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Bioenergetics of Exercising Humans

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Abstract

Human muscles, limbs and supporting ventilatory, cardiovascular, and metabolic systems are well adapted for walking, and there is reasonable transfer of efficiency of movement to bicycling. Our efficiency and economy of movement of bipedal walking (≈30%) are far superior to those of apes. This overall body efficiency during walking and bicycling represents the multiplicative interaction of a phosphorylative coupling efficiency of ≈60%, and a mechanical coupling efficiency of ≈50%. These coupling efficiencies compare well with those of other species adapted for locomotion. We are capable runners, but our speed and power are inferior to carnivorous and omnivorous terrestrial mammalian quadrupeds because of biomechanical and physiological constraints. But, because of our metabolic plasticity (i.e., the ability to switch among carbohydrate (CHO)‐ and lipid‐derived energy sources) our endurance capacity is very good by comparison to most mammals, but inferior to highly adapted species such as wolves and migratory birds. Our ancestral ability for hunting and gathering depends on strategy and capabilities in the areas of thermoregulation, and metabolic plasticity. Clearly, our competitive advantage of survival in the biosphere depends in intelligence and behavior. Today, those abilities that served early hunter‐gatherers make for interesting athletic competitions due to wide variations in human phenotypes. In contemporary society, the stresses of regular physical exercise serve to minimize morbidities and mortality associated with physical inactivity, overnutrition, and aging. © 2012 American Physiological Society. Compr Physiol 2:537‐562, 2012.

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Figure 1. Figure 1.

Antoine‐Laurent de Lavoisier measures oxygen consumption on co‐investigator Armand Seguin during foot treadle exercise, circa 1780. Drawings ascribed to his wife Marie Anne Paulze Lavoisier, who depicted herself at the table on the far right. The drawing is entitled “Expérience sur la respiration humaine” (Experiments into Respiration). Courtesy of the Division of Rare and Manuscript Collections, Cornell University Library.

Figure 2. Figure 2.

Group mean values (± SE) of studies on 17 men showing linear and parallel increments in pulmonary and working muscle (leg) oxygen uptake. Pulmonary and leg VO2 measurements yield delta efficiencies of measurements (29.1 ±0.6%) and (33.7 ± 2.4%) for whole body and working muscles, respectively. The difference between y intercepts shows that the body provides significant metabolic support for processes outside the exercising legs, but that these metabolic “costs,” such as the work of breathing and gluconeogenesis, change in proportion to muscle power output. From Poole et al. and used with permission.

Figure 3. Figure 3.

Working muscle respiratory quotient (RQ) as determined by femoral arterial and venous CO2 and O2 concentration difference measurement. Values are means ± SEM for eight subjects. Exercise data are means of last 30 min of exercise. Subjects studied 2× before training (i.e., @ 45% and 65% VO2peak), and twice after training (i.e., ABT = same absolute intensity as 65% pretraining, and RLT = same relative intensity as pretraining, i.e., 65% VO2peak). *Significantly different from pretraining (45%) (P < 0.05); Δsignificantly different from rest, P < 0.05). Results show working muscle to be carbohydrate dependent, both before and after training. From Bergman et al. and used with permission.

Figure 4. Figure 4.

Results of an extensive literature search showing blood glucose and free fatty acid flux rates (Ra) and net muscle glycogenolysis as functions of relative exercise intensity (REL) as given by % VO2max. This form of analysis indicates exponential increments in muscle glycogenolysis and glucose Ra as functions of relative exercise intensity. In contrast, the analysis shows multicomponent polynomial response of plasma FFA flux, with easy to moderate intensity exercise (i.e., 25%‐40% VO2max) eliciting a large rise in flux, but crossover and decreasing flux at approximately 50% VO2max. Note that plasma free fatty acid (FFA) flux is predicted to reach minimal values as VO2max is approached. For glycogen utilization, y = 2.11 e(0.04×), r2 = 0.87; for glucose Ra, y = 9.8 e(0.02×), r2 = 0.84, and for FFA Ra, y = −0.833 + 1.14× − 0.013×2, r2 = 0.87. From Brooks and Trimmer and used with permission.

Figure 5. Figure 5.

Effect of exercise intensity on the balance of lipid (°) and carbohydrate (▪) oxidation in four mammalian species (goats, dogs, rats, and humans). Mean (± SEM) data on dogs and goats are shown in the center and quadrants; other data on rats and humans have been included from the literature. Regardless of body size and configuration or aerobic capacity, the same patterns of energy substrate partitioning during physical activity are apparent. In this respect the data are to be compared to those in Figure . Redrawn, with permission, from two separate figures in Roberts et al. by GAB.

Figure 6. Figure 6.

Relationship between respiratory gas exchange ratio RER = VCO2/VO2 in trained (T) and untrained (UT) men during sustained exercise. Subjects were studied in fed and over night fasted (postabsorptive) conditions. Trained and fasted individuals have the lowest RERs, but only during easy to mild‐intensity exercise. Overall, results show predominance of carbohydrate (CHO) over Lox during exercise regardless of training state or dietary condition. From Bergman and Brooks and used with permission.

Figure 7. Figure 7.

(A) Effect of exercise intensity and training on the plasma glucose rate of disappearance (Rd). Values are means ±SE of last 15 and 30 min for rest and exercise, respectively, for 17 women. (B) Relationship between glucose rate of disappearance (Rd) exercise intensity as given by %VO2max in 19 men and 17 women, before and after 10 to 12 weeks of endurance training. Note the exponential rise in glucose use as a function of exercise power output. Values are means ± SE; Δsignificantly different from rest, P < 0.05. *Significantly different from 45UT (untrained), P < 0.05. From Friedlander et al. and used with permission.

Figure 8. Figure 8.

Contributions of energy from different substrate sources during rest and exercise before and after training. SE and statistical symbols are for total energy expenditure only. Values are for nine subjects. CHO, carbohydrate. ΔSignificantly different from rest; *significantly different from 45UT; +significantly different from 65UT; and #significantly different from ABT, P < 0.05. From Friedlander et al. and used with permission.

Figure 9. Figure 9.

(A) Effect of exercise intensity and training on plasma FFA Rd. Values are means 6 SE of the last 15 and 30 min for rest and exercise, respectively; n = 8 young women. ΔSignificantly different from rest; *significantly different from 45UT; +significantly different from 65UT; and #significantly different from ABT (P < 0.05). From Friedlander et al. . (B) Effect of exercise intensity and training on plasma FFA rate of disappearance (Rd) in 10 young men before and after 10 weeks of supervised endurance training. Values are means ± SE of the last 15 and 30 min for rest and exercise, respectively; n = 9 subjects. *Significantly different from pretraining (45UT); Δsignificantly different from rest; +significantly different from 65UT; and #significantly different between resting conditions, P < 0.05. From Friedlander et al. and used with permission.

Figure 10. Figure 10.

(A) Contributions of different lipid sources to total lipid metabolism during rest and exercise before and after training. SE and statistical symbols are for total lipid metabolism only; n = 8, mean ± SE. ΔSignificantly different from rest and *significantly different from 45UT (P < 0.05). (B) Contributions of energy from different substrate sources during rest and exercise normalized to percent energy expenditure; n = 8. From Friedlander et al. .

Figure 11. Figure 11.

Effect of exercise intensity and training on glycerol venous‐arterial difference. Values are mean ± SEM for eight subjects. Little net glycerol release occurs from working limb muscle indicative of insignificant intramuscular triglyceride (IMTG) mobilization during contractions. Symbols represent moderate intensity exercise before endurance training (45% Pre), hard exercise before training (65% Pre), after training the same absolute (ABT) intensity that elicited 65% VO2peak before training (65% Old), and exercise that elicited 65% of the posttraining VO2peak [new, relative hard exercise (RLT)]. From Bergman et al. and used with permission.

Figure 12. Figure 12.

Effects of graded exercise and exercise training on resting and working limb triglyceride (A) and cholesterol LDL‐C (B) and HDL‐C (C). Exercise and exercise training effects are physiologically insignificant. From Jacobs et al. and used with permission.

Figure 13. Figure 13.

Absolute substrate oxidation rates (mean ± SEM) in men before during and after 60 min of exercise at 65% VO2peak. Lipid and CHO oxidation rates shown by solid and crosshatched bars, respectively. Data show dominance of CHO oxidation during physical activity, and crossover to lipid oxidation during recovery. Data on women are not shown. From Kuo et al. and used with permission.

Figure 14. Figure 14.

Plasma FFA rate of appearance (Ra) as determined from continuous infusion of [1−13C]palmitate in 10 men studied at rest and during and after two exercise intensities (45% VO2peak for 90 min and 65% VO2peak for 60 min). The same subjects were also studied on a nonexercise day (control) to account for diurnal variations. Plasma FFA Ra rose significantly during exercise, compared to preexercise rest, and remained elevated in 3 h of recovery whether compared to preexercise rest or time of day matched resting control. From Henderson et al. and used with permission.

Figure 15. Figure 15.

Effect of work rat and speed of movement on a leg cycle ergometer (mean ± SE) of 12 young males during steady‐rate exercise. Caloric values determined from VO2 and RER. The essentially linear relationship with perhaps a slight exponential rise in caloric output at higher work rates dictates either constant or decreasing efficiency. Because the caloric cost of each exercise power output increases with increments in pedaling speed, decreasing efficiency with increasing speed is indicated. Note that the y‐intercepts measured during unloaded cycling deviate from rest (≈ 1 kcal/min) and significantly from linearity for all but the slowest cycling cadence making “gross,” “net,” and “work” efficiency calculations invalid, and indicating use of the “delta” method of efficiency calculation. From Gaesser and Brooks and used with permission.

Figure 16. Figure 16.

The effect of work rate on delta (Δ) efficiency (mean ± SE) for 12 young men pedaling at a slow cadence (40 RPM) on a leg cycle ergometer. In contrast to other (gross, net, and work) modes of calculation, the data (From Fig. ) demonstrates decreasing efficiency with increments in power output. From Gaesser and Brooks and used with permission.

Figure 17. Figure 17.

The effect of work rate on delta (Δ) efficiency (mean ± SE) for 12 young men pedaling at a rapid cadence (100 RPM) on a leg cycle ergometer, calculations based on data in Figure . As with slow cadence pedaling (Fig. ), the results demonstrate decreasing efficiency with increments in power output when cycling at a fast cadence. Note that the range of computed efficiencies (25%‐35%) is similar for low and high cadence pedaling. From Gaesser and Brooks and used with permission.

Figure 18. Figure 18.

Effects of work rate on delta (Δ) efficiency (mean ± SE) for nine young men during treadmill gradient walking at 3.0, 4.5, and 6.0 km/h. Results gradient (vertical) work as well as horizontal work against an impeding force demonstrate decreasing efficiency with increments in muscle power output. As with results in [Figs. ()], computations based on caloric values determined from VO2 and RER during steady‐rate, submaximal exercise. From Donovan and Brooks and used with permission.

Figure 19. Figure 19.

Relationship between external work and metabolic cost of human interosseous (hand) muscle in which metabolic cost was determined by 31P‐MRS. The least squares linear regression of data yields a very high, 68% mechanical coupling efficiency (i.e., external work from ATP hydrolysis) [Work output (J) = 0.68 ± 0.09 ATP cost (J) − 2.2 ± 0.9 (J)]. Assuming a phosphorylative coupling efficiency of 50%, overall Δ efficiency approximates 34%. Used with permission. From Jubrias et al. and used with permission.

Figure 20. Figure 20.

Rate of muscle ATP turnover (mmol ATP/kg dry wt/s) during 0‐5, 5‐15, and 15‐180 s of two bouts of intense knee extensor exercise (EX1) and (EX2) separated by 3 min of rest. ATP turnover estimated as the sum of muscle anaerobic energy production determined as energy release related to utilization of CP (hatched part of bar), net lactate production determined as the sum of accumulation in muscle (open bar) and release to the blood (horizontally lined bar), net ATP utilization (vertically lined bar), others sources, and aerobic energy production (filled bar), determined from muscle oxygen uptake and estimated utilization of oxygen from myoglobin. Values are means ± SE. Modified from Figure 4 in Bangsbo et al. and used with permission.

Figure 21. Figure 21.

Muscle mechanical efficiency, determined as work per total energy production during the interval between 15‐180 s of an intense knee extensor exercise, in which total energy production was determined from metabolic measurements (open bars) and as the sum of total heat production and work performed. Values are means ± SE. #significantly (P < 0.05) different from values determined during the first 15 s of exercise. Values are means ± SE. Modified from Figure 6 in Bangsbo et al. and used with permission.

Figure 22. Figure 22.

A compilation of results of Stuart et al. who studied leg ergometer cycling efficiency of sprinters (fast twitch) and distance runners (slow twitch) athletes. (A) Higher rates of energy expenditure in sprinters exercising at given exercise power outputs indicate lesser efficiency. (B) Higher metabolic costs of exercise in sprinters makes for a lesser computed “gross” efficiency. (C, D) For both groups, delta (Δ) and instantaneous calculations show decreasing exercise efficiencies as exercise power outputs increase. Interestingly, while greater slopes of caloric expenditure regressed on power output make computed Δ and instantaneous efficiencies less at lower exercise power outputs, the computed efficiencies converge, or cross over at higher power outputs. Used with permission.



Figure 1.

Antoine‐Laurent de Lavoisier measures oxygen consumption on co‐investigator Armand Seguin during foot treadle exercise, circa 1780. Drawings ascribed to his wife Marie Anne Paulze Lavoisier, who depicted herself at the table on the far right. The drawing is entitled “Expérience sur la respiration humaine” (Experiments into Respiration). Courtesy of the Division of Rare and Manuscript Collections, Cornell University Library.



Figure 2.

Group mean values (± SE) of studies on 17 men showing linear and parallel increments in pulmonary and working muscle (leg) oxygen uptake. Pulmonary and leg VO2 measurements yield delta efficiencies of measurements (29.1 ±0.6%) and (33.7 ± 2.4%) for whole body and working muscles, respectively. The difference between y intercepts shows that the body provides significant metabolic support for processes outside the exercising legs, but that these metabolic “costs,” such as the work of breathing and gluconeogenesis, change in proportion to muscle power output. From Poole et al. and used with permission.



Figure 3.

Working muscle respiratory quotient (RQ) as determined by femoral arterial and venous CO2 and O2 concentration difference measurement. Values are means ± SEM for eight subjects. Exercise data are means of last 30 min of exercise. Subjects studied 2× before training (i.e., @ 45% and 65% VO2peak), and twice after training (i.e., ABT = same absolute intensity as 65% pretraining, and RLT = same relative intensity as pretraining, i.e., 65% VO2peak). *Significantly different from pretraining (45%) (P < 0.05); Δsignificantly different from rest, P < 0.05). Results show working muscle to be carbohydrate dependent, both before and after training. From Bergman et al. and used with permission.



Figure 4.

Results of an extensive literature search showing blood glucose and free fatty acid flux rates (Ra) and net muscle glycogenolysis as functions of relative exercise intensity (REL) as given by % VO2max. This form of analysis indicates exponential increments in muscle glycogenolysis and glucose Ra as functions of relative exercise intensity. In contrast, the analysis shows multicomponent polynomial response of plasma FFA flux, with easy to moderate intensity exercise (i.e., 25%‐40% VO2max) eliciting a large rise in flux, but crossover and decreasing flux at approximately 50% VO2max. Note that plasma free fatty acid (FFA) flux is predicted to reach minimal values as VO2max is approached. For glycogen utilization, y = 2.11 e(0.04×), r2 = 0.87; for glucose Ra, y = 9.8 e(0.02×), r2 = 0.84, and for FFA Ra, y = −0.833 + 1.14× − 0.013×2, r2 = 0.87. From Brooks and Trimmer and used with permission.



Figure 5.

Effect of exercise intensity on the balance of lipid (°) and carbohydrate (▪) oxidation in four mammalian species (goats, dogs, rats, and humans). Mean (± SEM) data on dogs and goats are shown in the center and quadrants; other data on rats and humans have been included from the literature. Regardless of body size and configuration or aerobic capacity, the same patterns of energy substrate partitioning during physical activity are apparent. In this respect the data are to be compared to those in Figure . Redrawn, with permission, from two separate figures in Roberts et al. by GAB.



Figure 6.

Relationship between respiratory gas exchange ratio RER = VCO2/VO2 in trained (T) and untrained (UT) men during sustained exercise. Subjects were studied in fed and over night fasted (postabsorptive) conditions. Trained and fasted individuals have the lowest RERs, but only during easy to mild‐intensity exercise. Overall, results show predominance of carbohydrate (CHO) over Lox during exercise regardless of training state or dietary condition. From Bergman and Brooks and used with permission.



Figure 7.

(A) Effect of exercise intensity and training on the plasma glucose rate of disappearance (Rd). Values are means ±SE of last 15 and 30 min for rest and exercise, respectively, for 17 women. (B) Relationship between glucose rate of disappearance (Rd) exercise intensity as given by %VO2max in 19 men and 17 women, before and after 10 to 12 weeks of endurance training. Note the exponential rise in glucose use as a function of exercise power output. Values are means ± SE; Δsignificantly different from rest, P < 0.05. *Significantly different from 45UT (untrained), P < 0.05. From Friedlander et al. and used with permission.



Figure 8.

Contributions of energy from different substrate sources during rest and exercise before and after training. SE and statistical symbols are for total energy expenditure only. Values are for nine subjects. CHO, carbohydrate. ΔSignificantly different from rest; *significantly different from 45UT; +significantly different from 65UT; and #significantly different from ABT, P < 0.05. From Friedlander et al. and used with permission.



Figure 9.

(A) Effect of exercise intensity and training on plasma FFA Rd. Values are means 6 SE of the last 15 and 30 min for rest and exercise, respectively; n = 8 young women. ΔSignificantly different from rest; *significantly different from 45UT; +significantly different from 65UT; and #significantly different from ABT (P < 0.05). From Friedlander et al. . (B) Effect of exercise intensity and training on plasma FFA rate of disappearance (Rd) in 10 young men before and after 10 weeks of supervised endurance training. Values are means ± SE of the last 15 and 30 min for rest and exercise, respectively; n = 9 subjects. *Significantly different from pretraining (45UT); Δsignificantly different from rest; +significantly different from 65UT; and #significantly different between resting conditions, P < 0.05. From Friedlander et al. and used with permission.



Figure 10.

(A) Contributions of different lipid sources to total lipid metabolism during rest and exercise before and after training. SE and statistical symbols are for total lipid metabolism only; n = 8, mean ± SE. ΔSignificantly different from rest and *significantly different from 45UT (P < 0.05). (B) Contributions of energy from different substrate sources during rest and exercise normalized to percent energy expenditure; n = 8. From Friedlander et al. .



Figure 11.

Effect of exercise intensity and training on glycerol venous‐arterial difference. Values are mean ± SEM for eight subjects. Little net glycerol release occurs from working limb muscle indicative of insignificant intramuscular triglyceride (IMTG) mobilization during contractions. Symbols represent moderate intensity exercise before endurance training (45% Pre), hard exercise before training (65% Pre), after training the same absolute (ABT) intensity that elicited 65% VO2peak before training (65% Old), and exercise that elicited 65% of the posttraining VO2peak [new, relative hard exercise (RLT)]. From Bergman et al. and used with permission.



Figure 12.

Effects of graded exercise and exercise training on resting and working limb triglyceride (A) and cholesterol LDL‐C (B) and HDL‐C (C). Exercise and exercise training effects are physiologically insignificant. From Jacobs et al. and used with permission.



Figure 13.

Absolute substrate oxidation rates (mean ± SEM) in men before during and after 60 min of exercise at 65% VO2peak. Lipid and CHO oxidation rates shown by solid and crosshatched bars, respectively. Data show dominance of CHO oxidation during physical activity, and crossover to lipid oxidation during recovery. Data on women are not shown. From Kuo et al. and used with permission.



Figure 14.

Plasma FFA rate of appearance (Ra) as determined from continuous infusion of [1−13C]palmitate in 10 men studied at rest and during and after two exercise intensities (45% VO2peak for 90 min and 65% VO2peak for 60 min). The same subjects were also studied on a nonexercise day (control) to account for diurnal variations. Plasma FFA Ra rose significantly during exercise, compared to preexercise rest, and remained elevated in 3 h of recovery whether compared to preexercise rest or time of day matched resting control. From Henderson et al. and used with permission.



Figure 15.

Effect of work rat and speed of movement on a leg cycle ergometer (mean ± SE) of 12 young males during steady‐rate exercise. Caloric values determined from VO2 and RER. The essentially linear relationship with perhaps a slight exponential rise in caloric output at higher work rates dictates either constant or decreasing efficiency. Because the caloric cost of each exercise power output increases with increments in pedaling speed, decreasing efficiency with increasing speed is indicated. Note that the y‐intercepts measured during unloaded cycling deviate from rest (≈ 1 kcal/min) and significantly from linearity for all but the slowest cycling cadence making “gross,” “net,” and “work” efficiency calculations invalid, and indicating use of the “delta” method of efficiency calculation. From Gaesser and Brooks and used with permission.



Figure 16.

The effect of work rate on delta (Δ) efficiency (mean ± SE) for 12 young men pedaling at a slow cadence (40 RPM) on a leg cycle ergometer. In contrast to other (gross, net, and work) modes of calculation, the data (From Fig. ) demonstrates decreasing efficiency with increments in power output. From Gaesser and Brooks and used with permission.



Figure 17.

The effect of work rate on delta (Δ) efficiency (mean ± SE) for 12 young men pedaling at a rapid cadence (100 RPM) on a leg cycle ergometer, calculations based on data in Figure . As with slow cadence pedaling (Fig. ), the results demonstrate decreasing efficiency with increments in power output when cycling at a fast cadence. Note that the range of computed efficiencies (25%‐35%) is similar for low and high cadence pedaling. From Gaesser and Brooks and used with permission.



Figure 18.

Effects of work rate on delta (Δ) efficiency (mean ± SE) for nine young men during treadmill gradient walking at 3.0, 4.5, and 6.0 km/h. Results gradient (vertical) work as well as horizontal work against an impeding force demonstrate decreasing efficiency with increments in muscle power output. As with results in [Figs. ()], computations based on caloric values determined from VO2 and RER during steady‐rate, submaximal exercise. From Donovan and Brooks and used with permission.



Figure 19.

Relationship between external work and metabolic cost of human interosseous (hand) muscle in which metabolic cost was determined by 31P‐MRS. The least squares linear regression of data yields a very high, 68% mechanical coupling efficiency (i.e., external work from ATP hydrolysis) [Work output (J) = 0.68 ± 0.09 ATP cost (J) − 2.2 ± 0.9 (J)]. Assuming a phosphorylative coupling efficiency of 50%, overall Δ efficiency approximates 34%. Used with permission. From Jubrias et al. and used with permission.



Figure 20.

Rate of muscle ATP turnover (mmol ATP/kg dry wt/s) during 0‐5, 5‐15, and 15‐180 s of two bouts of intense knee extensor exercise (EX1) and (EX2) separated by 3 min of rest. ATP turnover estimated as the sum of muscle anaerobic energy production determined as energy release related to utilization of CP (hatched part of bar), net lactate production determined as the sum of accumulation in muscle (open bar) and release to the blood (horizontally lined bar), net ATP utilization (vertically lined bar), others sources, and aerobic energy production (filled bar), determined from muscle oxygen uptake and estimated utilization of oxygen from myoglobin. Values are means ± SE. Modified from Figure 4 in Bangsbo et al. and used with permission.



Figure 21.

Muscle mechanical efficiency, determined as work per total energy production during the interval between 15‐180 s of an intense knee extensor exercise, in which total energy production was determined from metabolic measurements (open bars) and as the sum of total heat production and work performed. Values are means ± SE. #significantly (P < 0.05) different from values determined during the first 15 s of exercise. Values are means ± SE. Modified from Figure 6 in Bangsbo et al. and used with permission.



Figure 22.

A compilation of results of Stuart et al. who studied leg ergometer cycling efficiency of sprinters (fast twitch) and distance runners (slow twitch) athletes. (A) Higher rates of energy expenditure in sprinters exercising at given exercise power outputs indicate lesser efficiency. (B) Higher metabolic costs of exercise in sprinters makes for a lesser computed “gross” efficiency. (C, D) For both groups, delta (Δ) and instantaneous calculations show decreasing exercise efficiencies as exercise power outputs increase. Interestingly, while greater slopes of caloric expenditure regressed on power output make computed Δ and instantaneous efficiencies less at lower exercise power outputs, the computed efficiencies converge, or cross over at higher power outputs. Used with permission.

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George A. Brooks. Bioenergetics of Exercising Humans. Compr Physiol 2012, 2: 537-562. doi: 10.1002/cphy.c110007