Linking pulmonary oxygen uptake, muscle oxygen utilization and cellular metabolism during exercise

A longitudinal examination of the effect of physical exercise on the emotional states of college students: exploring the sense of coherence as a mediator through a cross-lagged panel analysis

Purpose

This longitudinal study aimed to investigate the causal relationship between physical exercise and emotional states among university students, focusing on the mediating role of sense of coherence.

Method

A total of 1,215 university students (aged 18-25 years) were recruited and completed questionnaires assessing physical activity (International Physical Activity Questionnaire-Short Form), emotional states (Positive and Negative Affect Schedule), and sense of coherence (Sense of Coherence Scale-13) at three time points over a three-month period. Preliminary analyses included independent samples t-tests, chi-square tests, and Pearson correlations. Cross-lagged panel mediation analysis was conducted using Mplus 8.3, with bootstrapping employed to test indirect effects.

Results

Results indicated that sense of coherence significantly predicted positive affect (β = 0.259-0.369, p < 0.001). Positive affect, in turn, predicted physical exercise (β = 0.083-0.182, p < 0.05), while negative affect also influenced physical exercise (β = -0.096-0.203, p < 0.05). Physical exercise indirectly influenced positive affect through sense of coherence (β = 0.037, p = 0.045), and positive affect indirectly influenced physical exercise through sense of coherence (β = 0.029, p = 0.028). Other indirect effects involving physical exercise, sense of coherence, and negative affect were non-significant.

Conclusion

This study underscores the importance of sense of coherence in promoting emotional well-being among university students and in the reciprocal relationship between physical exercise and positive emotional states. Findings suggest that interventions targeting sense of coherence may enhance the emotional benefits of physical exercise. Future research should explore other potential mediators and moderators of the relationship between physical exercise and emotions and examine the effectiveness of sense of coherence-based interventions on well-being in this population.

Blood volume versus deoxygenated NIRS signal: computational analysis of the effects muscle O2 delivery and blood volume on the NIRS signals

Near-infrared spectroscopy (NIRS) signals quantify the oxygenated (ΔHbMbO2) and deoxygenated (ΔHHbMb) heme group concentrations. ΔHHbMb has been preferred to ΔHbMbO2 in evaluating skeletal muscle oxygen extraction because it is assumed to be less sensitive to blood volume (BV) changes, but uncertainties exist on this assumption. To analyze this assumption, a computational model of oxygen transport and metabolism is used to quantify the effect of O2 delivery and BV changes on the NIRS signals from a canine model of muscle oxidative metabolism (Sun Y, Ferguson BS, Rogatzki MJ, McDonald JR, Gladden LB. Med Sci Sports Exerc 48: 2013-2020, 2016). The computational analysis accounts for microvascular (ΔHbO2, ΔHHb) and extravascular (ΔMbO2, ΔHMb) oxygenated and deoxygenated forms. Simulations predicted muscle oxygen uptake and NIRS signal changes well for blood flows ranging from resting to contracting muscle. Additional NIRS signal simulations were obtained in the absence or presence of BV changes corresponding to a heme groups concentration changes (ΔHbMb = 0-48 µM). Under normal delivery (Q = 1.0 L·kg-1·min-1) in contracting muscle, capillary oxygen saturation (So2) was 62% with capillary ΔHbO2 and ΔHHb of ± 41 µΜ for ΔHbMb = 0. An increase of BV (ΔHbMb = 24 µΜ) caused a ΔHbO2 decrease (16µΜ) almost twice as much as the increase observed for ΔHHb (9 µΜ). When So2 increased to more than 80%, only ΔHbO2 was significantly affected by BV changes. The analysis indicates that microvascular So2 is a key factor in determining the sensitivity of ΔHbMbO2 and deoxygenated ΔHHbMb to BV changes. Contrary to a common assumption, the ΔHHbMb is affected by BV changes in normal contracting muscle and even more in the presence of impaired O2 delivery.NEW & NOTEWORTHY Deoxygenated is preferred to the oxygenated near-infrared spectroscopy signal in evaluating skeletal muscle oxygen extraction because it is assumed to be insensitive to blood volume changes. The quantitative analysis proposed in this study indicates that even in absence of skin blood flow effects, both NIRS signals in presence of either normal or reduced oxygen delivery are affected by blood volume changes. These changes should be considered to properly quantify muscle oxygen extraction by NIRS methods.

Using an Electromyography Method While Measuring Oxygen Uptake to Appreciate Physical Exercise Intensity in Adolescent Cyclists: An Analytical Study

Background and Objectives: During physical exercise, the electrical signal of the muscle fibers decreases due to repeated muscle contractions held at different intensities. The measured signal is strongly related to the motor unit activation rate, which is dependent on the chemical mediators and the available energy. By reducing the energy availability, adenosine triphosphate (ATP) production will decrease and therefore the muscle fibers activation rate will be negatively affected. Such aspects become important when taking into account that the training intensity for many young athletes is rather controlled by using the heart rate values. Yet, on many occasions, we have seen differences and lack of relationship between the muscle activation rate, the heart rate values and the lactate accumulation. Materials and Methods: We conducted a prospective analytical study conducted during a 4-month period, on a sample of 30 participants. All study participants underwent an incremental exercise bike test to measure maximum aerobic capacity as well as the muscle activation rate in the vastus lateralis by using an electromyography method (EMG). Results: With age, the EMG signal dropped, as did the electromyography fatigue threshold (EMG_FT) point, as seen through p = 0.0057, r = −0.49, CI95% = −0.73 to −0.16, and electromyography maximum reached point (EMG_MRP) (p = 0.0001, r = −0.64, CI95% = −0.82 to −0.36), whereas power output increased (p = 0.0186, r = 0.427). The higher the power output, the lower the signal seen by measuring active tissue EMG_FT (p = 0.0324, r = −0.39) and EMG_MRP (p = 0.0272, r = −0.40). Yet, with changes in median power output, the power developed in aerobic (p = 0.0087, r = 0.47), mixed (p = 0.0288, r = 0.39), anaerobic (p = 0.0052, r = 0.49) and anaerobic power (p = 0.004, r = 0.50) exercise zones increased. Conclusions: There has been reported a relationship between aerobic/anaerobic ventilatory thresholds (VT₁ and VT₂) and EMG_FT, EMG_MRP, respectively. Each change in oxygen uptake increased the power output in EMG_FT and EMG_MRP, improving performances and therefore overlapping with both ventilatory thresholds.

Cardiopulmonary responses to maximal aerobic exercise in patients with cystic fibrosis

Cystic fibrosis (CF) is a debilitating chronic condition, which requires complex and expensive disease management. Exercise has now been recognised as a critical factor in improving health and quality of life in patients with CF. Hence, cardiopulmonary exercise testing (CPET) is used to determine aerobic fitness of young patients as part of the clinical management of CF. However, at present there is a lack of conclusive evidence for one limiting system of aerobic fitness for CF patients at individual patient level. Here, we perform detailed data analysis that allows us to identify important systems-level factors that affect aerobic fitness. We use patients’ data and principal component analysis to confirm the dependence of CPET performance on variables associated with ventilation and metabolic rates of oxygen consumption. We find that the time at which participants cross the gas exchange threshold (GET) is well correlated with their overall performance. Furthermore, we propose a predictive modelling framework that captures the relationship between ventilatory dynamics, lung capacity and function and performance in CPET within a group of children and adolescents with CF. Specifically, we show that using Gaussian processes (GP) we can predict GET at the individual patient level with reasonable accuracy given the small sample size of the available group of patients. We conclude by presenting an example and future perspectives for improving and extending the proposed framework. The modelling and analysis have the potential to pave the way to designing personalised exercise programmes that are tailored to specific individual needs relative to patient’s treatment therapies.

Impact of venous return on pulmonary oxygen uptake kinetics during dynamic exercise: in silico time series analyses from muscles to lungs

The aim of the present study was to investigate whether a single-compartment (SCM) and a multi-compartment (MCM) venous return model will produce significantly different time-delaying and distortive effects on pulmonary oxygen uptake (V̇o2pulm) responses with equal cardiac outputs (Q̇) and muscle oxygen uptake (V̇o2musc) inputs. For each model, 64 data sets were simulated with alternating Q̇ and V̇o2musc kinetics—time constants (τ) ranging from 10 to 80 s—as responses to pseudorandom binary sequence work rate (WR) changes. Kinetic analyses were performed by using cross-correlation functions (CCFs) between WR with V̇o2pulm and V̇o2musc. Higher maxima of the CCF courses indicate faster system responses—equal to smaller τ values of the variables of interest (e.g., τV̇o2musc). The models demonstrated a highly significant relationship for the resulting V̇o2pulm responses ( r = 0.976, P < 0.001, n = 64). Both models showed significant differences between V̇o2pulm and V̇o2musc kinetics for τV̇o2musc ranging from 10 to 30 s ( P < 0.05 each). In addition, a significant difference in V̇o2pulm kinetics ( P < 0.05) between the models was observed for very fast V̇o2musc kinetics (τ = 10 s). The combinations of fast Q̇ dynamics and slow V̇o2musc kinetics yield distinct deviations in the resultant V̇o2pulm responses compared with V̇o2musc kinetics. Therefore, the venous return models should be used with care and caution if the aim is to infer V̇o2musc by means of V̇o2pulm kinetics. Finally, the resultant V̇o2pulm responses seem to be complex and most likely unpredictable if no cardiodynamic measurements are available in vivo.

NEW & NOTEWORTHY A single-compartment and a multi-compartment venous return model were tested to see whether they result in different pulmonary oxygen uptake (V̇o2pulm) kinetics from equal cardiac output and muscle oxygen uptake (V̇o2musc) kinetics. To infer V̇o2musc kinetics by means of V̇o2pulm kinetics, both models should only be used for V̇o2musc time constants ranging from 40 to 80 s. The resultant V̇o2pulm responses seem to be complex and most likely unpredictable if no cardiodynamic measurements are available.

Temporal dissociation between muscle and pulmonary oxygen uptake kinetics: influences of perfusion dynamics and arteriovenous oxygen concentration differences in muscles and lungs

PURPOSE

The aim of the study was to test whether or not the arteriovenous oxygen concentration difference (avDO₂) kinetics at the pulmonary (avDO₂pulm) and muscle (avDO₂musc) levels is significantly different during dynamic exercise.

METHODS

A re-analysis involving six publications dealing with kinetic analysis was utilized with an overall sample size of 69 participants. All studies comprised an identical pseudorandom binary sequence work rate (WR) protocol-WR changes between 30 and 80 W-to analyze the kinetic responses of pulmonary ([Formula: see text]) and muscle ([Formula: see text]) oxygen uptake kinetics as well as those of avDO₂pulm and avDO₂musc.

RESULTS

A significant difference between [Formula: see text] (0.395 ± 0.079) and [Formula: see text] kinetics (0.330 ± 0.078) was observed (p < 0.001), where the variables showed a significant relationship (r_SP = 0.744, p < 0.001). There were no significant differences between avDO₂musc (0.446 ± 0.077) and avDO₂pulm kinetics (0.451 ± 0.075), which are highly correlated (r = 0.929, p < 0.001).

CONCLUSION

It is suggested that neither avDO₂pulm nor avDO₂musc kinetic responses seem to be responsible for the differences between estimated [Formula: see text] and measured [Formula: see text] kinetics. Obviously, the conflation of avDO₂ and perfusion ([Formula: see text] ) at different points in time and at different physiological levels drive potential differences in [Formula: see text] and [Formula: see text] kinetics. Therefore, [Formula: see text] should, in general, be considered whenever oxygen uptake kinetics are analyzed or discussed.

Gas exchange kinetics following concentric-eccentric isokinetic arm and leg exercise

PURPOSE

To evaluate the effects of exercise velocity (60, 150, 240deg∙s^-1) and muscle mass (arm vs leg) on changes in gas exchange and arterio-venous oxygen content difference (avDO₂) following high-intensity concentric-eccentric isokinetic exercise.

METHODS

Fourteen subjects (26.9±3.1years) performed a 3×20-repetition isokinetic exercise protocol. Recovery beat-to-beat cardiac output (CO) and breath-by-breath gas exchange were recorded to determine post-exercise half-time (t_1/2) for oxygen uptake (V˙O₂pulm), carbon dioxide output (V˙CO₂pulm), and ventilation (V˙_E).

RESULTS

Significant differences of the t_1/2 values were identified between 60 and 150deg∙s^-1. Significant differences in the t_1/2 values were observed between V˙O₂pulm and V˙CO₂pulm and between V˙CO₂pulm and V˙_E. The time to attain the first avDO₂-peak showed significant differences between arm and leg exercise.

CONCLUSIONS

The present study illustrates, that V˙O₂pulm kinetics are distorted due to non-linear CO dynamics. Therefore, it has to be taken into account, that V˙O₂pulm may not be a valuable surrogate for muscular oxygen uptake kinetics in the recovery phases.

Exercise: Kinetic considerations for gas exchange

The activities of daily living typically occur at metabolic rates below the maximum rate of aerobic energy production. Such activity is characteristic of the nonsteady state, where energy demands, and consequential physiological responses, are in constant flux. The dynamics of the integrated physiological processes during these activities determine the degree to which exercise can be supported through rates of O₂ utilization and CO₂ clearance appropriate for their demands and, as such, provide a physiological framework for the notion of exercise intensity. The rate at which O₂ exchange responds to meet the changing energy demands of exercise--its kinetics--is dependent on the ability of the pulmonary, circulatory, and muscle bioenergetic systems to respond appropriately. Slow response kinetics in pulmonary O₂ uptake predispose toward a greater necessity for substrate-level energy supply, processes that are limited in their capacity, challenge system homeostasis and hence contribute to exercise intolerance. This review provides a physiological systems perspective of pulmonary gas exchange kinetics: from an integrative view on the control of muscle oxygen consumption kinetics to the dissociation of cellular respiration from its pulmonary expression by the circulatory dynamics and the gas capacitance of the lungs, blood, and tissues. The intensity dependence of gas exchange kinetics is discussed in relation to constant, intermittent, and ramped work rate changes. The influence of heterogeneity in the kinetic matching of O₂ delivery to utilization is presented in reference to exercise tolerance in endurance-trained athletes, the elderly, and patients with chronic heart or lung disease.

A validated model of oxygen uptake and circulatory dynamic interactions at exercise onset in humans

At the onset of muscular exercise, the kinetics of pulmonary O2 uptake (Vo2P) reflect the integrated dynamic responses of the ventilatory, circulatory, and neuromuscular systems for O2 transport and utilization. Muscle O2 uptake (Vo2m) kinetics, however, are dissociated from Vo2P kinetics by intervening O2 capacitances and the dynamics of the circulation and ventilation. We developed a multicompartment computational model (MCM) to investigate these dynamic interactions and optimized and validated the MCM using previously published, simultaneously measured Vo2m, alveolar O2 uptake (Vo2A), and muscle blood flow (Qm) in healthy young men during cycle ergometry. The model was used to show that 1) the kinetics of Vo2A during exercise transients are very sensitive to preexercise blood flow distribution and the absolute value of Qm, 2) a low preexercise Qm exaggerates the magnitude of the transient fall in venous O2 concentration for any given Vo2m kinetics, necessitating a tighter coupling of Qm/Vo2m (or a reduction in the available work rate range) during the exercise transient to avoid limits to O2 extraction, and 3) information regarding exercise-related alterations in O2 uptake and blood flow in nonexercising tissues and their effects on mixed venous O2 concentration is required to accurately predict Vo2A kinetics from knowledge of Vo2m and Qm dynamics. Importantly, these data clearly demonstrate that Vo2A kinetics are nonexponential, nonlinear distortions of Vo2m kinetics that can be explained in a MCM by interactions among circulatory and cellular respiratory control processes before and during exercise.

PathCase-SB: integrating data sources and providing tools for systems biology research

BACKGROUND

Integration of metabolic pathways resources and metabolic network models, and deploying new tools on the integrated platform can help perform more effective and more efficient systems biology research on understanding the regulation of metabolic networks. Therefore, the tasks of (a) integrating under a single database environment regulatory metabolic networks and existing models, and (b) building tools to help with modeling and analysis are desirable and intellectually challenging computational tasks.

RESULTS

PathCase Systems Biology (PathCase-SB) is built and released. This paper describes PathCase-SB user interfaces developed to date. The current PathCase-SB system provides a database-enabled framework and web-based computational tools towards facilitating the development of kinetic models for biological systems. PathCase-SB aims to integrate systems biology models data and metabolic network data of selected biological data sources on the web (currently, BioModels Database and KEGG, respectively), and to provide more powerful and/or new capabilities via the new web-based integrative framework.

CONCLUSIONS

Each of the current four PathCase-SB interfaces, namely, Browser, Visualization, Querying, and Simulation interfaces, have expanded and new capabilities as compared with the original data sources. PathCase-SB is already available on the web and being used by researchers across the globe.

Modeling oxygenation in venous blood and skeletal muscle in response to exercise using near-infrared spectroscopy

Noninvasive, continuous measurements in vivo are commonly used to make inferences about mechanisms controlling internal and external respiration during exercise. In particular, the dynamic response of muscle oxygenation (Sm(O(2))) measured by near-infrared spectroscopy (NIRS) is assumed to be correlated to that of venous oxygen saturation (Sv(O(2))) measured invasively. However, there are situations where the dynamics of Sm(O(2)) and Sv(O(2)) do not follow the same pattern. A quantitative analysis of venous and muscle oxygenation dynamics during exercise is necessary to explain the links between different patterns observed experimentally. For this purpose, a mathematical model of oxygen transport and utilization that accounts for the relative contribution of hemoglobin (Hb) and myoglobin (Mb) to the NIRS signal was developed. This model includes changes in microvascular composition within skeletal muscle during exercise and integrates experimental data in a consistent and mechanistic manner. Three subjects (age 25.6 +/- 0.6 yr) performed square-wave moderate exercise on a cycle ergometer under normoxic and hypoxic conditions while muscle oxygenation (C(oxy)) and deoxygenation (C(deoxy)) were measured by NIRS. Under normoxia, the oxygenated Hb/Mb concentration (C(oxy)) drops rapidly at the onset of exercise and then increases monotonically. Under hypoxia, C(oxy) decreases exponentially to a steady state within approximately 2 min. In contrast, model simulations of venous oxygen concentration show an exponential decrease under both conditions due to the imbalance between oxygen delivery and consumption at the onset of exercise. Also, model simulations that distinguish the dynamic responses of oxy-and deoxygenated Hb (HbO(2), HHb) and Mb (MbO(2), HMb) concentrations (C(oxy) = HbO(2) + MbO(2); C(deoxy) = HHb + HMb) show that Hb and Mb contributions to the NIRS signal are comparable. Analysis of NIRS signal components during exercise with a mechanistic model of oxygen transport and metabolism indicates that changes in oxygenated Hb and Mb are responsible for different patterns of Sm(O(2)) and Sv(O(2)) dynamics observed under normoxia and hypoxia.

Non-invasive estimation of metabolic flux and blood flow in working muscle: effect of blood-tissue distribution

Muscle oxygenation measurements by near infrared spectroscopy (NIRS) are frequently obtained in humans to make inferences about mechanisms of metabolic control of respiration in working skeletal muscle. However, these measurements have technical limitations that can mislead the evaluation of tissue processes. In particular, NIRS measurements of working muscle represent oxygenation of a mix of fibers with heterogeneous activation, perfusion and architecture. Specifically, the relative volume distribution of capillaries, small arteries, and venules may affect NIRS data. To determine the effect of spatial volume distribution of components of working muscle on oxygen utilization dynamics and blood flow changes, a mathematical model of oxygen transport and utilization was developed. The model includes blood volume distribution within skeletal muscle and accounts for convective, diffusive, and reactive processes of oxygen transport and metabolism in working muscle. Inputs to the model are arterial O2 concentration, cardiac output and ATP demand. Model simulations were compared to exercise data from human subjects during a rest-to-work transition. Relationships between muscle oxygen consumption, blood flow, and the rate coefficient of capillary-tissue transport are analyzed. Blood volume distribution in muscle has noticeable effects on the optimal estimates of metabolic flux and blood flow in response to an exercise stimulus.

Models of muscle contraction and energetics

How does skeletal muscle manage to regulate the pathways of ATP synthesis during large-scale changes in work rate while maintaining metabolic homeostasis remains unknown. The classic model of metabolic regulation during muscle contraction states that accelerating ATP utilization leads to increasing concentrations of ADP and Pi, which serve as substrates for oxidative phosphorylation and thus accelerate ATP synthesis. An alternative model states that both the ATP demand and ATP supply pathways are simultaneously activated. Here, we review experimental and computational models of muscle contraction and energetics at various organizational levels and compare them with respect to their pros and cons in facilitating understanding of the regulation of energy metabolism during exercise in the intact organism.

Role of NADH/NAD+ transport activity and glycogen store on skeletal muscle energy metabolism during exercise: in silico studies

Skeletal muscle can maintain ATP concentration constant during the transition from rest to exercise, whereas metabolic reaction rates may increase substantially. Among the key regulatory factors of skeletal muscle energy metabolism during exercise, the dynamics of cytosolic and mitochondrial NADH and NAD+ have not been characterized. To quantify these regulatory factors, we have developed a physiologically based computational model of skeletal muscle energy metabolism. This model integrates transport and reaction fluxes in distinct capillary, cytosolic, and mitochondrial domains and investigates the roles of mitochondrial NADH/NAD+ transport (shuttling) activity and muscle glycogen concentration (stores) during moderate intensity exercise (60% maximal O2 consumption). The underlying hypothesis is that the cytosolic redox state (NADH/NAD+) is much more sensitive to a metabolic disturbance in contracting skeletal muscle than the mitochondrial redox state. This hypothesis was tested by simulating the dynamic metabolic responses of skeletal muscle to exercise while altering the transport rate of reducing equivalents (NADH and NAD+) between cytosol and mitochondria and muscle glycogen stores. Simulations with optimal parameter estimates showed good agreement with the available experimental data from muscle biopsies in human subjects. Compared with these simulations, a 20% increase (or approximately 20% decrease) in mitochondrial NADH/NAD+ shuttling activity led to an approximately 70% decrease (or approximately 3-fold increase) in cytosolic redox state and an approximately 35% decrease (or approximately 25% increase) in muscle lactate level. Doubling (or halving) muscle glycogen concentration resulted in an approximately 50% increase (or approximately 35% decrease) in cytosolic redox state and an approximately 30% increase (or approximately 25% decrease) in muscle lactate concentration. In both cases, changes in mitochondrial redox state were minimal. In conclusion, the model simulations of exercise response are consistent with the hypothesis that mitochondrial NADH/NAD+ shuttling activity and muscle glycogen stores affect primarily the cytosolic redox state. Furthermore, muscle lactate production is regulated primarily by the cytosolic redox state.

Metabolic dynamics in skeletal muscle during acute reduction in blood flow and oxygen supply to mitochondria: in-silico studies using a multi-scale, top-down integrated model

Control mechanisms of cellular metabolism and energetics in skeletal muscle that may become evident in response to physiological stresses such as reduction in blood flow and oxygen supply to mitochondria can be quantitatively understood using a multi-scale computational model. The analysis of dynamic responses from such a model can provide insights into mechanisms of metabolic regulation that may not be evident from experimental studies. For the purpose, a physiologically-based, multi-scale computational model of skeletal muscle cellular metabolism and energetics was developed to describe dynamic responses of key chemical species and reaction fluxes to muscle ischemia. The model, which incorporates key transport and metabolic processes and subcellular compartmentalization, is based on dynamic mass balances of 30 chemical species in both capillary blood and tissue cells (cytosol and mitochondria) domains. The reaction fluxes in cytosol and mitochondria are expressed in terms of a general phenomenological Michaelis-Menten equation involving the compartmentalized energy controller ratios ATP/ADP and NADH/NAD(+). The unknown transport and reaction parameters in the model are estimated simultaneously by minimizing the differences between available in vivo experimental data on muscle ischemia and corresponding model outputs in coupled with the resting linear flux balance constraints using a robust, nonlinear, constrained-based, reduced gradient optimization algorithm. With the optimal parameter values, the model is able to simulate dynamic responses to reduced blood flow and oxygen supply to mitochondria associated with muscle ischemia of several key metabolite concentrations and metabolic fluxes in the subcellular cytosolic and mitochondrial compartments, some that can be measured and others that can not be measured with the current experimental techniques. The model can be applied to test complex hypotheses involving dynamic regulation of cellular metabolism and energetics in skeletal muscle during physiological stresses such as ischemia, hypoxia, and exercise.

Model of oxygen transport and metabolism predicts effect of hyperoxia on canine muscle oxygen uptake dynamics

Previous studies have shown that increased oxygen delivery, via increased convection or arterial oxygen content, does not speed the dynamics of oxygen uptake, V̇o2m, in dog muscle electrically stimulated at a submaximal metabolic rate. However, the dynamics of transport and metabolic processes that occur within working muscle in situ is typically unavailable in this experimental setting. To investigate factors affecting V̇o2m dynamics at contraction onset, we combined dynamic experimental data across working muscle with a mechanistic model of oxygen transport and metabolism in muscle. The model is based on dynamic mass balances for O2, ATP, and PCr. Model equations account for changes in cellular ATPase, oxidative phosphorylation, and creatine kinase fluxes in skeletal muscle during exercise, and cellular respiration depends on [ADP] and [O2]. Model simulations were conducted at different levels of arterial oxygen content and blood flow to quantify the effects of convection and diffusion of oxygen on the regulation of cellular respiration during step transitions from rest to isometric contraction in dog gastrocnemius muscle. Simulations of arteriovenous O2 differences and V̇o2m dynamics were successfully compared with experimental data (Grassi B, Gladden LB, Samaja M, Stary CM, Hogan MC. J Appl Physiol 85: 1394–1403, 1998; and Grassi B, Gladden LB, Stary CM, Wagner PD, Hogan MC. J Appl Physiol 85: 1404–1412, 1998), thus demonstrating the validity of the model, as well as its predictive capability. The main findings of this study are: 1) the estimated dynamic response of oxygen utilization at contraction onset in muscle is faster than that of oxygen uptake; and 2) hyperoxia does not accelerate the dynamics of diffusion and consequently muscle oxygen uptake at contraction onset due to the hyperoxia-induced increase in oxygen stores. These in silico derived results cannot be obtained from experimental observations alone.