Older adults (O) may have a longer phase I pulmonary O(2) uptake kinetics (Vo(2)(p)) than young adults (Y); this may affect parameter estimates of phase II Vo(2)(p). Therefore, we sought to: 1) experimentally estimate the duration of phase I Vo(2)(p) (EE phase I) in O and Y subjects during moderate-intensity exercise transitions; 2) examine the effects of selected phase I durations (i.e., different start times for modeling phase II) on parameter estimates of the phase II Vo(2)(p) response; and 3) thereby determine whether slower phase II kinetics in O subjects represent a physiological difference or a by-product of fitting strategy. Vo(2)(p) was measured breath-by-breath in 19 O (68 ± 6 yr; mean ± SD) and 19 Y (24 ± 5 yr) using a volume turbine and mass spectrometer. Phase I Vo(2)(p) was longer in O (31 ± 4 s) than Y (20 ± 7 s) (P < 0.05). In O, phase II τVo(2)(p) was larger (P < 0.05) when fitting started at 15 s (49 ± 12 s) compared with fits starting at the individual EE phase I (43 ± 12 s), 25 s (42 ± 10 s), 35 s (42 ± 12 s), and 45 s (45 ± 15 s). In Y, τVo(2)(p) was not affected by the time at which phase II Vo(2)(p) fitting started (τVo(2)(p) = 31 ± 7 s, 29 ± 9 s, 30 ± 10 s, 32 ± 11 s, and 30 ± 8 s for fittings starting at 15 s, 25 s, 35 s, 45 s, and EE phase I, respectively). Fitting from EE phase I, 25 s, or 35 s resulted in the smallest CI τVo(2)(p) in both O and Y. Thus, fitting phase II Vo(2)(p) from (but not constrained to) 25 s or 35 s provides consistent estimates of Vo(2)(p) kinetics parameters in Y and O, despite the longer phase I Vo(2)(p) in O.
"where Y (t) represents VO2 at any time (t); Y
Bsln is the baseline VO2 during 4 km/h/min walking; Amp is the steady-state
increase in VO2 above the baseline value; τ is the time constant defined as the
duration of time for VO2 to increase to 63% of the steady-state increase; and
TD is the time delay (so that the model is not constrained to pass through the origin.) After excluding the initial 20 s of values, while still allowing TD to vary freely (to
optimize the accuracy of parameter estimates), VO2 values were modeled from 20
s to 4 min (240 s) of the step transition; this ensured that each subject had attained a
VO2 steady-state, yet did not bias the model fit during the on-transient15, 16). Model parameters were estimated by least-squares nonlinear
regression (Microsoft Office Excel 2010, Microsoft Japan Co., Ltd., Tokyo, Japan) in which
the best fit was defined by minimization of the residual sum of squares and minimal
residual variations around the Y-axis (Y=0). "
[Show abstract][Hide abstract] ABSTRACT: [Purpose] The objective of this study was to determine the validity of pulmonary oxygen uptake kinetics in assessment of the ability of skeletal muscles to utilize oxygen. [Subjects] We evaluated 12 young, healthy males. [Methods] The subjects completed a series of tests to determine their peak oxygen uptake, pulmonary oxygen uptake kinetics at the onset of moderate-intensity treadmill exercise, and the rate of decline in electromyographic (EMG) mean power frequency (MPF) (EMG MPFrate) during one continuous, fatiguing, isometric muscle action of the plantar flexors until exhaustion at approximately 60% maximum voluntary contraction. We discussed the relationships between pulmonary oxygen uptake kinetics and EMG MPFrate reflecting the ability of skeletal muscles to utilize oxygen and between pulmonary oxygen uptake kinetics and peak oxygen uptake reflecting the ability to deliver oxygen to skeletal muscles. We hypothesized that pulmonary oxygen uptake kinetics may be more highly correlated with EMG MPFrate than peak oxygen uptake. [Results] Pulmonary oxygen uptake kinetics (33.9 ± 5.9 s) were more significantly correlated with peak oxygen uptake (50.6 ± 5.5 mL/kg/min) than EMG MPFrate (-14.7 ± 8.7%/s). [Conclusion] Pulmonary oxygen uptake kinetics is a noninvasive index that is mainly usable for evaluation of the ability of cardiovascular system to deliver oxygen to skeletal muscles in healthy young adults with slower pulmonary oxygen uptake kinetics (>20 s).
"LBF and HR were fit from the first data point after the start of the exercise transient until the end of the exercise bout. On the other hand, the initial 20 s of VO 2p data was excluded to avoid inclusion of data points from Phase 1 VO 2p in the fitting of Phase 2 VO 2p (Murias et al. 2011b). Moreover, the TD was allowed to vary freely to optimize the accuracy of the estimated parameters. "
[Show abstract][Hide abstract] ABSTRACT: The adjustment of pulmonary oxygen uptake (VO2p), heart rate (HR), limb blood flow (LBF), and muscle deoxygenation [HHb] were examined during the transition to moderate-intensity, knee-extension exercise in six older adults (70 ± 4 years) under 2 conditions: normoxia (FIO2=20.9%) and hypoxia (FIO2=15%). The subjects performed repeated step transitions from an active baseline (3 W) to an absolute work rate (21 W) in both conditions. Phase 2 VO2p, HR, LBF, and [HHb] data were fit with an exponential model. Under hypoxic conditions, no change was observed in HR kinetics, on the other hand, LBF kinetics was faster (Norm, 34±3 sec; Hypo 28±2), whereas the overall [HHb] adjustment ( ) was slower (Norm, 28±2; Hypo 33±4 sec). Phase 2 VO2p kinetics were unchanged (p<0.05). The faster LBF kinetics and slower [HHb] kinetics reflect an improved matching between O2 delivery and O2 utilization at the microvascular level, preventing the phase 2 VO2p kinetics from become slower in hypoxia. Moreover the absolute blood flow values were higher in hypoxia (1.17 ± 0.2 l*min-1) compared to normoxia (0.96 ± 0.2 l*min-1) during the steady state exercise at 21 watts. These findings support the idea that, for older adults exercising at a low work rate, an increase of limb blood flow offsets the drop in arterial oxygen content (CaO2) caused by breathing an hypoxic mixture.
"This phase reflects the adjustment of VO2 due to the use of active skeletal muscles. Phase III is the steady state phase of VO2p and VO2 during moderate exercise intensities [2,3]. For work rates associated with sustained acidosis, the mono-exponential component is slowed compared with lower intensities below the lactate threshold. "
[Show abstract][Hide abstract] ABSTRACT: Background
This study investigated two different mathematical models for the kinetics of anaerobic power. Model 1 assumes that the work power is linear with the work rate, while Model 2 assumes a linear relationship between the alactic anaerobic power and the rate of change of the aerobic power. In order to test these models, a cross country skier ran with poles on a treadmill at different exercise intensities. The aerobic power, based on the measured oxygen uptake, was used as input to the models, whereas the simulated blood lactate concentration was compared with experimental results. Thereafter, the metabolic rate from phosphocreatine break down was calculated theoretically. Finally, the models were used to compare phosphocreatine break down during continuous and interval exercises.
Good similarity was found between experimental and simulated blood lactate concentration during steady state exercise intensities. The measured blood lactate concentrations were lower than simulated for intensities above the lactate threshold, but higher than simulated during recovery after high intensity exercise when the simulated lactate concentration was averaged over the whole lactate space. This fit was improved when the simulated lactate concentration was separated into two compartments; muscles + internal organs and blood. Model 2 gave a better behavior of alactic energy than Model 1 when compared against invasive measurements presented in the literature. During continuous exercise, Model 2 showed that the alactic energy storage decreased with time, whereas Model 1 showed a minimum value when steady state aerobic conditions were achieved. During interval exercise the two models showed similar patterns of alactic energy.
The current study provides useful insight on the kinetics of anaerobic power. Overall, our data indicate that blood lactate levels can be accurately modeled during steady state, and suggests a linear relationship between the alactic anaerobic power and the rate of change of the aerobic power.
Theoretical Biology and Medical Modelling 07/2012; 9(1):29. DOI:10.1186/1742-4682-9-29 · 0.95 Impact Factor
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