Respiratory and muscular response to acute non-metabolic fatigue during ramp incremental cycling

Easy Prediction of the Maximal Lactate Steady-State in Young and Older Men and Women

Maximal Lactate steady-state (MLSS) demarcates sustainable from unsustainable exercise and is used for evaluation/monitoring of exercise capacity. Still, its determination is physically challenging and time-consuming. This investigation aimed at validating a simple, submaximal approach based on blood lactate accumulation ([Δlactate]) at the third minute of cycling in a large cohort of men and women of different ages. 68 healthy adults (40♂, 28♀, 43 ± 17 years (range 19-78), VO_2max 45 ± 11 ml^-1·kg^-1·min^-1 (25-68)) performed 3-5 constant power output (PO) trials with a target duration of 30 minutes to determine the PO corresponding to MLSS. During each trial, [Δlactate] was calculated as the difference between the third minute and baseline. A multiple linear regression was computed to estimate MLSS based on [Δlactate], subjects` gender, age and the trial PO. The estimated MLSS was compared to the measured value by paired t-test, correlation, and Bland-Altman analysis. The group mean value of estimated MLSS was 180 ± 51 W, not significantly different from (p = 0.98) and highly correlated with (R² = 0.89) measured MLSS (180 ± 54 watts). The bias between values was 0.17 watts, and imprecision 18.2 watts. This simple, submaximal, time- and cost-efficient test accurately and precisely predicts MLSS across different samples of healthy individuals (adjusted R² = 0.88) and offers a practical and valid alternative to the traditional MLSS determination.

An Intensity-dependent Slow Component of HR Interferes with Accurate Exercise Implementation in Postmenopausal Women

Heart rate (HR) targets are commonly used to administer exercise intensity in sport and clinical practice. However, as exercise protracts, a time-dependent dissociation between HR and metabolism can lead to a misprescription of the intensity ingredient of the exercise dose.

Metabolic instability vs fibre recruitment contribution to the [Formula: see text] slow component in different exercise intensity domains

This study focused on the steady-state phase of exercise to evaluate the relative contribution of metabolic instability (measured with NIRS and haematochemical markers) and muscle activation (measured with EMG) to the oxygen consumption (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{V}O_2}$$\end{document}V˙O2) slow component (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{V}O_2}{_s}{_c}$$\end{document}V˙O2sc) in different intensity domains. We hypothesized that (i) after the transient phase, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{V}O_2}$$\end{document}V˙O2, metabolic instability and muscle activation tend to increase differently over time depending on the relative exercise intensity and (ii) the increase in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{V}O_2}{_s}{_c}$$\end{document}V˙O2sc is explained by a combination of metabolic instability and muscle activation. Eight active men performed a constant work rate trial of 9 min in the moderate, heavy and severe intensity domains. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{V}O_2}$$\end{document}V˙O2, root mean square by EMG (RMS), deoxyhaemoglobin by NIRS ([HHb]) and haematic markers of metabolic stability (i.e. [La⁻], pH, HCO₃⁻) were measured. The physiological responses in different intensity domains were compared by two-way RM-ANOVA. The relationships between the increases of [HHb] and RMS with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{V}O_2}$$\end{document}V˙O2 after the third min were compared by simple and multiple linear regressions. We found domain-dependent dynamics over time of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{V}O_2}$$\end{document}V˙O2, [HHb], RMS and the haematic markers of metabolic instability. After the transient phase, the rises in [HHb] and RMS showed medium–high correlations with the rise in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{V}O_2}$$\end{document}V˙O2 ([HHb] r = 0.68, p < 0.001; RMS r = 0.59, p = 0.002). Moreover, the multiple linear regression showed that both metabolic instability and muscle activation concurred to the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{V}O_2}{_s}{_c}$$\end{document}V˙O2sc (r = 0.75, [HHb] p = 0.005, RMS p = 0.042) with metabolic instability possibly having about threefold the relative weight compared to recruitment. Seventy-five percent of the dynamics of the \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\dot{V}O_2}{_s}{_c}$$\end{document}V˙O2sc was explained by [HHb] and RMS.

Bioenergetics of the VO2 slow component between exercise intensity domains

During heavy and severe constant-load exercise, VO2 displays a slow component (VO2sc) typically interpreted as a loss of efficiency of locomotion. In the ongoing debate on the underpinnings of the VO2sc, recent studies suggested that VO2sc could be attributed to a prolonged shift in energetic sources rather than loss of efficiency. We tested the hypothesis that the total cost of cycling, accounting for aerobic and anaerobic energy sources, is affected by time during metabolic transitions in different intensity domains. Eight active men performed 3 constant load trials of 3, 6, and 9 min in the moderate, heavy, and severe domains (i.e., respectively below, between, and above the two ventilatory thresholds). VO2, VO2 of ventilation and lactate accumulation ([La-]) were quantified to calculate the adjusted oxygen cost of exercise (AdjO2Eq, i.e., measured VO2 - VO2 of ventilation + VO2 equivalent of [La-]) for the 0-3, 3-6, and 6-9 time segments at each intensity, and compared by a two-way RM-ANOVA (time × intensity). After the transient phase, AdjO2Eq was unaffected by time in moderate (ml*3 min-1 at 0-3, 0-6, 0-9 min: 2126 ± 939 < 2687 ± 1036, 2731 ± 1035) and heavy (4278 ± 1074 < 5121 ± 1268, 5225 ± 1123) while a significant effect of time was detected in the severe only (5863 ± 1413 < 7061 ± 1516 < 7372 ± 1443). The emergence of the VO2sc was explained by a prolonged shift between aerobic and anaerobic energy sources in heavy (VO2 - VO2 of ventilation: ml*3 min-1 at 0-3, 0-6, 0-9 min: 3769 ± 1128 < 4938 ± 1256, 5091 ± 1123, [La-]: 452 ± 254 < 128 ± 169, 79 ± 135), while a prolonged metabolic shift and a true loss of efficiency explained the emergence of the VO2sc in severe.

Prolonged static stretching causes acute, nonmetabolic fatigue and impairs exercise tolerance during severe-intensity cycling

We tested the hypothesis that static stretching, an acute, nonmetabolic fatiguing intervention, reduces exercise tolerance by increasing muscle activation and affecting muscle bioenergetics during cycling in the "severe" intensity domain. Ten active men (age, 24 ± 2 years; body mass, 74 ± 11 kg; height, 176 ± 8 cm) participated in identical constant-load cycling tests of equal intensity, of which 2 tests were carried out under control conditions and 2 were done after stretching. This resulted in a 5% reduction of maximal isokinetic sprinting power output. We measured (i) oxygen consumption, (ii) electromyography, (iii) deoxyhemoglobin, (iv) blood lactate concentration; (v) time to exhaustion, and (vi) perception of effort. Finally, oxygen consumption and deoxyhemoglobin kinetics were determined. Force reduction following stretching was accompanied by augmented muscle excitation at a given workload (p = 0.025) and a significant reduction in time to exhaustion (p = 0.002). The time to peak oxygen consumption was reduced by stretching (p = 0.034), suggesting an influence of the increased muscle excitation on the oxygen consumption kinetics. Moreover, stretching was associated with a mismatch between O₂ delivery and utilization during the isokinetic exercise, increased perception of effort, and blood lactate concentration; these observations are all consistent with an increased contribution of the glycolytic energy system to sustain the same absolute intensity. These results suggest a link between exercise intolerance and the decreased ability to produce force. Novelty We provided the first characterization of the effects of prolonged stretching on the metabolic response during severe cycling. Stretching reduced maximal force and augmented muscle activation, which in turn increased the metabolic response to sustain exercise.