actually, these enzymes catalyze the top reaction in Equation B, the direct combination of CO2 with OH to form HCO3

CA[CE82] II catalyzes both reactions in Equation B[CE83]:

image

CA II has one of the highest turnover numbers of any known enzyme: Each second, one CA II molecule can convert more than 1 million CO2 molecules to HCO3 ions. In the erythrocyte, this rapid reaction is important for the carriage of CO2 from the peripheral blood vessels to the lungs (see p. 681). In the average cell, CAs are important for allowing the rapid buffering of H+ by the CO2/HCO3 buffer pair and probably also for minimizing pH gradients near membranes with transporters engaging in the transport of H+ and image.

In humans, the homozygous absence of normal CA II causes CA II deficiency syndrome, characterized by osteopetrosis, renal tubular acidosis, and cerebral calcification. At least seven different mutations can cause genetic defects. The mutation that is common in patients of Arabic descent causes mental retardation but less severe osteopetrosis. Other patients may carry two different mutations. Indeed, the first three patients described with CA II deficiency syndrome, sisters in the same family, were compound heterozygotes, having received one mutation from their mother and a second from their father.

Although CA I deficiency exists, the homozygous condition has no obvious consequences because CA I and CA II normally contribute approximately equally to the CA activity in red blood cells.

Table 1 Some Human Carbonic Anhydrasesa

Isoform

Molecular Mass (kDa)

Cellular Location

Tissue Distribution

Relative Activity (%)

Sensitivity to Sulfonamides (e.g., Acetazolamide)

I

29

Cytosol

RBCs and GI tract

15

High

II

29

Cytosol

Nearly ubiquitous

100

High

III

29

Cytosol

8% of soluble protein in slow-twitch (type I) muscle

1

Low

IV

35

Extracellular surface of membrane (GPI-linked)

Widely distributed, including acid-transporting epithelia

~100

Moderate

IX

54/58

Catalytic domain on extracellular surfaceb

Certain cancers

~100

High

XII

44

Catalytic domain on extracellular surfaceb

Certain cancers

~30

Binds ACZ with unknown affinity

XIV

54

Catalytic domain on extracellular surfaceb

Kidney, heart, skeletal muscle, brain

~100

?

aSeveral additional CAs have been cloned. In some cases, they have not been functionally characterized.

bIntegral membrane protein with one membrane-spanning segment.

ACZ, acetazolamide; GPI, glycosyl phosphatidylinositol; RBC, red blood cell.

REFERENCE

Purkerson JM, and Schwartz GJ: The role of carbonic anhydrases in renal physiology. Kidney Int 71:103–115, 2007.

Sly WS, and Hu PY: Human carbonic anhydrases and carbonic anhydrase deficiency. Annu Rev Biochem 64:375–401, 1995.

Wykoff CC, Beasley N, Watson PH, Campo L, Chia SK, English R, Pastorek J, Sly WS, Ratcliffe P, and Harris AL: Expression of the hypoxia-inducible and tumor-associated carbonic anhydrases in ductal carcinoma in situ of the breast. Am J Pathol 158:1011–1019, 2001.

Contributed by Emile Boulpaep and Walter Boron

Van Slyke’s Manometric Method for Determining Total CO2

In 1924, Van Slyke and Neill introduced a technique for determining what is today known as the “total CO2” of blood (see Web Note 0680b, Total CO2) and other solutions. This technique quickly became the standard for determining total CO2 in clinical chemistry laboratories. Moreover, the Van Slyke approach is the foundation even for modern, automated approaches for determining total CO2.

Although the original approach requires painstaking precision in the laboratory to obtain reliable results, the fundamental principle is a rather simple two-step process. First, one uses an acid (Van Slyke and Neill used 1 N lactic acid) to titrate virtually all of the carbamino hemoglobin, carbonate (CO2–3), and bicarbonate (HCO3) to carbon dioxide (CO2), which enters the gaseous phase. Second, one uses a manometer to measure the pressure (P) of a known volume (V) of this CO2 gas. The ideal gas law tells us that

Equation 1

image

Here, n is the number of molecules, R is the universal gas constant, and T is the absolute temperature. Thus, with the proper corrections for nonideality, it is possible to compute the number of CO2 molecules.

We now examine the titration reactions in more detail. For the titration of carbamino hemoglobin (Hb) by the H+ in lactic acid, two reactions occur in series:

Equation 2

image

These reactions are the reverse of the ones shown in Equation 29–10 on p. 678 of the text.

The titration of CO2–3 by the H+ in lactic acid yields HCO3:

Equation 3

image

Finally, the titration of this newly formed HCO3—as well as the preexisting HCO3 (which is a far larger amount under physiological conditions)—by the H+ in lactic acid yields carbonic acid (H2CO3), which in turn yields with CO2and H2O

Equation 4

image

Because the pK governing the equilibrium CO2 + H2image H2CO3 is approximately 2.6, more than 99.7% of the newly formed H2CO3 goes on to form CO2.

In practice, the technique used to generate the CO2 gas also extracts a variable amount of O2 from the solution. In other words, the CO2 in the gas phase is mixed with an amount of O2 that is difficult to predict. Therefore, Van Slyke and Neill introduced an additional step to their analysis: They added 1 N NaOH to convert all total CO2 to CO2–3, thereby removing the CO2 from the gas phase. This last step allowed them to obtain, with precision, the amount of CO2 gas in the gas phase and thus to calculate the amount of total CO2 that had been in their sample.

REFERENCE

Simoni RD, Hill RL, and Vaughan M: The determination of gases in blood and other solutions by vacuum extraction and manometric measurement. I. [Classics. A paper in a series reprinted to celebrate the centenary of the JBC in 2005.], J Biol Chem 277:e16, 2002.

Van Slyke DD, and Neill JM: The determination of gases in blood and other solutions by vacuum extraction and manometric measurement. I. J Biol Chem 61:523–573, 1924. [Available online at the JBC web site by accessing the commentary in the Simoni et al. reference]

Contributed by Emile Boulpaep and Walter Boron

Gas Channels

The traditional view had been that all gases cross all cell membranes by simply dissolving in the lipid phase of the membrane. The first evidence that the gas dogma was in need of refinement was the observation (Waisbren et al., 1994) that apical membranes of gastric gland cells are impermeable to CO2 and NH3, and that apical membranes of colonic crypts are impermeable to NH3 (Singh et al., 1995). Low permeabilities to gases and H2O may be a general property of membranes facing inhospitable environments (Cooper et al., 2002), including the mechanical stresses experienced by red blood cells (RBCs) and capillary endothelial cells. Cells exposed to such hostile environments may have evolved specialized, robust membranes with unique lipid composition and/or protein or oligosaccharide coatings at the membrane surface.

The second observation that upset the gas dogma was the discovery that CO2 passes through the water channel aquaporin 1 (AQP1; Nakhoul et al., 1998; Cooper et al., 1998). Peter Agre shared the 2003 Nobel Prize in Chemistry for discovering AQPs and their H2O permeability. The physiological role of AQPs transcends water. For example, AQP7 and AQP9 transport glycerol. Might AQP1’s CO2permeability be physiologically relevant? The first such evidence was the demonstration that an AQP plays a critical role in CO2 uptake for photosynthesis by tobacco leaves (by Uehlein et al., 2003). Endeward et al. (2008) demonstrated that approximately half of the CO2 permeability of human RBCs passes through AQP1.

The AQPs form homotetramers, and each monomer has a pore for H2O. Molecular dynamics (MD) simulations suggest that CO2 could pass single file with H2O through each of the four aquapores as well as through the central pore between the four monomers (Wang et al., 2007). Preliminary inhibitor studies from the Boron Lab confirm this prediction, indicating that approximately 40% of the CO2 that passes through AQP1 moves through the four aquapores, whereas the remaining 60% passes through the central pore. The MD simulations suggest that virtually all of the O2 passes through the central pore.

A second family of gas channels is the Rh proteins. The bacterial Rh homologue AmtB forms a homotrimer, and each monomer appears to have a pore for NH3. The RhAG protein from the human Rh complex in RBCs is permeable both to NH3 and to CO2 (Endeward et al., 2008). Preliminary work from the Boron Lab indicates that NH3 moves exclusively through one of the three ammonia pores, whereas CO2 moves mainly through the central pore of both AmtB and RhAG.

Interestingly, gas channels exhibit selectivity for gas in much the same way as ion channels exhibit selectivity for ions. For example, AQP4 (heavily expressed at the blood–brain barrier) and AQP5 (heavily expressed in alveolar type I pneumocytes) are virtually totally selective for CO2 over NH3. AQP1 (heavily expressed in RBCs) is intermediate in its CO2/NH3 selectivity, AmtB is shifted more toward NH3selectivity, and RhAG (heavily expressed in RBCs) is even more shifted toward NH3 selectivity over CO2. This work is the first evidence for gas selectivity by a protein channel (Musa-Aziz et al., 2009).

REFERENCE

Cooper GJ, and Boron WF: Effect of PCMBS on CO2 permeability of Xenopus oocytes expressing aquaporin 1 or its C189S mutant. Am J Physiol 275:C1481–C1486, 1998.

1. Cooper GJ, Y Zhou, P Bouyer, II Grichtchenko & WF Boron. Transport of volatile solutes through AQP1. J Physiol 542:17–29, 2002.

Endeward V, Musa-Aziz R, Cooper GJ, Chen LM, Pelletier MF, Virkki LV, Supuran CT, King LS, Boron WF, and Gros G: Evidence that aquaporin 1 is the major pathway for CO2 transport in the human erythrocyte membrane. FASEB J 20:1974–1981, 2006.

Endeward V, Cartron JP, Ripoche P, and Gros G: RhAG protein of the Rhesus complex is a CO2 channel in the human red cell membrane. FASEB J 22:64–73, 2008.

Musa-Aziz R, Chen LM, Pelletier MF, and Boron WF: Relative CO2/NH3 selectivities of AQP1, AQP4, AQP5, AmtB, and RhAG. Proc Natl Acad Sci USA 106:5406–5411, 2009.

Nakhoul NL, Davis BA, Romero MF, and Boron WF: Effect of expressing the water channel aquaporin-1 on the CO2 permeability of Xenopus oocytes. Am J Physiol 274:C543–C548, 1998.

Singh SK, Binder HJ, Geibel JP, and Boron WF: An apical permeability barrier to NH3/NH4+ in isolated, perfused colonic crypts. Proc Natl Acad Sci USA 92:11573–11577, 1995.

Uehlein N, Lovisolo C, Siefritz F, and Kaldenhoff R: The tobacco aquaporin NAQP1 is a membrane CO2 pore with physiological functions. Nature 425:734–737, 2003.

Waisbren SJ, Geibel JP, Modlin IM, and Boron WF: Unusual permeability properties of gastric gland cells. Nature 368:332–335, 1994.

Wang Y, Cohen J, Boron WF, Schulten K, and Tajkhorshid E: Exploring gas permeability of cellular membranes and membrane channels with molecular dynamics. J Struct Biol 157:534–544, 2007.

Contributed by Walter Boron

Carbonic Anhydrases

The carbonic anhydrases (CAs) are a family of zinc-containing enzymes with at least 16 members among mammals; Table 1 accompanying this Web Note lists some of these isoforms. Physiologically, the CAs catalyze the interconversion of CO2 and HCO3, although they can also cleave aliphatic and aromatic ester linkages. Carbonic anhydrase I (CA I) is present mainly in the cytoplasm of erythrocytes. CA II is a ubiquitous cytoplasmic enzyme. CA IV is a GPI-linked enzyme (see p. 18 of the text) found, for example, on the outer surface of the apical membrane of the renal proximal tubule (see Fig. 39–2A on p. 854). A hallmark of many CAs is their inhibition by sulfonamides (e.g., acetazolamide).

Before considering the action of CA, it is instructive to examine the interconversion of CO2 and HCO3 in the absence of enzyme. When [CO2] increases,

Equation 1

image

CO2 can also form HCO3 by directly combining with OH, a reaction that becomes important at high pH values, when [OH] is also high:

Equation 2

image

Because the dissociation of H2O replenishes the consumed OH, the two mechanistically distinct pathways for HCO3 formation are functionally equivalent. Of course, both reaction sequences are reversible. However, in the absence of CA, the overall speed of the interconversion between CO2 and HCO3 is slow at physiological pH. In fact, it is possible to exploit this slowness experimentally to generate and CO2/HCO3 solutions that are temporarily “out of equilibrium” (see Web Note 654a, Out-of-Equilibrium CO2HCO3 Solutions). Unlike normal (i.e., equilibrated) solutions, such out-of-equilibrium solutions can have virtually any combination of [CO2], [HCO3], and pH in the physiological range.

Structural biologists have solved the crystal structures of several CAs. At the reaction site, three histidines coordinate a zinc atom that, along with a threonine, plays a critical role in binding CO2 and HCO3. In CA II, the fastest of the CAs, a fourth histidine acts as a proton acceptor/donor. Extensive site-directed mutagenesis studies have provided considerable insight into the mechanism of the CA reaction. The CAs have the effect of catalyzing the slow CO2hydration in Equation A. Actually, these enzymes catalyze the top reaction in Equation B, the direct combination of CO2 with OH to form HCO3

CA II catalyzes both reactions in Equation B:

image

CA II has one of the highest turnover numbers of any known enzyme: Each second, one CA II molecule can convert more than 1 million CO2 molecules to HCO3 ions. In the erythrocyte, this rapid reaction is important for the carriage of CO2 from the peripheral blood vessels to the lungs (see p. 681). In the average cell, CAs are important for allowing the rapid buffering of H+ by the CO2/HCO3 buffer pair and probably also for minimizing pH gradients near membranes with transporters engaging in the transport of H+ and image.

In humans, the homozygous absence of normal CA II causes CA II deficiency syndrome, characterized by osteopetrosis, renal tubular acidosis, and cerebral calcification. At least seven different mutations can cause genetic defects. The mutation that is common in patients of Arabic descent causes mental retardation but less severe osteopetrosis. Other patients may carry two different mutations. Indeed, the first three patients described with CA II deficiency syndrome, sisters in the same family, were compound heterozygotes, having received one mutation from their mother and a second from their father.

Although CA I deficiency exists, the homozygous condition has no obvious consequences because CA I and CA II normally contribute approximately equally to the CA activity in red blood cells.

Table 1 Some Human Carbonic Anhydrasesa

Isoform

Molecular Mass (kDa)

Cellular Location

Tissue Distribution

Relative Activity (%)

Sensitivity to Sulfonamides (e.g., Acetazolamide)

I

29

Cytosol

RBCs and GI tract

15

High

II

29

Cytosol

Nearly ubiquitous

100

High

III

29

Cytosol

8% of soluble protein in slow-twitch (type I) muscle

1

Low

IV

35

Extracellular surface of membrane (GPI-linked)

Widely distributed, including acid-transporting epithelia

~100

Moderate

IX

54/58

Catalytic domain on extracellular surfaceb

Certain cancers

~100

High

XII

44

Catalytic domain on extracellular surfaceb

Certain cancers

~30

Binds ACZ with unknown affinity

XIV

54

Catalytic domain on extracellular surfaceb

Kidney, heart, skeletal muscle, brain

~100

?

aSeveral additional CAs have been cloned. In some cases, they have not been functionally characterized.

bIntegral membrane protein with one membrane-spanning segment.

ACZ, acetazolamide; GPI, glycosyl phosphatidylinositol; RBC, red blood cell.

REFERENCE

Purkerson JM, and Schwartz GJ: The role of carbonic anhydrases in renal physiology. Kidney Int 71:103–115, 2007.

Sly WS, and Hu PY: Human carbonic anhydrases and carbonic anhydrase deficiency. Annu Rev Biochem 64:375–401, 1995.

Wykoff CC, Beasley N, Watson PH, Campo L, Chia SK, English R, Pastorek J, Sly WS, Ratcliffe P, and Harris AL: Expression of the hypoxia-inducible and tumor-associated carbonic anhydrases in ductal carcinoma in situ of the breast. Am J Pathol 158:1011–1019, 2001.

Contributed by Emile Boulpaep and Walter Boron

John Scott Haldane

John Scott Haldane (1860–1936) was born in Edinburgh, UK, where he received his medical degree in 1884. He began his academic career at Queen’s College, Dundee, before moving to Oxford. Haldane is credited with several notable discoveries:

• He showed that high blood levels of CO2 are a more powerful stimulus for breathing than low levels of O2 (1905).

• He developed a method for the staged decompression of deep-sea divers, avoiding the bends on the return of the divers to the surface. He published the first diving decompression tables (1908).

• He—along with Christiansen and Douglas—showed that the CO2 content of the blood decreases with increasing PO2, known as the “Haldane effect” (1914). This effect is responsible for approximately half of the CO2 exchange in the blood.

See the following web sites:

http://www.geo.ed.ac.uk/scotgaz/people/famousfirst1349.html

http://www.diegoweb.com/diving/cards/page2.html

REFERENCE

Christiansen J, Douglas CG, and Haldane JS: The absorption and dissociation of carbon dioxide by human blood. J Physiol 48:244–277, 1914.

Contributed by Emile Boulpaep and Walter Boron

Spatial Differences in Alveolar Dimensions

The total area of the lungs is not distributed evenly among all alveoli. First, all else being equal, some alveoli are “naturally” larger than others. Thus, some have a greater area for diffusion than do others, and some have a thinner wall than do others.

Second, the position of an alveolus in the lung can affect its size. As discussed in Chapter 27, when a person is positioned vertically, the effects of gravity cause the intrapleural pressure to be more negative near the apex of the lung than near the base (see Fig. 27–2 on p. 631 of the text). Thus, other things being equal, alveoli near the apex of the lung tend to be more inflated so that they have a greater area and smaller thickness compared to alveoli near the base of the lung.

Third, during inspiration, alveoli undergo an increase in volume that causes their surface area to increase and their wall thickness to decrease. However, these changes are not uniform among alveoli. Again, the differences can be purely anatomic: All other things being equal, some alveoli “naturally” have a greater static compliance (see p. 634 of the text) than others. Thus, during inspiration, their area will increase more, and their wall thickness will decrease more. However, other things being equal, the compliance of an alveolus also depends on its position in the lung. As discussed in Chapter 31, the relatively overinflated alveoli near the apex of the lung (in an upright individual) have a relatively low compliance. In other words, during inspiration these apical alveoli have a smaller volume increase (see Fig. 31–5Don p. 707). Thus, their area for diffusion undergoes a relatively smaller increase, and their wall thickness undergoes a relatively smaller decrease, than alveoli near the base of the lung.

In summary, for all of the reasons we have discussed, the area and thickness parameters vary widely among alveoli at the end of a quiet inspiration, and the relation among these differences changes dynamically during a respiratory cycle.

Contributed by Emile Boulpaep and Walter Boron

Three-Ply Structure of the Alveolar Barrier

See the following review:

Maina JN, and West JB: Thin and strong! The bioengineering dilemma in the structural and functional design of the blood–gas barrier. Physiol Rev 85:811–844, 2005.

An Analogy for the Diffusion-Limited Uptake of Carbon Monoxide

The following may be a helpful analogy for how the partial pressure of carbon monoxide (PCO) changes with time as blood flows down a pulmonary capillary. Keep in mind that if the linear velocity of the blood is constant, time corresponds to distance down the capillary as shown on the x axis in Figure 30-5B on p. 690 of the text. Imagine a basement that is somewhat leaky to water. The leakiness of the wall is analogous to the diffusing capacity (DL) of the lung. After a severe rainstorm, the water outside the basement rises to a level that is 100 cm above the floor of the basement. This 100 cm of water is analogous to the alveolar PCO. The combination of the hydrostatic pressure gradient of 100 cm and the leakiness of the wall allows water to leak in at the rate of 100 L/min. Thus, the influx of water is analogous to the uptake of CO by the pulmonary capillary blood (V.CO). Fortunately, the basement is equipped with a sump pump—which is activated by the presence of water—that removes water at 99 L/min. The sump pump is analogous to hemoglobin, and the pumping of the water is analogous to the binding of CO to hemoglobin. Thus, under the conditions of this example, the pump can remove all but 1 L/min of the incoming water so that water level (analogous to PCO) will slowly rise. By how much will the water level rise within 5 hours, a period that is analogous to the time that a red blood cell spends in a pulmonary capillary?

If the leakiness of the basement wall is low (low DL), then the water level may rise by only a few centimeters during the 5-hour period. Thus, even though a large amount of water may have entered during the 5 hours, the basement water level never rose enough to equilibrate with the outside water level, which was 100 cm above the floor. The reason for this failure of the water to equilibrate is that the pump was able to remove almost all the water. If the leakiness of the basement wall is higher (higher DL), then the water level after 5 hours may be 50 cm—but still less than the water level outside the wall.

It is important to recognize that the failure of the water to equilibrate across the wall in our examples was not a function of the water per se but of three parameters: (1) the relatively low leakiness of the basement wall (low DL), (2) the modest 100-cm pressure gradient driving water across the wall into the basement (a low PACO), and (3) the high capacity of the pump for removing water (CO binding capacity of hemoglobin). Obviously, if the wall were substantially leakier, if the pressure gradient were substantially higher, or if the pump were substantially slower, the water level in the basement could have risen to as much as 100 cm during the 5-hour period—but never more. However, given low driving pressure and the high pump capacity, the total amount of water that entered the basement during the 5-hour period was limited by the leakiness of the basement wall. If the leakiness had been twice as great, the amount of water entering the basement during the 5-hour period also would have been twice as great. Thus, the entry of water was leakiness limited.

Contributed by Emile Boulpaep and Walter Boron

Assumptions Underlying Figure 30-5C

In our analysis—in which we are halving or doubling DL—we are assuming that DL is strictly a reflection of Fick’s law. That is, we are assuming that DL equals DM, and we are ignoring the buffering of carbon monoxide by hemoglobin.

In our example in which we have doubled DL (curve labeled “DL = 2” in Fig. 30–5C), we showed that the partial pressure of carbon monoxide (PCO) at the end of the pulmonary capillary has doubled. The CO content of the blood at the end of the pulmonary capillary (Cc’CO) also very nearly doubles. Cc’CO has two components—the CO freely dissolved in blood and the CO bound to hemoglobin. The latter is by far the more important. At the low capillary PCOvalues in our example, the relationship between capillary PCO and the CO saturation of hemoglobin is approximately linear. According to Henry’s law, the relationship between PCO and dissolved CO is also linear. Thus, the total CO content of blood at the end of the capillary is approximately proportional to PCO at the end of the capillary in our example. Thus, when DL doubles, both the PCO and the total CO content of the blood also double at the end of the pulmonary capillary.

Contributed by Emile Boulpaep and Walter Boron

Assumptions Underlying Figure 30-5D

In analyzing Figure 30-5D, we have assumed that the linear velocity of the pulmonary-capillary blood is proportional to the flow (Q). Thus, when the flow doubles, we are assuming that the contact time of the blood with the alveolar capillary would fall by half.

This assumption requires that the dimensions of the vessel be fixed (i.e., that neither the diameter nor the length of the capillary increase), and that the increase in flow not recruit new blood vessels. In fact, as discussed in Chapter 31, neither of these assumptions is correct. First, starting from a low perfusion pressure, increasing the perfusion pressure causes the recruitment of pulmonary vessels that previously were not conducting blood. Second, pulmonary vessels are highly compliant so that increases in perfusion pressure cause the vessels to dilate. For both reasons (i.e., recruitment and dilation), pulmonary vascular resistance falls as the perfusion pressure increases. Thus, if the flow doubles, the contact time of the blood with the alveolar capillary will fall, but by less than half.

Contributed by Emile Boulpaep and Walter Boron

Making CO Uptake Perfusion Limited, or Making N2O Uptake Diffusion Limited

After analyzing our railway-car analogy, we are now in a position to consider factors that could—at least in principle—render the transport of CO predominantly perfusion limited or that could—at least in principle—render the transport of N2O predominantly diffusion limited. Let us first consider CO uptake.

At least six changes to the system (see Table 1) could cause pulmonary capillary PCO (PcCO) to reach alveolar PCO (PACO) by the end of the capillary, and thus cause CO transport no longer to be limited by DLCO.

1. Increase DLCO (i.e., increase number of workers in the analogy of Figure 30-7 on p. 694 of the text). This change would increase the flow of CO into the capillary for each diffusion event and thus increase both the rate at which the hemoglobin would load up with CO and the rate at which free CO (proportional to PCO) could accumulate in the capillary. Another way of increasing the flow of CO into the capillary would be to increase PCO, which would increase the driving force for CO diffusion. Keep in mind that it is the product of PCO and DLCO that, according to Fick’s law, determines diffusion.

2. Decrease (or totally eliminate) hemoglobin (i.e., decrease the carrying capacity of each railway car). In the extreme, eliminating hemoglobin would force all incoming CO to remain free in solution so that free [CO] (i.e., PcCO) would rapidly rise along the pulmonary capillary.

3. Increase the CO content of mixed venous blood (partially preloading railway cars with dummy boxes before the cars enter the dock area). By partially loading the hemoglobin with CO before the blood even came into contact with the alveoli, we would reduce the amount of additional CO that could bind to hemoglobin before the Hb–CO complex was in equilibrium with free CO. With fewer binding sites available for the CO diffusing in from the alveoli, the level of free CO would rise more rapidly. In the extreme, PcCO would reach PACO by the end of the capillary.

4. Decrease Q. (decrease train speed). By increasing the contact time of capillary blood with the alveoli, we would allow each bolus of capillary blood to undergo more diffusion events as it moves a certain distance along the length of the capillary. Thus, for a given distance traveled along the capillary, the blood would take up more CO, more CO would bind to hemoglobin, and more CO would also remain free—so that PcCO would more closely approach PACO.

5. Lengthen the capillary (increase length of loading dock, with a proportional increase in the number of workers). The effect of this maneuver is the same as for point 4 in that it increases the contact time of the blood with the pulmonary capillary.

6. Distend the capillary while keeping Q.constant (decrease train speed). In this case, we would decrease the linear velocity of the blood, increasing the contact time with the capillary. The effect, however, would not be quite as dramatic as that in point 4 because the increase in diameter would decrease the surface-to-volume ratio so that each bolus of blood would be able to avail itself of a smaller surface area for diffusion. Keep in mind that linear velocity will decrease with the square of the radius, whereas surface area will increase only linearly with area.

At least four changes to the system would cause the transport of N2O, normally perfusion limited, to become diffusion limited (see Table 2). In other words, capillary PN2O would fail to reach alveolar PN2O by the end of the pulmonary capillary.

1. Greatly decrease DLN2O (i.e., decrease the number of workers). The result will be to slow diffusion. In the extreme, we could decrease the flow of N2O so much that the N2O fails to achieve equilibrium by the end of the capillary. Another way of decreasing the flow of N2O into the capillary would be to decrease PN2O, which would decrease the driving force for N2O diffusion. Keep in mind that it is the product of PN2O and DLN2O that, according to Fick’s law, determines diffusion.

2. Increase Q. (increase train speed). An increase in Q. increases the linear velocity of the blood and thus decreases the time available for N2O diffusion into a bolus of blood. If the increase in Q. is sufficiently large, then the amount of N2O diffusing into the lumen will be so small that capillary PN2O will never reach alveolar PN2O. That is, the contact time will be insufficient for N2O to achieve equilibrium.

3. Shorten the capillary (decrease length of the loading dock). Like the increase in Q, the decrease in capillary length will decrease the contact time for a bolus of blood with the pulmonary capillary.

4. Decrease capillary diameter while keeping Q.constant (increase train speed). This maneuver would increase the linear velocity of the blood, decreasing the contact time of a bolus of blood with the capillary. The effect might be even more dramatic than that in point 2 because the decrease in diameter would increase the surface-to-volume ratio so that each bolus of blood would be able to avail itself of a greater surface area for diffusion.

If you are wondering why the N2O analysis has two terms less than the CO analysis, one term is missing because N2O does not interact with hemoglobin (point 2 for CO), and a second term is missing because we cannot further decrease the mixed venous N2O content below zero (point 3 for CO).

Table 1

Changes That Could Theoretically Make the Transport of a Diffusion-Limited Gas (Co) Become Perfusion Limited

Changea

Why Change Makes Transport Perfusion Limited

↑ DL or ↑ PACO (↑ number of workers)

If CO could enter rapidly enough, it could load the Hb with CO and cause free [CO] to rise rapidly.

↓ [Hemoglobin] (↓ capacity of each car)

Because carrying capacity for CO is reduced, a given rate of CO transport causes the concentration of free CO to rise rapidly.

↑ CimageCO (partially preload cars with dummy boxes)

If the Hb were sufficiently preloaded with CO, not much additional CO would need to enter to fully load the Hb.

↓ Q (↓ train speed)

If the contact time of blood with alveolar air were sufficiently long, enough CO could enter to load the Hb, causing the concentration of free CO to rise rapidly.

↑ Capillary length (lengthen loading dock)

By increasing the contact time of blood with alveolar air, Hb would eventually become loaded, as described above.

↑ Capillary diameter at fixed image (↓ train speed)

As above, contact time would increase.

aExpressions in parentheses refer to the railway car analogy in Figure 30-7 on p. 694 of the text.

Table 2

Changes That Could Theoretically Make the Transport of a Perfusion-Limited Gas (N2O) Become Diffusion Limited

Changea

Why Change Makes Transport Perfusion Limited

↓ DL or ↓ PACO (↓ number of workers)

If N2O entered slowly enough, would fail to reach by the end of the capillary.

↑ image (↑ train speed)

If the contact time of blood with alveolar air were sufficiently brief, not enough N2O would enter the blood to cause PCN2O to reach PCN2O by the end of the capillary

↓ Capillary length (shorten loading dock)

By decreasing contact time of blood with alveolar air, N2O would fail to reach diffusion equilibrium, as described above.

↓ Capillary diameter at constant image (↑ train speed)

As above, contact time would decrease.

aExpressions in parentheses refer to the railway car analogy in Figure 30-7 on p. 694 of the text.

Contributed by Emile Boulpaep and Walter Boron

Effect of Nonuniformity of Ventilation on Alveolar Air Samples

In Chapter 31, we introduce the single-breath N2 washout technique and Fowler’s method for measuring anatomic dead space (see p. 701 of the text). In this approach, the subject inhales one breath of 100% O2, and we assume that the inspired 100% O2 distributes evenly throughout all the alveoli of the lungs. If ventilation is indeed uniform, the inspired O2 dilutes alveolar N2 uniformly in all regions of the lung. Thus, when the subject exhales, the air emerging from the alveolar airspaces should have a uniform [N2], and the plateau of the single-breath N2 washout should be flat, as shown by the red curve in Figure 31-2C on p. 702 labeled “Pure alveolar air.”

However, if the alveoli are unevenly ventilated, the inhaled 100% O2 will not distribute uniformly throughout the lungs and therefore will not uniformly dilute the preexisting alveolar N2. Regions of the lung that are relatively hypoventilated will receive relatively less 100% O2 during the single inspiration so that they will be relatively poor in O2 but rich in N2. Conversely, hyperventilated regions will receive relatively more of the inhaled 100% O2 and hence will be O2 rich and N2 poor. During the expiration, we no longer observe a plateau for [N2]. Why? After exhalation of the anatomic dead space, the first alveolar air out of the lungs is dominated by the O2-rich/N2-poor gas coming from the relatively hyperventilated airways, which inflate and deflate relatively quickly. As the expiration continues, the alveolar air gradually becomes increasingly dominated by the O2-poor/N2-rich gas from the hypoventilated airways, which inflate and deflate relatively slowly. Because of this shift from hyper- to hypoventilated regions, the [N2] gradually creeps upward—that is, there is no clear plateau—in subjects with a sufficiently high nonuniformity of ventilation.

Contributed by Emile Boulpaep and Walter Boron

Capillary Reserve in Renal Glomerulus

The DL reserve for O2 along the pulmonary capillaries is reminiscent of the filtration reserve that exists along the capillaries of the glomerulus in the kidney (see p. 773 of the text). In both cases, the system is able to accommodate a substantial increase in blood flow before saturating.

Contributed by Emile Boulpaep and Walter Boron

Effect of CO2 on the Diffusing Capacity (DL)

An increase in arterial PCO2 causes an increase in pulmonary capillary blood (Vc) and thus an increase in the (θ· Vc) term of DL:

image

The preceding equation is a repetition of Equation 30–15 on p. 689 of the text. We will see in Chapter 31 that a high PCO2 causes pulmonary vasoconstriction (see p. 712 of the text). Evidently, the predominant effect of increasing PCO2 (e.g., caused by breathing CO2) is to constrict pulmonary venules more than arterioles, thereby distending the pulmonary capillaries and thus increasing Vc. Note that according to this scenario, CO2 has no effect on DM (i.e., it has no direct effect on diffusion per se).

REFERENCE

J Appl Physiol 15:543–549, 1960.

J Appl Physiol 19:734–744, 1964.

Schnermann J, Chou C-L, Ma T, Traynor T, Knepper MA, and Verkman AS: Defective proximal tubular fluid reabsorption in transgenic aquaporin-1 null mice. Proc Natl Acad Sci USA 95:9660–9664, 1998.

Contributed by Emile Boulpaep and Walter Boron

Exercise-Induced Arterial Hypoxemia in Females

In elite male athletes—and thoroughbred race horses, which are bred to have an impressive cardiac output—maximal aerobic exercise may lead to arterial hypoxemia—a fall in the PO2 of arterial blood. The reason for this hypoxemia is believed to be a cardiac output that outstrips the lung’s diffusion reserve (see p. 697 of the text), leading to a failure to reach diffusion equilibrium in the pulmonary capillaries (i.e., diffusion-limited O2 transport). Note that in most men—those with normal levels of maximal cardiac output—maximum exercise does not lead to arterial hypoxemia. Instead, the exercise-induced increase in ventilation maintains a near-normal arterial PO2 and usually a lower than normal arterial PCO2.

In women, however, it is common for exercise to lead to arterial hypoxemia. This effect does not correlate with level of physical fitness, but it appears to be constitutional, possibly reflecting an exercise-induced increase in ventilation–perfusion mismatch.

REFERENCE

Harms CA, McClaran SR, Nickele GA, Pegelow DF, Nelson WB, and Dempsey JA: Exercise-induced arterial hypoxaemia in healthy young women. J Physiol 507:619–628, 1998.

Contributed by Emile Boulpaep and Walter Boron

Inhaled versus Exhaled Volume

The rate of O2 consumption (e.g., 250 mL/min) is generally greater than the rate of CO2 production (e.g., 200 mL/min) on an atypical Western diet. That is, the respiratory quotient (RQ) is generally less than unity (see p. 706 of the text). As a result, every minute we inhale slightly more air than we exhale (e.g., 250 mL/min – 200 mL/min = 50 mL/min). Because of this difference, in reporting ventilatory volumes, respiratory physiologists have standardized on the volume of exhaled air (VE), which, as we have noted, is slightly smaller than the volume of inhaled air (VI).

Contributed by Emile Boulpaep and Walter Boron

Oscillations in PO2 and PCO2 during Breathing

We will assume that the volume of alveolar air after a quiet expiration is 3000 mL (the functional residual capacity), and that this air has a PO2 of 98.4 mm Hg—the nadir of PO2 during our hypothetical respiratory cycle. The subsequent inspiration delivers to the alveoli 350 mL of fresh air (at 500 mL tidal volume less 150 mL of anatomic dead space) that has a PO2 of 149 mm Hg. Thus, after the 350 mL of fresh air mixes with the 3000 mL of preexisting alveolar air, the alveolar PO2 will be:

Equation 1

image

This value is the zenith of PO2 during our hypothetical respiratory cycle. During the ensuing several seconds, the alveolar PO2 drifts back down to 98.4 mm Hg as O2 diffuses from the alveolar air into the pulmonary–capillary blood. Thus, during a respiratory cycle, alveolar PO2 oscillates from a low of 98.4 mm Hg to a high of 103.6 mm Hg, with a mean PO2 of 101 mm Hg. In other words, alveolar PO2oscillates around a mean of 101 mm Hg, with the peak and nadir deviating from the mean by approximately 2.6 mm Hg—an amplitude of approximately 5 mm Hg.

In the case of CO2, the analysis is similar. After a quiet expiration, the 3000 mL of alveolar air has a PCO2 of 42.2 mm Hg—the zenith of PCO2 during our hypothetical respiratory cycle. The subsequent inspiration delivers to the alveoli 350 ml of fresh air, which has a PCO2 of approximately 0 mm Hg. Thus, after the 350 mL of fresh air mixes with the 3000 mL of preexisting alveolar air, the alveolar PCO2 will be:

Equation 2

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This value is the nadir of PCO2 during our hypothetical respiratory cycle. During the ensuing several seconds, the alveolar PCO2 drifts back up to 42.2 mm Hg as CO2 diffuses from the pulmonary–capillary blood to the alveolar air. Thus, during a respiratory cycle, alveolar PCO2 oscillates from a high of 42.2 mm Hg to a low of 37.8 mm Hg, with a mean PCO2 of 40 mm Hg. In other words, alveolar PCO2 oscillates around a mean of 40 mm Hg, with the peak and nadir deviating from the mean by approximately 2.2 mm Hg—an amplitude of approximately 4 mm Hg.

Contributed by Emile Boulpaep and Walter Boron

The Shape of the Single-Breath Nitrogen Washout Curve

Exhaling vigorously causes turbulence (see p. 641 of the text) in the larger airways, further blurring the boundary between dead space and alveolar air. The greater the mixing, the more spread out is the S-shaped transition in Figure 31-2C on p. 702 of the text.

Breath holding not only blurs the boundary (because more time is available for diffusional mixing of N2 in the alveolar spaces with the O2 in the dead space) but also moves the boundary to the left. In fact, if you were to hold your breath infinitely long, all the O2 in your conducting airways would be contaminated with N2. As a result, the N2 profile in Figure 31-2B or 31–2C would be a low, stable value from the very first milliliter of exhaled air. That is, there would be no gray area, and it would appear—according to the Fowler technique—as if you did not have any dead space.

Inhaling a large tidal volume of 100% O2 increases the apparent anatomic dead space as measured by the Fowler technique. The reason is that the conducting airways have a finite compliance (see p. 634 of the text)—lower than the compliance of alveoli but still greater than zero. Thus, with a large inhalation (and thus a rather negative intrapleural pressure), the conducting airways dilate somewhat, and this dilation is reflected in a larger than normal value for anatomic dead space.

Contributed by Emile Boulpaep and Walter Boron

Obtaining a Sample of Alveolar Air

How do we obtain the alveolar air sample? As noted in our discussion of Fowler’s single-breath nitrogen washout technique on p. 701 of the text, we ask the subject to make a prolonged expiratory effort. We discard the first several hundred milliliters of expired air—which contains pure dead-space air, a mixture of dead-space and alveolar air, and some pure alveolar air—to be certain that we do not contaminate our sample with air from the conducting airways. We then collect the end-tidal sample of air—pure alveolar air—and assay it for PCO2.

Contributed by Emile Boulpaep and Walter Boron

Christian Bohr (1855–1911)

Christian Bohr, a native of Copenhagen, was an eminent physiologist and also the father of the physicist Niels Bohr. The major contributions of Christian Bohr were the first description of dead space(specifically the physiologicaldead space) and the description of the Bohr effect.

REFERENCE

http://en.wikipedia.org/wiki/Christian_Bohr

The Bohr Equation

The principle of Bohr’s approach is that the CO2 concentration of the expired air is the CO2 concentration of the alveolar air—as diluted by the CO2 in the dead space, which contains no CO2. Imagine that we have a volume of expired air (VE). The total amount of CO2 present in this expired air is the sum of the CO2 contributed by the volume of air from the dead space (VD) and the CO2 contributed by the volume of air coming from the alveoli (VE – VD):

Equation 1

image

Knowing that the amount of the gas is simply the product of the volume and the concentration of the gas in that volume, we can write

Equation 2

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Note that the volume of air coming from the alveoli is not the total volume of alveolar air, which might be a couple of liters, but rather that part of the expired volume that came from the alveoli. For example, if the expired volume were 500 mL and the dead space were 150 mL, the air coming from the alveoli (VE – VD) would be 350 mL.

Because [CO2]D is virtually zero, we can drop the “conducting airway” term from Equation 2. In other words, the cross-hatched area beneath the dashed line in Figure 31-3B on p. 703 of the text is equal to the red area under the solid red line. The simplified version of Equation 2 is thus

Equation 3

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Furthermore, because the CO2 concentration is proportional to the CO2 partial pressure, and because the proportionality constant is the same for the expired air and the alveolar air,

Equation 4

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We can rearrange this equation and solve for the ratio VD/VE, which is the fraction of the expired volume that came from the dead space:

Equation 5

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This is the Bohr equation. Typically, VD/VE ranges between 0.20 and 0.35. For a VD of 150 mL and a VE of 500 mL, VD/VE would be 0.30. Because the partial pressure of CO2 in the dead-space air is virtually zero, PECO2 must be less than PACO2. For example, imagine that the alveolar PCO2 were 40 mm Hg and the average PCO2 in the expired air were 28 torr:

Equation 6

image

Equation 5 makes good intuitive sense. In an extreme hypothetical case in which we reduced VD to zero, the expired air would be entirely from the alveoli so that

Equation 7

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On the other hand, if the tidal volume and the dead space were both 150 ml, then all of the expired air would be dead-space air. Thus, the PECO2 would have to be zero, and

Equation 8

image

If the tidal volume were increased from 500 to 600 mL and VD remained at 150 mL, the ratio VD/VE would fall from 0.30 to 0.25. With a greater VE, the alveolar air would make a greater contribution to the mixed expired air so that the mean expired PCO2 would be 30 torr (i.e., closer to PACO2) instead of only 28. Thus, if you wish to compute VD using Bohr’s approach, it is best to use an expired volume that is larger than VD but not too much larger.

Contributed by Emile Boulpaep and Walter Boron

The Conversion Factor 0.863

Unfortunately for the student of respiratory physiology, the way customs have evolved for measuring respiratory volumes and partial pressures is a case study in mixed conventions. In a rational world, all parameters would be measured under a consistent set of conditions. In the real world of respiratory science, however, the parameters you (and clinicians) will need to compute alveolar ventilation, alveolar PCO2and alveolar PO2 are measured under at least three very different sets of conditions. As a result, the student is faced with “correction factors” such as 0.863. Our advice to the student, when working numerical problems, is to insert the laboratory data directly into the correct equation—which you ought to intuitively understand—and use the proper correction factor. You will get the correct answer. Before explaining the origin of 0.863 in Equation 31–11 on p. 704 of the text, we examine the system of units in which clinical laboratories report each of the three terms in that equation.

First, V.A, the alveolar ventilation, is reported in the same units as V.E (i.e., the rate at which air is expired from the lungs). If you collect all the warm, moist air that a subject exhales over a period of 1 min, the laboratory would report that volume BTPS (body temperature and pressure, saturated with H2O vapor), precisely the same volume that the sample of expired air would have occupied in the warm, moist confines of the lung. See the box titled “Conventions for Measuring Volumes of Gases” on p. 617 of the text.

Second, VCO2, the rate at which the body produces CO2, is measured at STPD (standard temperature and pressure, dry). Thus, if you collect a sample of warm, moist expired air expired over a period of 1 min and gave it to a clinical laboratory for analysis, the laboratory V.CO2 will report the volume that the dry CO2 in the sample would occupy at 0°C. The rationale is that this is the way chemists treat gases.

Third, PACO2, the partial pressure of CO2 in the alveoli, is reported in BTPD (body temperature and pressure, dry). If you obtain a sample of alveolar air and send it to a clinical laboratory, the lab would take the warm, moist air you sent and keep it at 37°C but remove the H2O. Of course, if the sample were in a rigid container and if PB were 760 torr, this removal of water vapor would lower the total pressure of the sample by 47 torr (i.e., the vapor pressure of water at 37°C) to 713 torr. To keep the pressure constant, the laboratory allows the sample volume to decrease to a volume that is 713/760 of the original volume. This, however, means that the mole fraction of CO2 increases by the fraction 760/713. Thus, the PCO2 in the warm, moist alveolar air is actually lower than the reported BTPD; the BTPS value of PACO2 is the reported value multiplied by (713/760) or approximately 0.983. The real tragedy of the convention for reporting PACO2 at BTPD is that the same laboratory will report arterial PCO2 as BTPS.

In deriving the factor “0.863,” we begin with a rearrangement of Equation 31–9 on p. 704 of the text, using a consistent set of units (i.e., BTPS):

Equation 1

image

Because V.CO2 is actually reported in STPD, our first task is to convert VCO2 (STPD) to VCO2 (BTPS). Because standard temperature is 0°C and body temperature is 37°C, we must multiply VCO2 (STPD) by the ratio of temperatures in degrees Kelvin, the factor [(273 + 37)/273]. Furthermore, as noted previously, when we add water vapor to a dry sample of a gas and then expand the volume to keep the total pressure fixed at PB, the partial pressure of that gas will decrease to (713/760) of its dry partial pressure. Thus,

Equation 2

image

Our final task is to replace (%CO2 BTPS)A with PACO2 (BTPD). Because PACO2 (BTPS) = (%CO2 BTPS)A × PB,

Equation 3

image

Because PACO2 is reported in BTPD, we must multiply it by the factor (713/760). Thus,

Equation 4

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Substituting the expression for (%CO2 BTPS)A in Equation 4 into Equation 2, we have

Equation 5

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In the previous equation, both VA and VCO2 are reported in milliliters/minute. Because it is customary to report VA in liters/minute, the factor 863 becomes 0.863:

Equation 6

L/min mL/min

image

Equation 6 is the alveolar ventilation equation.

For example, if VCO2 is 200 mL/min and PACO2 is 40 mm Hg,

Equation 7

image

Contributed by Emile Boulpaep and Walter Boron

Obtaining a Sample of Alveolar Air

How do we obtain the alveolar air sample? As noted in our discussion of Fowler’s single-breath nitrogen washout technique on p. 701 of the text, we ask the subject to make a prolonged expiratory effort. We discard the first several hundred milliliters of expired air—which contains pure dead-space air, a mixture of dead-space and alveolar air, and some pure alveolar air—to be certain that we do not contaminate our sample with air from the conducting airways. We then collect the end-tidal sample of air—pure alveolar air—and assay it for PCO2.

Contributed by Emile Boulpaep and Walter Boron

The Alveolar Gas Equation

The alveolar gas equation allows one to compute the ideal alveolar PO2 (PAO2) from one’s knowledge of the alveolar PCO2 (PaCO2), as well as two other parameters, the mole fraction of O2 in the dry inspired air (FIO2) and the respiratory quotient (RQ). We begin by deriving an expression for RQ, which, as described in Chapter 58 on p. 1231 of the text, is defined as the ratio of the rate of metabolic CO2 production (VCO2) to the rate of O2 consumption (VO2):

Equation 1

image

For RQ values less than unity, the body consumes more O2 than it produces CO2 so that the inspired alveolar ventilation (VAI) must be greater than the expired alveolar ventilation (VAE). Because the metabolically produced CO2must all appear in the expired alveolar gas, VCO2 is the fraction of the expired alveolar ventilation that is CO2 gas (FACO2):

Equation 2

image

Similarly, the consumed O2 must all enter the body via the lungs; VO2 is the difference between (1) the amount of O2 entering the alveoli during inspirations over a certain period of time and (2) the amount of O2 exiting the alveoli during expirations over that same time interval:

Equation 3

image

Here, FIO2 is the mole fraction of O2 in the inspired air, and FAO2 is the mole fraction of O2 in the expired alveolar air. Substituting the expressions for VCO2 (Equation 2) and VO2 (Equation 3) into the definition of RQ (Equation 1), we have

Equation 4

image

We now need an expression for the ratio VAI/VAE. In deriving this expression, the fundamental assumption is that the N2 gas in the lungs is not metabolized. Thus, in the steady state, the amount of N2 entering the alveoli with inspirations over a certain period of time is the same as the amount of N2 leaving the alveoli with the expirations over the same period. In other words,

Equation 5

image

Here, FIN2 is the mole fraction of N2 in this inspired gas, and FAN2 is the mole fraction of N2 in this expired alveolar air. For the rest of this derivation, we consider only dry gases; the laboratory reports all partial pressure (P) and mole fraction (F) values in terms of the “dry” gas (see the box on p. 595 of the text). Thus, considering only the dry inspired air, the mole fractions of N2, O2, and CO2 must sum to 1:

Equation 6

image

Because the inspired air contains virtually no CO2 (i.e., FICO2 ≈ 0),

Equation 7

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Similarly, considering only the dry expired air, the mole fractions of N2, O2, and CO2 must likewise sum to 1:

Equation 8

image

If we now substitute the expressions for FIN2 (Equation 7) and FAN2 (Equation 8) into Equation 5,

Equation 9

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Solving for the ratio of inspired to expired alveolar ventilation,

Equation 10

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We now have the ratio (VAI/VAE) that we needed for Equation 4. Substituting Equation 10 into Equation 4,

Equation 11

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If we now solve Equation 11 for FAO2,

Equation 12

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Realizing that the “dry” partial pressure (P) is the product of mole fraction (the previous “F” terms) and (PB – 47), we can multiply Equation 12 through by (PB – 47) to arrive at our final equation, which expresses quantities in terms of partial pressures:

Equation 13

image

Remember that all the partial pressure and mole fraction values in Equation 13 refer to dry gases. Thus, PIO2 is FIO2 × (PB – 47).

On p. 706 of the text, we provide a simplified version of Equation 13:

Equation 14

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Why is this equation a reasonable approximation? Examination of Equation 13 and Equation 14 shows that they are identical except that the term in brackets in Equation 13 is replaced by 1/RQ in Equation 14. For Equation 13, we can rearrange the term in brackets as follows:

Equation 15

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Under physiological conditions—when FIO2 is 0.21 and RQ is 0.8—the previous expression evaluates to 0.958/RQ, which is quite close to 1/RQ—that is, Equation 14 is a reasonable approximation of Equation 13 under these conditions.

When RQ is unity, the term in brackets in Equation 13 evaluates to unity, and Equation 13 simplifies to Equation 31–16 on p. 706 of the text:

Equation 16

image

Contributed by Emile Boulpaep and Walter Boron

Detecting Nonuniformity of Ventilation

We have already seen how 133Xe scanning can be useful in detecting the physiological nonuniformity of ventilation. Obviously, because of limitations in scanning technology, 133Xe scans are helpful only if sufficiently large regions of the lung have sufficiently large differences in ventilation. However, a 133Xe scan might not detect a nonuniformity of ventilation in which many small, well-ventilated airways are intermingled with many small, poorly ventilated airways. Two other approaches that we have mentioned in other contexts would detect such a nonuniformity of ventilation.

The first is the single-breath N2 washout technique, which we introduced in our discussion of Fowler’s method for measuring anatomic dead space (see p. 700 of the text). In this approach, the subject inhales one breath of 100% O2, and we assume that the inspired 100% O2 distributes evenly throughout all the alveoli of the lungs. If ventilation is indeed uniform, the inspired O2 dilutes alveolar N2 uniformly in all regions of the lung. Thus, when the subject exhales, the air emerging from the alveolar airspaces should have a uniform [N2], and the plateau of the single-breath N2 washout should be flat, as shown by the red curve in Figure 31-2C on p. 702 labeled “Pure alveolar air.”

However, if the alveoli are unevenly ventilated, the inhaled 100% O2 will not be distributed uniformly throughout the lungs and therefore will not uniformly dilute the preexisting alveolar N2. Regions of the lung that are relatively hypoventilated will receive relatively less 100% O2 during the single inspiration so that they will be relatively poor in O2 but rich in N2. Conversely, hyperventilated regions will receive relatively more of the inhaled 100% O2 and hence will be O2 rich and N2 poor. During the expiration, we no longer observe a plateau for [N2]. Why? After exhalation of the anatomic dead space, the first alveolar air out of the lungs is dominated by the O2-rich/N2-poor gas coming from the relatively hyperventilated airways—which inflate and deflate relatively quickly. As the expiration continues, the alveolar air gradually becomes dominated increasingly more by the O2-poor/N2-rich gas from the hypoventilated airways, which inflate and deflate relatively slowly. Because of this shift from hyper- to hypoventilated regions, the [N2] gradually creeps upward—that is, there is no clear plateau—in subjects with a sufficiently high nonuniformity of ventilation.

A second test for unevenness of ventilation is the seven-minute N2 washout. We saw in Chapter 26 how to compute lung volume from the volume of distribution of N2 (see p. 626). The general approach is for a subject to inhale 100% O2, allow that O2 to dilute the preexisting alveolar N2, and then exhale into a collection container. If this breathing pattern is continued for a standard period of 7 min, and if ventilation is evenly distributed, virtually all of the preexisting N2 washes out of the lungs (see inset of Fig. 26–9B on p. 627). We already learned that from the amount of N2 washed into the collection container, we can compute VL. However, we can also use this experiment to assess the evenness of ventilation. In a normal individual, the mean alveolar [N2] in the expired air is less than 2.5% after 7 min of O2 breathing. However, if some airways are poorly ventilated, their N2 will not be washed out as well after 7 min of O2 breathing so that the [N2] in these hypoventilated airways may be substantially greater than 2.5%. Because these hypoventilated airways contribute to the total expired alveolar air, the mean expired alveolar [N2] after 7 min will be elevated. Obviously, the degree of elevation depends on the volume of hypoventilated airways and the extent of their hypoventilation.

Contributed by Emile Boulpaep and Walter Boron

Effect of Changes in Compliance on the Time Constant Governing Changes in Lung Volume

On p. 646 of the text, we saw that during inspiration and expiration, the time course of lung volume (VL) is approximately exponential. The time constant (τ) for the change in VL (ΔVL) is the time required for the change in VL to be approximately 63% complete. Moreover, Web Note 0646c, Calculating the Time Constant for a Change in Lung Volume, explains why τ is the product of airway resistance (R) and alveolar compliance (C):

Equation 1

image

Decreased compliance. In the example discussed under restrictive pulmonary disease on p. 708, we decreased the compliance of one lung by half. Of course, other things being equal, the ΔV of the affected lung will be half normal, as illustrated in Figure 31-6A on p. 708. What is not so obvious is that τ of the affected lung will also be half normal. In other words, the lung with half-normal compliance will achieve its final volume twice as fast as normal. The reason is that, with a normal airway resistance, the inhaled air—at any instant in time—will flow at a more or less normal rate so that the affected lung achieves its half-normal ΔV earlier than the normal lung.

Although it might seem that the decreased in this example is a good thing, the problem is that the reduced ΔV translates to less ventilation, and that is not a good thing. As described in the text, this reduced ventilation increases the nonuniformity of ventilation, which in turn—as discussed later—tends to lead to hypoxia and respiratory acidosis.

Increased compliance. What would be the effect of increasing the static compliance of one lung? A disease that increases the static compliance is emphysema (see Fig. 27–5 on p. 634 of the text). Other things being equal, an increase in compliance will cause the ΔV of the affected lung to be greater than normal. At the same time, of the affected lung will also be increased. The reason is that, with a normal airway resistance, the inhaled air—at any instant in time—will flow at a more or less normal rate so that the affected lung achieves its greater than normal ΔV later than a normal lung. If is too large, then the time that the person allows for inspiration may not be long enough for the affected lung to increase its volume to the level that it could achieve if the inspiration were infinitely long. As a result, the inspiration will be truncated, and the true ΔV for the affected lung will be less than normal, thereby exacerbating the unevenness of ventilation. Moreover, the greater the respiratory frequency, the greater the truncation of the inspiration, and thus the greater the exacerbation of the unevenness of ventilation.

Figure 27-15A on p. 648 of the text illustrates the effect of increased airway resistance on the time course of VL, and Figure 27-15B illustrates the effect on the change in lung volume, which is proportional to dynamic compliance. In the example in Figure 27-15, the static compliance was normal and the final ΔV was the same for the normal and affected lung. The example we are discussing in this Web Note is just the opposite (i.e., a normal airway resistance but altered compliance). Nevertheless, the principle of how increases in τ affect ventilation is the same: The greater the τ, the greater the chance that increased respiratory frequency will lead to a truncated inspiration, and thus a greater unevenness of ventilation.

Although we have focused on inspiration in these examples, the same principles apply to expiration; namely, the greater the τ greater the chance of a truncated expiration.

Contributed by Emile Boulpaep and Walter Boron

Effect of Changes in Compliance on the Time Constant Governing Changes in Lung Volume

On p. 646 of the text, we saw that during inspiration and expiration, the time course of lung volume (VL) is approximately exponential. The time constant (τ) for the change in VL (ΔVL) is the time required for the change in VL to be approximately 63% complete. Moreover, Web Note 0646c, Calculating the Time Constant for a Change in Lung Volume, explains why is the product of airway resistance (R) and alveolar compliance (C):

Equation 1

image

Decreased compliance. In the example discussed under restrictive pulmonary disease on p. 708, we decreased the compliance of one lung by half. Of course, other things being equal, the ΔV of the affected lung will be half normal, as illustrated in Figure 31-6A on p. 708. What is not so obvious is that τ of the affected lung will also be half normal. In other words, the lung with half-normal compliance will achieve its final volume twice as fast as normal. The reason is that, with a normal airway resistance, the inhaled air—at any instant in time—will flow at a more or less normal rate so that the affected lung achieves its half-normal ΔV earlier than the normal lung.

Although it might seem that the decreased τ in this example is a good thing, the problem is that the reduced ΔV translates to less ventilation, and that is not a good thing. As described in the text, this reduced ventilation increases the nonuniformity of ventilation, which in turn—as discussed later—tend to lead to hypoxia and respiratory acidosis.

Increased compliance. What would be the effect of increasing the static compliance of one lung? A disease that increases the static compliance is emphysema (see Fig. 27–5 on p. 634 of the text). Other things being equal, an increase in compliance will cause the ΔV of the affected lung to be greater than normal. At the same time, τ of the affected lung will also be increased. The reason is that, with a normal airway resistance, the inhaled air—at any instant in time—will flow at a more or less normal rate so that the affected lung achieves its greater than normal ΔV later than a normal lung. If is too large, then the time that the person allows for inspiration may not be long enough for the affected lung to increase its volume to the level that it could achieve if the inspiration were infinitely long. As a result, the inspiration will be truncated, and the true ΔV for the affected lung will be less than normal, thereby exacerbating the unevenness of ventilation. Moreover, the greater the respiratory frequency, the greater the truncation of the inspiration, and thus the greater the exacerbation of the unevenness of ventilation.

Figure 27-15A on p. 648 of the text illustrates the effect of increased airway resistance on the time course of VL, and Figure 27-15B illustrates the effect on the change in lung volume, which is proportional to dynamic compliance. In the example in Figure 27-15, the static compliance was normal and the final ΔV was the same for the normal and the affected lung. The example we are discussing in this Web Note is just the opposite (i.e., a normal airway resistance but altered compliance). Nevertheless, the principle of how increases in τ affect ventilation is the same: The greater the τ, the greater the chance that increased respiratory frequency will lead to a truncated inspiration, and thus a greater unevenness of ventilation.

Although we have focused on inspiration in these examples, the same principles apply to expiration; namely, the greater the τ the greater the chance of a truncated expiration.

Contributed by Emile Boulpaep and Walter Boron

Additional Factors Affecting the Resistance of Pulmonary Vessels

Alveolar vessels. On pp. 709–710 of the text, we noted that two major factors affect the caliber of alveolar vessels (i.e., vessels surrounded by alveoli): transmural pressure and lung volume (VL) per se. The cardiac cycle and the respiratory cycle are two factors that can affect the transmural pressure of alveolar vessels. A third factor is an indirect effect of increasing lung volume. (This indirect effect is in addition to the direct effect of increasing VL, which stretches the vessels longitudinally and crushes them as they are viewed in cross section.) Let us compare two static conditions—resting at functional residual capacity (FRC) and holding our lung volume at total lung capacity (TLC). To achieve the higher lung volume, we needed to shift PIP in the negative direction. As discussed in the text on p. 710, this decrease in PIP dilates extra-alveolar vessels. Because the volume of these vessels increases, the pressure falls inside all the vessels in the thorax. This decrease in intravascular pressure at negative PIP values accentuates the collapse of the alveolar vessels at high lung volumes.

Extra-alveolar vessels. On p. 710 of the text, we considered only static conditions. What happens when—starting at TLC (where the PIP at rest is very negative)—one makes a maximal expiratory effort? Instantly, PIP becomes very positive, tending to collapse the extra-alveolar vessels, just as this maneuver tends to collapse conducting airways (see pp. 648–650). However, the mechanical tethering (or radial traction) of other structures on the extra-alveolar vessels tends to oppose their collapse, just as—at a high VL—mechanical tethering tends to keep conducing airways open during expiration. However, the effects of mechanical tethering decrease as VL falls during expiration.

Contributed by Emile Boulpaep and Walter Boron

Notes on the Differences between Anatomic and Physiological Dead Space

There is a fundamental difference between the anatomic and alveolar dead space. The conducting airways are in series with and upstream from (proximal to) the alveoli. The conducting airways have the composition of inspired air only after an inspiration; after an expiration, they have the composition of alveolar air. On the other hand, unperfused alveoli are in parallel with normal alveoli and have the composition of inspired air, regardless of the position in the respiratory cycle.

Contributed by Emile Boulpaep and Walter Boron

Bronchiolar Constriction during Alveolar Dead-Space Ventilation

The precise mechanism of bronchiolar constriction in response to alveolar dead-space ventilation is unknown. However, it is intriguing to speculate that, at least in part, the mechanism may parallel that for the autoregulation of blood flow in the brain. The vascular smooth muscle cells (VSMCs) of the penetrating cerebral arterioles constrict in response to respiratory alkalosis, which is why one feels dizzy after hyperventilating. This constriction of the VSMCs occurs when one imposes an alkalosis in the complete absence of CO2/HCO3. Furthermore, the alkalosis-induced vasoconstriction is due entirely to a pH decrease on the outside of the VSMC. In other words, these cells have some sort of an extracellular pH sensor. A pH increase on the inside of the cell actually has the opposite effect: vasodilation. During extracellular acidosis, the vessels dilate.

Contributed by Emile Boulpaep and Walter Boron

The Shunt Equation

shunt is one extreme of a image –image. mismatch and arises when blood perfuses unventilated alveoli. Alveoli may be unventilated because they are downstream from an obstructed conducting airway. Regardless of the mechanism that prevents airflow to these alveoli, the resulting right-to-left shunt causes mixed venous blood to remain relatively unoxygenated and go directly to the left side of the heart, where it mixes with oxygenated “arterial” blood. This process is known as venous admixture.

Imagine that 80% of the blood flow to the lungs goes to alveoli that are appropriately ventilated but that 20% goes to alveoli that are downstream from completely obstructed conducting airways. The total perfusion of the lungs is imageT. The shunt perfusion of the unventilated alveoli is imageS, 20% in this example, and the shunted blood has an O2 content (units: mL O2/dL) identical to that of mixed venous blood (Cimage). The difference (imageT – imageS) is the perfusion to the normally ventilated alveoli, 80% in our example, and this unshunted blood has an O2 content appropriate for the end of a pulmonary capillary (Cc′).

The blood emerging from the lungs is a mixture of shunted and unshunted blood so that the O2 emerging from the lung is partially O2 carried by the shunted blood and partially O2 carried by the unshunted blood:

Equation 1

image

How much O2 per minute emerges from the lungs in the systemic arterial blood? This amount is the product of the O2 content of this arterial blood (Ca) and the total blood flow out the lungs (imageT):

Equation 2

image

Similarly, the O2 contributed by the shunted blood is the product of the O2 content and the flow of shunted blood:

Equation 3

image

Finally, the amount of O2 contributed per minute by the unshunted blood is

Equation 4

image

Inserting the expressions for each of the terms of Equation 2 through Equation 4 into Equation 1,

Equation 5

image

Rearranging this equation and solving for the fraction of total blood flow that is represented by the shunt (imageS / imageT), we have

Equation 6

image

This expression is known as the shunt equation.

What does Equation 6 predict for imageS / imageT in our example? We will assume that the O2 content of mixed venous blood is 15 mL O2/dL blood, whereas that for blood at the end of the pulmonary capillaries is 20 mL O2/dL blood. These values are similar to those summarized in Table 28–3 on p. 659. If our hypothetical subject—who is afflicted with a 20% shunt—has systemic arterial blood with an O2 content of 19 mL O2/dL blood, then the shunt equation predicts

Equation 7

image

Thus, the shunt equation predicts that the shunt is 20% of the total blood flow, which is reasonable, inasmuch as we started the example by assuming that 80% of the blood flowed through properly ventilated alveoli.

Contributed by Emile Boulpaep and Walter Boron

Right-to-Left Shunts

Two congenital anomalies of the great vessels in which there may be sizable right-to-left shunts are tetralogy of Fallot and transposition of the great vessels. Both conditions can cause severe hypoxemia.

Contributed by Emile Boulpaep and Walter Boron

Analysis of V/Q Patterns in Figure 31-13

The following is a discussion of Figure 31-13 on page 719 that is more complete than the material presented in the text starting at the bottom of the right column on page 718 (heading: “Normal Lungs”).

Figure 31-13 is a highly simplified example illustrating the principles underlying how an individual with a normal imageAimage in each lung handles CO2 (Figure 31-13A) and O2 (Figure 31-13B) as blood flows through the lungs, the systemic circulation, and then back to the lungs. We make the following assumptions:

• Total imageA (4.2 L/min) and image (5 L/min) are normal.

• imageA and image. are evenly divided between the two lungs. Thus, the overall imageA / image. ratio is (4.2 L/min)/(5 L/min) or 0.84. Of course, the imageA / image. in each of the two lungs is also 0.84.

• imageA and image. are uniformly distributed within each lung. In other words, we are ignoring the usual apex-to-base inequalities of both imageA and Q. (see Fig. 31–10A on p. 715 of the text). In addition, we assume that the lungs are free of pathological causes of either alveolar dead-space ventilation or shunt.

• The system has no physiological shunts right-to-left shunts.

• The PACO2 in each lung will be 40 mm Hg, and the PAO2, 100 mm Hg.

• Total-body imageCO2 will be 200 mL/min and total-body imageO2 will be 250 mL/min.

• The entire system is in a steady state.

Predicting precisely how imageA / image. abnormalities affect the CO2 and O2 partial pressures in the three key compartments (alveoli, arterial blood and mixed-venous blood) is extremely complicated, in part because changes in PCO2 and pH affect O2 carriage (the Bohr effect, p. 677 in the text) and changes in PO2 affect CO2 carriage (the Haldane effect, p. 682 in the text). Moreover, in reality, imageAimage, and the imageA / image. ratio are not uniform throughout each lung. However, although the examples in the text are greatly simplified, they illustrate the principles of how imageA / image. mismatches lead to abnormalities in the arterial blood gases. We begin here with a discussion of the normal condition. We will consider alveolar dead-space ventilation in WebNote and shunt in WebNote

We will now follow the blood during one circuit through the circulation to see the relationship among the composition of the arterial blood, the CO2 and O2 transport rates in the lung, and the composition of the mixed-venous blood.

CO2 Handling First consider the fate of CO2 in the following six steps (Figure 31-13A on p. 719):

Each lung must first receive and then exhale half of the total 200 mL/min of CO2 that body metabolism produces. In other words, 100 mL of CO2 enters each lung each minute, and because they are in a steady state, each lung exhales precisely this same amount each minute.

In each lung, an alveolar ventilation of 2.1 L/min dilutes 100 mL of exhaled CO2 (i.e., the exhaled 100 mL of CO2 is contained within the 2100 mL of exhaled air). This combination of imageA and VCO2corresponds to an alveolar PCO2of ~40 mm Hg.

Because CO2 transport is perfusion limited (see p. 697 in the text), the blood that emerges from each lung has the same PCO2 as the alveolar air, 40 mm Hg. According to the CO2 dissociation curve, we see that this PCO2 of 40 mm Hg corresponds to an arterial CO2 content of 48 mL/dL (lower panel of Figure 31-13A, point a).

As the blood flows through the systemic capillaries, it picks up the 200 mL/min of CO2 produced by metabolism. Given a cardiac output of 5 L/min, we can use the Fick principle (p. 442 in text) to compute how much the CO2content must rise in the capillaries for each 100 mL of blood:

Equation 1

image

Thus, the mixed-venous CO2 content must be 48 + 4 = 52 mL/dL.

According to the CO2 dissociation curve, when the CO2 content of the blood is 52 mL/dL, the mixed-venous PCO2 must be 46 mm Hg (lower panel of Figure 31-13A, point image).

Completing the cycle, as the blood completes the cycle and passes through the pulmonary capillaries, the PCO2 falls from 46 to its original value of 40 mm Hg as 100 mL of CO2 diffuses from the pulmonary capillaries to the alveoli each min in each lung. Simultaneously, the CO2 content falls from 52 to 48 mL/dL as CO2 evolves into the alveolar air at the rate of 100 mL/min in each lung (200 mL/min, total).

O2 Handling Now consider the fate of O2, illustrated in six steps in Figure 31-13B. The situation for O2 is comparable to that for CO2, although the fluxes are all in a direction opposite to those for CO2.

Step 1: Each lung must take up half of the 250 mL/min O2 required by body metabolism, that is 125 mL/min for each lung.

Step 2: For a PACO2 of 40 mm Hg and a respiratory quotient or RQ (see Equation 31–14 on p. 706) of 0.8, the alveolar gas equation (see Equation 31–17 on p. 706) predicts a PAO2 of ~100 mm Hg for each lung.

Step 3: The transport of O2, like that of CO2, is perfusion limited (see p. 697 in the text), so that the blood emerging from each lung has a PO2 of ~100 mm Hg. According to the O2 dissociation curve, a PO2 of 100 mm Hg corresponds to an arterial O2 content of 20 mL/dL (Figure 31-13B/inset, point a).

Step 4: As the blood flows through the systemic capillaries, it must give up 250 mL/min of O2, which will be consumed by metabolism. According to the Fick principle, the decrease in O2 content that occurs as the blood passes through the systemic capillaries is:

Equation 2

image

Thus, the mixed-venous O2 content must be 20 – 5 = 15 mL/dL.

Step 5: From the O2 dissociation curve (Figure 31-13B/inset, point v_), we see that a mixed-venous O2 content of 15 mL/dL corresponds to a mixed-venous O2 of 40 mm Hg (Figure 31-13B/inset, point image).

Step 6: Completing the cycle, as the blood passes through the lungs, it must pick up 125 mL/min of O2 in each lung. This influx of O2 causes the O2 content to increase from 15 to 20 mL/dL, as the blood PO2increases from 40 to 100 mm Hg.

Contributed by Emile Boulpaep and Walter Boron

Surgical Removal of One Lung

As we saw in Figure 30-10 on p. 698 of the text, O2 reaches diffusion equilibrium approximately one-third of the way down the pulmonary capillary of a healthy, young adult at rest. If one of the two lungs were removed surgically, the remaining lung would receive twice its normal complement of blood flow. However, provided that alveolar ventilation, FIO2, barometric pressure, and DL were normal, diffusion equilibrium for O2 would still occur before the end of the pulmonary capillary. If the ventilation–perfusion relationship were also normal for this subject, then arterial PO2 would be normal—at least at rest. However, during exercise, O2 transport could well become diffusion limited. Moreover, if DL were substantially below normal, or if imageA / image. relationships were problematic, then the subject could exhibit arterial hypoxemia even at rest. Therefore, in patients considered for total pneumonectomy, it is critical to evaluate pulmonary function preoperatively to determine that the patient would be able to survive postoperatively on the remaining lung.

Contributed by Walter Boron

Analysis of V-Q Patterns in Figure 31-14

The following is a discussion of Figure 31-14 on page 721 that is more complete than the material presented in the text starting at the top of the left column on page 720 (heading: “Alveolar Dead-Space Ventilation Affecting One Lung”).

Like Figure 31-13Figure 31-14 is a highly simplified example that illustrates the principles underlying how alveolar dead space ventilation affects the handling of CO2 and O2. Except as noted later in this paragraph, all assumptions and parameter values for this example are the same as for the normal case in Figure 31-13 (see WebNote). The key difference in the example in Figure 31-14 is that the left lung receives no perfusionalveolar dead space ventilation. The total [image] remains at 5 liter/min, but all of this perfusion goes to the right lung. Notice that the imageA of 4.2 liter/min is evenly distributed between the two lungs. Thus, the imageA/[image] of the left lung is thus 2.1/0 or ∞, whereas the imageA/[image] of the right lung is 2.1/5 or 0.42. The overall imageA/[image] remains 0.84. Can the low imageA/[image] of the normal lung make up for the high imageA/[image] of the abnormal lung?

CO2 Handling First consider the fate of CO2 in the following seven steps (Figure 31-14 on p. 721):

In the steady state, the normal right lung must eliminate the entire complement of metabolically produced CO2 production, which is 200 mL/min. This rate of CO2 delivery to the right lung is twice its normal level.

In the right lung, the normal alveolar ventilation of 2.1 liter/min must now dilute twice the normal amount of CO2. Thus, alveolar PCO2 in this right lung must be twice normal (i.e., ~80 mm Hg).

Because no blood is flowing to the left lung, its alveolar PCO2 is the same as the PCO2 of inspired air (i.e., ~0 mm Hg). Half of the alveolar air that the subject expires comes the right lung, and half comes from the left lung. Thus, the mean PACO2 is (80 + 0)/2 = 40 mm Hg, which is normal! As we will see below, this mean alveolar PCO2 is important for computing the “alveolar-arterial” difference.

Because the transport of CO2 across the blood-gas barrier is perfusion limited (see p. 697 in the text), the blood leaving the right lung has a PCO2 that is the same as the alveolar PCO2 of the right lung, 80 mm Hg. Because no blood exits from the left lung, the systemic arterial blood also has a PCO2 of 80 mm Hg. According to the CO2 dissociation curve (lower panel of Figure 31-14A, point a), a PCO2 of 80 mm Hg (which represents a substantial degree of respiratory acidosis) corresponds to a CO2 content of ~67 mL/dL.

In the systemic capillaries, metabolically produced CO2 enters the blood at the rate of 200 mL/min. As we already know from our analysis of the normal condition in Figure 31-13A, adding 200 mL CO2 to 5 liters of blood increases the CO2 content by 4 mL/dL:

Equation 1

image

Thus, the CO2 content of the blood at the end of the systemic capillaries will be 67 + 4 = 71 mL/dL.

According to the CO2 dissociation curve (lower panel of Figure 31-14A, point image), when the CO2 content of the blood is 71 mL/dL, the mixed-venous PCO2 must be 87 mm Hg.

Completing the cycle, we see that as the blood passes through the pulmonary capillaries of the right lung, the PCO2 falls from 87 back to its original value of 80 mm Hg. Simultaneously, the CO2 content falls from 71 to its original value of 67 mL/dL as CO2 evolves into the alveolar air at the rate of 200 mL/min.

Thus, even with a severe VA/Q abnormality, the lung is able to expel usual 200 mL/min of CO2, but at a tremendous price: a very high arterial PCO2 and thus respiratory acidosis (see pages 657 and 661 in the text).

O2 Handling Now consider the fate of O2 (Figure 31-14B):

The normal right lung must deliver all the O2 required by the body, 250 mL/min. This rate of O2 abstraction from the right lung is twice normal.

Because the imageA/[image] ratio of the normal right lung is so low (i.e., half normal), the alveolar PO2 in the right lung must be far lower than the usual value of ~100 mm Hg. Because the PACO2 in this lung is 80 mm Hg, and RQ is 0.8, we use the alveolar gas equation (see Equation 31–17 on p. 706) to compute a PACO2 of 51 mm Hg.

Because no blood flow goes to the left lung, its imageA/[image] is, and thus its alveolar PO2 is the same as the PO2 of inspired air (i.e., 149 mm Hg). The mean PAO2 of air expired from the two lungs is (51 + 149)/2 = 100 mm Hg is normal … just as the mean PACO2 was normal.

Because the transport of O2 across the blood-gas barrier is perfusion limited (see p. 697 in the text), the PO2 of the blood leaving the right lung is the same as the alveolar PO2 of the right lung, 51 mm Hg. Because no blood exits from the left lung, the systemic arterial blood has the same PO2 as the blood leaving the right lung, namely 51 mm Hg. From the O2 dissociation curve (lower panel of Figure 31-14B, point a), we see that a PO2 of 51 mm Hg dictates an O2 content of only 14 mL/dL.

In the systemic capillaries, O2 leaves the blood at the rate of 250 mL/min. As we al-ready know from our analysis of Figure 31-13B, removing 250 mL of O2 from 5 liters of blood decreases the O2 content by 5 mL/dL:

Equation 2

image

Thus, the O2 content of the blood at the end of the systemic capillaries will be 14 – 5 = 9 mL/dL.

According to the O2 dissociation curve, when the O2 content is 9 mL/dL, the mixed-venous PO2 must be 37 mm Hg (lower panel of Figure 31-14B, point image).

Completing the cycle, we see that as the blood passes through the pulmonary capillaries of the right lung, the PO2 rises from 37 to 51 mm Hg, and the O2 content rise from 9 to 14 mL/dL as O2 enters from the alveolar air at the rate of 250 mL/min.

Thus, even with a severe imageA/[image] abnormality, the lung is able to import usual 250 mL/min of O2, but at a tremendous price: a very low arterial PO2 (hypoxia).

Beware that this analysis, as complicated as it may seem, is highly oversimplified. For example, in Step 4 and Step 6 of the CO2 analysis, we used a standard CO2 dissociation curve. However, we know that hypoxia will increase the CO2 carrying capacity of blood (Haldane effect, p. 682 in the text). Similarly, in Step 4 and Step 6 of the O2 analysis, we used a standard O2 dissociation curve. However, we know that respiratory acidosis will decrease the O2carrying capacity of blood (Bohr effect, p. 677 in the text). Nevertheless, the take-home message is clear. Even if overall imageA and [image] are normal, an uneven distribution of perfusion leads to respiratory acidosis and hypoxia. Thus, the hyperperfused “good” lung cannot make up for the deficit incurred by the hypoperfused “bad lung,” In our example, the fundamental problem is that ventilating unperfused alveoli in the left lung reduces the effective alveolar ventilation by half.

Contributed by Emile Boulpaep and Walter Boron

Analysis of V-Q Patterns in Figure 31-15

The following is a discussion of Figure 31-15 (on p. 722 of the text) that is more complete than the material presented in the text starting in the right column on page 720 (Heading: “Shunt Affecting One Lung”).

Like Figure 31-13Figure 31-15 is a highly simplified example that illustrates the principles underlying how alveolar dead-space ventilation affects the handling of CO2 and O2. Except as noted later in this paragraph, all assumptions and parameter values for this example are the same as for the normal case in Figure 31-13 (see WebNote). The key difference in the example in Figure 31-15 is that the left lung receives to ventilation—shunt. The total imageA remains 4.2 liter/min, but all of this ventilation goes to the right lung. Notice that the [image] of 5 L/min is evenly distributed between the two lungs. Thus, the imageA/[image] of the left lung is 0/2.5 or 0, whereas the imageA/[image] of the right lung is 4.2/2.5 or 1.68. Can the high imageA/[image] of the hyperventilated right lung make up for the low imageA/[image] of the unventilated left lung?

CO2 Handling First, we will consider the fate of CO2 in the following seven steps (Figure 31-15A):

In the steady state, the normal right lung must eliminate the entire metabolic production of CO2, 200 mL/min. This rate of CO2 delivery to the right lung is twice normal.

The twice-normal amount of CO2 is diluted into a twice-normal alveolar ventilation of 4.2 L/min, so that the alveolar PCO2 in this right lung must be normal (i.e., 40 mm Hg).

Because no air flow goes to the left lung, the air distal to the obstruction in the left lung will have the same PCO2 and the same PO2 as mixed-venous blood. However, because this air is not in direct communication with atmosphere, it does not contribute to the mean alveolar PCO2 of the expired air. Thus, the mean PACO2 is simply the PCO2 of the alveolar air in the right lung, 40 mm Hg, which is normal!

Because the transport of CO2 across the blood-gas barrier is perfusion limited (see p. 697 in the text), the blood leaving the right lung has a PCO2 that is the same as the alveolar PCO2 on the right, 40 mm Hg. According to the CO2dissociation curve (lower panel of Figure 31-15A, point c), when the blood has a PCO2 of 40 mm Hg, it must have a CO2 content of 48 mL/dL. This is the CO2 content after the right lung has extracted CO2 at the rate of 200 mL/min.

What was the CO2 content of the blood before the CO2 was extracted? That is, what was the mixed-venous PCO2? According to the Fick principle, the change in CO2 content as the blood passes through the right lung is simply the rate of CO2 extraction divided by the blood flow:

Equation 1

image

Normally (see Figure 31-13A), the CO2 content of the pulmonary capillary blood would fall by only 4 mL/dL as it equilibrated with the alveolar air. However, because the rate of CO2 extraction is twice normal, the decrease in CO2content is also twice normal. Thus, the mixed-venous CO2 content must be 48 + 8 = 56 mL/dL. From the CO2 dissociation curve, we see that this CO2 content corresponds to a mixed-venous PCO2 of 51 mm Hg (lower panel of Figure 31-15A, point image). Notice that the alveolar air in the obstructed left has a PCO2 of 51 mm Hg, the same as that of the mixed-venous blood.

What happens when the blood from the hyperventilated right lung mixes with the shunted blood from the unventilated left lung? Although one might be tempted to average the two PCO2 values (i.e., 40 and 51 mm Hg), this is a mistaken instinct. Instead, one must average the two CO2 contents. As we noted above, the CO2 content of blood emerging from the right lung is 48 mL/dL. The CO2 content of blood emerging from the left lung is the same as for the mixed-venous blood we examined in the previous step, 56 mL/dL. Thus, the mixed arterial CO2 content is (48 + 56)/2 = 52 mL/dL (lower panel of Figure 31-15A, point a).

According to the CO2 dissociation curve, a CO2 content of 52 mL/dL corresponds to an arterial PCO2 of 46 mm Hg (lower panel of Figure 31-15A, point a).

In the systemic capillaries, adding 200 mL/min of CO2 to 5 liter of blood increases the CO2 content by 4 mL/dL, raising the CO2 content from 52 mL/dL (lower panel of Figure 31-15A, point a) to 56 mL/dL (lower panel of Figure 31-15A, point image). Notice that 56 mL/dL is the mixed-venous value we arrived at above in Step 5.

According to the CO2 dissociation curve, a CO2 content of 56 mL/dL corresponds to a mixed-venous PCO2 of 51 mm Hg (lower panel of Figure 31-15A, point image). This is the same value that we arrived at above in Step 5.

Thus, even with the severe VA/Q abnormality represented by shunt, the lung is once again able to expel usual 200 mL/min of CO2, but once again at a price: a high arterial PCO2 (respiratory acidosis). Because there is a imageA/[image] mismatch in this example, we expect there to be an alveolar-arterial difference for PCO2. Because the mean alveolar PCO2 is 40 mm Hg, and the arterial PCO2 is 46 mm Hg in our example, the A-a difference is 40 – 46 or –6 mm Hg.

O2 Handling The changes in O2 handling are more extreme (Figure 31-15B).

The normal right lung must deliver all the O2 required by the body, 250 mL/min. This rate of O2 abstraction from the right lung is twice normal.

Because the VA/Q ratio of the normal right lung is twice normal, and the O2 extraction rate is twice normal, we would expect the alveolar PO2 in the right lung to be the normal value of ~100 mm Hg. Put differently, because the inspired PO2 (i.e., 149 mm Hg), the alveolar PCO2 of the right lung (i.e., 40 mm Hg) and the RQ (i.e., 0.8) are all normal, the alveolar gas equation (see Equation 31–17 on p. 706) yields a normal PO2 for the right lung, ~100 mm Hg.

Of course, the PO2 in the unventilated left lung (imageA/[image] = 0) is the same as the PO2 of mixed-venous blood. However, because this air is not in direct communication with atmosphere, it does not contribute to the mean alveolar PO2of the expired air. Thus, the mean PAO2 is simply the PO2 of the alveolar air in the right lung, ~100 mm Hg, which is normal!

Because the transport of O2 across the blood-gas barrier is perfusion limited (see p. 697 in the text), the PO2 of the blood leaving the right lung is the same as the PO2 in the right lung, ~100 mm Hg. Thus, according to the O2dissociation curve (lower panel of Figure 31-15B, point c), the O2 content of this blood must be 20 mL/dL. This value is the O2 content after the right lung has added O2 at the rate of 250 mL/min.

What was the O2 content of the mixed-venous blood? According to the Fick principle, the increase in O2 content as the blood passes through the right lung is simply the rate of O2 extraction divided by the blood flow. Normally (Figure 31-13B), the O2 content would rise by only 5 mL/dL as the blood equilibrated with the alveolar air. However, because the rate of O2 extraction from the lung is twice normal, the increase in O2 content is also twice normal:

Equation 2

image

Thus, the mixed-venous O2 content must be 10 mL/dL less than the O2 content of the end-capillary blood (i.e., 20 mL/dL). The mixed-venous O2 content is thus 20 – 10 = 10 mL/dL. From the O2 dissociation curve, we see that this O2 content corresponds to a mixed-venous PO2 of 29 mm Hg (lower panel of Figure 31-15B, point image). The alveolar air in the obstructed left has a PO2 of 29, the same as that of the mixed-venous blood.

What happens when the blood from the hyperventilated right lung mixes with the shunted blood from the unventilated left lung? One must average the O2 contents of the blood emerging from the right and left lungs. As we noted above, the O2 content of blood emerging from the right lung is 20 mL/dL. The O2 content of blood emerging from the left lung is the same as for the mixed-venous blood we examined in the previous step, 10 mL/dL. Thus, the mixed arterial O2 content is (20 + 10)/2 = 15 mL/dL (lower panel of Figure 31-15B, point a).

From the O2 dissociation curve, we see that a mixed-arterial O2 content of 15 mL/dL corresponds to a PO2 of ~40 mm Hg (lower panel of Figure 31-15B, point a).

In the systemic capillaries, the tissues extract 250 mL of O2 per minute. Removing 250 mL of O2 from 5 liter of blood decreases the O2 content by 5 mL/dL. Thus, the O2 content of the blood at the end of the systemic capillaries will be 15 – 5 = 10 mL/dL. This is the same figure we arrived at in Step 5 (lower panel of Figure 31-15B, point image).

According to the O2 dissociation curve, an O2 content of 10 mL/dL corresponds to an mixed-venous PO2 of 29 mm Hg (lower panel of Figure 31-15B, point image). This is the same figure we arrived at in Step 5.

Thus, even with the severe imageA/[image] abnormality represented by shunt, the lung is able to import the usual 250 mL/min of O2, but at a price of an extremely low arterial PO2 (hypoxia).

The alveolar-arterial difference for PO2 in this example is 100 – 40 or, 60 mm Hg, indicating a imageA/[image] mismatch of considerable magnitude. In this extreme example, we entirely eliminated airflow to one lung. Less extreme examples of uneven distribution of airflow will lead to less severe degrees of respiratory acidosis and hypoxia.

Again, beware that this example, like the ones in Figure 31-13 and Figure 31-14, is highly oversimplified. Nevertheless, it is clear that even if overall imageA/[image] is normal, and even if the distribution of perfusion is normal, an uneven distribution of ventilation leads to respiratory acidosis and hypoxia. Thus, the overventilated “good” lung cannot make up for the deficit incurred by the underventilated “bad lung.” One fundamental problem is that blood with a normal gas composition from the hyperventilated good lung mixes with shunted blood with a high PCO2 and low PO2. The consequences are perhaps easiest to grasp for O2 transport. The blood leaving the normal right lung has a normal O2 content. The shunted blood leaving the unventilated left lung has a very low O2 content, which is the same as that of mixed-venous blood. Thus, the mixed-arterial blood must have a low O2 content and must be hypoxic.

A second fundamental problem is that—because of the shape of the O2-hemoglobin dissociation curve—hyperventilating a good lung cannot proportionally increase the O2 content of the blood leaving that lung. What would happen if the subject were to hyperventilate? Not much. It is true that increasing alveolar ventilation might increase the right alveolar PO2 above its starting value of 100 mm Hg. However, because the hemoglobin is already 97.5% saturated with O2 at a PO2 of 100 mm Hg, the added ventilation would do little good. The subject would remain hypoxic.

Contributed by Emile Boulpaep and Walter Boron

A–a Differences for CO2 (Robin Test)

changes in imageA/Q mismatches not only lead to an A–a difference in PO2 but also lead to an A–a difference in the CO2 partial pressure (Robin test). In our example of alveolar dead space (see Fig. 31–14A on p. 721 of the text), the A–a difference for CO2 was 40–80 or –40 mm Hg, and in our example of shunt (see Fig. 31–15A on p. 722 of the text), it was 40–46 or –6 mm Hg. A–a differences for CO2 are smaller than those for O2 both because alveolar PCO2 values are lower and because the CO2 dissociation curve is more linear. Clinicians generally do not use the PCO2 A–a difference as an index of a imageA/Q mismatch. In fact, they generally assume that the mean alveolar PCO2 is identical to the arterial PCO2, and they use this value in the alveolar gas equation (see Equation 31–17 on p. 706 of the text) for computing the mean alveolar PO2 needed to determine the A–a difference for PO2.

Contributed by Emile Boulpaep and Walter Boron

Brain Death

As stated in the text, respiratory output is often the last brain function to be lost in comatose patients, in which case its cessation marks the onset of brain death. In the United States, the legal definition of “brain death” is the irreversible loss of clinical function of the entire brain, which does not include the spinal cord. Brain death is legally equivalent to other forms of death. The declaration of brain death requires a careful neurological exam testing all reflexes mediated by cranial nerves, evaluating the patient for evidence of behaviors that require brain function, and ruling out any reversible cause such as hypothermia or drug overdose.

Contributed by George Richerson

Experimental Preparations for Studying the Neural Control of Ventilation

One of the most difficult challenges in neurobiology today is to understand how neurons function within neural networks to generate normal behaviors. Although it is one of the most primitive in the mammalian brain, the neural network controlling respiration is still highly complex. The experimental preparations and techniques used to study respiration are also shared by neuroscientists studying other neural networks and include the following:

Intact, awake, behaving animals and humans permit direct correlation of results with behavior. Investigators primarily use this approach to measure body movements, lung volume changes, or electrical activity in muscles or peripheral nerves.

Anesthetized, paralyzed, mechanically ventilated animals permit better control of experimental variables and more intensive surgical techniques. Paralysis reduces movement of the brain so that individual neurons can be studied using extracellular recordings of single neurons.

The whole brain or large portions of the brain can be isolated in vitro by perfusing the brain via the arterial system or by removing the spinal cord and lower brainstem of a neonatal rat from the body and keeping them alive submerged in artificial cerebrospinal fluid (CSF). Because the brainstem circuitry is intact, a respiratory rhythm may still be produced. Elimination of the lungs and heart results in reduction of movement, making intracellular recording easier.

Brain slices are prepared by cutting the medulla into thin slices and are kept alive in artificial CSF. These slices can be used to study individual neurons in relative isolation, for example, with intracellular microelectrodes or patch-clamp recordings. Simple synaptic connections, limited to a restricted subset of that present in vivo, can also be studied.

Dissociated neurons can be studied acutely or after days to weeks in tissue culture. These approaches isolate neurons from synaptic input and permit highly stable recordings so that their biophysical properties can be studied with a high degree of precision and control.

These approaches to studying neural networks are at the same time very powerful and very limited. Results can vary depending on the species studied, on age, and on whether the subject is awake or anesthetized. Each experimental preparation has advantages for answering specific questions, as well as disadvantages. For example, it is not possible to define the properties of individual neurons while they are still part of a complex neural network. On the other hand, the respiratory rhythm is usually no longer present in “reduced” preparations, making it difficult to know if a given neuron is actually involved in respiratory control. All of these approaches suffer, more or less, from effects due to measurement of their responses—the biological equivalent of the Heisenberg uncertainty principle. There is ischemia in the center of en bloc tissue, traumatic damage of neurons in brain slices, de-differentiation of some neuronal properties in culture, and effects of anesthetics and prolonged surgery in vivo. For this reason, it is important that each result be verified and each theory be tested using many of these approaches, instead of relying on only one.

Contributed by George Richerson

Evolution of the Respiratory Central Pattern Generator

The medulla actually has two identical respiratory central pattern generators (CPGs), one on each side. All of the elements of the respiratory controller—drive inputs, sensory feedback, respiratory-related neurons, and motor neurons—are bilateral. Thus, after a midsagittal transection, each side of the medulla generates an independent respiratory rhythm. As noted in the textbook, the location of the respiratory CPG is not universally agreed upon.

The respiratory CPG probably evolved in fish, where blood–gas exchange across the gills requires pumping by branchial structures, thus explaining why the CPG is located in the medulla. CPGs generate all repetitive motor activities (see p. 414 of the text). In invertebrates, these include swimming in sea slugs and movements of the stomach in lobsters. The mechanisms of rhythm generation discovered in these systems have led to establishment of general principles that have been valuable in promoting understanding of CPGs in mammals.

Contributed by George Richerson

Role of the Pons in the Control of Ventilation

See the special issue of Respiratory Physiology and Neurobiology. The following is the lead/introductory article.

REFERENCE

McCrimmon DR, Milsom WK, and Alheid GF: The rhombencephalon and breathing: A view from the pons. Respir Physiol Neurobiol 143:103–104, 2004.

Contributed by George Richerson

Robert Gesell

See the following reference:

REFERENCE

Gesell R: Respiration and its adjustments. Annu Rev Physiol 1:185–216, 1939.

Role of the Pons in the Control of Ventilation

See the special issue of Respiratory Physiology and Neurobiology. The following is the lead/introductory article.

REFERENCE

McCrimmon DR, Milsom WK, and Alheid GF: The rhombencephalon and breathing: A view from the pons. Respir Physiol Neurobiol 143:103–104, 2004.

Contributed by George Richerson

DRG Neurons

For example, an interneuron in the dorsal respiratory group (DRG) may synapse on a DRG premotor neuron, which, in turn, may descend into the spinal cord and reach one of the paired phrenic motor nuclei in the ventral horn of the spinal cord. There, the premotor neuron synapses on the cell bodies of phrenic motor neurons, whose axons follow the phrenic nerve to the diaphragm.

Contributed by George Richerson

The Ventral Respiratory Group

Aside from input from muscle-spindle fibers (see p. 405 of the text), which provide feedback to pharyngeal and laryngeal motor neurons, the ventral respiratory group (VRG) does not receive any monosynaptic sensory input.

Rostral VRG. Within the nucleus retrofacialis is a region known as the Bötzinger complex. This region is the rostral VRG, which contains primarily expiratory interneurons projecting to other respiratory nuclei, including the caudal VRG.

Intermediate VRG. Within and near the nucleus ambiguus and the nucleus para-ambigualis is the intermediate VRG. The majority of respiratory-related neurons in the intermediate VRG are inspiratory. The nucleus ambiguuscontains somatic motor neurons that leave the medulla via CN IX and X to supply the larynx and pharynx and prevent collapse of the upper airways during inspiration. In addition, this nucleus contains parasympathetic preganglionic neurons that supply airways in the lung and other structures via CN X. Finally, the nucleus ambiguus contains some motor neurons with respiratory-related activity that send axons out the trigeminal nerve (CN V), presumably for opening the mouth; the facial nerve (CN VII) for flaring the nostrils; and the accessory nerve (CN XI) to activate other accessory muscles of respiration during strong inspirations.

The nucleus para-ambigualis surrounds the nucleus ambiguus and contains premotor neurons that project to inspiratory motor neurons in the spinal cord and interneurons that have local connections to other neurons of the medulla. Like some neurons in the dorsal respiratory group (DRG), the inspiratory premotor neurons in the nucleus para-ambigualis drive primary muscles of inspiration. However, unlike neurons in the DRG, the inspiratory premotor neurons in the nucleus para-ambigualis also drive accessory muscles.

The pre-Bötzinger complex (see p. 731 of the text) is in the rostral portion of the intermediate VRG. It is not yet well-defined anatomically but instead is defined by the electrophysiological properties of its component neurons, which continue to produce bursts of respiratory activity in brain slices. The anatomical location roughly corresponds to a region slightly ventral and lateral to the nucleus ambiguus just caudal to the Bötzinger complex. The pre-Bötzinger complex contains inspiratory neurons that include local interneurons and premotor neurons. There is evidence that this region may be the respiratory central pattern generator.

Caudal VRG. Within the nucleus retroambigualis is the caudal portion of the VRG, which contains mostly expiratory premotor neurons. Many of these travel down the spinal cord to synapse on motor neurons that innervate muscles of expiration, such as the internal intercostal and abdominal muscles. Because a quiet expiration is a passive event, these are accessory muscles of expiration. Thus, the premotor neurons in the caudal VRG are normally silent and become active only during forced expirations. These premotor neurons appear to receive their stimulatory drive from neurons in the rostral VRG.

Contributed by George Richerson

Origin of the Terms Bötzinger Complex and Pre-Bötzinger Complex

The Bötzinger complex—the most rostral portion of the ventral respiratory group—is not named after a scientist or even a grateful patient. Rather, the Bötzinger complex received its name from Professor Jack Feldman (currently of UCLA) while he was at a banquet for a scientific meeting in Hirschhorn, Germany, in 1978.

Feldman had discovered this region and reported on it at a meeting in Stockholm the previous year—but had not published the work. At the Hirschhorn meeting, a colleague who had been at the Stockholm meeting presented some new data based on Feldman’s previous presentation. Worrying that this forgotten corner of the medulla would go unnamed—or, worse yet, be named after the wrong person—Feldman proposed a toast in which he suggested that this anatomical area be named after some aspect of the Hirschhorn meeting. So Professor Feldman picked up the bottle of wine that happened to be at the table—Bötzinger (a rather unremarkable white wine)—and the rest is neurophysiological history … the Bötzinger complex.

Twelve years later, Feldman and his colleagues identified an area slightly caudal to the Bötzinger complex. This area appeared to be the source of the respiratory rhythm in the preparation with which they were working. The group thought that the logical name—the post-Bötzinger complex—would connote less importance to the region than the authors thought it deserved. So, they chose the anatomically incorrect pre-Bötzinger complex. The reviewers of the subsequent paper seemed not to notice, and the name stuck.

REFERENCE:

1. Smith JC, Ellenberger HH, Ballanyiy K, Richter DW, Feldman JL: Pre-Bötzinger complex: a brainstem region that may generate respiratory rhythm in mammals, Science 254:726-729, 1991.

Contributed by Emile Boulpaep and Walter Boron

The Ventral Respiratory Group

Aside from input from muscle-spindle fibers (see p. 405 of the text), which provide feedback to pharyngeal and laryngeal motor neurons, the ventral respiratory group (VRG) does not receive any monosynaptic sensory input.

Rostral VRG. Within the nucleus retrofacialis is a region known as the Bötzinger complex. This region is the rostral VRG, which contains primarily expiratory interneurons projecting to other respiratory nuclei, including the caudal VRG.

Intermediate VRG. Within and near the nucleus ambiguus and the nucleus para-ambigualis is the intermediate VRG. The majority of respiratory-related neurons in the intermediate VRG are inspiratory. The nucleus ambiguuscontains somatic motor neurons that leave the medulla via CN IX and X to supply the larynx and pharynx and prevent collapse of the upper airways during inspiration. In addition, this nucleus contains parasympathetic preganglionic neurons that supply airways in the lung and other structures via CN X. Finally, the nucleus ambiguus contains some motor neurons with respiratory-related activity that send axons out the trigeminal nerve (CN V), presumably for opening the mouth; the facial nerve (CN VII) for flaring the nostrils; and the accessory nerve (CN XI) to activate other accessory muscles of respiration during strong inspirations.

The nucleus para-ambigualis surrounds the nucleus ambiguus and contains premotor neurons that project to inspiratory motor neurons in the spinal cord and interneurons that have local connections to other neurons of the medulla. Like some neurons in the dorsal respiratory group (DRG), the inspiratory premotor neurons in the nucleus para-ambigualis drive primary muscles of inspiration. However, unlike neurons in the DRG, the inspiratory premotor neurons in the nucleus para-ambigualis also drive accessory muscles.

The pre-Bötzinger complex (see p. 731 of the text) is in the rostral portion of the intermediate VRG. It is not yet well-defined anatomically but instead is defined by the electrophysiological properties of its component neurons, which continue to produce bursts of respiratory activity in brain slices. The anatomical location roughly corresponds to a region slightly ventral and lateral to the nucleus ambiguus just caudal to the Bötzinger complex. The pre-Bötzinger complex contains inspiratory neurons that include local interneurons and premotor neurons. There is evidence that this region may be the respiratory central pattern generator.

Caudal VRG. Within the nucleus retroambigualis is the caudal portion of the VRG, which contains mostly expiratory premotor neurons. Many of these travel down the spinal cord to synapse on motor neurons that innervate muscles of expiration, such as the internal intercostal and abdominal muscles. Because a quiet expiration is a passive event, these are accessory muscles of expiration. Thus, the premotor neurons in the caudal VRG are normally silent and become active only during forced expirations. These premotor neurons appear to receive their stimulatory drive from neurons in the rostral VRG.

Contributed by George Richerson

Neural Activity during the Respiratory Cycle

Some respiratory-related neurons (RRNs) fire mostly during early inspiration, others evenly throughout in inspiration, and still others during late expiration, or evenly throughout expiration. Some fire during both inspiration and expiration, but with a peak of activity during one of the two phases of ventilation.

The figure that accompanies this Web Note is an expansion of Figure 32-5C on p. 731 of the text. The figure that accompanies this Web Note includes four additional panels, E–I. Figure 32-5E on p. 731 is the same as panel H in the accompanying figure.

As shown in Figure 32-5C on p. 731 of the text—as well as panel°C of the accompanying figure—the activity of the phrenic nerve varies in a characteristic way during these three phases. During the inspiratory phase, phrenic nerve output to the diaphragm gradually increases in activity over 0.5–2 s, followed by a precipitous decline at the onset of expiration. The ramp increase in activity helps to ensure a smooth increase in lung volume. Although not evident in panel C, during expiratory phase 1 (or the postinspiratory phase), there may be a paradoxical burst of activity in the phrenic nerve. This burst offsets the large elastic recoil of the lungs at the end of inspiration. This elastic recoil would tend to collapse the lungs rapidly if the tone of the inspiratory muscles decreased too abruptly.

During expiratory phase 2, the phrenic nerve is inactive. During a quiet expiration, which is normally a passive event, the accessory muscles of expiration are also inactive. However, during a forced expiration, the accessory muscles of expiration (e.g., internal intercostals and abdominal muscles) become active during E2.

Underlying the activity of the phrenic nerve—and the other motor nerves supplying the muscles of inspiration and expiration—is a spectrum of firing patterns of different RRNs throughout the medulla, some of which are shown in panels D–I in the accompanying figure. RRNs can be broadly classified as inspiratory or expiratory, but for each class there are many subtypes of RRNs, each presumably with different functions in generating and shaping the “respiratory output”—that is, the activity of the nerves to each of the respiratory muscles.

The tracings in the accompanying figure are idealized drawings. These recordings would have been made in a preparation such as the brain of a cat with an extracellular electrode recording the activity of a particular RRN. A cuff electrode on the phrenic nerve would have simultaneously recorded the activity of the phrenic nerve. All the panels in the accompanying figure refer to the condition of eupnea. The following letters refer to the panel designation:

A. Lung volume. Note that inspiration is shorter than expiration.

B. Airflow. Airflow into the lung is represented by a downward deflection in the record. Note that the airflow is zero when lung volume is not changing (e.g., at the transition from inspiration to expiration).

C. Phrenic nerve activity. Typical waveform of phrenic nerve output during eupnea.

D. An RRN with inspiratory ramp activity. Note that the neuron fires during inspiration with a gradually increasing firing rate.

E. An RRN with early burst activity. The neuron fires during early inspiration and then with a decrementing firing rate.

F. An RRN with constant inspiratory activity. The neuron fires with a relatively constant rate during inspiration.

G. An RRN with late-onset inspiratory activity. The neuron is silent except for a short burst late in inspiration. This neuron could be part of an “off switch” that terminates inspiration.

H. An RRN with early expiratory activity. The neuron fires during the first expiratory phase or E1, immediately after inspiration (postinspiratory), and then the firing rate decrements.

I. An RRN with expiratory ramp activity. The firing rate gradually increases during the second expiratory phase or E2.

The various groups of respiratory neurons in the brainstem consist of networks of neurons with firing patterns, such as those outlined in the previous passage. Although the precise role that each type of RRN plays in generating and shaping the respiratory motor output is unknown, it is instructive to consider some of the neurons that make up, for example, the dorsal respiratory group (DRG). In the DRG, most RRNs (>90%) are inspiratory, and three of the most common of these are known as Iα, Iβ, and P neurons.

I β neurons (the I stands for “inspiratory”) fire with a “ramp” pattern (see part D), presumably because they are driven by the “central inspiratory activity” that drives inspiration. In addition, they receive sensory input directly from pulmonary stretch receptors; lung inflation stimulates Iβ neurons. Many I neurons do not send their axons to the spinal cord but instead are interneurons whose axons synapse locally within the DRG. Thus, Iβ neurons probably integrate sensory information from pulmonary stretch receptors and may play a key role in some respiratory reflexes, such as the Hering–Breuer reflex (see p. 731 of the text).

P neurons, unlike the Iβ neurons, are not driven by the central inspiratory activity. However, they do receive direct input from pulmonary stretch receptors so that their activity simply tracks changes in lung volume. Thus, like the Iβ neurons, the P neurons presumably are important for sensory integration.

Iα neurons, like the Iβ neurons, fire with a ramp pattern (see part D). Input from other DRG neurons tends to inhibit Iα neurons with increases in lung inflation. Iα neurons are premotor neurons; their axons synapse on phrenic motor neurons and external intercostal motor neurons. That is, the firing of an Iα neuron indirectly tends to cause a muscle of inspiration to contract. Thus, it is not surprising that the firing pattern of the Iα neurons is similar to that of the phrenic nerve. Collaterals of Iα neurons also branch off and synapse on neurons in the ventral respiratory group.

image

Neural activity during the respiratory cycle. The activity of respiratory-related neurons in the medulla (examples of which are shown in D–I) leads to the phasic activity of the phrenic nerve (C) and other respiratory nerves, which produces airflow (B), causing lung volume to change (A). ENG, electroneurogram; Exp, expiration; FRC, functional residual capacity; Insp, inspiration; TV, tidal volume; Vm, membrane potential.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

Properties of the DRG versus VRG

The table that accompanies this Web Note is an expansion of Table 32–2 on p. 731 of the text.

Properties of the DRG and VRG

 

VRG

Property

DRG

Rostral

Intermediate

Caudal

Location

Dorsal medulla

Midway between dorsal and ventral surfaces of medulla

Major component

Nucleus tractus solitarius (NTS)

Nucleus retrofacialis (NRF) or Bötzinger complex

Pre-Bötzinger complex, nucleus ambiguus (NA), and nucleus para-ambigualis (NPA)

Nucleus retroambigualis (NRA)

Dominant activity

Inspiratory

Expiratory

Inspiratory

Expiratory

Major input

Sensory via CN IX and X

Rostral VRG

Major output

(a) Pre-motor neurons image spinal cord image primary muscles of inspiration

Interneurons image DRG and caudal VRG

(a) Motor (via CN IX and X) image accessory muscles of inspiration

Pre-motor image spinal cord image accessory muscles of expiration

 

(b) Interneurons image VRG

 

(b) Pre-motor image spinal cord image primary and accessory muscles of inspiration

 

DRG, dorsal respiratory group; VRG, ventral respiratory group.

Origin of the Terms Bötzinger Complex and Pre-Bötzinger Complex

The Bötzinger complex—the most rostral portion of the ventral respiratory group—is not named after a scientist or even a grateful patient. Rather, the Bötzinger complex received its name from Professor Jack Feldman (currently of UCLA) while he was at a banquet for a scientific meeting in Hirschhorn, Germany, in 1978.

Feldman had discovered this region and reported on it at a meeting in Stockholm the previous year—but had not published the work. At the Hirschhorn meeting, a colleague who had been at the Stockholm meeting presented some new data based on Feldman’s previous presentation. Worrying that this forgotten corner of the medulla would go unnamed—or, worse yet, be named after the wrong person—Feldman proposed a toast in which he suggested that this anatomical area be named after some aspect of the Hirschhorn meeting. So Professor Feldman picked up the bottle of wine that happened to be at the table—Bötzinger (a rather unremarkable white wine)—and the rest is neurophysiological history … the Bötzinger complex.

Twelve years later, Feldman and his colleagues identified an area slightly caudal to the Bötzinger complex. This area appeared to be the source of the respiratory rhythm in the preparation with which they were working. The group thought that the logical name—the post-Bötzinger complex—would connote less importance to the region than the authors thought it deserved. So, they chose the anatomically incorrect pre-Bötzinger complex. The reviewers of the subsequent paper seemed not to notice, and the name stuck.

REFERENCE:

1. Smith JC, Ellenberger HH, Ballanyiy K, Richter DW, Feldman JL: Pre-Bötzinger complex: a brainstem region that may generate respiratory rhythm in mammals, Science 254:726-729, 1991.

Contributed by Emile Boulpaep and Walter Boron

Neural Activity during the Respiratory Cycle

Some respiratory-related neurons (RRNs) fire mostly during early inspiration, others evenly throughout in inspiration, and still others during late expiration, or evenly throughout expiration. Some fire during both inspiration and expiration, but with a peak of activity during one of the two phases of ventilation.

The figure that accompanies this Web Note is an expansion of Figure 32-5C on p. 731 of the text. The figure that accompanies this Web Note includes four additional panels, E–I. Figure 32-5E on p. 731 is the same as panel H in the accompanying figure.

As shown in Figure 32-5C on p. 731 of the text—as well as panel°C of the accompanying figure—the activity of the phrenic nerve varies in a characteristic way during these three phases. During the inspiratory phase, phrenic nerve output to the diaphragm gradually increases in activity over 0.5–2 s, followed by a precipitous decline at the onset of expiration. The ramp increase in activity helps to ensure a smooth increase in lung volume. Although not evident in panel C, during expiratory phase 1 (or the postinspiratory phase), there may be a paradoxical burst of activity in the phrenic nerve. This burst offsets the large elastic recoil of the lungs at the end of inspiration. This elastic recoil would tend to collapse the lungs rapidly if the tone of the inspiratory muscles decreased too abruptly.

During expiratory phase 2, the phrenic nerve is inactive. During a quiet expiration, which is normally a passive event, the accessory muscles of expiration are also inactive. However, during a forced expiration, the accessory muscles of expiration (e.g., internal intercostals and abdominal muscles) become active during E2.

Underlying the activity of the phrenic nerve—and the other motor nerves supplying the muscles of inspiration and expiration—is a spectrum of firing patterns of different RRNs throughout the medulla, some of which are shown in panels D–I in the accompanying figure. RRNs can be broadly classified as inspiratory or expiratory, but for each class there are many subtypes of RRNs, each presumably with different functions in generating and shaping the “respiratory output”—that is, the activity of the nerves to each of the respiratory muscles.

The tracings in the accompanying figure are idealized drawings. These recordings would have been made in a preparation such as the brain of a cat with an extracellular electrode recording the activity of a particular RRN. A cuff electrode on the phrenic nerve would have simultaneously recorded the activity of the phrenic nerve. All the panels in the accompanying figure refer to the condition of eupnea. The following letters refer to the panel designation:

A. Lung volume. Note that inspiration is shorter than expiration.

B. Airflow. Airflow into the lung is represented by a downward deflection in the record. Note that the airflow is zero when lung volume is not changing (e.g., at the transition from inspiration to expiration).

C. Phrenic nerve activity. Typical waveform of phrenic nerve output during eupnea.

D. An RRN with inspiratory ramp activity. Note that the neuron fires during inspiration with a gradually increasing firing rate.

E. An RRN with early burst activity. The neuron fires during early inspiration and then with a decrementing firing rate.

F. An RRN with constant inspiratory activity. The neuron fires with a relatively constant rate during inspiration.

G. An RRN with late-onset inspiratory activity. The neuron is silent except for a short burst late in inspiration. This neuron could be part of an “off switch” that terminates inspiration.

H. An RRN with early expiratory activity. The neuron fires during the first expiratory phase or E1, immediately after inspiration (postinspiratory), and then the firing rate decrements.

I. An RRN with expiratory ramp activity. The firing rate gradually increases during the second expiratory phase or E2.

The various groups of respiratory neurons in the brainstem consist of networks of neurons with firing patterns, such as those outlined in the previous passage. Although the precise role that each type of RRN plays in generating and shaping the respiratory motor output is unknown, it is instructive to consider some of the neurons that make up, for example, the dorsal respiratory group (DRG). In the DRG, most RRNs (>90%) are inspiratory, and three of the most common of these are known as Iα, Iβ, and P neurons.

Iβ neurons (the I stands for “inspiratory”) fire with a “ramp” pattern (see panel D), presumably because they are driven by the “central inspiratory activity” that drives inspiration. In addition, they receive sensory input directly from pulmonary stretch receptors; lung inflation stimulates Iβ neurons. Many Iβ neurons do not send their axons to the spinal cord but instead are interneurons whose axons synapse locally within the DRG. Thus, Iβ neurons probably integrate sensory information from pulmonary stretch receptors and may play a key role in some respiratory reflexes, such as the Hering–Breuer reflex (see p. 731 of the text).

P neurons, unlike the Iβ neurons, are not driven by the central inspiratory activity. However, they do receive direct input from pulmonary stretch receptors so that their activity simply tracks changes in lung volume. Thus, like the Iβ neurons, the P neurons presumably are important for sensory integration.

Iα neurons, like the Iβ neurons, fire with a ramp pattern (see panel D). Input from other DRG neurons tends to inhibit Ie neurons with increases in lung inflation. Iα neurons are premotor neurons; their axons synapse on phrenic motor neurons and external intercostal motor neurons. That is, the firing of an Iα neuron indirectly tends to cause a muscle of inspiration to contract. Thus, it is not surprising that the firing pattern of the Iα neurons is similar to that of the phrenic nerve. Collaterals of Iα neurons also branch off and synapse on neurons in the ventral respiratory group.

image

Neural activity during the respiratory cycle. The activity of respiratory-related neurons in the medulla (examples of which are shown in panels D–I) leads to the phasic activity of the phrenic nerve (C) and other respiratory nerves, which produces airflow (B), causing lung volume to change (A). ENG, electroneurogram; Exp, expiration; FRC, functional residual capacity; Insp, inspiration; TV, tidal volume; Vm, membrane potential.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

DRG Neuron with Ca2+-Activated K+ Current

A second type of neuron in the DRG has a large amount of Ca2+-activated K+ current (see p. 203 in the text). After the neuron fires several action potentials, the accumulation of Ca2+ inside the cell slowly activates this KCa channel, hyperpolarizing the cell and limiting the firing rate. Thus, suddenly depolarizing such a neuron triggers a burst of firing that tapers off as KCa channels activate. The decrease in firing rate, called “spike-frequency adaptation,” mimics the early burst activity of some RRNs (see Web Note 0731c, Neural Activity during the Respiratory Cycle). Like the A-type current, KCa channels could cause these neurons to have an appropriate firing pattern, even in the absence of rigidly patterned synaptic input.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

Patterned input

Independent of intrinsic membrane properties, the patterned synaptic input that many RRNs receive from other respiratory neurons can also influence the firing pattern. For example, the early-burst activity of the neuron in the upper panel of Fig 32-6 parallels the strong excitatory synaptic input that the neuron receives during the early part of inspiration, as well as the inhibitory synaptic input that it receives during expiration.

Some firing patterns of RRNs result in part from inhibitory connections between neurons. For example, the early-burst inspiratory neurons in the preceding paragraph appear to inhibit late-onset inspiratory neurons (see WebNote Revised2e--Neural Activity during the Respiratory Cycle, specifically panel G in the accompanying figure), and vice versa. As a result of this reciprocal inhibition, only one of the two subtypes of inspiratory neurons can be maximally active at any one time.

In addition to patterned synaptic input from RRNs, respiratory neurons also receive input from other neuronal systems, allowing the respiratory system to respond appropriately to challenges and to be integrated with many different brain functions. Some of the neurotransmitters released onto respiratory neurons—both by RRNs and by neurons from other regions of the CNS—are listed in Table 1.

In summary, both intrinsic membrane properties and patterned synaptic input can cause RRNs to fire in their characteristic patterns. In theory, either of these properties might be sufficient to ensure that these neurons have the right firing pattern. The presence of both properties illustrates a general concept that appears to be important in critical biologic systems: redundancy. For those body systems critical for life support, use of multiple mechanisms may ensure that normal functioning will occur despite severe perturbations.

Table 1

NEUROTRANSMITTERS RELEASED ONTO RESPIRATORY NEURONS

Glutamate

GABA (gamma aminobutyric acid)

Serotonin (5-HT, 5-hydroxytryptamine)

Norepinephrine

Dopamine

Acetylcholine

Thyrotropin-releasing hormone (TRH)

Substance P

Corticotropin-releasing hormone (CRH)

Endorphins

Enkephalins

Contributed by George Richerson

The Central Pattern Generator as an “Emergent Property”

One of the network models includes three key elements for generating normal inspiratory output: (1) central inspiratory activity, (2) an integrator, and (3) an inspiratory off switch. A group of neurons in the DRG would generate “central inspiratory activity” that would in turn cause a steady increase in firing of premotor neurons such as the Iα neurons (discussed in Web Note 0731c, Neural Activity during the Respiratory Cycle), which drive inspiratory motor neurons, and the Iβ interneurons (discussed in Web Note 0731c, Neural Activity during the Respiratory Cycle). The Iβ interneurons also receive input from the pulmonary stretch receptors. Thus, the I interneurons “integrate” information from both the command to the inspiratory muscles and the resultant lung inflation. When the integrator determines that the inspiration has proceeded far enough, it triggers the inspiratory “off-switch” neurons, the late-onset inspiratory neurons in panel G in Web Note 0731c, Neural Activity during the Respiratory Cycle. According to the model, the activated inspiratory off-switch neurons cause inspiration to stop by resetting central inspiratory activity, allowing expiration to take over. Expiration is passive and ends when central inspiratory activity builds up enough to initiate firing of inspiratory neurons again.

According to the model, neurons of the so-called pneumotaxic center in the pons can also trigger the inspiratory off switch. This hypothesis fits with experimental data because interrupting input from both the pneumotaxic center and the pulmonary stretch receptors (i.e., input carried by vagal afferents) results in loss of the off switch and thus in apneusis (see p. 727 of the text).

One of the difficulties with network models is that the exact identity of each of the components of the model is not certain.

Contributed by George Richerson, Emile Boulpaep and Walter Boron

Site of the Respiratory CPG

Given the long history of the field and the many investigators working on different aspects of the problem, any conclusion about the precise location of a respiratory central pattern generator (CPG) is bound to be controversial.

In the case of the pre-Bötzinger complex (see p. 731 of the text), some critics believe that the pattern of respiratory output generated resembles gasping. In addition, the conditions normally used to study the activity are artificial. Also, destroying the pre-Bötzinger complex in adult rats leads to ataxic breathing and yet the animals survive. However, most investigators agree that the pre-Bötzinger complex plays an important role in breathing, and defining the mechanisms of rhythm generation in the pre-Bötzinger complex will be important for understanding normal breathing. For example, it is now clear that there are pacemaker neurons within the pre-Bötzinger complex. Some of these pacemaker neurons are inhibited by hypoxia, whereas others are unaffected. This observation provides a possible explanation for why the pattern of breathing can change from eupnea to gasping when the oxygen levels in the brain become low, such as from cardiac arrest.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

Corneille Jean François Heymans

Corneille Jean François Heymans (1892–1968) was born in Ghent, Belgium. He obtained his doctorate in medicine at the University of Ghent in 1920. Afterwards, he worked with E. Gley at the Collège de France in Paris, M. Arthus in Lausanne, H. Meyer in Vienna, E. H. Starling at University College London, and C. F. Wiggers at Western Reserve University in Cleveland. In 1922, Heymans returned to Ghent to become Lecturer in Pharmacodynamics, and in 1930 he succeed his father as Professor of Pharmacology.

For his work on the carotid and aortic bodies and their role in the regulation of respiration, he received the 1938 Nobel Prize in Physiology or Medicine.

REFERENCE

http://nobelprize.org/nobel_prizes/medicine/laureates/1938

Contributed by Walter Boron

The Glomus Cell

Curiously, the sensory endings of the carotid sinus nerve also contain vesicles, so the synapse formed with glomus cells may be bidirectional. The function of this synapse from the carotid sinus nerve onto the glomus cells is unknown.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

Peripheral Chemoreceptors

Recent progress on the physiology of glomus cells has largely been a result of the ability to study glomus cells in culture and in the isolated carotid body in vitro.

Regarding the model of Figure 32-11 on p. 738 of the text, some controversy—which may reflect species differences—exists about which K+ channel is the target of hypoxia. Some evidence favors the charybdotoxin-sensitive, Ca2+-activated K+ channel. Other data point to a Ca2+-insensitive, voltage-gated K+ channel and a voltage-insensitive “resting” K+ channel.

Although one report (Williams et al., 2004) suggested that hemoxygenase-2 (HO-2) is a universal O2 sensor, the results of a later study (Ortega-Sáenz et al., 2006) showed that mice deficient in HO-2 have a normal ability to sense decrease in [O2].

REFERENCE

Hoshi T, and Lahiri S: Oxygen sensing: It’s a gas! Science 306:2050–2051, 2004.

Ortega-Sáenz P, Pascual A, Gómez-Díaz R, and López-Barneo J: Acute oxygen sensing in heme oxygenase-2 null mice. Proc J Gen Physiol 128:405–411, 2006.

Williams SEJ, Wootton P, Mason HS, Bould J, Iles DE, Riccardi D, Peers C, and Kemp PJ: Hemoxygenase-2 is an oxygen sensor for a calcium-sensitive potassium channel. Science 306:2093–2097, 2004.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

CO2-Induced pH Changes in CSF and BECF

As noted in the text, because the cerebrospinal fluid (CSF) and brain extracellular fluid (BECF) have a lower protein content than either blood plasma or whole blood, the buffering power of the CSF and BECF is much lower than that of blood. Thus, increases in PCO2—initial at least—cause larger pH decreases in the CSF and BECF than in blood. Over time, as summarized on p. 738 of the text, the choroid plexus and perhaps the blood–brain barrier increase the active transport of HCO3 into the CSF and BECF. This transport represents a metabolic compensation to respiratory acidosis (see pp. 665–666 of the text). During this compensation, the pH values of the CSF and BECF gradually rise, and thus the size of the net CO2-induced acidification gradually becomes smaller.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

Central Chemoreceptor

If the blood–brain barrier is so permeable to CO2—and if the pH change in the brain extracellular fluid is so large and so fast—why does it take 5–10 min to produce a maximal ventilatory response to hypercapnia? The delay may be due to (1) a slower change in pH at the actual (i.e., unknown) location of chemosensation, (2) a delay in the chemotransduction events, or (3) a delay in the response of the central pattern generator or respiratory motor neurons to input from the central chemoreceptor neurons.

Studies on brain slices and cultured cells show that acidosis stimulates neurons in many brainstem nuclei. These include the ventrolateral medulla discussed in the text, the medullary raphe (see Fig. 32–13B on p. 740 of the text), the nucleus ambiguus, and the nucleus tractus solitarius (NTS)—all in the medulla—as well as the locus coeruleus and the hypothalamus. Experiments in the laboratory of Eugene Nattie have provided evidence that at least some of these acidosis-stimulated neurons are in fact respiratory chemoreceptors. In intact animals, microinjecting acetazolamide into these regions increases ventilation. Acetazolamide blocks carbonic anhydrase, the enzyme that catalyzes the hydration of CO2 to H+ and HCO3 (see Web Note 0654b, Carbonic Anhydrases). Presumably, this blockade produces a localized region of acidosis that activates nearby chemosensitive neurons. Indeed, acetazolamide microinjections suggest that chemosensitive areas include the ventrolateral medulla, medullary raphe, the nucleus ambiguus, the NTS, and locus coeruleus.

It remains unclear how important the aforementioned regions are to normal respiratory chemoreception. If they all are central chemoreceptors, then these multiple sensors may be another example of redundancy in a critical system. Alternatively, instead of all being involved in the response to CO2 under normal conditions in adults, some of these neurons may come into play only in special circumstances, such as during severe acid–base disturbances; when one is asleep, or during a particular time during development of an infant.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

Medullary Raphé Neurons

Panel A in the figure that accompanies this Web Note shows how an increase in PCO2 (respiratory acidosis) raises the firing rate of a serotonergic neuron. Panel B in the accompanying figure shows how the same increase in PCO2lowers the firing rate of a GABAergic neuron.

image

The figure shows the results of patch pipette recordings of neurons cultured from the medullary raphe of rats. Those that are stimulated by acidosis are serotonergic, and those that are inhibited are GABAergic. (Data from Wang W, Pizzonia JH, and Richerson GB: Chemosensitivity of rat medullary raphe neurones in primary tissues culture. J Physiol 511:433–450, 1998.).

Contributed by George Richerson

Sudden Infant Death Syndrome

Sudden infant death syndrome (SIDS) is defined as the sudden death of an infant younger than 1 year of age that remains unexplained after a complete clinical review, autopsy, and death scene investigation. SIDS is the leading cause of post-neonatal infant death in developed countries, causing six deaths each day in the United States alone. SIDS usually occurs during sleep in infants who were previously thought to be healthy. The consensus is that the majority of SIDS cases are due to abnormalities of breathing and arousal in response to high CO2 and/or low O2. When a vulnerable infant is exposed to an exogenous stressor, such as covering of the mouth by a blanket, he or she is unable to respond appropriately. Consistent with this explanation, the incidence of SIDS has decreased by 50% following the recommendation that mothers lie babies on their backs when putting them to sleep (the “Back to Sleep” campaign). Although the pathophysiology of SIDS remains unknown, work has revealed a number of abnormalities of serotonin neurons in the medulla that may cause an infant to be vulnerable (Paterson et al., 2006). These abnormalities seem to involve a delay in maturation of these neurons due to environmental and/or genetic factors. Because serotonin neurons are central respiratory chemoreceptors (Richerson, 2004) and are also involved in cardiovascular and thermoregulatory control, as well as regulation of sleep and arousal, a delay in their normal maturation could explain SIDS. Ongoing work is aimed at identifying those infants with serotonin neuron defects before they die and finding a treatment to prevent SIDS in those infants.

REFERENCE

Paterson DS, et al.: Multiple serotonergic brainstem abnormalities in sudden infant death syndrome. JAMA 296:2124–2132, 2006.

Richerson GB: Serotonin neurons as CO2 sensors that maintain pH homeostasis. Nature Rev Neurosci 5:449–461, 2004.

Contributed by George Richerson

Slowly Adapting Pulmonary Stretch Receptors

Within the tracheobronchial tree are mechanoreceptors that detect changes in lung volume by sensing stretch of the airway walls. These are pulmonary stretch receptors (PSRs). One type of PSR responds to stretch with a sudden increase in firing that then decays (i.e., “adapts”) very slowly over time. These slowly adapting PSRs are located from the extrathoracic trachea down through the intrapulmonary bronchi; their afferent axons are myelinated. Except for hypocapnia, chemical stimuli do not selectively excite these receptors, whose function may be partly to inform the brain about lung volume to optimize respiratory output.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

Rapidly Adapting Pulmonary Stretch Receptors

In addition to the slowly adapting pulmonary stretch receptors (PSRs) discussed in Web Note 0743a, Slowly Adapting Pulmonary Stretch Receptors, the lung has PSRs that respond to inflation at a higher volume. A sudden, maintained inflation causes their firing rate to increase suddenly and then to decrease (i.e., “adapt”) within 1 s to 20% or less of the initial rate. Rapid deflation also stimulates them. The distribution of these receptors is not as well characterized as that for the slowly adapting PSRs, but they seem to be located throughout the tracheobronchial tree. Their afferent axons are myelinated.

Unlike the slowly adapting PSRs, the rapidly adapting PSRs are also very sensitive to a variety of chemical stimuli; hence the term irritant receptors. These agents include histamine, serotonin, prostaglandins, bradykinin, ammonia, cigarette smoke, and ether. In some cases, the chemical directly stimulates the receptor. In others, the chemical first triggers a bronchoconstriction, and this volume change then activates the “stretch receptor.” An important function of these receptors may be to detect pathophysiological processes in the airway, such as chemical irritation, congestion, and inflammation. These receptors also detect the histamine that produces bronchoconstriction in asthma.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

C Fibers

A rich network of extremely thin, unmyelinated axons—C fibers—innervates receptors in the alveoli and conducting airways. Like the slowly adapting PSRs (see Web Note 0743a, Slowly Adapting Pulmonary Stretch Receptors) that are innervated by myelinated nerve fibers, C-fiber receptors respond to both chemical and mechanical stimuli. Alveolar C-fiber receptors become active very soon (i.e., 1 or 2 s) after the injection of certain chemicals into the blood of the right atrium of the heart,* suggesting that the receptors may be very near pulmonary capillaries; hence the name juxtacapillary or J receptors. The J receptors respond “chemically” to inflammatory agents released in the airway wall: histamine, serotonin, bradykinin, and prostaglandins. They also respond to mechanical stimuli, including lung or vascular congestion.

The C-fiber receptors in conducting airways are less sensitive to lung inflation than their alveolar counterparts, but they are more sensitive to chemical mediators of inflammation. Stimulating C-fiber receptors elicits a triad of rapid shallow breathing, bronchoconstriction, and increased secretion of mucus into airways—all of which may be defense mechanisms. Bronchoconstriction and rapid, shallow breathing would enhance turbulence (see Fig. 27–11Con p. 643 of the text), favoring the deposition of foreign substances in mucus higher up in the bronchial tree, where mucus-secreting cells are located.

The afferent nerve fibers for all sensors located in the tracheobronchial tree and lung parenchyma travel to the medulla in the vagus nerve (CN X) via either myelinated or unmyelinated fibers. The myelinatedfibers rapidlytransmit impulses from PSRs and are readily blocked by cooling (~8–10°C). Unmyelinated nerve fibers—the C fibers discussed previously—slowly transmit impulses from J receptors near alveoli, as well as other receptors in conducting airways, and conduct impulses even at 4°C. This differential temperature sensitivity is a useful tool for studying respiratory reflexes. For a discussion of the effects of myelination and axon diameter on axon conduction velocity, see the passage in the text that begins on p. 317.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

* After entering the ventricle and being injected into the pulmonary veins, this blood rapidly reaches the alveolar capillaries, very near where the alveolar C-fiber receptors are thought to be.

External Compression of Thoracic Vessels

The example in which severe coughing leads to syncope is a special case in which the external compression of the vessels in the thorax causes an increase in their resistance and, thus, a decrease in venous return. Keep in mind that not only does the inferior vena cava have a rather low pressure but also all pulmonary vessels (i.e., arteries, capillaries, and veins) have a low pressure. Thus, all of these vessels are particularly susceptible to collapse by increasing the surrounding pressure.

Contributed by George Richerson, Emile Boulpaep, and Walter Boron

Definition of a Nephron

The connecting tubule, initial collecting tubule, cortical collecting tubule, and medullary collecting duct all derive embryologically from the ureteric bud. Because the more proximal elements all derive embryologically from the metanephric blastema, the segments from the connecting tubule through the medullary collecting duct were treated in the past as an entity separate from the other components of the nephron. Today, the term “nephron” usually includes both the proximal segments and the collecting duct system.

Contributed by Erich Windhager and Gerhard Giebisch

Finnish-Type Nephrosis

A critical protein in the slit diaphragm is nephrin, which is specifically located at the slit diaphragm of glomerular podocytes. Nephrin plays an essential role in the maintenance of normal glomerular permeability because its absence leads to severe proteinuria. Thus, a rare human autosomal disease, characterized by the absence of nephrin (Finnish-type nephrosis with massive albuminuria), further supports the critical role of slit diaphragm proteins in defining glomerular permeability to macromolecules. Figure 33-3I on p. 752 in the text provides a view of glomerular filtration slits and includes slit diaphragm proteins of functional importance. It is likely that changes in phosphorylation of podocyte proteins modulate the permeability properties of the slit membrane to proteins.

REFERENCE

Benzing T: Signaling at the slit diaphragm. J Am Soc Nephrol 15:1382–1391, 2004.

Tryggvason K: Unraveling the mechanisms of glomerular ultrafiltration: Nephrin, a key component of the slit diaphragm. J Am Soc Nephrol 10:2440–2445, 1999.

Contributed by Gerhard Giebisch and Erich Windhager

Tubule Segments of the Nephron

In Figure 33-6 in the text (p. 755), we identified 11 distinct segments (lettered A–K) in the nephron. The following is a description of the cells that make up each of these segments:

A. Proximal convoluted tubule: The first portion of the PCT consists of S1 cells, and the latter portion consists of S2 cells. Both cells have abundant apical microvilli and a deeply infolded basolateral membrane. They also have a rich supply of mitochondria, which lie between the infoldings. These complexities diminish from the S1 to the S2 segments.

B. Proximal straight tubule: The first portion of the PST consists of S2 cells, and the latter portion consists of S3 cells. The ultrastructural complexity diminishes from the S2 to the S3 segments.

C. Descending thin limb: The cells are less complex and flatter than those of the S3 segment of the proximal tubule.

D. Ascending thin limb: Away from the nucleus, these cells are even thinner than those of the descending limb.

E. Thick ascending limb: The cells, which lack microvilli, are substantially taller and more complex than those of the thin limbs.

F. Distal convoluted tubule: The cells are very similar to those of the thick ascending limb.

G. Connecting tubule: This segment consists of both connecting tubule cells, which secrete kallikrein, and intercalated cells, which are rich in mitochondria.

H. Initial collecting tubule: The ICT is defined as the segment just before the first confluence of tubules. Approximately one third of the cells in this segment are intercalated cells, and the rest are principal cells.

I. Cortical collecting tubule: The CCT is defined as the segment after the first confluence of tubules. The cells in this segment are very similar to those in the ICT.

J. Outer medullary collecting duct: The principal cells in this nephron segment have a modest cell height. The number of intercalated cells progressively decreases along the length of this segment.

K. Inner medullary collecting duct: This segment consists only of principal cells. Even at the beginning of the IMCD, the principal cells are taller than in the OMCD. At the end of the IMCD, the “papillary” collecting duct cells are extremely tall.

Contributed by Erich Windhager and Gerhard Giebisch

Tamm–Horsfall Protein

The Tamm–Horsfall protein (THP), also known as uromodulin, is the soluble cleavage product of an abundant GPI-linked protein (see p. 14 in the text) on the apical membrane of the TAL cells. THP, normally the most abundant protein in urine, may play a role in the defense against pathogenic bacteria in the genitourinary system.

REFERENCE

Serafini-Cessi F, Malagolini N, and Cavallone D: Am J Kidney Dis 42:658–676, 2003.

Contributed by Walter Boron

Erythropoietin

Erythropoietin (EPO) is made mainly in the kidney by fibroblast-like type I interstitial cells in the cortex and outer medulla (see p. 757 in the text). EPO is a growth factor related to other cytokines, and it acts through a tyrosine kinase-associated receptor (p. 70) to stimulate the production of proerythroblasts in the bone marrow, as well as the development of red cells from their progenitor cells. In fetal life, the liver, rather than the kidney, produces EPO. Even in the adult, Kupffer cells in the liver produce some EPO.

Four lines of evidence indicate that the stimulus for EPO synthesis is a decrease in local PO2. First, EPO synthesis increases with anemia. Second, EPO production increases with lowered renal blood flow. Third, EPO synthesis increases with central hypoxia (i.e., low arterial PO2), such as may occur with pulmonary disease or living at high altitude (p. 1275). In all three of these cases, local PO2 declines as tissues respond to a decrease in O2 delivery by extracting more O2 from each volume of blood that passes through the kidney. Finally, EPO production increases when Hb has a high O2 affinity. Here, the renal cells must lower PO2 substantially before O2 dissociates from Hb. Thus, mutant hemoglobins with high O2 affinities, stored blood (which has low 2,3-DPG levels), and alkaline blood all lead to increased EPO production.

Besides local hypoxia, several hormones and other agents stimulate EPO production. For example, prostaglandin E2 (PGE2) and adenosine appear to stimulate EPO synthesis by increasing intracellular levels of cAMP. Norepinephrine and thyroid hormone also stimulate EPO release. Finally, androgens stimulate—whereas estrogens inhibit—EPO synthesis, explaining at least in part why women in their childbearing years have lower hematocrit levels than do men.

Because the kidneys are the major source of EPO, renal failure leads to reduced EPO levels and anemia. The development of recombinant EPO has had a major impact in ameliorating the anemia of chronic renal failure.

Contributed by Walter Boron

In Vitro Preparations for Studying Renal Function in the Research Laboratory

Clearance methods treat the whole kidney as a “black box.” Thus, using clearance methods, it is very difficult to determine which nephron segments are responsible for which transport processes. It is also impossible to determine which nephrons are responsible for overall urinary excretion. To learn how single nephrons function, and also to understand how individual segments of the nephron contribute to overall nephron function, renal physiologists have developed a series of invasive techniques for studying the function of renal cells in the research laboratory:

Free-flow micropuncture: It is possible to insert, under microscopic observation, a sharpened micropipette into tubule segments at or near the surface of the kidney or into exposed parts of the renal papilla. In these cases, one can collect fluid from identified tubule segments, as illustrated in Figure 33-9A (p. 761) for a superficially located proximal tubule. The investigator collects tubule fluid at a rate that is comparable to the flow rate in the undisturbed nephron and then analyzes this fluid for the solute of interest.

Stationary or stopped-flow microperfusion: In this approach, the investigator deposits an aqueous solution between two oil columns inside the tubule lumen and periodically withdraws samples for analysis (Figure 33-9B). An advantage of this technique is that one can choose the initial composition of the fluid deposited in the lumen.

Continuous microperfusion: This approach is similar to the stationary approach in that a pair of oil blocks isolate the artificial perfusion fluid from the tubule fluid normally present (Figure 33-9C). A difference is that one continuously infuses fluid by means of a carefully calibrated microperfusion pump and then collects the perfusate in a micropipette located at the distal end of the perfused tubule segment. In addition, it is possible to perfuse the peritubular capillary network by means of separate micropipettes. This approach permits one to evaluate the effects of changes of the peritubular environment on tubule transport. The simultaneous perfusion of the lumen and peritubular capillaries affords excellent control over the environment of the tubule cells at both apical and basolateral surfaces.

Perfusion of isolated tubules: It is possible to microdissect a single segment from almost any part of the nephron and perfuse the single isolated tubule on the stage of a microscope (Figure 33-9D). The isolated, perfused tubule technique offers two distinct advantages over the in vivo micropuncture and microperfusion techniques discussed previously. First, one can study tubules from any segment of the nephron, not just superficial tubule segments. Second, the tubules can be isolated from nephron populations (juxtamedullary as well as superficial) located anywhere in the kidney. This consideration is important because of the heterogeneity that exists among nephrons. Thus, the isolated, perfused tubule technique offers the ultimate in control over the environment of tubule cells.

In addition to the previous four preparations, which permit one to study a defined tubule segment from a single nephron, several other preparations are available for studying cellular and subcellular events. This more narrowly focused approach is achieved at the expense of disrupting the normal tubule and vascular organization of the kidney:

Suspensions of tubules or of single cells: These preparations have enough cell mass to permit the determination of cellular metabolism under a variety of experimental conditions. Although this approach can also be used to study solute transport, a disadvantage is that because the cells have lost their normal polarity, it is impossible to assign function to either apical or basolateral membranes.

Tubule cells in culture: This preparation offers the advantage that the sidedness of the apical and basolateral membranes is preserved. On the other hand, one must be aware that cells in culture—whether primary cultures or continuous cell lines—may acquire a phenotype different from that of tubule cells in vivo.

Membrane vesicles: This preparation is an extension of the single-cell suspension technique but takes the isolation a step further. When one disrupts tubule cells, the fragments of their plasma membranes spontaneously take the form of membrane vesicles—small, irregularly shaped volumes that are completely surrounded by a piece of cell membrane, complete with its lipids and proteins. It is possible to purify membrane vesicles into fractions that consist mainly of luminal (“brush border”) cell membranes or basolateral cell membranes. These vesicles maintain many of the transport functions of tubule cells in vivoand can be examined in ways that allow one to study specific transport systems in vesicles derived primarily from the apical versus basolateral membrane (see Figure 5-12 on p. 127). Two important caveats to this method should be recognized. First, vesicles may exhibit large variations in their passive leakiness via pathways that are not normally present in tubule cells in vivo. Second, many of the normal cytoplasmic constituents are absent from the vesicle preparation so that signal transduction mechanisms may not function normally.

Contributed by Gerhard Giebisch & Erich Windhager

Symbols of the Clearance Equation

In Equation 33–3 in the text (p. 758), we present the Clearance Equation1 as

Equation 1

image

Here C is the clearance, X is the solute, UX is the concentration of X in the urine, image is the flow of urine (volume per unit time), and PX is the concentration of X in the urine. Most clinical texts replace the symbol image simply with image[AUTHOR: BOTH SYMBOLS APPEAR TO BE THE SAME. PLEASE CLARIFY] We use image to distinguish an absolute volume of urine from the rate of urine production.

This use of symbols is very different from elsewhere in the text and, indeed, from elsewhere in the discipline of physiology. A cellular physiologist might write the same equation in the form

Equation 2

image

Indeed, an advantage of writing the clearance equation in its totally unofficial form (Equation 2) is that it avoids confusing PX with the standard symbol for the permeability to X.

1Attributed to John M. Russell. Imagine that you are in Brussels on a sunny day, gazing at the famous fountain that features the statue of a little boy urinating into a pool of water. The sunlight (which contains ultraviolet or “UV” rays) is obviously above the stream of urine (“pee”), yielding “UV over P.”

Contributed by Erich Windhager, Gerhard Giebisch, Emile Boulpaep, and Walter Boron

In Vitro Preparations for Studying Renal Function in the Research Laboratory

Clearance methods treat the whole kidney as a “black box.” Thus, using clearance methods, it is very difficult to determine which nephron segments are responsible for which transport processes. It is also impossible to determine which nephrons are responsible for overall urinary excretion. To learn how single nephrons function, and also to understand how individual segments of the nephron contribute to overall nephron function, renal physiologists have developed a series of invasive techniques for studying the function of renal cells in the research laboratory:

Free-flow micropuncture: It is possible to insert, under microscopic observation, a sharpened micropipette into tubule segments at or near the surface of the kidney or into exposed parts of the renal papilla. In these cases, one can collect fluid from identified tubule segments, as illustrated in Figure 33-9A (p. 761) for a superficially located proximal tubule. The investigator collects tubule fluid at a rate that is comparable to the flow rate in the undisturbed nephron and then analyzes this fluid for the solute of interest.

Stationary or stopped-flow microperfusion: In this approach, the investigator deposits an aqueous solution between two oil columns inside the tubule lumen and periodically withdraws samples for analysis (Figure 33-9B). An advantage of this technique is that one can choose the initial composition of the fluid deposited in the lumen.

Continuous microperfusion: This approach is similar to the stationary approach noted previously in that a pair of oil blocks isolate the artificial perfusion fluid from the tubule fluid normally present (Figure 33-9C). A difference is that one continuously infuses fluid by means of a carefully calibrated microperfusion pump and then collects the perfusate in a micropipette located at the distal end of the perfused tubule segment. In addition, it is possible to perfuse the peritubular capillary network by means of separate micropipettes. This approach permits one to evaluate the effects of changes of the peritubular environment on tubule transport. The simultaneous perfusion of the lumen and peritubular capillaries affords excellent control over the environment of the tubule cells at both apical and basolateral surfaces.

Perfusion of isolated tubules: It is possible to microdissect a single segment from almost any part of the nephron and perfuse the single isolated tubule on the stage of a microscope (Figure 33-9D). The isolated, perfused tubule technique offers two distinct advantages over the in vivo micropuncture and microperfusion techniques discussed previously. First, one can study tubules from any segment of the nephron, not just superficial tubule segments. Second, the tubules can be isolated from nephron populations (juxtamedullary as well as superficial) located anywhere in the kidney. This consideration is important because of the heterogeneity that exists among nephrons. Thus, the isolated, perfused tubule technique offers the ultimate in control over the environment of tubule cells.

In addition to the previous four preparations, which permit one to study a defined tubule segment from a single nephron, several other preparations are available for studying cellular and subcellular events. This more narrowly focused approach is achieved at the expense of disrupting the normal tubule and vascular organization of the kidney:

Suspensions of tubules or of single cells: These preparations have enough cell mass to permit the determination of cellular metabolism under a variety of experimental conditions. Although this approach can also be used to study solute transport, a disadvantage is that because the cells have lost their normal polarity, it is impossible to assign function to either apical or basolateral membranes.

Tubule cells in culture: This preparation offers the advantage that the sidedness of the apical and basolateral membranes is preserved. On the other hand, one must be aware that cells in culture—whether primary cultures or continuous cell lines—may acquire a phenotype different from that of tubule cells in vivo.

Membrane vesicles: This preparation is an extension of the single-cell suspension technique but takes the isolation a step further. When one disrupts tubule cells, the fragments of their plasma membranes spontaneously take the form of membrane vesicles—small, irregularly shaped volumes that are completely surrounded by a piece of cell membrane, complete with its lipids and proteins. It is possible to purify membrane vesicles into fractions that consist mainly of luminal (“brush border”) cell membranes or basolateral cell membranes. These vesicles maintain many of the transport functions of tubule cells in vivoand can be examined in ways that allow one to study specific transport systems in vesicles derived primarily from the apical versus basolateral membrane (see Figure 5-12 on p. 127). Two important caveats to this method should be recognized. First, vesicles may exhibit large variations in their passive leakiness via pathways that are not normally present in tubule cells in vivo. Second, many of the normal cytoplasmic constituents are absent from the vesicle preparation so that signal transduction mechanisms may not function normally.

Contributed by Gerhard Giebisch and Erich Windhager

Units of Clearance

Clearance values are conventionally given in milliliters of total plasma per minute, even though plasma consists of 93% “water” and 7% protein, with only the “plasma water”—that is, the protein-free plasma solution, including all solutes small enough to undergo filtration—undergoing glomerular filtration. As noted in Chapter 5 (see Table 5–2), the concentrations of plasma solutes can be expressed in millimoles per liter of total plasma or millimoles per liter of protein-free plasma (i.e., plasma water). Customarily, clinical laboratories report values in millimoles (or milligrams) per 100 ml of plasma, not plasma water. When we say that the GFR is 125 ml/min, we mean that each minute the kidney filters all ions and small solutes contained in 125 ml of plasma. However, because the glomerular capillary blood retains the proteins, only 0.93 × 125 ml = 116 ml of plasma water appears in Bowman’s capsule. Nevertheless, GFR is defined in terms of volume of blood plasma filtered per minute rather than in terms of the volume of protein-free plasma solution that actually arrives in Bowman’s space (i.e., the filtrate).

Contributed by Erich Windhager and Gerhard Giebisch

Clearance Ratio

The clearance ratio is the ratio of the clearances of X (CX) and inulin (CIn):

Equation 1

image

The symbols U, image, and P have the same meanings as in Chapter 33; namely, U is urine concentration, image is urine flow, PX is the plasma concentration of the solute X, and PIn is the plasma concentration of inulin. We can now regroup the terms in the rightmost quotient to create the following expression:

Equation 2

image

We will now show that—if the tubules transport neither X nor inulin—the numerator, UX/(UIn/PIn), is in fact the concentration of X in Bowman’s capsule, UFX, where the symbol UF means ultrafiltrate. Between Bowman’s capsule and the final urine, the reabsorption of water by the tubules should have concentrated both inulin and X to the same extent, provided neither inulin nor X is secreted or absorbed. The extent to which inulin has been concentrated is merely UIn/PIn. Therefore, if we know the concentration of X in the urine, we merely divide UX by UIn/PIn to obtain the concentration of X in Bowman’s capsule:

Equation 3

image

Therefore, in Equation 2 we can replace the term UX/(UIn/PIn) by UFX:

Equation 4

image

Thus, the ratio UFX/PX is the same as the clearance ratio, which is the value shown in the rightmost column of Table 34–2 (p. 770). The clearance ratio is an index of sieving coefficient (UFX/PX) of the glomerular filtration barrier for solute X.

Contributed by Erich Windhager and Gerhard Giebisch

Filtration of Solutes through Water-Filled Pores

Filtration of solutes across the glomerular capillary barrier can be modeled as the movement of molecules through water-filled pores. The flux of a solute (JX)—the rate at which X crosses a unit area of the barrier—through such glomerular pores is the sum of the convective and the diffusional flux:

Equation 1

image

In this equation, JV is the flux of fluid volume through the barrier, which is proportional to GFR. PX and UFX are the solute concentrations in plasma and filtrate, respectively.1 σX is the reflection coefficient for X (see p. 489 in the text). The reflection coefficient is a measure of how well the barrier restricts or “reflects” the movement of the solute X as water moves across the barrier by convective flow. σX varies between zero (when convective movement of X is unrestricted) and unity (when the solute cannot at all pass through the pore together with water). We use “permeability” here in the same sense as “permeability coefficient” in Chapter 5 (p. 112) and as discussed in the webnote Definition of Permeability Coefficient.

As discussed in the text on p. 770 and shown in Table 34–2, the filtrate/filtrand ratio (UFX/PX) is unity for small solutes, such as urea, glucose, sucrose, and inulin. For these solutes, filtration does not lead to a development of a concentration gradient across the glomerular barrier. In other words, (PX-UFX) is zero. Thus, the diffusional flux in Equation 1 disappears, and all the movement of these small molecules must occur by convection.

For larger molecules, both the convective and diffusional terms in Equation 1 contribute to the flux of the solute X. At a normal GFR, any restriction to the movement of X (i.e., σX > 0) will cause the concentration of X in the filtrate to be less than that in the plasma (UFX < PX). As a result, there is a concentration gradient favoring the diffusion of X from plasma into Bowman’s space, as described by Equation 1. Two factors will enhance the relative contribution of the diffusional component. First, the more restricted the solute is by the barrier, the lower the concentration of X in the filtrate, and thus the greater is the driving force for diffusion. Second, the greater the GFR, the greater the flow of water into Bowman’s space, and the greater the dilution of X in Bowman’s space, the lower is UFX, and thus the greater is the driving force for diffusion of X.

For partially restricted molecules, the greater the GFR, the lower the UFX—as we just saw—and thus the lower the filtrate/filtrand ratio. In the extreme case in which GFR falls to zero, the filtrate/filtrand ratio approaches unity as even relatively large molecules ultimately reach diffusion equilibrium. On the other hand, if GFR increases to very high values, the convective flow of water carrying low concentrations of the partially restricted solute dominates, and the filtrate/filtrand concentration ratio decreases. Because hemodynamic factors such as blood pressure affect GFR (see p. 772), one must carefully control these factors—and thus GFR—in order to use clearance ratios of macromolecules to characterize glomerular permeability.

1Caution! Do not confuse PX with the permeability of X, an issue discussed in webnote Symbols of the Clearance Equation.

Contributed by Erich Windhager and Gerhard Giebisch

Starling Forces along the Glomerular Capillary

The πGC curve in Figure 34-5B on p. 772 of the textbook is the result of a computer simulation that is based on Equation 34–4 on p. 771:

Equation 1

image

Recall from the textbook that by definition, filtration fraction (FF) is related to glomerular filtration rate (GFR) and renal plasma flow (RPF) by Equation 34–6 on p. 773, which is reproduced here:

Equation 2

image

Thus,

Equation 3

image

image

Equation 1 is presented in textbooks—including ours—as if it applies to the macroscopic GFR (e.g., 125 ml/min) that the two kidneys together produce via the actions of all approximately 2 million of their glomeruli. In reality, Equation 1 only applies to a microscopic GFR—that is, a rate of filtration at a particular point along the glomerular capillary of a particular glomerulus.1 The reasons are that (1) GC—and thus PUF—changes continuously along the glomerular capillary, and (2) Kf as well as this GC profile are not identical for all glomeruli. Thus, Equation 1 is valid only at a particular point along a particular glomerular capillary, where GC has a particular value.2 The same is true for Equation 3. To make this point more clear, we define the microscopic filtration fraction (ff) and its counterpart kf*—relevant for a small stretch of glomerular capillary—as we march down the capillary:

Equation 4

image

We now apply Equation 4 at multiple points along a theoretical, monolithic capillary, arbitrarily dividing the capillary into 100 identical segments. For the first of these 100 segments, we assume that all the terms that determine PUFhave the values shown in Figure 34-5A at distance (x) = 0:

PGC = 50 mm Hg

πGC = 25 mm Hg

PBS = 10 mm Hg

πBS = 0 mm Hg

Thus, at x = 0, the forces favoring filtration are (PGCBS) = 50 mm Hg (green curve in Figure 34-5C), whereas the forces opposing filtration are (PBSGC) = 35 mm Hg (red curve in Figure 34-5C). The net ultrafiltration pressure (PUF) at time = 0 is therefore 50-35 = 15 mm Hg (vertical distance between the green and red curves, colored gold in Figure 34-5C).

We then apply Equation 4, multiplying this (PUF)Distance=0 by a preassigned value for kf*. Recall that this value of kf* has built into it not only the microscopic filtration coefficient per se but also RPF, and it has the units (mm Hg)–1. Thus, the product of kf* and PUF in our model is the fraction of the initial ECF volume (inside the glomerular capillary) lost in the first of 100 segments of the capillary—the microscopic filtration fraction. Next, we will see that for a normal renal plasma flow, kf* has the value 0.0001765 (mm Hg)–1. Thus, the faction of ECF lost from the capillary in the first 1% of the capillary is

Equation 5

image

That is, approximately 0.265% of the ECF originally in the capillary is lost (i.e., filtered) in the first 1% of the glomerular capillary. In other words, after the blood has passed the 1% mark, the ECF volume remaining in the glomerular capillary would be only 100%-0.265% = 99.735% as large as it was at the outset.

Because the mass of proteins in the blood ECF is fixed (we assume no filtration of proteins), πGC must rise by the fraction by which ECF falls. In our example, at the end of the first 1% of distance, πGC would be (25 mm Hg)/0.99735 25.0664 mm Hg. We then use this new value of GC in the computation for the second iteration (i.e., for the second increment of 1%), and so on for a total of 100 iterations—that is, for the entire 100% of the distance. At the end of 100 iterations, we can sum up the 100 microscopic ff values to arrive at the macroscopic FF.

Assigning the value for kf* is slightly tricky. We do it in the following way. First, we define a standard GFR value (which we take to be 125 ml/min) and a standard RPF value (600 ml/min). Next, we guess at a provisional value for the standard kf*, insert it into the previous equation, go through the 100 iterations, and then add up the 100 ff values to arrive at the macroscopic FF. From this FF value—as well as RPF—we compute GFR using Equation 2. If this provisional standard kf* does not produce the desired GFR of 125 ml/min, we make another guess and repeat the process until we eventually arrive at the standard kf*. In our case, this standard kf* is 0.0001765 (mm Hg)–1. Note that this value includes the standard RPF of 600 ml/min.

The πGC curve in Figure 34-5B actually represents a “low” RPF of 70.6 ml/min versus the standard RPF of 600 ml/min. The ratio of these two values is 600/70.6 8.5, and in our model we achieve this low RPF by multiplying our standard kf* by a factor of approximately 8.5, from 0.0001765 (mm Hg)–1 to 0.0015 (mm Hg)–1.

Note that because πGC exponentially rises from its initial value of 25 mm Hg to an asymptotic value of 40 mm Hg, PUF exponentially decays from a maximal value of 15 mm Hg to zero, as shown by the vertical distance between the green and red curves (the gold area) in Figure 34-5C.

1This principle also applies to the version of Fick’s law that we use to describe the diffusion of gases from the alveolar air to the blood or vice versa. See Equation 30–4 on p. 685, which is the simplified version of the equation (analogous to Equation 1), as well as the more precise Equation 30–9 on p. 687.

2As in the textbook, we are assuming that the values of all the other parameters are fixed.

Contributed by Walter Boron

Dependence of GRF and RPF on RPF[AUTHOR: TITLE AS MEANT? “RPF” USED TWICE?]

A previous WebNote described our computer model for generating plots of πGC versus distance along the glomerular capillary. The curves in Figure 34-6A on p. 773 in the text are the same as in Figure 34-5Con p. 772, and they represent a low renal plasma flow (RPF) of 70.6 ml/min. For this condition of low RPF, we computed the πGC curve using a kf* of 0.0015 (mm Hg)–1. (Remember from WebNote that kf* is the embodiment of both the microscopic Kfand RPF.) As described in the previous WebNote, summing up the individual filtration events along the capillary yields the filtered fraction (FF), which is 37.5% in this case. This is one of the points along the left end of the curve in Figure 34-6E. Multiplying RPF and FF yields the macroscopic glomerular filtration rate (GFR), which is the rather low value of 26.47 ml/min. This is one of the points along the left end of the curve in Figure 34-6D.

The curves in Figure 34-6B on p. 773 represent a normal RPF of 600 ml/min. For this condition of normal RPF, we computed the πGC curve using a kf* of 0.0001765 (mm Hg)–1. Summing up the individual filtration events along the capillary yields the FF, which is 20.8% in this case. This is the identified point along the curve in Figure 34-6E. Multiplying RPF and FF yields the macroscopic GFR, which is the normal value of 125 ml/min. This is the identified point along the curve in Figure 34-6D.

The curves in Figure 34-6C on p. 773 represent a high RPF of 1200 ml/min. For this high RPF, we computed the GC curve using a kf* of 0.00008825 (mm Hg)–1—that is, half the value in the “normal” example. Summing up the individual filtration events along the capillary yields the FF, which is 11.9% in this case. This is one of the points along the right end of the curve in Figure 34-6E. Multiplying RPF and FF yields the macroscopic GFR, which is the elevated value of 142.6 ml/min. This is one of the points along the right end of the curve in Figure 34-6D.

Using the approach outlined in the previous WebNote. we generated GC curves—and thus FF and GFR values—for a wide range of RPF values. The plots in Figures 34–6D and 34–6E are the results of these simulations.

Contributed by Walter Boron

Effects of Hemodynamic Changes on Fluid Reabsorption by the Peritubular Capillaries

The text analyzes an example in which expansion of the extracellular fluid volume inhibits the renin–angiotensin system, producing hemodynamic changes—that is, decreases in both afferent and efferentarteriolar resistance, but more so the latter. Thus, the fractional rise in glomerular filtration rate (GFR) is less than the fractional rise in renal plasma flow (RPF) so that the filtration fraction (FF) falls. The analysis in the text focuses on forces inside the peritubular capillaries: PPC and PC. In addition, the hemodynamic changes in our example also lead to altered forces outside the peritubular capillaries: These changes in interstitial forces reduce fluid absorption—from the tubule lumen to the interstitium—by the proximal tubule. Thus, in this example an increase in extracellular fluid volume leads to changes in renal hemodynamics, leading to a parallel rise in GFR and a fall in fluid reabsorption from the proximal tubule to its peritubular capillaries. The result is an appropriate increase in fluid excretion into the urine.

The effect of hemodynamic changes on Na+ and fluid transport is discussed in more depth in Chapter 35, beginning on page 791 of the text.

Contributed by Emile Boulpaep and Walter Boron

Starling Forces along the Glomerular Capillary

Figure 34-9B on p. 776 of the textbook shows the same pair of curves as Figure 34-6B on p. 773. These represent a normal renal plasma flow (RPF) of 600 ml/min

Contributed by Walter Boron

Systemic versus Local Roles of the JGA

The juxtaglomerular apparatus (JGA) performs two, apparently opposite functions: maintaining a constant GFR (tubuloglomerular feedback or TGF) and maintaining a constant whole-body blood pressure by modulating renin release. TGF (see p. 778 in the text) is a local phenomenon, whereas the release of renin has systemic consequences (p. 870).

In the case of tubuloglomerular feedback (i.e., the local response), decreased renal perfusion pressure, reduced filtered load, or enhanced proximal fluid reabsorption all lead to a decrease in the flow of tubule fluid past the macula densa, as well as to a decrease in Na+ delivery and Na+ concentration. Within seconds after such a transient disturbance, and by an unknown mechanism, TGF dilates the afferent arteriole of the same nephron in an attempt to increase SNGFR and restore fluid and Na+ to that particular macula densa.

In the case of renin release (i.e., the systemic response), by contrast, a sustained fall in arterial pressure or a contraction of the extracellular volume reduces fluid delivery to many macula densas, leading to the release of renin. Renin, in turn, causes an increase in local and systemic concentrations of ANG II. Besides causing general vasoconstriction, ANG II constricts the afferent and efferent glomerular arterioles, thereby decreasing GFR. This effect is opposite to that of TGF: TGF dilates a single afferent arteriole, whereas renin release constricts many afferent and efferent arterioles.

TGF may be viewed as a mechanism designed to maintain a constant SNGFR, whereas renin release is aimed at maintaining blood pressure by both systemic and renal vasoconstriction (i.e., hemodynamic effects), as well as by reducing SNGFR and enhancing tubule Na+ reabsorption (Na+-retaining effects). TG feedback is a minute-to-minute, fine control of SNGFR that can be superseded by the intermediate to long-term effects of the powerful renin response, which comes into play whenever plasma volume and blood pressure are jeopardized. It must be emphasized that renin release is governed not only by the juxtaglomerular apparatus but also by other mechanisms, particularly changes in the activity of sympathetic nerves (p. 872).

Contributed by Emile Boulpaep and Walter Boron

Agents That Modify Renal Hemodynamics

Effects of various vasoactive agents on renal blood flow (RBF), glomerular filtration rate (GFR), and glomerular filtration coefficient (Kf):

Agent

RBF

GFR

Kf

Catecholamines

     

Norepinephrine

image,↓

Epinephrine

image,↓

Dopamine

NA

Peptides

     

Arginine vasopressin

image or ↓

image

Parathyroid hormone

image

image or ↓

Atrial natriuretic peptide

image or ↑

image or ↑

image or ↑

Angiotensin II

image or ↓

Bradykinin

image

image or ↓

Glucagon

NA

Endothelin

Arachidonate metabolites

     

PGE2, PGI2

image or ↑

image or ↓

Thromboxane A2

Leukotrienes C4, D4

20 HETE

image

Other

     

ATP

image

Adenosine

↓ then ↑

image

Histamine

image

Platelet-activating factor

Acetylcholine

image

image or ↓

NO

image or ↑

NA, not applicable.

Contributed by Gerhard Giebisch & Erich Windhager

Effects of Epinephrine on Renal Hemodynamics

Epinephrine increases renal vascular resistance. At lower epinephrine levels, GFR may be maintained despite a significant reduction of RBF, similar to the effects of moderate sympathetic nerve stimulation (see pp. 779–780 in the text). This effect implies preferential efferent vasoconstriction. At higher doses, epinephrine decreases both GFR and RBF, similar to the effects of intense sympathetic nerve stimulation.

Contributed by Gerhard Giebisch and Erich Windhager

Isosmotic Reabsorption by the Proximal Tubule

The reabsorption of solutes by the proximal tubule is virtually isomotic. That is, if the osmolality of the luminal fluid is, for example, 300 mOsm, then the osmolality of the reabsorbate (i.e., the fluid being reabsorbed from lumen to basolateral interstitium, which is practically continuous with the blood) is approximately 300 mOsm. In fact, the reabsorbate almost certainly must be slightly hypertonic (e.g., 301 mOsm) to the luminal fluid because it is the transport of solutes from lumen to basolateral interstitium that pulls H2O along osmotically. However, the osmotic water permeability (Pf) of the proximal tubule is so high—due to the extremely high expression of the water channel AQP1—that the H2O nearly keeps up, so to speak, with the solutes, in an osmotic sense. A mathematical way of stating this fact is that the ratio of the NaCl reabsorptive flux (JNaCl) to the reabsorptive volume or H2O flux (JV) is nearly the same as the osmolality of the lumen:

Equation 1

image

In proximal tubules from AQP1 null mice, the flow of water cannot keep up with the transport of solutes, and thus the reabsorbate is rather hypertonic to the lumen. As a result, the lumen becomes increasingly hypotonic—that is, the proximal tubule becomes a “diluting segment” like the TAL.

REFERENCE

Schnermann J, Chou C-L, Ma T, et al.: Defective proximal tubular fluid reabsorption in transgenic aquaporin-1 null mice. Proc Natl Acad Sci USA 95:9660–9664, 1998.

Vallon V, Verkman AS, and Schnermann J: Luminal hypotonicity in proximal tubules of aquaporin-1-knockout mice. Am J Physiol Renal Physiol 278:F1030–F1033, 2000.

Contributed by Walter Boron

The Proximal Tubule Reabsorbate Is Slightly Hyperosmotic

As discussed in the text on pp. 787–788, investigators have found that the lumen of the proximal tubule becomes slightly hypo-osmolar as the reabsorption of salt and water proceeds. Because the ultrafiltrate in Bowman’s space is truly isosmotic with blood plasma, the reabsorbate (i.e., the fluid that the tubule reabsorbed) must have been hyperosmolar. Once the tubule has reabsorbed a slightly hyperosmolar solution, it has established an osmotic gradient along which water can flow by osmosis. Because the water permeability of the proximal tubule—due primarily to the water channel AQP1—is so high, not much of a transepithelial osmotic gradient is necessary to drive the observed rate of fluid reabsorption.

In mice lacking AQP1, the water permeability of the proximal tubule is so low that the diffusion of H2O can no longer keep up with the active reabsorption of NaCl, NaHCO3, and other solutes. As a result, the reabsorbate can become markedly hyperosmolar, and the fluid left behind becomes markedly hypo-osmolar. This situation is reminiscent of that in the thick ascending limb (TAL), which is sometimes called the “diluting segment.”

REFERENCE

Schnermann J, Chou CL, Ma T, et al.: Defective proximal tubular fluid reabsorption in transgenic aquaporin-1 null mice. Proc Natl Acad Sci USA 95:9660–9664, 1998.

Vallon V, Verkman AS, and Schnermann J: Luminal hypotonicity in proximal tubules of aquaporin-1-knockout mice. Am J Physiol Renal Physiol 278:F1030–F1033, 2000.

Contributed by Emile Boulpaep and Walter Boron

Stationary Microperfusion

We discuss several laboratory techniques, including stationary or stopped-flow microperfusion, in the following webnote:

Clearance methods treat the whole kidney as a “black box.” Thus, using clearance methods, it is very difficult to determine which nephron segments are responsible for which transport processes. It is also impossible to determine which nephrons are responsible for overall urinary excretion. To learn how single nephrons function, and also to understand how individual segments of the nephron contribute to overall nephron function, renal physiologists have developed a series of invasive techniques for studying the function of renal cells in the research laboratory:

Free-flow micropuncture: It is possible to insert, under microscopic observation, a sharpened micropipette into tubule segments at or near the surface of the kidney or into exposed parts of the renal papilla. In these cases, one can collect fluid from identified tubule segments, as illustrated in Figure 33-9A (p. 761) for a superficially located proximal tubule. The investigator collects tubule fluid at a rate that is comparable to the flow rate in the undisturbed nephron and then analyzes this fluid for the solute of interest.

Stationary or stopped-flow microperfusion: In this approach, the investigator deposits an aqueous solution between two oil columns inside the tubule lumen and periodically withdraws samples for analysis (Figure 33-9B). An advantage of this technique is that one can choose the initial composition of the fluid deposited in the lumen.

Continuous microperfusion: This approach is similar to the stationary approach noted previously in that a pair of oil blocks isolate the artificial perfusion fluid from the tubule fluid normally present (Figure 33-9C). A difference is that one continuously infuses fluid by means of a carefully calibrated microperfusion pump and then collects the perfusate in a micropipette located at the distal end of the perfused tubule segment. In addition, it is possible to perfuse the peritubular capillary network by means of separate micropipettes. This approach permits one to evaluate the effects of changes of the peritubular environment on tubule transport. The simultaneous perfusion of the lumen and peritubular capillaries affords excellent control over the environment of the tubule cells at both apical and basolateral surfaces.

Perfusion of isolated tubules: It is possible to microdissect a single segment from almost any part of the nephron and perfuse the single isolated tubule on the stage of a microscope (Figure 33-9D). The isolated, perfused tubule technique offers two distinct advantages over the in vivo micropuncture and microperfusion techniques discussed previously. First, one can study tubules from any segment of the nephron, not just superficial tubule segments. Second, the tubules can be isolated from nephron populations (juxtamedullary as well as superficial) located anywhere in the kidney. This consideration is important because of the heterogeneity that exists among nephrons. Thus, the isolated, perfused tubule technique offers the ultimate in control over the environment of tubule cells.

In addition to the previous four preparations, which permit one to study a defined tubule segment from a single nephron, several other preparations are available for studying cellular and subcellular events. This more narrowly focused approach is achieved at the expense of disrupting the normal tubule and vascular organization of the kidney:

Suspensions of tubules or of single cells: These preparations have enough cell mass to permit the determination of cellular metabolism under a variety of experimental conditions. Although this approach can also be used to study solute transport, a disadvantage is that because the cells have lost their normal polarity, it is impossible to assign function to either apical or basolateral membranes.

Tubule cells in culture: This preparation offers the advantage that the sidedness of the apical and basolateral membranes is preserved. On the other hand, one must be aware that cells in culture—whether primary cultures or continuous cell lines—may acquire a phenotype different from that of tubule cells in vivo.

Membrane vesicles: This preparation is an extension of the single-cell suspension technique but takes the isolation a step further. When one disrupts tubule cells, the fragments of their plasma membranes spontaneously take the form of membrane vesicles—small, irregularly shaped volumes that are completely surrounded by a piece of cell membrane, complete with its lipids and proteins. It is possible to purify membrane vesicles into fractions that consist mainly of luminal (“brush border”) cell membranes or basolateral cell membranes. These vesicles maintain many of the transport functions of tubule cells in vivoand can be examined in ways that allow one to study specific transport systems in vesicles derived primarily from the apical versus basolateral membrane (see Figure 5-12 on p. 127). Two important caveats to this method should be recognized. First, vesicles may exhibit large variations in their passive leakiness via pathways that are not normally present in tubule cells in vivo. Second, many of the normal cytoplasmic constituents are absent from the vesicle preparation so that signal transduction mechanisms may not function normally.

Contributed by Gerhard Giebisch and Erich Windhager

Isosmotic Reabsorption by the Proximal Tubule

The reabsorption of solutes by the proximal tubule is virtually isosmotic. That is, if the osmolality of the luminal fluid is, for example, 300 mOsm, then the osmolality of the reabsorbate (i.e., the fluid being reabsorbed from lumen to basolateral interstitium, which is practically continuous with the blood) is approximately 300 mOsm. In fact, the reabsorbate almost certainly must be slightly hypertonic (e.g., 301 mOsm) to the luminal fluid because it is the transport of solutes from lumen to basolateral interstitium that pulls H2O along osmotically. However, the osmotic water permeability (Pf) of the proximal tubule is so high—due to the extremely high expression of the water channel AQP1—that the H2O nearly keeps up, so to speak, with the solutes, in an osmotic sense. A mathematical way of stating this fact is that the ratio of the NaCl reabsorptive flux (JNaCl) to the reabsorptive volume or H2O flux (JV) is nearly the same as the osmolality of the lumen:

Equation 1

image

In proximal tubules from AQP1 null mice, the flow of water cannot keep up with the transport of solutes, and thus the reabsorbate is rather hypertonic to the lumen. As a result, the lumen becomes increasingly hypotonic—that is, the proximal tubule becomes a “diluting segment” like the TAL.

REFERENCE

Schnermann J, Chou C-L, Ma T, et al.: Defective proximal tubular fluid reabsorption in transgenic aquaporin-1 null mice. Proc Natl Acad Sci USA 95:9660–9664, 1998.

Vallon V, Verkman AS, and Schnermann J: Luminal hypotonicity in proximal tubules of aquaporin-1-knockout mice. Am J Physiol Renal Physiol 278:F1030–F1033, 2000.

Contributed by Walter Boron

Acute Effects of IV Aldosterone

The accompanying figure shows the renal effects of intravenously administered aldosterone on electrolyte excretion in humans. The acute effects include significant decreases in Na+ and Cl excretion, as well as increases in K+ and NH4+ excretion. The reverse changes occur in adrenalectomy, and the administration of mineralocorticoids (e.g., aldosterone) promptly reverses these deficiencies.

image

Data from Liddle GW: Aldosterone antagonists. Arch Intern Med 102:998–1005, 1958.

Contributed by Gerhard Giebisch and Erich Windhager

Reaction Catalyzed by 11β-HSD

Refer to Figure 50-2, specifically the cortisol molecule (4-pregnen-11β, 17α, 21-triol-3, 20-dione), which has two highlighted hydroxyl groups—one on the C ring at position 11 and another on the D ring at position 17. The enzyme 11β-hydroxysteroid dehydrogenase (11βHSD) removes one H from the hydroxyl group at position 11 and another H from the same carbon, yielding a ketone group (0O=C) at position 11. The product of this reaction is cortisone (4-pregnen-17α, 21-diol-3, 11, 20-trione). Thus, the enzyme converts a triol (three hydroxyl groups)/dione (two ketone groups) to a diol (two hydroxyl groups)/trione (three ketone groups).

Contributed by Contributed by Eugene Barrett

Licorice as a Cause of Apparent Mineralocorticoid Excess

Glycyrrhizic acid is a chemical that consists of glycyrrhetinic acid (3-beta-hydroxy-11-oxoolean-12-en-30-oic acid) conjugated to two glucuronic acid moieties. Glycyrrhizic acid is 150-fold sweeter than sucrose. It is naturally produced by the plant Glycyrrhiza glabra (Leguminosae) and is also present in European licorice. American licorice manufacturers generally substitute anise for glycyrrhizic acid.

Glycyrrhetinic acid and the glycyrrhetinic acid moiety of glycyrrhizic acid have the curious property that they inhibit the enzyme 11β-hydroxysteroid dehydrogenase (11βHSD). This enzyme converts cortisol into cortisone (see webnote). Because cortisol has a much higher affinity for the mineralocorticoid receptor than does the breakdown product cortisone, inhibition of 11βHSD produces the same symptoms as a bona fide excess of mineralocorticoids. As described on p. 794 in the text, this excess leads to Na+ retention and hypertension.

These compounds also inhibit 15-hydroxyprostaglandin dehydrogenase in the surface cells of the stomach and thereby increase levels of prostaglandins that protect the stomach from acid damage. This same action may also promote the release of mucus in the airway, which is why the active compounds of licorice have been used as expectorants.

True licorice has long been used as an herbal medicine.

REFERENCE

http://pubs.acs.org/cen/whatstuff/stuff/print/8032licorice.html.

Contributed by Emile Boulpaep and Walter Boron

Effects of AVP on Na+ Channels

As noted in the text, AVP increases the number of open Na+ channels (NPo) in the initial and cortical collecting tubules. This effect may reflect fusion of Na+-channel-containing vesicles with the apical cell membrane and/or activation of pre-existing Na+ channels in the membrane by cAMP-dependent protein kinase.

Contributed by Gerhard Giebisch & Erich Windhager

Renal Actions of Atrial Natriuretic Peptide (ANP)

The accompanying figure summarizes the effects of ANP on targets along the nephron.

Regarding Step 13 in the figure, patch-clamp studies show that cGMP directly decreases the activity of nonselective cation channels in the apical membrane of the medullary collecting duct.

image

Sites of action of atrial natriuretic peptide. ANG, angiotensin; GFR, glomerular filtration rate; UNa, urine sodium concentration. (Data from Atlas SA, Maack T: Atrial natriuretic factor. In Handbook of Physiology: Renal Physiology, E, Windhager, Ed., Oxford University Press, N.Y. 1992, pp 1577–1674.)

Contributed by Gerhard Giebisch & Erich Windhager

Urea Transporters

The urea transporters belong to the SLC14 family of transporters. The family has two gene members, SLC14A1 and SLC14A2. Both mediate facilitated diffusion. That is, the movement of urea is not coupled to that of another solute, but it nevertheless exhibits saturation and other hallmarks of carrier-mediated transport.

The SLC14A1 gene has at least two variants: UT-B1 (aka UT3) and UT-B2 (aka UT11). These are expressed in the descending vasa recta and RBCs.

The SLC14A2 gene has at least eight variants: UT-A1 (aka UT1), UT-A1b, UT-A2 (aka UT2), UT-A2b, UT-A3 (UT4), UT-A3b, UT-A4, and UT-A5. These are expressed predominantly in the kidney but also in other organs.

The putative fundamental topology of a UT protein is 5 membrane-spanning segments (TMs), a large extracellular loop, and an additional 5 TMs (for a total of 10 TMs). Somewhat paradoxically, the UT-A1 variant of SLC14A2—the first UT discovered—is a concatamer of two such units, linked by a long intracellular loop; it therefore has a total of 20 putative TMs.

REFERENCE

Bradford AD, Terris JM, Ecelbarger CA, et al.: 97- and 117-kDa forms of collecting duct urea transporter UT-A1 are due to different states of glycosylation. Am J Physiol Renal Physiol 281:F133–F143, 2001.

Sands J: Mammalian urea transporters. Annu Rev Physiol 65:543–566, 2003.

Shayakul C and Hediger MA: The SLC14 gene family of urea transporters. Pflügers Arch 447:603–609, 2004.

Contributed by Walter Boron

Urea Transporters

The urea transporters belong to the SLC14 family of transporters. The family has two gene members, SLC14A1 and SLC14A2. Both mediate facilitated diffusion. That is, the movement of urea is not coupled to that of another solute, but nevertheless it exhibits saturation and other hallmarks of carrier-mediated transport.

The SLC14A1 gene has at least two variants: UT-B1 (aka UT3) and UT-B2 (aka UT11). These are expressed in the descending vasa recta and RBCs.

The SLC14A2 gene has at least eight variants: UT-A1 (aka UT1), UT-A1b, UT-A2 (aka UT2), UT-A2b, UT-A3 (UT4), UT-A3b, UT-A4, and UT-A5. These are expressed predominantly in the kidney but also in other organs.

The putative fundamental topology of a UT protein is 5 membrane-spanning segments (TMs), a large extracellular loop, and an additional 5 TMs (for a total of 10 TMs). Somewhat paradoxically, the UT-A1 variant of SLC14A2—the first UT discovered—is a concatamer of two such units, linked by a long intracellular loop; it therefore has a total of 20 putative TMs.

REFERENCE

Bradford AD, Terris JM, Ecelbarger CA, et al.: 97- and 117-kDa forms of collecting duct urea transporter UT-A1 are due to different states of glycosylation. Am J Physiol Renal Physiol 281:F133–F143, 2001.

Sands J: Mammalian urea transporters. Annu Rev Physiol 65:543–566, 2003.

Shayakul C and Hediger MA: The SLC14 gene family of urea transporters. Pflügers Arch 447:603–609, 2004.

Contributed by Walter Boron

Using Membrane Vesicles to Study Glucose Transport

We describe the membrane vesicle technique in webnote 0757cFigure 5-12 on p. 127 in the text illustrates the use of this technique to explore how the Na+ gradient affects glucose uptake. The vesicles are made from brush border membrane vesicles (i.e., made from the apical membrane of the proximal tubule). In the absence of Na+ in the experimental medium, glucose enters renal brush border membrane vesicles slowly until reaching an equilibrium value (green curve in the central graph of Figure 5-12). At this point, internal and external glucose concentrations are identical. The slow increase in intravesicular [glucose] occurs by diffusion in the absence of Na+. In contrast, adding Na+to the external medium establishes a steep inwardly directed Na gradient, thereby dramatically accelerating glucose uptake (red curve in the central graph of Figure 5-12). The result is a transient “overshoot” during which glucose accumulates above the equilibrium level. Thus, in the presence of Na+, the vesicle clearly transports glucose uphill. Similar gradients of other cations, such as K+, have no effect on glucose movement beyond that expected from diffusion alone.

A negative cell voltage can also drive Na/glucose cotransport, even when there is no Na+ gradient. In experiments in which the internal and external Na+ concentrations are the same, making the inside of the vesicles electrically negative accelerates glucose uptake (not shown).

In vesicle experiments performed on vesicles made from the basolateral membrane, the overshoot in intravesicular [glucose] does not occur, even in the presence of an inward Na+ gradient. Thus, the Na/glucose cotransporter is restricted to the apical membrane.

Contributed by Gerhard Giebisch and Erich Windhaget

Clinical Correlates of Splay in the Glucose Titration Curve

Splay can be clinically important. Patients with proximal tubule disease—mainly of hereditary nature and often observed in children—have a lower threshold but a normal Tm. Thus, splay is exaggerated, presumably because some individual cotransporters have a low glucose affinity but normal maximal transport rate (see Equation 5–16 on p. 116 in the text). This abnormality results in glucose excretion at a lower than normal plasma [glucose]. Other patients have a normal threshold but a significantly reduced Tm (primary renal glucosuria). These patients, including those with Fanconi syndrome, have a reduced number of Na/glucose cotransporters. Thus, once plasma [glucose] exceeds the threshold, these patients excrete more glucose than normal. In addition, destruction of renal parenchyma by disease processes may diminish the activity of the basolateral Na–K pump and thus reduce the driving force for Na+across the brush border membrane, resulting in glucosuria.

Contributed by Erich Windhager and Gerhard Giebisch

Glucose Clearance

As stated in the text, the glucose clearance is zero at plasma glucose values below the threshold and gradually rises as plasma glucose rises. We can express the excretion of glucose quantitatively at plasma concentrations beyond the threshold, where the glucose reabsorption rate (Tm) has reached its maximum:

image

All three terms in the previous equation are plotted in Figure 36-4A. The first term in the equation (UG × image) is represented by the green curve. The second term (GFR × PG) is the yellow curve. The term (TG) is the red curve. Dividing both sides of the equation by PG yields the glucose clearance (CG):

image

Thus, as plasma [glucose] approaches infinity, the right-hand term reduces to GFR, and therefore glucose clearance approaches inulin clearance (Figure 36-4B). In patients with an extremely low threshold (see webnote 0800--Clinical Correlates of Splay in the Glucose Titration Curve), glucose clearance even more closely approximates GFR.

Contributed by Erich Windhager and Gerhard Giebisch

Role of OAT1 and OAT3 in the Renal Transport of Organic Anions

OAT1 and OAT3 transporters are members of the SLC22 family of organic ion transporters (see Table 5–4 on p. 118 as well as p. 129 in the text). The OAT1 and OAT3 proteins shown in Figure 36-8B on p. 807 are in fact the same transporters as shown in Figure 36-9B on p. 808. The “organic anion” entering the cell across the basolateral membrane in Figure 36-8B could be any of several monovalent organic anions (including the nonphysiological PAH), and the dicarboxylate exiting the cell across the basolateral membrane in Figure 36-9B could be any of several dicarboxylates, including αKG.

REFERENCE

Koepsell H and Endou H: The SLC22 drug transporter family. Pflügers Arch 447:666–676, 2004.

Contributed by Emile Boulpaep and Walter Boron

Tertiary Active Transport of Urate

The apical uptake of urate in exchange for monocarboxylates (URAT1) or for dicarboxylates (OAT4) in Figure 35-11B are examples of tertiary active transport.

In the case of monocarboxylates, an undefined Na/monocarboxylate cotransporter at the apical membrane mediates the uptake of monocarboxylates (an example of secondary active transport via Na).

In the case of dicarboxylates, NaDC1 at the apical membrane mediates the uptake of dicarboxylates (also an example of secondary active transport via Na).

In both cases, the Na–K pump at the basolateral membrane (a primary active transporter) extrudes Na+ from the cell and thereby establishes the out-to-in Na+ gradient.

Treatment of Salicylate Poisoning

As noted in the text on p. 811, physicians can treat salicylate by using the principle outlined in Figure 36-13C, namely by increasing the urinary pH and thereby increasing the trapping of the salicylate anion in the urine. The most common causes of salicylate poisoning are the accidental or suicidal overdose of aspirin. Signs of the poisoning include a severe metabolic acidosis and a compensatory respiratory alkalosis. The twofold purpose of the treatment is to neutralize the metabolic acidosis and to eliminate the salicylate. The treatment is to administer NaHCO3 intravenously to alkalinize the urine above a pH of 7.5 while making sure that the plasma pH does not exceed 7.55. By the effect shown in Figure 36-13C, this maneuver increases the excretion of the poison.

Treatment of a PCP Overdose

Phencyclidine hydrochloride—whose formal name is phenyl cyclohexyl piperidine HCl (PCP) and whose street names include “angel dust”—can be thought of as the salt BH+ Cl. When dissolved in water, the BH+ will equilibrate with the neutral form of the drug (B) as follows: BH+ B + H+.

It is possible to treat PCP intoxication by using the principle outlined in Figure 36-13D, namely by decreasing the urinary pH and thereby increasing the trapping of the phencyclidine cation (BH+) in the urine. Although originally developed as an intravenous anesthetic in the 1950s, its use was discontinued in 1965 because of its side effects, which include hallucinations and confusion. Today, the most common cause of PCP intoxication is recreational drug use. The therapy has two goals: to promote the rapid urinary excretion of the drug and to treat the neurological symptoms with antidotes that target the neurotransmitter systems most activated in a particular patient. Regarding the urinary excretion, acidification of the urine can increase the rate of excretion 100-fold. Acidification of the urine can be promoted by administering vitamin C (ascorbic acid) or ammonium chloride. By the effect shown in Figure 36-13D, this maneuver increases the excretion of the drug. In the absence of urinary acidification, the slow clearance of PCP means that screening for substance abuse can produce a positive urine test as many as 7 days after casual use and 30 days after chronic use.

The same approach can be used to increase the clearance of other weak bases, such as the psychotropic drug remoxipride.

REFERENCE

Price WA and Giannini AJ: Management of PCP intoxication. Am Fam Physician 32:115–118, 1985.

Widerlov E, Termander B, and Nilsson MI: Effect of urinary pH on the plasma and urinary kinetics of remoxipride in man. Eur J Clin Pharmacol 37:359–363, 1989.

http://www.drug-addiction.net

http://www.sayno.com/pcp.html

Contributed by Erich Windhager and Gerhard Giebisch

The Type II Na/Phosphate Cotransporter NaPi-IIa

As noted in the text, the apical Na/phosphate cotransporter (NaPi-IIa, SLC34A1—see Table 5–4 on p. 118 in the text) translocates three Na+ ions and one divalent phosphate ion (HPO2–4) and thus the process is electrogenic. As pH along the lumen of the proximal tubule falls, the relative concentration of H2PO2–4 falls as well so that one might expect that the uptake of inorganic phosphate by NaPi-IIa would become less effective. On the other hand, the affinity of NaPi-IIa for HPO2–4 is so high (Ki ≌ 50μM) that the effect should not be severe.

Contributed by Jürg Biber

Regulation of Ca2+ Reabsorption

In addition to the factors discussed beginning on p. 817 in the text, several other factors modulate the handling of Ca2+.

Effective Circulating Volume

A reduction in effective circulating volume triggers four parallel effector pathways (p. 869) that act to restore volume. One of these pathways—the sympathetic division of the ANS—increases Na+reabsorption by the proximal tubule (p. 793). Because proximal tubule Ca2+ reabsorption depends largely on transepithelial voltage and solvent drag (p. 815), which in turn depend on Na+ reabsorption, it is not surprising that volume contraction, which increases Na+ reabsorption, also increases Ca2+ reabsorption. Volume expansion has the opposite effects on both Na+ and Ca2+ reabsorption.

Acid–Base Balance

Metabolic alkalosis increases renal Ca2+ reabsorption (i.e., decreases excretion) at the level of the distal convoluted tubule, probably by relieving the inhibition of apical TRP5/6 Ca2+ channels by H+. This effect is independent of the PTH status, as well as of Na+ transport. The latter observation suggests that factors such as solvent drag and diffusion are not involved.

Phosphate Depletion

Chronic phosphate depletion impairs Ca2+ reabsorption at both proximal and distal sites. The effects are independent of the decrease in PTH secretion that follows phosphate depletion; the basis for the effect is otherwise unknown.

Contributed by Gerhard Giebisch and Erich Windhager

Regulation of Ca2+ and Mg2+ Reabsorption

In addition to the factors discussed beginning on p. 817 in the text, several other factors modulate the handling of Ca2+:

Effective Circulating Volume: A reduction in effective circulating volume triggers four parallel effector pathways (p. 869) that act to restore volume. One of these pathways—the sympathetic division of the ANS—increases Na+reabsorption by the proximal tubule (p. 793). Because proximal tubule Ca2+ reabsorption depends largely on transepithelial voltage and solvent drag (p. 807), which in turn depend on Na+reabsorption, it is not surprising that volume contraction, which increases Na+ reabsorption, also increases Ca2+ reabsorption. Volume expansion has the opposite effects on both Na+ and Ca2+ reabsorption.

Acid–Base Balance: Metabolic alkalosis increases renal Ca2+ reabsorption (i.e., decreases excretion) at the level of the distal convoluted tubule, probably by relieving the inhibition of apical TRP5/6 Ca2+channels by H+. This effect is independent of the PTH status, as well as of Na+ transport. The latter observation suggests that factors such as solvent drag and diffusion are not involved.

Phosphate Depletion: Chronic phosphate depletion impairs Ca2+ reabsorption at both proximal and distal sites. The effects are independent of the decrease in PTH secretion that follows phosphate depletion; the basis for the effect is otherwise unknown.

In addition to the factors discussed beginning on p. 820, other factors modulate the handling of Mg2+, of which two are discussed here:

Effective Circulating Volume: As is true for Ca2+, a decrease in effective circulating volume leads to an increase in Na+ reabsorption and an increase in the forces that drive Mg2+ reabsorption via paracellular pathways. Thus, volume contraction increases Mg2+ reabsorption, whereas volume expansion has the opposite effect.

Acid–Base Balance: As is the case for Ca2+, alkalosis increases Mg2+ reabsorption. However, for Mg2+, the effect is at the level of the TAL.

Contributed by Gerhard Giebisch and Erich Windhager

Regulation of Mg2+Reabsorption

In addition to the factors discussed beginning on p. 820 in the text, other factors modulate the handling of Mg2+, of which two are discussed here:

Effective Circulating Volume: As is true for Ca2+, a decrease in effective circulating volume leads to an increase in Na+ reabsorption and an increase in the forces that drive Mg2+ reabsorption via paracellular pathways. Thus, volume contraction increases Mg2+ reabsorption, whereas volume expansion has the opposite effect.

Acid–Base Balance: As is the case for Ca2+, alkalosis increases Mg2+ reabsorption. However, for Mg2+, the effect is at the level of the TAL.

Contributed by Gerhard Giebisch and Erich Windhager

Hormonal Response to Acute K+ Loading

As noted in the textbook, ingestion of a K+-rich meal leads to only small increases in extracellular [K+]o because of the actions of insulin, epinephrine, and aldosterone on target tissues (see Figure 37-3 on p. 823).

As discussed on p. 1079, increases in [K+]o depolarize cells in the pancreatic islets, leading to the release of insulin.

As discussed on p. 1071, chromaffin cells in the adrenal medulla secrete epinephrine and, to a lesser extent, norepinephrine. Extremely large increases in [K+]o—so large that they would be fatal—do indeed promote the secretion of the aforementioned catecholamines. Physiological increases in [K+]o do not. Thus, physiological levels of epinephrine are permissive for K+ sequestration.

As discussed on p. 1068, increases in [K+]o depolarize glomerulosa cells in the adrenal cortex, promoting the secretion of aldosterone.

Contributed by Emile Boulpaep and Walter Boron

Electrical Profile across an Epithelial Cell in the Thick Ascending Limb

Figure 5-20B on p. 142 of the text shows the electrical profile typical of a cell from the renal proximal tubule. There, Vte (the transepithelial potential difference) is -3 mV with reference to the interstitial space because the membrane potential of -67 mV across the apical membrane (Va) is less negative than the membrane potential of -70 mV across the basolateral membrane (Vbl).

The situation in the thick ascending limb (TAL) is a right-to-left mirror image of that in Figure 5-20B. A typical Vte in the TAL would be +15 mV (see Table 35–1 on p. 785) with reference to the interstitial space. The reason for this lumen-positive Vte is that the membrane potential across the apical membrane (e.g., -70 mV) is more negative than the membrane potential across the basolateral membrane (e.g., -55 mV).

Contributed by Emile Boulpaep and Walter Boron

Paradoxical Inhibition of K+ Secretion by Thiazide Diuretics in Low-Cl- States

As noted on p. 828 of the text, K+ secretion in the distal nephron is strongly flow dependent as the result of the high K+ permeability of the apical membrane. Figure 37-8 illustrates this effect. Accordingly, all diuretics (e.g., furosemide, thiazides, and acetazolamide) that act proximal to the collecting duct—and thus increase the luminal flow at the level of the collecting duct—enhance K+ secretion by the collecting duct. Thus, these diuretics enhance K+excretion and are termed kaliuretic agents (i.e., they are not “K+ sparing” diuretics).

An exception to this general rule is the administration of thiazide diuretics in low-Cl states (hypochloremia), where the diuretic inhibits K+ secretion. The basis of this paradox is that because luminal [Cl] is low all along the nephron—including the cortical collecting tubule (CCT)—the apical K/Cl cotransporter (KCC) in the CCT (Figure 37-7D) makes an unusually large contribution to K+ secretion in a low-Clstate. When such a patient takes a thiazide diuretic, the drug inhibits the Na/Cl cotransporter in the apical membrane of the distal convoluted tubule (DCT), which is illustrated in Figure 35-4C. As a result, luminal [Cl] is higher than it otherwise would be in the DCT and also downstream in the CCT. In the CCT, the higher than otherwise luminal [Cl] now acts as a brake on the apical K/Cl cotransporter, thereby decreasing K+ secretion.

Contributed by Erich Windhager and Gerhard Giebisch

Acute Effects of IV Aldosterone

The figure shows the renal effects of intravenously administered aldosterone on electrolyte excretion in humans. The acute effects include significant decreases in Na+ and Cl excretion, as well as increases in K+ and NH4+ excretion. The reverse changes occur in adrenalectomy, and the administration of mineralocorticoids (e.g., aldosterone) promptly reverses these deficiencies.

image

Data from Liddle GW: Aldosterone antagonists. Arch Intern Med 102:998–1005, 1958.

Contributed by Erich Windhager and Gerhard Giebisch

“Effective Osmolal-less” versus “Osmolal-less” Water Clearance

In the textbook, we defined free-water clearance as the clearance of water that is devoid of all solutes. However, if you were interested in how a gain or loss of water would affect cell volume, you would really be interested in the clearance of water that is devoid of impermeant or effective solutes (see discussion of effective osmolality on p. 138). These effective osmoles do not include urea because cells are generally highly permeable to urea due to the presence of transport pathways for urea (see p. 797). Therefore, it may be useful to consider the clearance of water that is devoid of all effective osmoles. We define this as “effective osmolal-less water clearance” to distinguish it from classical free-water clearance, which is the “osmolal-less water clearance.”

Urea can be one of the major contributors to urine osmolality UOsm and thus an important contributor to osmolal clearance:

Equation 1

image

Equation 1 is also Equation 38–6 on p. 836. Because urea equilibrates freely across cell membranes, it does not influence the effective plasma osmolality (Peffect-Osm) nor the distribution of water between cells and the extracellular fluid. Thus, we could convert Equation 1 to an expression for effective osmolal clearance by substituting Ueffective-Osm for UOsm in Equation 1 and Peffective-Osm for POsm. The resulting new expression for effective osmolal clearance is

Equation 2

image

Note that in both the numerator and the denominator, we are only considering the effective osmoles in urine and plasma.

By analogy to Equation 38–7 in the textbook, the effective osmolal-less water clearance is

Equation 3

image

Because plasma levels of urea are generally quite low (i.e., Peffective-Osm POsm), the important issue is the extent to which urea contributes to the total osmolality of the urine (i.e., the extent to which UOsm exceeds Ueffective-Osm).

Contributed by Emile Boulpaep and Walter Boron

Simplifications of the Countercurrent Multiplier Model in Figure 38-3

The model shown in Figure 38-3 is simplified in several respects:

• Perhaps the most significant simplification is that we regard the ascending limb as being functionally uniform from bottom to top. In fact, the bottom of the ascending limb is “thin” (tALH), whereas the top is “thick” (TAL). Both the tALH and the TAL separate salt from water, but they do so by very different mechanisms. As discussed in the text, the “single effect” is the result of passive NaCl reabsorption in the thin and active NaCl reabsorption in the thick ascending limb (p. 833).

• We assume that at every site, the ascending limb establishes a transepithelial gradient of 200 mOsm.

• In Figure 38-3, we separate the generation of the single effect (left column) from the axial movement of fluid along the loop (right column). In fact, the two occur simultaneously.

• Figure 38-3 considers only four cycles rather than the essentially limitless number of cycles in the real kidney. Thus, in our example, we reached an osmolality of only 600 mOsm at the tip of the loop, whereas 1200 mOsm would be a more realistic maximal value. More iterations would generate a larger tip osmolality.

• The model does not include any dissipation of the gradient along the corticomedullary axis by either diffusion or washout via medullary blood flow. In the text, we noted that after 39 cycles of our model, we would eventually achieve an osmolality of 1200 mOsm at the tip of the loop. What we did not say is that if we had continued with even more iterations, we would have achieved even higher, unrealistic osmolalities. In the real kidney, a balance between the single effect and washout would create a stable corticomedullary gradient of osmolality.

Contributed by Emile Boulpaep and Walter Boron

Spectrum of Urinary Concentrating Abilities among Different Mammals

The countercurrent multiplication theory accounts for the observation that the osmolality of the final urine in different species is roughly proportional to the relative length of the loop of Henle. Comparing the absolute lengths of loops of Henle is a gross simplification because of the large variation of the absolute size of kidneys in different species. A better correlation exists between maximal concentrating ability and the ratio of medullary thickness to cortical thickness. For instance, the beaver, whose kidney has no papilla, maximally concentrates the final urine to approximately 600 mOsm and has a medullary:cortical ratio of 1.3. Humans, on the other hand, achieve a maximal concentration of approximately 1200 mOsm and have a medullary:cortical ratio of 3.0. Finally, the desert rodent Psammomys, which can achieve a urine osmolality of almost 6000 mOsm, has a medullary:cortical ratio of 10.7.

Another important factor for explaining interspecies differences in concentrating ability is the fraction of nephrons that have long loops of Henle. This fraction varies from 0% (i.e., long loops are totally absent) in the beaver to approximately 14% in humans and 100% in the desert rodent Psammomys.

Contributed by Erich Windhager and Gerhard Giebisch

Simplifications of the Countercurrent Multiplier Model in Figure 38-3

The model shown in Figure 38-3 is simplified in several respects:

• Perhaps the most significant simplification is that we regard the ascending limb as being functionally uniform from bottom to top. In fact, the bottom of the ascending limb is “thin” (tALH), whereas the top is “thick” (TAL). Both the tALH and the TAL separate salt from water, but they do so by very different mechanisms. As discussed in the text, the “single effect” is the result of passive NaCl reabsorption in the thin and active NaCl reabsorption in the thick ascending limb (p. 833).

• We assume that at every site, the ascending limb establishes a transepithelial gradient of 200 mOsm.

• In Figure 38-3, we separate the generation of the single effect (left column) from the axial movement of fluid along the loop (right column). In fact, the two occur simultaneously.

• Figure 38-3 considers only four cycles rather than the essentially limitless number of cycles in the real kidney. Thus, in our example, we reached an osmolality of only 600 mOsm at the tip of the loop, whereas 1200 mOsm would be a more realistic maximal value. More iterations would generate a larger tip osmolality.

• The model does not include any dissipation of the gradient along the corticomedullary axis by either diffusion or washout via medullary blood flow. In the text, we noted that after 39 cycles of our model, we would eventually achieve an osmolality of 1200 mOsm at the tip of the loop. What we did not say is that if we had continued with even more iterations, we would have achieved even higher, unrealistic osmolalities. In the real kidney, a balance between the single effect and washout would create a stable corticomedullary gradient of osmolality.

Contributed by Emile Boulpaep and Walter Boron

Urea Reabsorption in the Distal Nephron

Of the urea filtered in the glomerulus, the proximal tubule reabsorbs ~50% by solvent drag (p. 783 in the text), leaving ~50% remaining in the nephron lumen as the fluid enters the thin descending limb. As the thin limbs of juxtamedullary nephrons (which make up ~10% of all nephrons) dip into the inner medulla (remember, these are the only nephrons whose loops of Henle dip into the inner medulla—see Fig. 33–2 on p. 751), they secrete—under maximal antidiuretic conditions—an amount of urea equivalent to ~50% of the total filtered load of urea summed over all of the nephrons. In other words, by the time the luminal fluid of juxtamedullary nephrons reaches the beginning of the TAL, the luminal urea content must be an extremely high fraction of the filtered load of these nephrons. The superficial nephrons, on the other hand, have ~50% of their filtered load of urea remaining (the fraction not reabsorbed by their proximal tubules) by the time their fluid reaches the beginning of their TALs. Averaging over all nephrons—the juxtamedullary nephrons with high urea levels and superficial nephrons with low urea levels—the fluid entering the “average” TAL has an amount of urea that corresponds to 100% of the total filtered load of urea for the entire kidney. This is the 100% to which the green box points in Figure 38-5.

Figure 38-5 indicates that, by time the tubule fluid reaches the junction of the outer and inner medulla, only 70% of the total filtered load of urea remains. Because the TAL, DCT, CNT, and CCT all have low urea permeabilities, it is perhaps somewhat surprising that 30% should have disappeared. Box #3 in the figure shows 30% of the total filtered load of urea being reabsorbed. Two events contribute to this 30%: (1) In the relatively few nephrons that are juxtamedullary, the [urea] in the TAL and CCT is very high, providing a gradient for passive urea loss in the cortex, where the interstitial [urea] is little more than in plasma (i.e., ~5 mM). (2) In the collecting-duct system, fluid from the many superficial nephrons (each of which has a relatively low amount of its filtered load of urea remaining) admixes with that from the few juxtamedullary nephrons (each of which has far more than its filtered load of urea remaining), producing a blend with an intermediary level of “urea remaining.” Thus the admixture of a few hundred percent remaining (from the juxtamedullary nephrons) with 50% remaining (from the superficial nephrons) contributes to the overall decrease in the percent of urea remaining to 70%.

Contributed by Erich Windhager and Gerhard Giebisch

Anatomic Arrangements between Vasa Recta and Thin Limbs in the Medulla

Although in some species, the ascending and descending vasa recta are closely intermingled in vascular bundles within the medulla, such close contact between the ascending and descending vessels is not necessary to create an effective countercurrent exchanger. It is only necessary that vessels at the same level equilibrate with the same interstitial fluid.

Contributed by Erich Windhager and Gerhard Giebisch

Multiple Effects of AVP on AQP2 Activity

On p. 846 in the text, we mentioned that arginine vasopressin (AVP) acts through cAMP and protein kinase A (PKA) to phosphorylate AQP2 and other proteins, with the net effect of increasing the trafficking of AQP2 from vesicular pools to the apical membrane of the collecting duct cells. Thus, AVP increases the number of water channels per unit area of apical membrane.

In addition, PKA also phosphorylates AQP2 as well as cAMP response element binding protein (CREB; p. 92). The phosphorylation of CREB, in the longer term, stimulates AQP2 synthesis, as indicated in Figure 38-9 on p. 847.

Contributed by Erich Windhager and Gerhard Giebisch

Pulmonary Disorders Causing SIADH

Several chronic, nonmalignant pulmonary disorders, including positive pressure ventilation, impede venous return. The return is reduced stretch of the atrial receptors (Figure 23-7 on p. 568 in the text). As discussed on p. 568, the afferent fibers from these stretch receptors project not only to the medulla (where they produce cardiovascular effects) but also to the hypothalamic neurons that synthesize and release arginine vasopressin (AVP). Decreased atrial stretch increases AVP release. Thus, the aforementioned pulmonary disorders result in a syndrome of inappropriate release of AVP—SIADH.

Contributed by Emile Boulpaep and Walter Boron

Acidoses of Renal Origin

Any overall decrease in the ability of the kidneys to excrete the daily load of approximately 70 mmol of nonvolatile acids will lead to a metabolic acidosis. In the strict sense of the term, renal tubular acidosis (RTA) is an acidosis that develops secondary to the dysfunction of renal tubules. In addition, an overall decrease in useful renal mass and GFR—as occurs in end-stage renal disease—also leads to an acidosis of renal origin. One system of organizing these maladies recognizes four types of RTAs:

• Uremic acidosis or RTA of glomerular insufficiency: The fundamental problem is a decrease in the total amount of NH3 that the proximal tubule can synthesize from glutamine (see p. 859 in the text).

• Proximal (type II) RTA: A specific dysfunction of the proximal tubule reduces the total amount of HCO3 that these nephron segments reabsorb.

• Classical distal (type I) RTA: A specific dysfunction of the distal tubule reduces the total amount of HCO3 that these nephron segments reabsorb. The mechanisms can include mutations to key proteins involved in distal H+secretion, such as H+ pumps, Cl–HCO3 exchangers, and carbonic anhydrase.

• Generalized distal (type III) RTA: A global dysfunction of the distal tubule—secondary to aldosterone deficiency or aldosterone resistance (p. 864)—leads to a reduced net excretion of acid.

Contributed by Erich Windhager and Gerhard Giebisch

Ammonium Secretion by the Medullary Collecting Duct

The medullary collecting duct also secretes some NH4+. As described in Figure 39-5D on page 860, the thick ascending limb (TAL) of juxtamedullary nephrons reabsorbs some NH4+ and deposits this NH4+ in the medullary interstitium, where it is partitioned between ammonium and ammonia according to the equilibrium NH4+ NH3 + H+. As pointed out in Figure 39-5D, this interstitial NH4+ (and NH3) can have three fates: (1) Some recycles back to the late proximal tubule and descending thin limb of Henle, (2) some bypasses the cortex by being secreted into the medullary collecting duct, and (3) some is washed out by the blood for export to the liver.

The mechanism of pathway (2) is depicted in Figure 39-5E. NH3 diffuses from the medullary interstitium, through the tubule cell and into the lumen via nonionic diffusion. The NH3 may pass through membrane proteins of the Rh family. The parallel extrusion of H+ across the apical membrane of the collecting-duct cell provides the luminal H+ that then titrates the luminal NH3 to NH4+, which is excreted. This luminal H+ pumping also generates OH inside the cells. Although not shown in Figure 39-5E, intracellular carbonic anhydrase converts this newly created OH (along with H2O) to HCO3, and basolateral Cl-HCO3 exchangers then export this newly created HCO3 to the interstitium. The HCO3, of course, ultimately is washed out by the blood. Thus, for each NH4+ formed in the lumen of the collecting duct by this route, the tubule cell transfers one “new” HCO3 to the blood.

Figure 39-5E also shows that the Na-K pump can also transport NH+4 directly into the collecting-duct cell. This intracellular NH+4 can then dissociate into NH3 (which can diffuse into the lumen) and H+(which moves into the lumen via the apical H+ pump), with the ultimate formation of NH4+ in the lumen. The NH+4 that enters the collecting-duct lumen by this route does not generate a new HCO3 ion.

Contributed by Erich Windhager, Gerhard Giebisch, Emile Boulpaep, and Walter Boron

Renal Na–H Exchangers

As described on p. 128 of the text, several related genes encode Na–H exchangers (see WebNote 0068 --The Na-H Exchangers [NHEs]).

In the renal proximal tubule, Na–H exchange is blocked by the removal of Na+ from the lumen. Although all Na–H exchangers are far less sensitive to amiloride than the ENaC epithelial Na+ channels (p. 786and Figure 35-4D), the apical NHE3 isoform in the proximal tubule is even less amiloride sensitive than the ubiquitous or “housekeeping” NHE1. The NHE1 isoform is present in the basolateral membranes of several nephron segments. The role of basolateral Na–H exchangers in acid-secreting nephron segments, such as the proximal tubule, is unclear; they may help regulate intracellular pH independently of transepithelial H+ secretion.

Given a 10:1 concentration gradient for Na+ from the proximal tubule lumen to the cell interior, a maximal pH gradient of 1 pH unit can be achieved by this gradient. Indeed, the late proximal tubule may have a luminal pH as low as approximately 6.4.

The NHE2 isoform is present at the apical membrane of the DCT, where it may participate in the apical step of H+ secretion.

Contributed by Peter Aronson, Emile Boulpaep, and Walter Boron

The β Intercalated Cell

Electrogenic H+ pumps are also present in β intercalated cells, which, to a first approximation, are backward α intercalated cells (Figure 39-4D). We discuss β intercalated cells (ICs) in the text on p. 863.

In β ICs, the electrogenic H+ pump is present in the basolateral membrane, and the Cl- HCO3 exchanger is in the apical membrane. Thus, unlike the α ICs, which engage in net HCO3 reabsorption, the β ICs engage in net HCO3secretion.

An interesting difference between the α ICs and the β ICs is that in the α cells, the Cl-HCO3 exchanger is a variant of AE1 (the Cl–HCO3 exchanger in red blood cells and a member of the SLC4 family), whereas in the β cells the Cl–HCO3 exchanger is molecularly quite different, being a member of the SLC26 family

In addition to the switch from α to β ICs, HCO3 secretion can also be stimulated by increased luminal del