INTRODUCTION

TOP ABSTRACT INTRODUCTION MODEL OF O2 UPTAKE... PROBLEM OF STUDY METHODS AND PROCEDURES RESULTS DISCUSSION REFERENCES

INDIRECT CALORIMETRY is the standard paradigm for determining the energy transfer rate and oxidative fuel utilization during exercise in humans, but only under steady-state conditions where CO₂ output (CO₂) is unaffected by acid-base disturbances. The requirement for steady state is a serious limitation, because most conditions of exercise are non-steady state. Consequently, there is an urgent need to extend the indirect calorimetric paradigm to determine the kinetics of muscle and whole body energetics and oxidation of fat and carbohydrate (CHO). The kinetic paradigm would provide opportunities to study 1) the contribution of fat and CHO to oxidative metabolism during the early transition to steady state, 2) the cellular mechanisms controlling oxidative metabolism, 3) the systemic controls involving alveolar gas exchange as well as convective O₂ transport and conductive O₂ diffusion, and 4) the interrelationship between oxidative CO₂ and acid-base effects on measured CO₂.

The complexity of physiological and metabolic processes makes developing a kinetic paradigm a daunting task. However, there are several principles of modeling that can help develop, as a first step, a simplified dynamic indirect calorimetric paradigm, which is based on O₂ uptake (O₂) kinetics. First, the shape of the dynamic O₂ response provides information on pulmonary, circulatory, and metabolic processes. Second, mathematically decomposing the response into its component parts potentially can represent a specific process or some combination of processes. Critical to this task is the selection of a mathematical model, which contains parameters that reflect the dynamic characteristics of the process under study. At that point, each process can be identified by performing experiments that test the parameters of the model against theory.

Previous authors (4-6, 43, 45) have initiated decomposition of O₂ kinetics. Whipp and colleagues (45) introduced the concept that O₂ kinetics during light to moderate exercise below the performer's lactate threshold involves three phases. Phase 1 is the rapid rise in pulmonary O₂ after the onset of exercise, which reaches a transient plateau or inflection point in 15-20 s. They proposed that this phase involves the rapid delivery of O₂-poor blood for alveolar exchange and called it the "cardiodynamic phase." After phase 1, the O₂ rises exponentially in phase 2 and reaches an apparent steady state (phase 3), reflecting an increase in O₂ of metabolically active tissues involved in exercise, primarily working muscles. Accordingly, phases 2 and 3 represent oxidative dynamics of working muscles. Results from simulation experiments by Barstow and co-workers (4, 5) are consistent with this assignment of circulatory (phase 1) and metabolic components (phases 2 and 3) to the dynamics of pulmonary O₂ for light to moderately intense exercise. It is important to notice that the shape of the O₂ kinetic response has information on the time course of cardiorespiratory (phase 1) and oxidative (phases 2 and 3) processes. Therefore, an accurate mathematical model of phase 2 and 3 O₂ kinetics may provide analytic information on the dynamics of oxidative metabolism of working muscles.

That the exercise-induced increase in pulmonary O₂ primarily represents the oxidation of working muscles is well established experimentally (1-3, 21, 23, 30, 33, 36, 39), thereby confirming the theoretical work (4, 5). For example, recently Odland et al. (30) showed that leg O₂ represents ~80% of whole body O₂ with virtually the same substrate oxidation [leg respiratory quotient (RQ) = 0.91 vs. respiratory exchange ratio (RER) = 0.92] during minutes 4-7 of cycling at 40% of maximal O₂ (O_{2 max}). Therefore, it is reasonable to propose that the oxidation of fat and CHO in working muscles contributes to O₂ in phases 2 and 3. Furthermore, as developed below, we proposed that the initial changes in the flux of these fuels are reflected in the dynamics of phase 2 O₂. Briefly, we propose that the flux of these fuels is initiated as a feedforward process driven by contraction-induced increases in calcium, cAMP, and epinephrine that simultaneously activate glycogenolysis, triglyceride (TG) lipolysis, and -oxidation. Subsequently, feedback controls modulate their fluxes as dictated by alterations in the redox and phosphorylation potentials and intermediates, including pyruvate, citrate, and the ratio of acetyl CoA to CoA. Therefore, we propose that the contraction-induced changes in key enzymes controlling glycogen, intracellular TG, and fatty acid fluxes initially dictate the dynamic of redox and phosphorylation states, which in turn control and drive the dynamic of oxidative phosphorylation and phase 2 O₂ of working muscle.

As recently reviewed by Tschakovsky and Hughson (40), if muscle O₂ utilization, particularly for light exercise, is limited by intrinsic metabolic inertia and not by O₂ transport inertia, then the primary determinants of phase 2 O₂ kinetics will include enzyme activation associated with phosphorylation and redox states in healthy individuals under normoxic conditions. Research from our laboratory supports this view (28). Our findings on myoglobin desaturation during plantar flexion exercise at various intensities suggest that intracellular PO₂ is not limiting, and therefore neither convective nor conductive O₂ transport is typically controlling oxidative dynamics in working skeletal muscle. How, then, is phase 2 O₂ controlled by metabolic inertia at the early unsteady state of exercise? Briefly, muscle contraction will rapidly increase cellular Ca²⁺ with activation of various ATPases and dehydrogenases. Also, the activity of various AMP protein kinases increases, which in turn activates glycogenolysis, intracellular TG lipolysis, and -oxidation (38). Therefore, glycogen and intramuscular TG should be the primary fuels utilized during the early transient, non-steady state (10, 12, 15-17, 20, 31, 42, 48). Carbon flux from these sources is linked to O₂ by the formation of reducing equivalents, FADH₂ and NADH, and their utilization by the electron transport chain (ETC). When fat oxidation dominates, such as when persons perform light to moderate exercise on a fat diet, we propose that TG lipolysis and -oxidation are rapidly activated at exercise onset. Consequently, -oxidation will be the dominant supplier of FADH₂ and NADH to ETC and the formation of acetyl CoA. In this case, acetyl CoA from fat oxidation will dominate the early rapid increase in tricarboxylic acid (TCA) cycle carbon flux and the rise of O₂ in phase 2. Furthermore, TG oxidation would be expected to have feedback control over glycogenolysis (via citrate) and would attenuate activation of the pyruvate dehydrogenase (PDH) complex via acetyl CoA and NADH (7). More specifically, increases in the NADH-to-NAD and acetyl CoA-to-CoA ratios from TG oxidation could feed back to attenuate the activation of the PDH complex. Studies (9, 15) have shown that lactate rapidly accumulates after the onset of exercise, leading to an increased cytosolic NAD-to-NADH ratio. Brooks and co-workers (8) recently proposed that lactate can be transported into the mitochondria and converted to pyruvate and NADH by matrix lactate dehydrogenase. We propose that this would rapidly enhance the mitochondrial NADH-to-NAD ratio and downregulate PDH, particularly when fat oxidation is dominant. Under these conditions in which fat (intracellular TG) is the dominant oxidative substrate, PDH complex activity must be insufficient initially in supplying acetyl CoA to the TCA cycle. Thus pyruvate oxidation would increase more slowly than intramuscular TG lipolysis and -oxidation at the onset of exercise. We think this slow CHO oxidation is not part of the so-called "O₂ drift," as described by Molé and Coulson (29), since it appears as an exponential dynamic as opposed to a linear drift, which often develops during prolonged exercise at moderate to high intensities.

If O₂ distinctly tracks the dynamics of fat and CHO oxidation as proposed, then O₂ in phase 2 would have at least two components that change at different speeds. Moreover, the relative contribution of these substrates could affect the O₂ kinetics, since their ATP-to-O₂ ratios differ because of differences in NADH and FADH₂ production. This can be expressed by Eq. 1

(1)

where f_CHO and f_Fat are the time-dependent fractions for CHO and fat oxidation, respectively. The coefficients in Eq. 1 were derived by assuming that glycogen and mixed intramuscular TG are oxidized during the first minutes of exercise up to the initial attainment of steady state. If the rate of ATP utilization is constant during constant-load muscular work, then the rate of O₂ utilization would vary according to the fractional oxidation of CHO and fat.

	MODEL OF O2 UPTAKE KINETICS

TOP ABSTRACT INTRODUCTION MODEL OF O2 UPTAKE... PROBLEM OF STUDY METHODS AND PROCEDURES RESULTS DISCUSSION REFERENCES

We propose that breath-by-breath O₂ in phase 2 increases as a biexponential and quantitatively represents the dynamics of intramuscular TG and glycogen oxidation during the transition from rest to the initial steady state of exercise. Furthermore, the dynamics of O₂ and the oxidation of these substrates are tightly coupled, and local controls are the dominant factors determining their kinetics. The controls could operate, as reviewed above, such that intramuscular TG oxidation increases more quickly than CHO oxidation with a step increase in work rate. In this case, O₂ kinetics during phase 2 should be expressed by two components, a fast component representing fat oxidation and a slow component reflecting the time course for CHO oxidation, as given by Eq. 2, which is modified from that of Barstow and Molé (6)

(2)

where O₂ describes the time course of muscle oxidation during phases 2 and 3, _R is the initial resting O₂, t is the time starting from the onset of exercise, TD is the time delay where phase 2 O₂ equals _R, _F and _C are the fast (fat) and slow (CHO) asymptotes representing the steady-state increase in O₂ at phase 3 due to fat and CHO oxidation for exercise, and _F and _C are the time constants defining the speed of fat and CHO oxidation, respectively. Given this assignment, steady-state RQ can be estimated from the asymptotic parameters of Eq. 2 by calculating the fractional contribution of CHO (f_CHO, Eq. 3) or fat (f_Fat, Eq. 4)

(3)

(4)

where f_CHO = _C/(_F + _C) and f_Fat = 1.00  f_CHO. With RQ, oxidative CO₂ can be calculated by using the definition of RQ as the ratio of oxidative CO₂ to O₂. For mild to moderate intensities of exercise below lactate threshold or ventilatory threshold (_TH), steady-state RER will be equivalent to RQ (30). Then individuals with different RQs (RERs for mild exercise) should have different f_CHO, f_Fat, _F, _C, and time constants.

	PROBLEM OF STUDY

TOP ABSTRACT INTRODUCTION MODEL OF O2 UPTAKE... PROBLEM OF STUDY METHODS AND PROCEDURES RESULTS DISCUSSION REFERENCES

In the present study we tested these predictions by evaluating the parameters of the O₂ kinetic model (Eq. 2) obtained for mild leg-cycling exercise in 82 subjects (38 women and 44 men) who had widely different steady-state RERs.

The following hypotheses were tested.

Hypothesis 1. Equation 2 will accurately describe phase 2 and 3 O₂ kinetics during mild exercise, as evidenced by the following equality: predicted CO₂ = measured steady-state CO₂.

Hypothesis 2. The asymptote of the fast term (_F) and its fractional contribution [_F/(_F + _C)] will be inversely related to steady-state RER, since we propose that _F is the oxidation of fat.

Hypothesis 3. Conversely, the asymptote of the slow term (_C) and its fractional contribution [_C/(_F + _C)] will be positively related to steady-state RER, since we propose that _C is the oxidation of CHO.

Hypothesis 4. The fast time constant (_F) will be negatively, whereas the slow time constant (_C) will be positively, related to RER.

Hypothesis 5. The TD will not be related to RER.

	METHODS AND PROCEDURES

TOP ABSTRACT INTRODUCTION MODEL OF O2 UPTAKE... PROBLEM OF STUDY METHODS AND PROCEDURES RESULTS DISCUSSION REFERENCES

Subjects. Eighty-two young adults (44 men and 38 women) volunteered to participate in the study after being informed of the requirements, procedures, and risks. Written consent was given in accordance with the requirements of the University's Institutional Review Board for Human Subjects Experimentation. All subjects were physically active, but none were involved in intense training for athletic competition.

Experimental protocol. The first session involved characterizing each subject with respect to body composition, _TH, O_{2 max}, and steady-state O₂ as a function of cycle power output.

Characterization of subjects. On arrival at the laboratory, the subject's body composition was determined by underwater weighing or by air plethysmography by use of the BOD POD (Life Measurements, Concord, CA), as previously described (26). Residual lung volume was determined by the method of Wilmore (46). Percent fat mass was determined from body density with the Siri equation (37). Next, the relationship between steady-state O₂ and leg-cycling power was assessed in the following way. After seat height was adjusted and recorded and the preferred cycling cadence was determined on the electrically braked cycle ergometer (ErgoLine 800S, SensorMedics), the subject rested for 15 min while the flowmeter and gas analyzers of the metabolic cart (model 2900, SensorMedics) were calibrated with a 3-liter syringe and standard O₂ and CO₂ gases, respectively. On-line breath-by-breath determinations of pulmonary ventilation (BTPS), O₂, CO₂, and RER (i.e., CO₂/O₂) were made continuously during consecutive 5-min periods of sitting rest and three intensities of exercise at 30, 60, and 90 W for women and 40, 80, and 120 W for men. The O₂ values were averaged between minutes 4 and 5 of exercise. These data and those obtained in subsequent experiments were regressed against cycling power by least-squares regression analysis (SigmaPlot, version 2.0, Jandel) and were used to define the relationship between O₂ and leg-cycling power output of Fig. 1.

View larger version (21K): [in this window] [in a new window]   Fig. 1.   O2 uptake (O2) as related to leg-cycling power: comparison of women and men. Regression for women: O2 = (451 ± 26.4) + (9.36 ± 0.259)power, standard error of estimate (SEE) = 162 ml/min, R2 = 0.90; regression for men: O2 = (485 ± 33.1) + (11.20 ± 0.194)power, SEE = 309 ml/min, R2 = 0.92. These coefficients are different from those reported in RESULTS, because they were derived by regression of each group's data.

1

1

O₂ kinetics for mild cycling exercise. One week after characterization, the subject began a series of three to eight sessions at 2- to 7-day intervals. Data used for analyses came from an initial, single bout of submaximal cycle ergometer exercise performed each session. Breath-by-breath determinations of gas exchange were made at rest on the bicycle ergometer for 5 min and during the mild "warm-up" bout for 5-10 min at 20-65 W (28-40% O_{2 max}).

Nonlinear regression analysis of O₂ kinetics. The breath-by-breath O₂ data for each bout were smoothed with a four-breath rolling average, interpolated to one value per second, and time aligned to the start of exercise. Next, the responses of three to eight experiments for the subject were averaged. Analysis of O₂ kinetics excluded phase 1. The end of phase 1 or the start of phase 2 for O₂ was determined as the breath before to the sudden, progressive fall in RER. This coincides with the inflection point or the end of the initial plateau of O₂. The data after phase 1 (e.g., phases 2 and 3) were then fit by a double-exponential model (Eq. 2) with a single TD by using standard nonlinear regression techniques provided by SigmaStat (version 1, Jandel Scientific).

Statistics. Values in RESULTS and Tables 1-4 are means ± SD. Group data illustrated in Figs. 2-5 are means ± SE. A difference was accepted as statistically significant for P  0.05 at a power 0.8. Significant gender differences were tested using the independent t-test. The tests for differences between time constants were determined with the dependent t-test. One-way ANOVA was employed to evaluate the effect of RER on the parameters of Eq. 2, with Bonferroni's post hoc test used when appropriate.

	RESULTS

TOP ABSTRACT INTRODUCTION MODEL OF O2 UPTAKE... PROBLEM OF STUDY METHODS AND PROCEDURES RESULTS DISCUSSION REFERENCES

Table 1 presents several characteristics of the volunteers. These results indicate that the participants' relative fatness, O_{2 max}, and _TH were in the expected range for nonobese, physically active young adults.

Figure 1 shows the relationship between the O₂ and leg-cycling power output for the men and women. Comparison of the intercepts, derived by linear regression analysis of each individual's relationship, showed no significant difference between the men and women [500 ± 226 vs. 427 ± 164 (SD) ml/min, respectively]. In contrast, the women responded with a significantly lower slope than the men (9.98 ± 1.74 vs. 10.97 ± 1.70 ml O₂ · min¹ · W¹, P = 0.02). These slopes are equivalent to 3.37 and 3.71 J metabolic energy/J mechanical work when the mean RER values of Table 2 are employed. The inverses of these values are estimates of the efficiency and indicate that the efficiency of leg cycling was 29.7 and 26.9% for the women and men, respectively.

Power, O₂, CO₂, and RER for mild exercise (20-65 W) are given in Table 2 for the women and men. The small differences between genders are attributed, in part, to the differences in efficiency and exercise intensity. On average, the exercise employed represented a O₂ equivalent to 40 and 28% O_{2 max} for the women and men, respectively. In both groups the intensity was well below the _TH of the participants (Table 1). Thus it is reasonable to assume that steady-state RER closely corresponds to RQ for mild exercise used to evaluate O₂ kinetics (30). In this case, the average RER of 0.87 observed for both groups (Table 2) indicates that CHO was the dominant fuel (~56% on average) for oxidative metabolism. This is consistent with the analysis of the habitual diets for the groups (1,984 ± 489 kcal, 14% protein, 59% CHO, and 27% fat for women and 2,952 ± 774 kcal, 16% protein, 53% CHO, and 31% fat for men). However, there were large individual differences in diets. Furthermore, it will be shown that the subjects responded to mild exercise with a wide range of RERs. RER was not related to cycle power output (r = 0.01) but was significantly associated with percent kilocalories from CHO in the diet (r = 0.483, P < 0.01).

The O₂ kinetic parameters obtained from nonlinear regression analysis of the model equation (Eq. 2) are presented in Table 3. No significant differences (P > 0.05) were found for the women and men. Comparison of asymptotes (_F and _C) and time constants (_F and _C) by dependent (paired) t-test for the combined group indicated that only the latter was significant (P < 0.0001).

View this table: [in this window] [in a new window]   Table 3.   Parameters for the O2 kinetic model

The parameters of the model were grouped by RER in 0.05-unit increments (except for values <0.8, which were lumped together) and analyzed by one-way ANOVA. As shown in Table 4, the TD was unchanged over the range of RER groupings. Similarly, _F was invariant with respect to RER = 0.78-0.97. In contrast, _C was inversely related to RER (r = 0.97). That is, for RER = 0.78 the slow time constant was 163 ± 59 s, but at RER = 0.97 the time constant of 14 ± 7.9 s was significantly faster (Table 4). At RER < 0.92, _F and _C were different (P < 0.05). These findings are illustrated in Fig. 2 by the relationships between the time constants and RER. Figure 2 shows that _C converges toward _F as RER approaches unity, making it impossible to discern a second-order dynamic response at RER  0.92. 

View this table: [in this window] [in a new window]   Table 4.   Grouping by steady-state RER for the parameters of the O2 kinetic model

View larger version (16K): [in this window] [in a new window]   Fig. 2.   Time constants of O2 kinetic model as related to steady-state respiratory exchange ratio (RER) for mild exercise. Values are group means ± SE. Time constants for fast (fat, F) and slow [carbohydrate (CHO), C] oxidative terms are significantly different (P < 0.05) at RER < 0.92.

The fast (_F) and the slow (_C) steady-state parameters of the kinetic model were significantly related to RER (Table 4, Fig. 3; P < 0.0001). More specifically, the absolute rate of the fast component was inversely related to RER and approached zero at RER = 1.00. The slow component showed the opposite (positive) relationship with RER. Because RER approximates RQ at steady state for mild exercise, as studied here, these relationships with RER imply that the fast and slow components represent fat and CHO oxidation, respectively. An initial test of this assignment is provided by the expected relationship between RQ and the fractional oxidation of fat (f_Fat) at steady state (Eq. 4): RQ = 1.00  0.293f_Fat, where f_Fat = [_F/(_F + _C)]. This prediction is illustrated by the theoretical dashed line of Fig. 4. Also shown are values we obtained for f_Fat for the RER groupings. Notice how closely they approximate the theorectical f_Fat at RER = 0.78, 0.82, and 0.88. At RER  0.92, there was a clear discrepancy between the estimated and theoretical f_Fat. This occurred where the time constants approached each other (Fig. 2), making it technically difficult to discern two unique components for O₂ kinetics for mild cycling exercise.

View larger version (18K): [in this window] [in a new window]   Fig. 3.   Fast (F) and slow (C) asymptotes of kinetic model as related to steady-state RER for mild exercise. Values are group means ± SE.

View larger version (22K): [in this window] [in a new window]   Fig. 4.   Fractional contribution of F as related to steady-state RER for mild exercise. Values are group means ± SE and individual values.

Equation 4 provides a method for calculating RQ and oxidative CO₂ from f_Fat. The estimated oxidative and measured CO₂ at steady state as well as the differences between them for the RER groupings are presented in Fig. 5, A and B, respectively. The discrepancies for the mean RERs of 0.92 and 0.97 were small (25 ± 5.8 and 41 ± 4.7 ml/min, respectively) but statistically significant (P < 0.05). However, the predicted and measured CO₂ were strongly related (Fig. 6A; r = 0.99). The mean difference was 11 ± 3.0 (SE) ml/min (Fig. 6B) over the domain of CO₂ evaluated.

View larger version (20K): [in this window] [in a new window]   Fig. 5.   Comparison of measured (Meas) and predicted (Pred) CO2 production (CO2, A) and differences (B) as related to steady-state RER for mild leg cycling. Values are group means ± SE.

View larger version (22K): [in this window] [in a new window]   Fig. 6.   Comparison of measured and predicted CO2: individual responses (A) and differences (B). Coefficient of determination (R2) was 0.99 (A), and difference (mean ± SE) was 11 ± 3.0 ml/min (B); 95% confidence interval is shown relative to mean difference (B).

	DISCUSSION

TOP ABSTRACT INTRODUCTION MODEL OF O2 UPTAKE... PROBLEM OF STUDY METHODS AND PROCEDURES RESULTS DISCUSSION REFERENCES

The present study showed that 1) our double-exponential model adequately described the O₂ kinetics for the subjects with RERs < 0.92, 2) _F was inversely correlated, whereas _C was positively correlated with steady-state RER, and 3) TD and _F were independent of RER, whereas _C was inversely related to RER. These findings suggest that the relative contributions of fat and CHO to oxidative metabolism determine the relative contributions of the fast and slow components of O₂ kinetics and the speed of the slow component. The possibility that these relationships reflect cause and effect is supported by the accurate estimates of steady-state RQ and CO₂ obtained with our kinetic model and indirect calorimetric paradigm. Therefore, it would appear that the fast component of O₂ represents fat oxidation while the slow component of O₂ is due to CHO oxidation.

Our findings show that steady-state O₂ increased in proportion to leg-cycling power output, indicating that aerobic metabolism behaves as a linear system, as has been consistently reported for exercise intensities below _TH (6, 14, 44). Furthermore, O₂ kinetics of mild exercise below _TH were strongly associated with RER, as seen in Table 4. For RER < 0.92, O₂ kinetics in phases 2 and 3 responded as a second-order linear system, inasmuch as respiration could be described by a fast and a slower exponential term. At RER  0.92, the system was statistically discerned only as a first-order linear system, i.e., with only a fast exponential term. This apparent change in the system's order came about because the slow time constant was inversely related to RER. That is, as RER increased, the slow time constant became faster, thereby converging toward the invariant fast time constant. This effect of RER probably is an important reason why we (6) and others (14, 44) could only describe O₂ kinetics with a monoexponential model for exercise intensities below _TH. Our experimental evidence helps explain this apparent transition in the system's order over the domain of RER.

It is thought that the rapid rise in muscle O₂ at the onset of exercise represents the oxidation of CHO. However, our finding of an inverse relationship between the fast O₂ component and RER suggests that this component reflects fat oxidation, not CHO oxidation. This is supported by the finding that our model accurately predicts steady-state RQ and oxidative CO₂ when the fast term is assigned to fat oxidation. Therefore, the transition from a double to a single exponential should occur as RER approaches unity, because the contribution of fat would progressively decrease and disappear at an RER of unity, leaving only CHO as the sole oxidative substrate. Unfortunately, it was difficult to identify the two components at RER  0.92. This practical limitation of the model probably is due to the inherent breath-by-breath noise and to the variability in the time constants in individuals with different muscle fiber type composition and recruitment patterns, which may affect O₂ kinetics independent of RER (24). These factors, combined with the acceleration of the slow time constant, make it technically difficult to discern two dynamic components at high RERs. Nevertheless, it is expected that detection will improve at exercise intensities higher than that for very mild exercise employed in this study because of greater signal-to-noise ratio for breath-by-breath O₂.

We have presented only correlational evidence in support of our model. Preliminary results from research in progress show that dietary-induced metabolic adaptations alter O₂ kinetics as predicted by our model. That is, metabolic adaptations to a fat diet increase the contribution of the fast (fat oxidation) component and reduce the contribution of the slow (CHO oxidation) term. The converse occurs when adaptations are induced by a CHO diet. Figure 7 is an example of these preliminary results in one subject. Notice the slow rise in O₂ for the subject on the fat diet (Fig. 7A) that appears to disappear on the CHO diet (Fig. 7B). In both cases, there is excellent agreement between the predicted RQ and measured steady-state RER. These results are encouraging, but we must reserve judgment until a more complete assessment of dietary effects can be made and other experimental tests of the model are undertaken and reported.

View larger version (17K): [in this window] [in a new window]   Fig. 7.   Representative effect of fat (A) and CHO (B) diets on O2 kinetics during mild leg-cycling exercise at 39 W in a man. For fat diet, solution to model Eq. 2 was as follows: O2 = 481 + 607exp[(t  15.6)/17.5] + 234exp[(t  15.6)/197.8], R2 = 0.92, measured RER = 0.79 vs. predicted respiratory quotient = 0.79. For CHO diet, solution to model Eq. 2 was as follows: O2 = 239 + 456exp[(t  4.6)/32.5] + 479exp[(t  4.6)/42.4], R2 = 0.98, measured RER = 0.87 vs. predicted respiratory quotient = 0.86.

Other considerations suggest that the dynamics of muscle fat oxidation are fast and represent oxidation of intramuscular TGs, whereas the slow component represents primarily glycogen oxidation during the transition to the initial steady state (5-10 min). At the initiation of all intensities of exercise, glycogenolysis is rapidly activated. Wahren et al. (41) showed that, during the first 2 min of forearm exercise, net glucose is released, indicating that glycogen is the primary CHO substrate utilized during this early period. Connett et al. (10) found in contracting dog gracilis muscle that the initial burst in the glycolytic rate is independent of muscle PO₂ and O₂. Lactate rapidly accumulated, indicating a mismatch between pyruvate production and oxidation. They suggested that aerobic glycolysis functions to reduce the cytosolic redox state via lactate accumulation to support mitochondrial fat oxidation. Consistent with this suggestion are the results of computer simulation studies on work-work transitions in the pyruvate-perfused heart. Garfinkel et al. (15) showed that pyruvate is mainly removed by lactate accumulation in the first 30 s of a step increase in work. Thus their findings are consistent with the view that intramuscular TG oxidation rapidly increases to support aerobic production of ATP with a step increase in work.

However, studies on net utilization of muscle TG have reported conflicting results (34). Some studies (22, 38) have shown muscle TG concentration to be unaltered by exercise, whereas others (12, 18, 19, 35) have found exercise to decrease intracellular TG concentration. Intracellular TGs do turn over (35). Therefore, these discrepancies suggest that the balance between TG synthesis and utilization can be variable under various conditions of exercise. Differences between total fat oxidation by indirect calorimetry and plasma free fatty acid oxidation suggest that intracellular TG can account for ~50% of the fat oxidized at steady state during prolonged exercise (13, 16, 17, 20, 32).

It is not known what contribution intramuscular TG makes to oxidative metabolism during the transient period of exercise. However, skeletal muscle has the enzymatic pathway for quickly increasing lipolysis of intramuscular TG to support the rapid increase in O₂ at the onset of exercise. Oscai and co-workers (31) studied an intramuscular TG lipase and showed that it is rapidly activated by protein phosphorylation mediated by cAMP-dependent protein kinase. Thus it is reasonable to assume that the activity of this lipase rapidly increases with the activation of phosphorylase at the onset of exercise. Presumably, -oxidation also increases in concert with activation of lipolysis, inasmuch as the expected rise in AMP protein kinase would phosphorylate and inactivate acetyl CoA carboxylase, which is responsible for synthesis of malonyl CoA (47). Consequently, a rapid fall in malonyl CoA would disinhibit carnitine acyl transferase I, which is the rate-limiting enzyme in -oxidation. Although more research on the dynamics of intracellular TG lipolysis is needed, these speculations suggest that the machinery is present and could activate intracellular TG oxidation rapidly to support the fast increase in muscle oxidation.

Consistent with this idea is indirect evidence which shows that the RER decreases at the start of phase 2 O₂ (24). Estimated "apparent" CO₂ retention from the RER decline is markedly greater than can be accounted for by the alkalinization produced from net H⁺ removal and phosphocreatine utilization by the creatine kinase reaction (unpublished observations). Therefore, this suggests that fat oxidation likely is increasing faster than CHO oxidation during the early rise in O₂. We have reviewed evidence elsewhere (26) which suggests that intramuscular TG is the immediate source of fatty acid oxidation and is rapidly oxidized. For example, Zierler (48) found that production of ¹⁴CO₂ lags the uptake of ¹⁴C-labeled plasma fatty acids in humans at rest when the arteriovenous RQ across the muscle was low, indicating dominance of intracellular fat oxidation. Paul and Issekutz (32) observed a similar delay in plasma fatty acid oxidation at the onset of exercise in the dog, even though the specific activity of ¹⁴C-labeled plasma fatty acids was at steady state. This probably occurred because the intramuscular TG pool was not labeled adequately. Consequently, this resulted in a rapid increase in CO₂ from unlabeled TG. Also, Issekutz and Paul (20) showed that, after prolonged infusion of [¹⁴C]palmitate for 190 min to label muscle TGs, ¹⁴CO₂ production rapidly increased during the onset of exercise, even though the specific activity of plasma [¹⁴C]palmitate had fallen to a nominal level 5 min into exercise after infusion was stopped. All these findings suggest that intramuscular TG is the immediate fuel for fatty acid oxidation at the onset of exercise.

Although it is unclear what specific factors influence the time constants, it is reasonable to assume that the fast time constant provides information related to the speed of fat oxidation. A comparison of our fast time constant with those reported for plasma [¹⁴C]palmitate oxidation demonstrates an important discrepancy between our data and the dynamics of plasma fatty acid oxidation. In this regard, plasma fatty acid oxidation probably does not contribute directly to the fast component during the initial phase of exercise, because its dynamic is very slow. Our fast time constant averaged 15 s (Table 3) and varied between 21 and 10 s for RERs of 0.78 and 0.97, respectively. In contrast, Havel et al. (16) reported that the time constant for plasma [¹⁴C]palmitate oxidation during walking at 3-4 miles/h in the fed state was 93-106 s and increased to 125-172 s in the fasted condition in six men. Notice that fasting slowed the kinetics, which is consistent with our finding that O₂ kinetics are slow when RER is low. For more vigorous exercise, Friedberg et al. (13) reported a time constant of 126 s for plasma [¹⁴C]palmitate oxidation. Clearly, the time constant for the fast O₂ component in our study is an order of magnitude faster than those reported for plasma fatty acid oxidation. Therefore, either our model is wrong or the fast O₂ component reflects the oxidation of intramuscular TGs.

In summary, the dynamics of O₂ during the rest-work transition are influenced by RER. Statistically modeling O₂ kinetics as a double exponential and assigning the fast and slow terms to fat and CHO oxidation, respectively, were shown to accurately predict steady-state RQ and oxidative CO₂ over a wide range of RERs for mild exercise. These results are consistent with available data and our theory, which proposes that the rapid rise in muscle O₂ involves a concerted interaction of modulators of the redox and phosphorylation states that feed back to modify the contraction-induced activation of intramuscular TG lipolysis, -oxidation, and glycogen utilization. If future experiments confirm the validation of this model and paradigm, then we will have a new quantitative method for assessing the gross dynamics of energy transfer and fat and CHO oxidation, which can be used to investigate various aspects of exercise metabolism and respiratory control in vivo.