Journal of Applied Physiology
Vol. 82, No. 4, pp. 1360-1369, April 1997
METABOLISM

Training-induced alterations of glucose flux in men

Anne L. Friedlander, Gretchen A. Casazza, Michael A. Horning, Melvin J. Huie, and George A. Brooks

Exercise Physiology Laboratory, Departments of Human Biodynamics and Integrative Biology, University of California, Berkeley, California 94720

ABSTRACT

INTRODUCTION

METHODS

RESULTS

DISCUSSION

ACKNOWLEDGEMENTS

FOOTNOTES

REFERENCES

ABSTRACT

Friedlander, Anne L., Gretchen A. Casazza, Michael A. Horning, Melvin J. Huie, and George A. Brooks. Training-induced alterations of glucose flux in men. J. Appl. Physiol. 82(4): 1360-1369, 1997.We examined the hypothesis that glucose flux was directly related to relative exercise intensity both before and after a 10-wk cycle ergometer training program in 19 healthy male subjects. Two pretraining trials [45 and 65% of peak O₂ consumption (O_{2 peak})] and two posttraining trials (same absolute and relative intensities as 65% pretraining) were performed for 90 min of rest and 1 h of cycling exercise. After training, subjects increased O_{2 peak} by 9.4 ± 1.4%. Pretraining, the intensity effect on glucose kinetics was evident with rates of appearance (R_a; 5.84 ± 0.23 vs. 4.73 ± 0.19 mg · kg¹ · min¹), disappearance (R_d; 5.78 ± 0.19 vs. 4.73 ± 0.19 mg · kg¹ · min¹), oxidation (R_ox; 5.36 ± 0.15 vs. 3.41 ± 0.23 mg · kg¹ · min¹), and metabolic clearance (7.03 ± 0.56 vs. 5.20 ± 0.28 ml · kg¹ · min¹) of glucose being significantly greater (P  0.05) in the 65% than the 45% O_{2 peak} trial. When R_d was expressed as a percentage of total energy expended per minute (R_{d E}), there was no difference between the 45 and 65% intensities. Training did reduce R_a (4.63 ± 0.25), R_d (4.65 ± 0.24), R_ox (3.77 ± 0.43), and R_{d E} (15.30 ± 0.40 to 12.85 ± 0.81) when subjects were tested at the same absolute workload (P  0.05). However, when they were tested at the same relative workload, R_a, R_d, and R_{d E} were not different, although R_ox was lower posttraining (5.36 ± 0.15 vs. 4.41 ± 0.42, P  0.05). These results show 1) glucose use is directly related to exercise intensity; 2) training decreases glucose flux for a given power output; 3) when expressed as relative exercise intensity, training does not affect the magnitude of blood glucose use during exercise; 4) training alters the pathways of glucose disposal.

stable isotopes; substrate selection; glucose recycling; relative vs. absolute intensity; exercise; crossover concept

INTRODUCTION

FACTORS THAT INFLUENCE the patterns of substrate utilization during exercise of different intensities are numerous, and there is controversy over the effects of exercise intensity and prior endurance training on these patterns. Some believe that training decreases blood glucose utilization and increases lipid utilization (4, 6, 14, 17), whereas others (24) have shown glucose rate of appearance (R_a) to be higher in athletes than nonathletes during hard and maximal exercise. In addition, studies that have employed a one-leg training regimen followed by a two-leg test have obtained ambiguous results regarding the effects of training on limb glucose uptake. For example, Kiens et al. (23) demonstrated that glucose uptake was only transiently lower in the trained leg and there were no differences in lactate release or muscle triglyceride use between trained and untrained legs working at a given power output. Two additional studies used one-leg training protocols but tested subjects at the same relative workloads either as determined by percentage of one-leg maximal O₂ consumption (O_{2 max}) (16) or corrected for leg muscle volume (10). Those studies showed an increase in trained leg glucose uptake that was, in part, responsible for the muscle glycogen sparing observed in the trained leg. Similar results were also found in treadmill-trained rats, in which glucose uptake was the same or higher posttraining whereas levels of muscle glycogenolysis were decreased (12, 37).

The studies mentioned above differ in their methodologies as well as in their observations regarding glucose utilization after training. For example, in the studies that reported decreased glucose utilization, whole body glucose kinetics at a given power output was measured, whereas most of the studies showing constant or increased utilization measured limb net glucose uptake. In addition, the testing protocols used by investigators differed in the workload selection. Those testing subjects at the same absolute workload after training found decreased glucose utilization, whereas those testing subjects at the same relative workloads did not observe decreased glucose uptake. Because circulating hormone levels and intramuscular factors that influence glucose flux are closely tied to relative work intensity for both untrained and trained individuals (11), endocrine factors may cause glucose flux to be more closely related to relative than absolute exercise intensity. Studies that use two-leg training and one-leg testing protocols confirm the importance of training-induced alterations in the endocrine regulation of glucose. Also, short-term training studies have demonstrated decreased glucose R_a and rate of disappearance (R_d) associated with rapid hormonal changes without any significant alterations in mitochondrial respiratory capacity (30).

To our knowledge, the effects of training on whole body glucose kinetics at given relative exercise intensities have not been systematically addressed in a longitudinal study. One cross-sectional study by Coggan et al. (5) compared highly trained and untrained subjects at 80% of peak O₂ consumption (O_{2 peak}) and found no difference in R_a but a reduction in glucose R_d in the trained subjects. However, the cross-sectional design of the study could be problematic because successful endurance athletes may have a genetic propensity to utilize greater amounts of lipid. Understanding the effects of exercise and training at given relative intensities should be considered important. Exercise prescriptions for the general population, as well as the training and competitive regimens of athletes, are geared to maximizing peak power output and endurance by maintaining the same or higher relative workloads as improvements occur. Endurance training may enhance the ability to utilize lipids during mild to moderate exercise, but the transition to hard exercise appears to result in a crossover to predominantly carbohydrate (CHO) utilization regardless of training status (2). The purpose of our study was to examine the effects of intensity and training on glucose kinetics in male subjects to evaluate the hypothesis that during hard exercise, blood glucose flux is not affected by training.

METHODS

1

1

(1)

(2)

(3)

(4)

(5)

(6)

RESULTS

Table 1. Characteristics of male subjects before and after 10 wk of endurance training Variable Pretraining Posttraining %Difference Age, yr 25.47 ± 0.73  Height, cm 179.76 ± 1.27  Weight, kg 78.62 ± 2.03  78.24 ± 1.89   0.39 ± 0.50  Body fat, %    Underwater weighing 15.50 ± 1.04  13.83 ± 0.91*  9.61 ± 4.01    Skin folds 14.45 ± 0.92  12.73 ± 0.83*  11.33 ± 3.48   O2 peak,   ml · kg1 · min1 46.50 ± 1.13  50.71 ± 1.27* 9.4 ± 1.39    l/min 3.63 ± 0.09  3.94 ± 0.11* 8.5 ± 1.33  Time to O2 peak, min 18.67 ± 1.12  22.95 ± 1.13* 27.63 ± 3.91 Values are means ± SE; n = 19. O2 peak, peak O2 consumption. Significantly different from pretraining values, * P < 0.05.  Workload during O2 peak test was increased every 3 min.

Table 2. Pre- and posttraining parameters of exercise power output and physiological strain during rest and exercise Variable Rest Exercise Pretraining Posttraining 45UT 65UT ABT RLT Workload, W 0 0 90.0 ± 6.2d,e 152.2 ± 6.4  152.7 ± 6.4  176.7 ± 6.1c,d,e  O2, ml · kg1 · min1 4.1 ± 0.34  4.26 ± 0.17  21.6 ± 0.72d,e 30.1 ± 0.75  29.7 ± 0.87  33.1 ± 0.84c,d,e Heart rate, beats/min 67.7 ± 1.76  63.6 ± 1.67a 128.2 ± 2.75d 157.8 ± 3.09  138.9 ± 2.55c,d 156.2 ± 2.56c,e Respiratory exchange ratio 0.86 ± 0.02  0.86 ± 0.01  0.91 ± 0.01  0.94 ± 0.01c 0.92 ± 0.01  0.94 ± 0.02c %Energy from CHO 52.2 ± 8.83  53.5 ± 7.3  68.9 ± 3.88  78.2 ± 5.39  73.4 ± 4.72  78.4 ± 5.85  Arterial glucose, mM 4.99 ± 0.11  4.81 ± 0.84  4.62 ± 0.10b 4.50 ± 0.10b 4.60 ± 0.13  4.65 ± 0.08 Values are means ± SE; n = 19 for all variables except respiratory exchange ratio and %energy from carbohydrate (CHO), n = 10. O2, O2 consumption; 45UT, 45% pretraining trial; 65UT, 65% pretraining trial; ABT, same absolute workload as 65UT; RLT, same relative workload (65% of posttraining O2 peak). All exercise values were significantly different from rest except for arterial glucose, which were different as marked. a Significantly different between resting conditions; b significantly different from rest; c significantly different from 45UT; d significantly different from 65UT; e significantly different from ABT, P < 0.05.

DISCUSSION

Results of our investigation corroborate those of previous studies showing a direct relationship between exercise intensity and blood glucose flux (24, 35). Furthermore, our results are consistent with the hypothesis that glucose R_a is exponentially related to relative effort as given by percent O_{2 peak} (3). Results of our study on the effects of training on glucose flux are consistent with investigations that training reduces glucose flux for exercise of a given power output (4, 7). However, our results obtained by using a longitudinal design differed from cross-sectional designs in that training did not affect glucose kinetics (R_a or R_d) when expressed at a given relative power output (5).

One of the criticisms often presented against the use of relative workloads as a means for testing the effects of training is that the energy expenditure during exercise and thus the metabolic flux differs between conditions. However, even when glucose R_d (or R_a) values were expressed as a percent of total energy expenditure, there was no difference in glucose flux pre- and posttraining at the same relative workload. Depicting glucose flux as a function of %energy expenditure (e.g., Fig. 2D) is appropriate because it eliminates the influence of varying metabolic flux rates when making comparisons at different absolute intensities.

There have been many defined power output studies demonstrating that both short- and long-term exercise training change the balance of substrate utilization away from CHO toward lipid utilization at given absolute workloads. Support for such a conclusion comes from observations posttraining in the form of decreases in RER values (4), increases in total fat oxidation (28), decreases in glucose flux (4), and reductions in the rate of muscle glycogenolysis (12, 20, 37). Although those studies provide useful information, they only address part of the issue of endurance training. Some of the changes in substrate utilization observed at the same absolute workload may arise from blunted hormonal responses rather than actual peripheral adaptations. Circulating levels of hormones are similar among people of widely varied training level when tested at the same relative workload despite dramatic differences in the absolute workload (11). To our knowledge, no long-term training studies have been completed that look at endurance training at the same relative workload. In one study by Kjaer et al. (24), the glucose kinetics of trained and untrained subjects were compared at maximal workloads. No differences were observed in glucose R_d between groups, although elevated glucose concentrations in the trained group resulted in lower metabolic clearance rates. Unfortunately, the non-steady-state conditions in that study leave the data open to interpretation. Another study by Coggan et al. (5) compared endurance athletes and untrained individuals for 30 min of exercise at 80% O_{2 peak} and showed no difference in glucose Ra but a lower glucose R_d in the trained subjects. However, it is unclear whether accurate flux values can be obtained under such conditions of high-intensity, short-duration exercise during which glucose concentrations are not stable. In addition, information from such cross-sectional studies should be interpreted with caution, given that a genetic propensity for lipid utilization may have predisposed such athletes to select and be successful at such endurance activities (1).

We chose to test our subjects in a fed, postabsorptive state so that the results would be more applicable to a nonlaboratory environment. Typically, subjects ate 1-2 h before reporting to the laboratory; subject preparation took a minimum of 1 h, and rest ranged from 90 to 120 min. Thus we report data on resting subjects fed 3.5-5 h previously and exercising subjects fed 4.5-6 h before study. For this reason, our RER values appear elevated above previous studies that used subjects who had not eaten for 6-12 h before the experiment (4, 28, 34). However, our values were in the same range as those of Jones et al. (22), who reported average RER values during steady-state exercise of 0.89 and 1.01 for 36 and 70% of O_{2 peak}, respectively. Our attempt to control diet and, thus, liver and muscle glycogen stores, may also explain why there was no difference in RER after training at the same absolute workload. A recent study in our laboratory using a cross-sectional design illustrated that, in the fed state, trained cyclists and untrained subjects showed no difference in RER values at workloads >20% of O_{2 peak} (B. C. Bergman and G. A. Brooks unpublished observations). Although the pretrial breakfast that we selected was composed of only CHO and protein, we do not believe that the composition of the meal elevated the RER values. Thomas et al. (39) have shown that, although the quantity of CHOs ingested affects the fuel selection, adding fat to a diet does not increase the amount of fat utilized. In addition, the thermic effect of the meal would not be expected to last more than 3-5 h, especially given the small size of the pretest meal consumed by our subjects.

In addition to feeding our subjects, the fact that we tested our subjects at the same relative workload means that the data may be more applicable to active adults as well as to athletes in a nonlaboratory setting. As athletes and others train and improve, they are capable of performing at higher absolute as well as relative power outputs. For the elite athlete, the proported advantages of increased fat utilization due to training (17) may be moot. Several studies have indicated that athletes work at very high intensity levels and, therefore, rely predominantly on CHO regardless of their muscle oxidative capacity (25, 31). The reliance on CHO may be partially a result of the decline in free fatty acid availability associated with high-intensity exercise (2, 13, 21, 34) but, mainly, fuel selection is determined by the glycolytic CHO flux rate (2, 9, 41). Glycolysis in working muscle is related to epinephrine levels, recruitment of type II muscle fibers, contraction-induced glycogenolysis, redox state, and other factors, many of which are directly influenced by relative exercise intensity. In the fed state, resting individuals usually have an RER value in the range 0.83-0.86, which indicates that ~50% of the energy comes from CHO sources. In the transition from rest to exercise and with increasing intensity, the oxidation of both fat and CHO sources increases in absolute terms, but CHO increases more, resulting in a relative decrease in the %contribution from lipid sources. Lipid oxidation reaches a turning point at ~50% of maximum exercise capacity and then declines in both relative and absolute terms (3, 19).

An explanation of how training results in a decreased glucose R_d for a given power output remains to be established. Houmard et al. (18) have demonstrated increased glucose transporter isoform GLUT-4 content in trained human muscle, and it is well known that for a given power output, insulin concentration is higher after training. Furthermore, training increases hexokinase activity and decreases glucose-6-phosphatase, both of which would favor glucose uptake and phosphorylation (4, 6). All of these adaptations suggest increased capacity for glucose uptake, but after training glucose uptake is less at a given absolute workload. Likely, some other training effect, such as superior mitochondrial respiratory control, lower malonyl-CoA levels, or decreased translocation or intrinsic activity of GLUT-4, is involved (2, 26, 33). As well, changes in vascular glucose conductance related to blood flow may cause muscle glucose uptake to decrease at a given power output after training.

Our subjects improved their O_{2 peak} by 9.4% overall, whereas other endurance training studies of comparable length have shown greater increases (7, 27, 28). However, unlike our program, which was designed to increase endurance capacity by progressively increasing the workload, others have used interval-training regimens. Although interval training is effective in increasing O_{2 max} (8), endurance training, as employed by us, results in peripheral adaptations such as increases in mitochondrial content (8, 9). Also, the capacity to increase O_{2 max} is dependent on both the initial starting value and genetic potential (1). The subjects who were recruited for our study were untrained but active young men and thus may not have been able to increase their maximum capacity to the same extent as their endurance capacity. Furthermore, short-term training studies that recorded a reduction in glucose R_a and an increase in whole body fat oxidation with no concomitant changes in O_{2 peak} provide evidence that large changes in maximum aerobic capacity are not critical to alter substrate selection (30). The effectiveness of our endurance training program can be seen in the decrement of kinetic and metabolite parameters after training. For example, at the same absolute workload, glucose flux and oxidation declined by 21 and 29%, respectively. There were also substantial decreases in lactate concentration (45%) and glucose recycling rate (62%) at the same absolute workload. Our endurance training program was also sufficient to cause significant decreases in glucose R_ox, recycling rate, and lactate concentration at the same relative workload (18, 50, and 18% respectively).

Training reduced glucose R_ox significantly despite similar values for R_d at the same relative workload. It is possible that pretraining values for R_ox were elevated because greater lacticacidosis caused the release of labeled bicarbonate (incorporated during the 90 min of rest). However, despite elevated blood lactate levels in our subjects at the end of exercise in the 65UT trial relative to posttraining (Fig. 2G), the lactate levels were falling in all four trials at the time of the steady-state exercise measurements. Thus it is unlikely that measured differences in glucose R_ox were caused by lactacidemia and the release of stored ¹³CO₂. However, in a study by Jones et al. (22), the authors reported RER values of 1.0 or greater during steady-state exercise at an intensity of 70% of O_{2 peak} and suggested that the high levels of lactate were sufficient to force the release of excess CO₂ despite the fall in lactate concentrations during the end of exercise. However, because the lactate values of Jones et al. were substantially higher than our 65UT values in the present study (9.94 vs. 3.3 mM, respectively), it remains unclear whether lactacidemia is influencing our R_ox calculations. An alternative conclusion is that training increased the nonoxidative disposal of glucose. However, the increase in nonoxidative glucose disposal after training is not a result of elevated glucose recycling because our values for recycling were reduced posttraining. Therefore, training resulted in pathways of glucose disposal that were not measured by our study design. We speculate that the increased nonoxidative disposal of glucose may be related to greater cycling of glucose through glycogen in trained muscle (J. Azevedo et al., unpublished observations). Possibly, the altered hormone profile after training may allow a greater proportion of the glycosyl units cycling through the futile cycle to remain in the form of glycogen. It is also possible that in trained subjects, nonactive muscle groups are more likely to direct glucose to glycogen than in the untrained subject.

The recycling rate of ¹³C was significantly reduced posttraining by 62 and 50% at the same absolute and relative workloads, respectively. This reduction in recycling rate is in contrast to several training studies performed in rats that found that gluconeogenesis from lactate was actually enhanced posttraining (12, 38, 40). The lower recycling rates in our study may have resulted from a reduction in the appearance of lactate. Figure 4, B and C, indicates that there was less lactate present and less recycling for a given concentration of norepinephrine. These data suggest a reduction in signaling and, perhaps, a downregulation of adrenergic receptors in response to endurance training. Also, Fig. 4A indicates that there was less recycling for a given concentration of lactate, suggesting that the clearance of lactate for the purpose of gluconeogenesis was reduced after training. It has been established previously that lower circulating levels of lactate after training in humans are a result of increased clearance and oxidation rather than a reduction in production (27, 32). If, in our study, more lactate was disposed of through oxidation, the results of increased nonoxidative glucose disposal, lower lactate concentration, decreased glucose recycling, and similar RER values after training may be explained.

ACKNOWLEDGEMENTS

The authors thank Gail Butterfield for consultation on all aspects of the study. We also thank Michelle Wilkerson, Robin Rynbrandt, and Tam Ho, who provided much of the laboratory support throughout the study. We are also grateful to all of the student trainers and especially Kevin Foley for assistance with the subject training and testing. Finally, we thank Jeff Trimmer for assistance with the catecholamine analysis.

FOOTNOTES

Address for reprint requests: A. L. Friedlander, Depts. of Human Biodynamics and Integrative Biology, at Univ. of California, 5101 VLSB Berkeley, Berkeley, CA 94720-4480 (E-mail:annef{at}uclink3.berkeley.edu).

Received 3 September 1996; accepted in final form 15 November 1996.

REFERENCES

1.	Bouchard, C., and L. Perusse. Heredity, activity level, fitness, and health. In: Physical Activity, Fitness, and Health, edited by C. Bouchard, R. J. Shepard, and T. Stevens. Champaign, IL: Human Kinetics, 1994, p. 106-118. .
2.	Brooks, G. A., and J. Mercier. Balance of carbohydrate and lipid utilization: the "crossover" concept. J. Appl. Physiol. 76: 2253-2261, 1994. [Abstract/Free Full Text] .
3.	Brooks, G. A., and J. K. Trimmer. Glucose kinetics during high-intensity exercise and the "crossover" concept. J. Appl. Physiol. 80: 1073-1074, 1996. [Free Full Text] .
4.	Coggan, A. R., W. M. Kohrt, R. J. Spina, D. M. Bier, and J. O. Holloszy. Endurance training decreases plasma glucose turnover and oxidation during moderate-intensity exercise in men. J. Appl. Physiol. 68: 990-996, 1990. [Abstract/Free Full Text] .
5.	Coggan, A. R., C. A. Raguso, B. D. Williams, L. S. Sidossis, and A. Gastaldelli. Glucose kinetics during high-intensity exercise in endurance-trained and untrained humans. J. Appl. Physiol. 78: 1203-1207, 1995. [Abstract/Free Full Text] .
6.	Coggan, A. R., R. J. Spina, W. M. Kohrt, and J. O. Holloszy. Effect of prolonged exercise on muscle citrate concentration before and after endurance training in men. Am. J. Physiol. 264 (Endocrinol. Metab. 27): E215-E220, 1993. [Abstract/Free Full Text] .
7.	Coggan, A. R., S. C. Swanson, L. A. Mendenhall, D. L. Habash, and C. L. Kien. Effect of endurance training on hepatic glycogenolysis and gluconeogenesis during prolonged exercise in men. Am. J. Physiol. 268 (Endocrinol. Metab. 31): E375-E383, 1995. [Abstract/Free Full Text] .
8.	Davies, K. J., L. Packer, and G. A. Brooks. Exercise bioenergetics following sprint training. Arch. Biochem. Biophys. 215: 260-265, 1982. [Medline] .
9.	Davies, K. J. A., L. Packer, and G. A. Brooks. Biochemical adaptation of mitochondria, muscle, and whole-animal respiration to endurance training. Arch. Biochem. Biophys. 209: 539-554, 1981. [Medline] .
10.	Dela, F., K. J. Mikines, B. Sonne, and H. Galbo. Effect of training on interaction between insulin and exercise in human muscle. J. Appl. Physiol. 76: 2386-2396, 1994. [Abstract/Free Full Text] .
11.	Deuster, P. A., G. P. Chroustos, A. Luger, J. E. DeBolt, L. L. Bernier, U. H. Trostmann, S. B. Kyle, L. C. Montgomery, Hormonal and metabolic responses of untrained, moderately trained and highly trained men to three exercise intensities. Metabolism 38: 141-148, 1989. [Medline] .
12.	Donovan, C. M., and K. D. Sumida. Training improves glucose homeostasis in rats during exercise via glucose production. Am. J. Physiol. 258 (Regulatory Integrative Comp. Physiol. 27): R770-R776, 1990. [Abstract/Free Full Text] .
13.	Dyck, D. J., C. T. Putman, J. F. Heigenhauser, E. Hultman, and L. L. Spriet. Regulation of fat-carbohydrate interaction in skeletal muscle during intense aerobic cycling. Am. J. Physiol. 265 (Endocrinol. Metab. 27): E852-E859, 1993. [Abstract/Free Full Text] .
14.	Gollnick, P. D. Metabolism of substrates: energy substrate metabolism during exercise and as modified by training. Federation Proc. 44: 353-357, 1985. [Medline] .
15.	Gutmann, I., and A. W. Wahlefeld. L-(+)-Lactate determination with lactate dehydrogenase and NAD. In: Methods of Enzymatic Analysis, edited by H. Bergmeyer. New York: Academic, 1974. , chapt. 3, p. 1464-1468.
16.	Henriksson, J. Training induced adaptation of skeletal muscle and metabolism during submaximal exercise. J. Physiol. (Lond.) 270: 661-675, 1977. [Abstract/Free Full Text] .
17.	Holloszy, J. O., and E. F. Coyle. Adaptations of skeletal muscle to endurance exercise and their metabolic consequences. J. Appl. Physiol. 56: 831-838, 1984. [Abstract/Free Full Text] .
18.	Houmard, J. A., M. H. Shinebarger, P. L. Dolan, N. Legett-Frazier, R. K. Bruner, M. R. McCammon, R. G. Israel, and G. L. Dohm. Exercise training increases GLUT-4 protein concentration in previously sedentary middle-aged men. Am. J. Physiol. 264 (Endocrinol. Metab. 27): E896-E901, 1993. [Abstract/Free Full Text] .
19.	Hultman, E. Fuel selection, muscle fibre. Proc. Nutr. Soc. 54: 107-121, 1995. [Medline] .
20.	Hurley, B. F., P. M. Nemeth, W. H. Martin, J. M. Hagberg, G. P. Dalsky, and J. O. Holloszy. Muscle triglyceride utilization during exercise: effect of training. J. Appl. Physiol. 60: 562-567, 1986. [Abstract/Free Full Text] .
21.	Issekutz, B., and H. I. Miller. Plasma free fatty acids during exercise and the effect of lactic acid. Proc. Soc. Exp. Biol. 100: 237-239, 1962. .
22.	Jones, N. L., G. J. F. Heigenhauser, A. Kuksis, C. G. Matsos, J. R. Sutton, and C. J. Toews. Fat metabolism in heavy exercise. Clin. Sci. Lond. 59: 469-478, 1980. [Medline] .
23.	Kiens, B., B. Essen-Gustavson, N. J. Christensen, and B. Saltin. Skeletal muscle substrate utililization during submaximal exercise in man: effects of endurance training. J. Physiol. (Lond.) 469: 459-478, 1993. [Abstract/Free Full Text] .
24.	Kjaer, M., P. A. Farrell, N. J. Christensen, and H. Galbo. Increased epinephrine response and inaccurate glucoregulation in exercising athletes. J. Appl. Physiol. 61: 1693-1700, 1986. [Abstract/Free Full Text] .
25.	Kjaer, M., N. H. Secher, F. W. Bach, and H. Galbo. Role of motor center activity for hormonal changes and substrate mobilization in humans. Am. J. Physiol. 253 (Regulatory Integrative Comp. Physiol. 22): R687-R695, 1987. [Abstract/Free Full Text] .
26.	Lopaschuk, G. D., and J. Gamble. Acetyl-CoA carboxylase: an important regulator of fatty acid oxidation in the heart. Can. J. Physiol. Pharmacol. 72: 1101-1109, 1994. [Medline] .
27.	MacRae, H. H. S., T. D. Noakes, and S. C. Dennis. Effects of endurance training on lactate removal by oxidation and gluconeogenesis during exercise. Eur. J. Physiol. 430: 964-970, 1995. . [Medline]
28.	Martin, W. H., G. P. Dalsky, B. F. Hurley, D. E. Mathews, D. M. Bier, J. M. Hagberg, M. A. Rogers, D. S. King, and J. O. Holloszy. Effect of endurance training on plasma free fatty acid turnover and oxidation during exercise. Am. J. Physiol. 265 (Endocrinol. Metab. 28): E708-E714, 1993. [Abstract/Free Full Text] .
29.	Mazzeo, R. S., and P. Marshall. Influence of plasma catacholamines on the lactate threshold during graded exercise. J. Appl. Physiol. 67: 1319-1322, 1989. [Abstract/Free Full Text] .
30.	Mendenhall, L. A., S. C. Swanson, D. L. Habash, and A. R. Coggan. Ten days of exercise training reduces glucose production and utilization during moderate-intensity exercise. Am. J. Physiol. 266 (Endocrinol. Metab. 29): E136-E143, 1994. [Abstract/Free Full Text] .
31.	O'Brien, M. J., C. A. Viguie, R. S. Mazzeo, and G. A. Brooks. Carbohydrate dependence during marathon running. Med. Sci. Sports Exercise 25: 1009-1017, 1993. [Medline] .
32.	Phillips, S. M., H. J. Green, M. A. Tarnopolsky, and S. M. Grant. Increased clearance of lactate after short-term training in men. J. Appl. Physiol. 79: 1862-1869, 1995. [Abstract/Free Full Text] .
33.	Richter, E. A. Glucose utilization. In: Exercise: Regulation and Integration of Multiple Systems, edited by L. B. Rowell, and J. T. Shepard. New York: Oxford Univ. Press, 1996. , chapt. 20, p. 912-951.
34.	Romijn, J. A., E. F. Coyle, L. S. Sidossis, A. Gastaldelli, J. F. Horowitz, E. Endert, and R. R. Wolfe. Regulation of endogenous fat and carbohydrate metabolism in relation to exercise intensity and duration. Am. J. Physiol. 265 (Endocrinol. Metab. 28): E380-E391, 1993. [Abstract/Free Full Text] .
35.	Romijn, J. A., E. F. Coyle, L. S. Sidossis, X. J. Zhang, and R. R. Wolfe. Relationship between fatty acid delivery and fatty acid oxidation during strenuous exercise. J. Appl. Physiol. 79: 1939-1945, 1995. [Abstract/Free Full Text] .
36.	Schoeller, D. A., C. Brown, K. Nakamura, A. Nakagawa, R. S. Mazzeo, G. A. Brooks, and T. F. Budinger. Influence of metabolic fuel on the 13C/12C ratio of breath CO2. Biomed. Mass Spectrom. 11: 557-561, 1984. [Medline] .
37.	Sumida, K. D., and C. M. Donovan. Endurance training fails to inhibit skeletal muscle glucose uptake during exercise. J. Appl. Physiol. 76: 1876-1881, 1994. [Abstract/Free Full Text] .
38.	Sumida, K. D., J. H. Urdiales, and C. M. Donovan. Enhanced gluconeogenesis from lactate in perfused livers after endurance training. J. Appl. Physiol. 74: 782-787, 1993. [Abstract/Free Full Text] .
39.	Thomas, C. D., J. C. Peters, G. W. Reed, N. N. Abumrad, and J. O. Hill. Nutrient balance and energy expenditure during ad libitum feeding of fat and high carbohydrate diets in men. Am. J. Clin. Nutr. 55: 934-942, 1992. [Abstract/Free Full Text] .
40.	Turcotte, L. P. Effects of training on glucose metabolism of gluconeogenesis-inhibited short-term fasted rats. J. Appl. Physiol. 68: 944-954, 1990. [Abstract/Free Full Text] .
41.	Van Baak, M. A., J. M. Mooij, and J. A. G. Wijnen. Effect of increased plasma non-esterified fatty acid concentrations on endurance performance during -adrenoceptor blockade. Int. J. Sports Med. 14: 2-8, 1993. [Medline] .
42.	Wolfe, R. R. Radioactive, and Stable Isotope Tracers in Biomedicine. New York: Wiley-Liss, 1992. ,