Energetics of muscular exercise

Energy cost of running uphill as compared to running on the level with impeding horizontal forces

PURPOSE

We have previously shown that accelerated running on flat terrain is biomechanically equivalent to running uphill at a constant speed. This hypothesis was further investigated comparing the energy cost of running at a constant speed either uphill, or on flat terrain against an equivalent horizontal impeding force, mimicking acceleration.

METHODS

Steady-state O2 consumption and the corresponding energy cost (per unit body mass and distance) were determined on 12 male subjects during treadmill running at speeds between 2.11 and 2.89 m/s: (i) on the level, (ii) uphill at 10 or 20% incline ( I ), or (iii) on the level against a horizontal traction force of 10 or 20% of the subject's body weight ( TF ). This allowed us to estimate the net efficiency ( n e t η ) of running against horizontal or vertical forces, as given by the ratio between the additional mechanical work output under TF , or the corresponding I condition, and the difference between the appropriate energy cost above that for running at constant speed on flat terrain.

RESULTS

The n e t η values when running uphill ( I ) amount to 0.35-0.40, whereas those for running against an equivalent impeding force ( TF ) are about 10% greater (0.45-0.50), a fact that may be due to a greater recovery of elastic energy in the TF as compared to the I condition.

CONCLUSION

Making allowance for these small differences, these data support the view of considering accelerated running on flat terrain biomechanically equivalent to running at a constant speed, up an equivalent slope.

Standing on the Shoulders of Giants: Essential Papers in Sports and Exercise Physiology

PURPOSE

The purpose of this survey was to create a list of essential historical and contemporary readings for undergraduate and graduate students in the field of exercise physiology.

METHODS

Fifty-two exercise physiologists/sport scientists served as referees, and each nominated ∼25 papers for inclusion in the list. In total, 396 papers were nominated by the referees. This list was then sent back to the referees, with the instructions to nominate the "100 essential papers in sports and exercise physiology."

RESULTS

The referees cast 4722 votes. The 100 papers with the highest number of votes received 51% (2406) of the total number of votes. A total of 37 papers in the list of "100 essential papers" were published >50 years ago, and 63 papers were published since 1973.

CONCLUSIONS

This list of essential studies will provide a perspective on contemporary studies, the "giant's shoulders" to enable young scholars to "see further" or to understand where they have "come from." This compilation is also meant to impress on students that, given the (lack of) technology available in the past, some of the early science required enormous intuitive leaps on the part of historical scientists.

The highest work rate associated with a predominantly aerobic contribution coincides with the highest work rate at which VO2max can be attained

PURPOSE

To estimate the highest power output at which predominant energy contribution is derived from the aerobic system (aerobic limit power: ALP) and to compare ALP with the upper boundary of the severe intensity exercise domain.

METHODS

Fifteen male individuals participated in this study. The upper boundary was estimated using i) linear relationship between time to achieve V ˙ O2max and time to task failure (PUPPERBOUND), ii) hyperbolic relationships between time to achieve V ˙ O2max vs. power output, and time to task failure vs. power output (PUPPERBOUND´), and iii) precalculated V ˙ O2max demand (IHIGH). ALP was estimated by aerobic, lactic, and phospholytic energy contributions using V ˙ O2 response, blood [lactate] response, and fast component of recovery V ˙ O2 kinetics, respectively.

RESULTS

ALP was determined as the highest power output providing predominant aerobic contribution; however, anaerobic pathways became the predominant energy source when ALP was exceeded by 5% (ALP + 5%) (from 46 to 52%; p = 0.003; ES:0.69). The V ˙ O2 during exercise at ALP was not statistically different from V ˙ O2max (p > 0.05), but V ˙ O2max could not be attained at ALP + 5% (p < 0.01; ES:0.63). ALP was similar to PUPPERBOUND and PUPPERBOUND´ (383 vs. 379 and 384 W; p > 0.05). There was a close agreement between ALP and PUPPERBOUND (r: 0.99; Bias: - 3 W; SEE: 6 W; TE: 8 W; LoA: - 17 to 10 W) and PUPPERBOUND´ (r: 0.98; Bias: 1 W; SEE: 8 W; TE: 8 W; LoA: - 15 to 17 W). ALP, PUPPERBOUND, and PUPPERBOUND´ were greater than IHIGH (339 ± 53 W; p < 0.001).

CONCLUSION

ALP may provide a new perspective to intensity domain framework.

Energetics of sinusoidal exercise below and across critical power and the effects of fatigue

PURPOSE

Previous studies investigating sinusoidal exercise were not devoted to an analysis of its energetics and of the effects of fatigue. We aimed to determine the contribution of aerobic and anaerobic lactic metabolism to the energy balance and investigate the fatigue effects on the cardiorespiratory and metabolic responses to sinusoidal protocols, across and below critical power (CP).

METHODS

Eight males (26.6 ± 6.2 years; 75.6 ± 8.7 kg; maximum oxygen uptake 52.8 ± 7.9 ml·min-1·kg-1; CP 218 ± 13 W) underwent exhausting sinusoidal cycloergometric exercises, with sinusoid midpoint (MP) at CP (CPex) and 50 W below CP (CP-50ex). Sinusoid amplitude (AMP) and period were 50 W and 4 min, respectively. MP, AMP, and time-delay (tD) between mechanical and metabolic signals of expiratory ventilation (V ˙ E ), oxygen uptake (V ˙ O 2 ), and heart rate ( f H ) were assessed sinusoid-by-sinusoid. Blood lactate ([La-]) and rate of perceived exertion (RPE) were determined at each sinusoid.

RESULTS

V ˙ O 2 AMP was 304 ± 11 and 488 ± 36 ml·min-1 in CPex and CP-50ex, respectively. Asymmetries between rising and declining sinusoid phases occurred in CPex (36.1 ± 7.7 vs. 41.4 ± 9.7 s forV ˙ O 2 tD up and tD down, respectively; P < 0.01), with unchanged tDs.V ˙ O 2 MP and RPE increased progressively during CPex. [La-] increased by 2.1 mM in CPex but remained stable during CP-50ex. Anaerobic contribution was larger in CPex than CP-50ex.

CONCLUSION

The lower aerobic component during CPex than CP-50ex associated with lactate accumulation explained lowerV ˙ O 2 AMP in CPex. The asymmetries in CPex suggest progressive decline of muscle phosphocreatine concentration, leading to fatigue, as witnessed by RPE.

Understanding optimal cadence dynamics: a systematic analysis of the power-velocity relationship in track cyclists with increasing exercise intensity

Background: This study aimed to investigate the changes in force-velocity (F/v) and power-velocity (P/v) relationships with increasing work rate up to maximal oxygen uptake and to assess the resulting alterations in optimal cadence, particularly at characteristic metabolic states. Methods: Fourteen professional track cyclists (9 sprinters, 5 endurance athletes) performed submaximal incremental tests, high-intensity cycling trials, and maximal sprints at varied cadences (60, 90, 120 rpm) on an SRM bicycle ergometer. Linear and non-linear regression analyses were used to assess the relationship between heart rate, oxygen uptake (V.O2), blood lactate concentration and power output at each pedaling rate. Work rates linked to various cardiopulmonary and metabolic states, including lactate threshold (LT1), maximal fat combustion (FATmax), maximal lactate steady-state (MLSS) and maximal oxygen uptake (V.O2max), were determined using cadence-specific inverse functions. These data were used to calculate state-specific force-velocity (F/v) and power-velocity (P/v) profiles, from which state-specific optimal cadences were derived. Additionally, fatigue-free profiles were generated from sprint data to illustrate the entire F/v and P/v continuum. Results: HR, V.O2 demonstrated linear relationships, while BLC exhibited an exponential relationship with work rate, influenced by cadence (p < 0.05, η2 ≥ 0.655). Optimal cadence increased sigmoidally across all parameters, ranging from 66.18 ± 3.00 rpm at LT1, 76.01 ± 3.36 rpm at FATmax, 82.24 ± 2.59 rpm at MLSS, culminating at 84.49 ± 2.66 rpm at V.O2max (p < 0.01, η2 = 0.936). A fatigue-free optimal cadence of 135 ± 11 rpm was identified. Sprinters and endurance athletes showed no differences in optimal cadences, except for the fatigue-free optimum (p < 0.001, d = 2.215). Conclusion: Optimal cadence increases sigmoidally with exercise intensity up to maximal aerobic power, irrespective of the athlete's physical condition or discipline. Threshold-specific changes in optimal cadence suggest a shift in muscle fiber type recruitment toward faster types beyond these thresholds. Moreover, the results indicate the need to integrate movement velocity into Henneman's hierarchical size principle and the critical power curve. Consequently, intensity zones should be presented as a function of movement velocity rather than in absolute terms.

V ˙ Lamax: determining the optimal test duration for maximal lactate formation rate during all-out sprint cycle ergometry

PURPOSE

This study aimed to ascertain the optimal test duration to elicit the highest maximal lactate formation rate ( V ˙ Lamax), whilst exploring the underpinning energetics, and identifying the optimal blood lactate sampling period.

METHODS

Fifteen trained to well-trained males (age 27 ± 6 years; peak power: 1134 ± 174 W) participated in a randomised cross-over design completing three all-out sprint cycling tests of differing test durations (10, 15, and 30 s). Peak and mean power output (W and W.kg-1), oxygen uptake, and blood lactate concentrations were measured. V ˙ Lamax and energetic contributions (phosphagen, glycolytic, and oxidative) were determined using these parameters.

RESULTS

The shortest test duration of 10 s elicited a significantly (p = 0.003; p < 0.001) higher V ˙ Lamax (0.86 ± 0.17 mmol.L-1.s-1; 95% CI 0.802-0.974) compared with both 15 s (0.68 ± 0.18 mmol.L-1.s-1; 95% CI 0.596-0.794) and 30 s (0.45 ± 0.07 mmol.L-1.s-1; 95% CI 0.410-0.487). Differences in V ˙ Lamax were associated with large effect sizes (d = 1.07, d = 3.15). We observed 81% of the PCr and 53% of the glycolytic work completed over the 30 s sprint duration was attained after 10 s. BLamaxpost were achieved at 5 ± 2 min (ttest 10 s), 6 ± 2 min (ttest 15 s), and 7 ± 2 min (ttest 30 s), respectively.

CONCLUSION

Our findings demonstrated a 10 s test duration elicited the highest V ˙ Lamax. Furthermore, the 10 s test duration mitigated the influence of the oxidative metabolism during all-out cycling. The optimal sample time to determine peak blood lactate concentration following 10 s was 5 ± 2 min.

Individualized physiology-based digital twin model for sports performance prediction: a reinterpretation of the Margaria-Morton model

Performance in many racing sports depends on the ability of the athletes to produce and maintain the highest possible work i.e., the highest power for the duration of the race. To model this energy production in an individualized way, an adaptation and a reinterpretation (including a physiological meaning of parameters) of the three-component Margaria-Morton model were performed. The model is applied to the muscles involved in a given task. The introduction of physiological meanings was possible thanks to the measurement of physiological characteristics for a given athlete. A method for creating a digital twin was therefore proposed and applied for national-level cyclists. The twins thus created were validated by comparison with field performance, experimental observations, and literature data. Simulations of record times and 3-minute all-out tests were consistent with experimental data. Considering the literature, the model provided good estimates of the time course of muscle metabolite concentrations (e.g., lactate and phosphocreatine). It also simulated the behavior of oxygen kinetics at exercise onset and during recovery. This methodology has a wide range of applications, including prediction and optimization of the performance of individually modeled athletes.

The mechanisms underpinning the slow component of [Formula: see text] in humans

PURPOSE

When exercising above the lactic threshold (LT), the slow component of oxygen uptake ([Formula: see text]) appears, mainly ascribed to the progressive recruitment of Type II fibers. However, also the progressive decay of the economy of contraction may contribute to it. We investigated oxygen uptake ([Formula: see text]) during isometric contractions clamping torque (T) or muscular activation to quantify the contributions of the two mechanisms.

METHODS

We assessed for 7 min T of the leg extensors, net oxygen uptake ([Formula: see text]) and root mean square (RMS) from vastus lateralis (VL) in 11 volunteers (21 ± 2 yy; 1.73 ± 0.11 m; 67 ± 14 kg) during cyclic isometric contractions (contraction/relaxation 5 s/5 s): (i) at 65% of maximal voluntary contraction (MVC) (FB-Torque) and; (ii) keeping the level of RMS equal to that at 65% of MVC (FB-EMG).

RESULTS

[Formula: see text] after the third minute in FB-Torque increased with time ([Formula: see text] = 94 × t + 564; R2 = 0.99; P = 0.001), but not during FB-EMG. [Formula: see text]/T increased only during FB-Torque ([Formula: see text]/T = 1.10 × t + 0.57; R2 = 0.99; P = 0.001). RMS was larger in FB-Torque than in FB-EMG and significantly increased in the first three minutes of exercise to stabilize till the end of the trial, indicating that the pool of recruited MUs remained constant despite [Formula: see text].

CONCLUSION

The analysis of the RMS, [Formula: see text] and T during FB-Torque suggests that the intrinsic mechanism attributable to the decay of contraction efficiency was responsible for an increase of [Formula: see text] equal to 18% of the total [Formula: see text].

A century of exercise physiology: concepts that ignited the study of human thermoregulation. Part 3: Heat and cold tolerance during exercise

In this third installment of our four-part historical series, we evaluate contributions that shaped our understanding of heat and cold stress during occupational and athletic pursuits. Our first topic concerns how we tolerate, and sometimes fail to tolerate, exercise-heat stress. By 1900, physical activity with clothing- and climate-induced evaporative impediments led to an extraordinarily high incidence of heat stroke within the military. Fortunately, deep-body temperatures > 40 °C were not always fatal. Thirty years later, water immersion and patient treatments mimicking sweat evaporation were found to be effective, with the adage of cool first, transport later being adopted. We gradually acquired an understanding of thermoeffector function during heat storage, and learned about challenges to other regulatory mechanisms. In our second topic, we explore cold tolerance and intolerance. By the 1930s, hypothermia was known to reduce cutaneous circulation, particularly at the extremities, conserving body heat. Cold-induced vasodilatation hindered heat conservation, but it was protective. Increased metabolic heat production followed, driven by shivering and non-shivering thermogenesis, even during exercise and work. Physical endurance and shivering could both be compromised by hypoglycaemia. Later, treatments for hypothermia and cold injuries were refined, and the thermal after-drop was explained. In our final topic, we critique the numerous indices developed in attempts to numerically rate hot and cold stresses. The criteria for an effective thermal stress index were established by the 1930s. However, few indices satisfied those requirements, either then or now, and the surviving indices, including the unvalidated Wet-Bulb Globe-Thermometer index, do not fully predict thermal strain.

A century of exercise physiology: concepts that ignited the study of human thermoregulation. Part 2: physiological measurements

In this, the second of four historical reviews on human thermoregulation during exercise, we examine the research techniques developed by our forebears. We emphasise calorimetry and thermometry, and measurements of vasomotor and sudomotor function. Since its first human use (1899), direct calorimetry has provided the foundation for modern respirometric methods for quantifying metabolic rate, and remains the most precise index of whole-body heat exchange and storage. Its alternative, biophysical modelling, relies upon many, often dubious assumptions. Thermometry, used for >300 y to assess deep-body temperatures, provides only an instantaneous snapshot of the thermal status of tissues in contact with any thermometer. Seemingly unbeknownst to some, thermal time delays at some surrogate sites preclude valid measurements during non-steady state conditions. To assess cutaneous blood flow, immersion plethysmography was introduced (1875), followed by strain-gauge plethysmography (1949) and then laser-Doppler velocimetry (1964). Those techniques allow only local flow measurements, which may not reflect whole-body blood flows. Sudomotor function has been estimated from body-mass losses since the 1600s, but using mass losses to assess evaporation rates requires precise measures of non-evaporated sweat, which are rarely obtained. Hygrometric methods provide data for local sweat rates, but not local evaporation rates, and most local sweat rates cannot be extrapolated to reflect whole-body sweating. The objective of these methodological overviews and critiques is to provide a deeper understanding of how modern measurement techniques were developed, their underlying assumptions, and the strengths and weaknesses of the measurements used for humans exercising and working in thermally challenging conditions.

Development and validation of dynamic bioenergetic model for intermittent ergometer cycling

PURPOSE

The aim of this study was to develop and validate a bioenergetic model describing the dynamic behavior of the alactic, lactic, and aerobic metabolic energy supply systems as well as different sources of the total metabolic energy demand.

METHODS

The bioenergetic supply model consisted of terms for the alactic, lactic, and aerobic system metabolic rates while the demand model consisted of terms for the corresponding metabolic rates of principal cycling work, pulmonary ventilation, and accumulated metabolites. The bioenergetic model was formulated as a system of differential equations and model parameters were estimated by a non-linear grey-box approach, utilizing power output and aerobic metabolic rate (MRae) data from fourteen cyclists performing an experimental trial (P2) on a cycle ergometer. Validity was assessed by comparing model simulation and measurements on a similar follow-up experimental trial (P3).

RESULTS

The root mean square error between modelled and measured MRae was 61.9 ± 7.9 W and 79.2 ± 30.5 W for P2 and P3, respectively. The corresponding mean absolute percentage error was 8.6 ± 1.5% and 10.6 ± 3.3% for P2 and P3, respectively.

CONCLUSION

The validation of the model showed excellent overall agreement between measured and modeled MRae during intermittent cycling by well-trained male cyclist. However, the standard deviation was 38.5% of the average root mean square error for P3, indicating not as good reliability.

A century of exercise physiology: concepts that ignited the study of human thermoregulation. Part 1: Foundational principles and theories of regulation

This contribution is the first of a four-part, historical series encompassing foundational principles, mechanistic hypotheses and supported facts concerning human thermoregulation during athletic and occupational pursuits, as understood 100 years ago and now. Herein, the emphasis is upon the physical and physiological principles underlying thermoregulation, the goal of which is thermal homeostasis (homeothermy). As one of many homeostatic processes affected by exercise, thermoregulation shares, and competes for, physiological resources. The impact of that sharing is revealed through the physiological measurements that we take (Part 2), in the physiological responses to the thermal stresses to which we are exposed (Part 3) and in the adaptations that increase our tolerance to those stresses (Part 4). Exercising muscles impose our most-powerful heat stress, and the physiological avenues for redistributing heat, and for balancing heat exchange with the environment, must adhere to the laws of physics. The first principles of internal and external heat exchange were established before 1900, yet their full significance is not always recognised. Those physiological processes are governed by a thermoregulatory centre, which employs feedback and feedforward control, and which functions as far more than a thermostat with a set-point, as once was thought. The hypothalamus, today established firmly as the neural seat of thermoregulation, does not regulate deep-body temperature alone, but an integrated temperature to which thermoreceptors from all over the body contribute, including the skin and probably the muscles. No work factor needs to be invoked to explain how body temperature is stabilised during exercise.

Energy cost differences between marathon runners and soccer players: Constant versus shuttle running

Purpose: In the last decades, the energy cost assessment provided new insight on shuttle or constant running as training modalities. No study, though, quantified the benefit of constant/shuttle running in soccer-players and runners. Therefore, the aim of this study was to clarify if marathon runners and soccer players present specific energy cost values related to their training experience performing constant and shuttle running. Methods: To this aim, eight runners (age 34 ± 7.30y; training experience 5.70 ± 0.84y) and eight soccer-players (age 18.38 ± 0.52y; training experience 5.75 ± 1.84y) were assessed randomly for 6' on shuttle-running or constant-running with 3 days of recovery in-between. For each condition, the blood lactate (BL) and the energy cost of constant (C_r) and shuttle running (C_Sh) was determined. To assess differences for metabolic demand in terms of C_r, C_Sh and BL over the two running conditions on the two groups a MANOVA was used. Results: V·O_2max were 67.9 ± 4.5 and 56.8 ± 4.3 ml·min^-1 kg^-1 (p = 0.0002) for marathon runners and soccer players, respectively. On constant running, the runners had a lower C_r compared to soccer players (3.86 ± 0.16 J kg^-1m^-1 vs. 4.19 ± 0.26 J kg^-1 m^-1; F = 9.759, respectively; p = 0.007). On shuttle running, runners had a higher C_Sh compared to soccer players (8.66 ± 0.60 J kg^-1 m^-1 vs. 7.86 ± 0.51 J kg^-1 m^-1; F = 8.282, respectively; with p = 0.012). BL on constant running was lower in runners compared to soccer players (1.06 ± 0.07 mmol L^-1 vs. 1.56 ± 0.42 mmol L^-1, respectively; with p = 0.005). Conversely, BL on shuttle running was higher in runners compared to soccer players 7.99 ± 1.49 mmol L^-1 vs. 6.04 ± 1.69 mmol L^-1, respectively; with p = 0.028). Conclusion: The energy cost optimization on constant or shuttle running is strictly related to the sport practiced.

Coupling of [Formula: see text] and [Formula: see text] kinetics: insights from multiple exercise transitions below the estimated lactate threshold

During a step-change in exercise power output (PO), ventilation ([Formula: see text]) increases with a similar time course to the rate of carbon dioxide delivery to the lungs ([Formula: see text]). To test the strength of this coupling, we compared [Formula: see text] and [Formula: see text] kinetics from ten independent exercise transitions performed within the moderate-intensity domain. Thirteen males completed 3-5 repetitions of ∆40 W step transitions initiated from 20, 40, 60, 80, 100, and 120 W on a cycle ergometer. Preceding the ∆40 W step transitions from 60, 80, 100, and 120 W was a 6 min bout of 20 W cycling from which the transitions of variable ∆PO were examined. Gas exchange ([Formula: see text] and oxygen uptake, [Formula: see text]) and [Formula: see text] were measured by mass spectrometry and volume turbine. The kinetics of the responses were characterized by the time constant (τ) and amplitude (Δ[Formula: see text]/Δ[Formula: see text]). Overall, [Formula: see text] kinetics were consistently slower than [Formula: see text] kinetics (by ~ 45%) and τ[Formula: see text] rose progressively with increasing baseline PO and with heightened ∆PO from a common baseline. Compared to τ[Formula: see text], τ[Formula: see text] was on average slightly greater (by ~ 4 s). Repeated-measures analysis of variance revealed that there was no interaction between τ[Formula: see text] and τ[Formula: see text] in either the variable baseline (p = 0.49) and constant baseline (p = 0.56) conditions indicating that each changed in unison. Additionally, for Δ[Formula: see text]/Δ[Formula: see text], there was no effect of either variable baseline PO (p = 0.05) or increasing ΔPO (p = 0.16). These data provide further evidence that, within the moderate-intensity domain, both the temporal- and amplitude-based characteristics of V̇_E kinetics are inextricably linked to those of [Formula: see text].

A Novel Approach to Determining the Alactic Time Span in Connection with Assessment of the Maximal Rate of Lactate Accumulation in Elite Track Cyclists

PURPOSE

Following short-term all-out exercise, the maximal rate of glycolysis is frequently assessed on the basis of the maximal rate of lactate accumulation in the blood. Since the end of the interval without significant accumulation (talac) is 1 of 2 denominators in the calculation employed, accurate determination of this parameter is crucial. Although the very existence and definition of talac, as well as the validity of its determination as time-to-peak power (tPpeak), remain controversial, this parameter plays a key role in anaerobic diagnostics. Here, we describe a novel approach to determination of talac and compare it to the current standard.

METHODS

Twelve elite track cyclists performed 3 maximal sprints (3, 8, and 12 s) and a high-rate, low-resistance pedaling test on an ergometer with monitoring of crank force and pedaling rate. Before and after each sprint, capillary blood samples were taken for determination of lactate accumulation. Fatigue-free force-velocity and power-velocity profiles were generated. talac was determined as tPpeak and as the time point of the first systematic deviation from the force-velocity profile (tFf).

RESULTS

Accumulation of lactate after the 3-second sprint was significant (0.58 [0.19] mmol L-1; P < .001, d = 1.982). tFf was <3 seconds and tPpeak was ≥3 seconds during all sprints (P < .001, d = - 2.111). Peak power output was lower than maximal power output (P < .001, d = -0.937). Blood lactate accumulation increased linearly with increasing duration of exercise (R2 ≥ .99) and intercepted the x-axis at ∼tFf.

CONCLUSION

Definition of talac as tPpeak can lead to incorrect conclusions. We propose determination of talac based on tFf, the end of the fatigue-free state that may reflect the beginning of blood lactate accumulation.

Amateur Female Athletes Perform the Running Split of a Triathlon Race at Higher Relative Intensity than the Male Athletes: A Cross-Sectional Study

Maximal oxygen uptake (V˙O2max), ventilatory threshold (VT) and respiratory compensation point (RCP) can be used to monitor the training intensity and the race strategy, and the elucidation of the specificities existing between the sexes can be interesting for coaches and athletes. The aim of the study was to compare ventilatory threshold (VT), respiratory compensation point (RCP), and the percentage of the maximal aerobic speed (MAS) that can be maintained in a triathlon race between sexes. Forty-one triathletes (22 men and 19 women), 42.1 ± 8.4 (26 to 60) years old, that raced the same Olympic triathlon underwent a cardiorespiratory maximal treadmill test to assess their VT, RPC, and MAS, and race speed. The maximal oxygen uptake (V˙O2max) (54.0 ± 5.1 vs. 49.8 ± 7.7 mL/kg/min, p < 0.001) and MAS (17 ± 2 vs. 15 ± 2 km/h, p = 0.001) were significantly higher in male than in female athletes. Conversely, there were no sex differences according to the percentage of V˙O2max reached at VT (74.4 ± 4.9 vs. 76.1 ± 5.4%, p = 0.298) and RCP (89.9 ± 3.6 vs. 90.6 ± 4.0%, p = 0.560). The mean speed during the race did not differ between sexes (12.1 ± 1.7 km/h and 11.7 ± 1.8 km/h, p = 0.506, respectively). Finally, men performed the running split at a lower percentage of speed at RCP than women (84.0 ± 8.7 vs. 91.2 ± 7.0%, respectively, p = 0.005). Therefore, male and female athletes accomplished the running split in an Olympic triathlon distance at distinct relative intensities, as female athletes run at a higher RCP percentage.

A Novel Approach to the Determination of Time- and Fatigue-Dependent Efficiency during Maximal Cycling Sprints

BACKGROUND

During maximal cycling sprints, efficiency (η) is determined by the fiber composition of the muscles activated and cadence-dependent power output. To date, due to methodological limitations, it has only been possible to calculate gross efficiency (i.e., the ratio of total mechanical to total metabolic work) in vivo without assessing the impact of cadence and changes during exercise. Eliminating the impact of cadence provides optimal efficiency (ηopt), which can be modeled as a function of time. Here, we explain this concept, demonstrate its calculation, and compare the values obtained to actual data. Furthermore, we hypothesize that the time course of maximal power output (Pmax) reflects time-dependent changes in ηopt.

METHODS

Twelve elite track cyclists performed four maximal sprints (3, 8, 12, 60 s) and a maximal-pedaling test on a cycle ergometer. Crank force and cadence were monitored continuously to determine fatigue-free force-velocity profiles (F/v) and fatigue-induced changes in Pmax. Respiratory gases were measured during and for 30 min post-exercise. Prior to and following each sprint, lactate in capillary blood was determined to calculate net blood lactate accumulation (ΔBLC). Lactic and alactic energy production were estimated from ΔBLC and the fast component of excess post-exercise oxygen consumption. Aerobic energy production was determined from oxygen uptake during exercise. Metabolic power (MP) was derived from total metabolic energy (WTOT). ηopt was calculated as Pmax divided by MP. Temporal changes in Pmax, WTOT, and ηopt were analyzed by non-linear regression.

RESULTS

All models showed excellent quality (R2 > 0.982) and allowed accurate recalculation of time-specific power output and gross efficiency (R2 > 0.986). The time-constant for Pmax(t) (τP) was closely correlated with that of ηopt (τη; r = 0.998, p < 0.001). Estimating efficiency using τP for τη led to a 0.88 ± 0.35% error.

CONCLUSIONS

Although efficiency depends on pedal force and cadence, the latter influence can be eliminated by ηopt(t) using a mono-exponential equation whose time constant can be estimated from Pmax(t).

Effect of recovery time on [Formula: see text]-ON kinetics in humans at the onset of moderate-intensity cycling exercise

PURPOSE

τ of the primary phase of [Formula: see text] kinetics during square-wave, moderate-intensity exercise mirrors that of PCr splitting (τPCr). Pre-exercise [PCr] and the absolute variations of PCr (∆[PCr]) occurring during transient have been suggested to control τPCr and, in turn, to modulate [Formula: see text] kinetics. In addition, [Formula: see text] kinetics may be slower when exercise initiates from a raised metabolic level, i.e., from a less-favorable energetic state. We verified the hypothesis that: (i) pre-exercise [PCr], (ii) pre-exercise metabolic rate, or (iii) ∆[PCr] may affect the kinetics of muscular oxidative metabolism and, therefore, τ.

METHODS

To this aim, seven active males (23.0 yy ± 2.3; 1.76 m ± 0.06, [Formula: see text]: 3.32 L min^-1 ± 0.67) performed three repetitions of series consisting of six 6-min step exercise transitions of identical workload interspersed with different times of recovery: 30, 60, 90, 120, 300 s.

RESULTS

Mono-exponential fitting was applied to breath-by-breath [Formula: see text], so that τ was determined. τ decays as a first-order exponential function of the time of recovery (τ = 109.5 × e^(-t/14.0) + 18.9 r² = 0.32) and linearly decreased as a function of the estimated pre-exercise [PCr] (τ = - 1.07 [PCr] + 44.9, r² = 0.513, P < 0.01); it was unaffected by the estimated ∆[PCr].

CONCLUSIONS

Our results in vivo do not confirm the positive linear relationship between τ and pre-exercise [PCr] and ∆[PCr]. Instead, [Formula: see text] kinetics seems to be influenced by the pre-exercise metabolic rate and the altered intramuscular energetic state.

Energetics of Floor Gymnastics: Aerobic and Anaerobic Share in Male and Female Sub-elite Gymnasts

Background

Artistic gymnastics is a popular Olympic discipline where female athletes compete in four and male athletes in six events with floor exercise having the longest competition duration in Women’s and Men’s artistic gymnastics (WAG, MAG). To date no valid information on the energetics of floor gymnastics is available although this may be important for specific conditioning programming. This study evaluated the metabolic profile of a simulated floor competition in sub-elite gymnasts.

Methods

17 (9 male, 8 female) sub-elite gymnasts aged 22.5 ± 2.6y took part in a floor-training-competition where oxygen uptake was measured during and until 15 min post-exercise. Additionally, resting and peak blood lactate concentration after exercise were obtained. The PCr-LA-O2 method was used to calculate the metabolic energy and the relative aerobic (WAER), anaerobic alactic (WPCr) and anaerobic lactic (WBLC) energy contribution. Further, the athletes completed a 30 s Bosco-jumping test, a countermovement jump and a drop jump.

Results

The competition scores were 9.2 (CI:8.9–9.3) in WAG and 10.6 (CI:10.4–10.9) in MAG. The metabolic profile of the floor routine was mainly aerobic (58.9%, CI: 56.0–61.8%) followed by the anaerobic alactic (24.2%, CI: 21.3–27.1%) and anaerobic lactic shares (16.9%, CI:14.9–18.8%). While sex had a significant (p = .010, d = 1.207) large effect on energy contribution, this was not the case for competition duration (p = .728, d = 0.061). Relative energy contribution of WAG and MAG differed in WAER (64.0 ± 4.7% vs. 54.4 ± 6.8%, p = .004, d = 1.739) but not in WPCr (21.3 ± 6.1% vs. 26.7 ± 8.0%, p = .144, d = 0.801) and WBLC (14.7 ± 5.4% vs. 18.9 ± 4.2%, p = .085, d = 0.954). Further no correlation between any energy share and performance was found but between WPCr and training experience (r = .680, p = .044) and WBLC and competition level (r = .668, p = .049).

Conclusion

The results show a predominant aerobic energy contribution and a considerable anaerobic contribution with no significant difference between anaerobic shares. Consequently, gymnastic specific aerobic training should not be neglected, while a different aerobic share in WAG and MAG strengthens sex-specific conditioning. All in all, the specific metabolic share must secure adequate energy provision, while relative proportions of the two anaerobic pathways seem to depend on training and competition history.

Reliability of the 3-Component Model of Aerobic, Anaerobic Lactic, and Anaerobic Alactic Energy Distribution (PCr-LA-O2) for Energetic Profiling of Continuous and Intermittent Exercise

Purpose: To assess the test–retest reliability of the continuous (PCr-LA-O2) and intermittent (PCr-LA-O2int) version of the 3-component model of energy distribution in an applied setting. Methods: Sixteen male handball players (age 23 [3] y, height 185 [7] cm, weight 85 [14] kg) completed the 30–15 Intermittent Fitness Test (30–15IFT) twice. Performance was assessed by peak speed (speed of the last successfully completed stage of the 30–15IFT [VIFT], in kilometers per hour) and time to exhaustion (in seconds). Oxygen uptake (in milliliters per kilogram per minute) and blood lactate concentrations (in millimoles per liter) were obtained before, during, and until 15 minutes after exercise. Total metabolic energy (in joules per kilogram), total metabolic power (in watts per kilogram), and energy shares (in joules per kilogram and percentage) of the aerobic (energy contribution of the aerobic system [WAERint]), anaerobic lactic, and anaerobic alactic (anaerobic alactic energy [WPCrint]) systems were calculated using both model versions, respectively. Results: Test–retest reliability was very good for VIFT (limits of agreement [LoA]: −1.13 to 0.63 km·h−1, coefficient of variation [CV%] 1.68), time to exhaustion (LoA: −101 to 38 s, CV% 2.92), peak oxygen uptake (LoA: −2.68 to 4.04 mL·min−1·kg−1, CV% 1.48), and peak heart rate (−6.9 to 7.7 beats·min−1, CV% 1.1), but moderate for change in blood lactate concentration (LoA: −3.84 to 4.07 mmol·L−1, CV% 11.43). Reliability of the modeled total energy and its fractions were high for total metabolic energy (LoA: −1489 to 1177 J·kg−1, CV% 2.88), total metabolic power (LoA: −2.0 to 1.9 W·kg−1, CV% 3.58), contribution of aerobic (LoA: −1673 to 1283 J·kg−1, CV% 3.62), WAERint (LoA: −1760 to 2160 J·kg−1, CV% 6.04), and moderate for anaerobic alactic (LoA: −368 to 439 J·kg−1, CV% 14.85), WPCrint (LoA: −1707 to 988 J·kg−1, CV% 9.98), and energy share of anaerobic lactic concentration (LoA: −229 to 235 J·kg−1, CV% 11.43). Conclusion: Considering the inherent fluctuations of the underlying energetics, the reliabilities of both versions of the 3-component model of energy distribution are acceptable for applied settings.

Putting perception into action with inverse optimal control for continuous psychophysics

Psychophysical methods are a cornerstone of psychology, cognitive science, and neuroscience where they have been used to quantify behavior and its neural correlates for a vast range of mental phenomena. Their power derives from the combination of controlled experiments and rigorous analysis through signal detection theory. Unfortunately, they require many tedious trials and preferably highly trained participants. A recently developed approach, continuous psychophysics, promises to transform the field by abandoning the rigid trial structure involving binary responses and replacing it with continuous behavioral adjustments to dynamic stimuli. However, what has precluded wide adoption of this approach is that current analysis methods do not account for the additional variability introduced by the motor component of the task and therefore recover perceptual thresholds that are larger compared to equivalent traditional psychophysical experiments. Here, we introduce a computational analysis framework for continuous psychophysics based on Bayesian inverse optimal control. We show via simulations and previously published data that this not only recovers the perceptual thresholds but additionally estimates subjects' action variability, internal behavioral costs, and subjective beliefs about the experimental stimulus dynamics. Taken together, we provide further evidence for the importance of including acting uncertainties, subjective beliefs, and, crucially, the intrinsic costs of behavior, even in experiments seemingly only investigating perception.

What is the physiological impact of reducing the 2,000 m Olympic distance in rowing to 1,500 m and 1,000 m for French young competitive rowers? Insights from the energy system contribution

French rowing federation reduced the competition distance to 1,500 and 1,000 m in rowers under 16- (U16) and 14-year-old (U14) respectively, to prepare them progressively to the Olympic 2,000 m distance in under 18-year-old (U18). This study aimed to check the hypothesis that relative aerobic (%EAe) and anaerobic (%EAn) energy contributions would be comparable between the competition distances since the more oxidative profile of younger age categories could offset the greater anaerobic contribution induced by shorter rowing races. Thirty-one 12- to 17-year-old competitive rowers performed a race of 2,000, 1,500, or 1,000 m on a rowing ergometer according to their age category. %EAe and %EAn were estimated from oxygen consumption, changes in blood lactate concentration and their energy equivalents. %EAe was lower in U16 than U18 (84.7 vs. 87.0%, p < 0.01), and in U14 than U16 (80.6 vs. 84.7%, p < 0.001). %EAn was higher in U16 than U18 (15.3 vs. 13.0%, p < 0.01), and in U14 than U16 (19.4 vs. 15.3%, p < 0.01). The results did not confirm our initial hypothesis since %EAe and %EAn were significantly different between the race distances, and thus age categories. However, %EAn in U18, U16 and U14 were found to be in the range of values previously found in adult rowers over the 2,000 m Olympic distance (12-30%). Therefore, on a practical level, the strategy implemented by the French rowing federation to reduce the competition distance in the younger age categories could be relevant to progressively prepare them to the physiological requirements encountered over the Olympic distance.

A century of exercise physiology: key concepts on coupling respiratory oxygen flow to muscle energy demand during exercise

After a short historical account, and a discussion of Hill and Meyerhof's theory of the energetics of muscular exercise, we analyse steady-state rest and exercise as the condition wherein coupling of respiration to metabolism is most perfect. The quantitative relationships show that the homeostatic equilibrium, centred around arterial pH of 7.4 and arterial carbon dioxide partial pressure of 40 mmHg, is attained when the ratio of alveolar ventilation to carbon dioxide flow ([Formula: see text]) is - 21.6. Several combinations, exploited during exercise, of pertinent respiratory variables are compatible with this equilibrium, allowing adjustment of oxygen flow to oxygen demand without its alteration. During exercise transients, the balance is broken, but the coupling of respiration to metabolism is preserved when, as during moderate exercise, the respiratory system responds faster than the metabolic pathways. At higher exercise intensities, early blood lactate accumulation suggests that the coupling of respiration to metabolism is transiently broken, to be re-established when, at steady state, blood lactate stabilizes at higher levels than resting. In the severe exercise domain, coupling cannot be re-established, so that anaerobic lactic metabolism also contributes to sustain energy demand, lactate concentration goes up and arterial pH falls continuously. The [Formula: see text] decreases below - 21.6, because of ensuing hyperventilation, while lactate keeps being accumulated, so that exercise is rapidly interrupted. The most extreme rupture of the homeostatic equilibrium occurs during breath-holding, because oxygen flow from ambient air to mitochondria is interrupted. No coupling at all is possible between respiration and metabolism in this case.

Can We Quantify the Benefits of "Super Spikes" in Track Running?

The recent and rapid developments in track spike innovation have been followed by a wave of record-breaking times and top performances. This has led many to question what role “super spikes” play in improving running performance. To date, the specific contributions of new innovations in footwear, including lightweight, resilient, and compliant midsole foam, altered geometry, and increased longitudinal bending stiffness, to track running performance are unknown. Based on current literature, we speculate about what advantages these features provide. Importantly, the effects of super spikes will vary based on several factors including the event (e.g., 100 m vs. 10,000 m) and the characteristics of the athlete wearing them. Further confounding our understanding of super spikes is the difficulty of testing them. Unlike marathon shoes, testing track spikes comes with a unique challenge of quantifying the metabolic energy demands of middle-distance running events, which are partly anaerobic. Quantifying the exact benefits from super spikes is difficult and we may need to rely on comparison of track performances pre- and post- the introduction of super spikes.

Impact of DanceSport on General Fitness from the Perspective of Chinese Athletes

Energy metabolism and motion are the essence of dance. Scientific training of athletes involves theoretical guidance in terms of fitness, talent-based selection, and high-performance practice. However, limited research work is carried out on the physiological strain of DanceSport competitions. Therefore, proper channel needs to be established for aerobic-based exercise on participant's performance and general fitness. Competition simulation is used to collect personal data from real-time experimentations. Database gathers athlete information based on age, gender, and performance. Furthermore, results are obtained from experiment, record, and simulation in comparison to evaluate athlete performance. Main purpose of this article is to discover the characteristics of DanceSport from the perspectives of energetics in 32 domestic elite. Finally, World DanceSport Federation Judging System 2.1 "WFJS2.1" strategy is utilized for international game challenges.

Over 55 years of critical power: Fact or artifact?

This report aims to generate an evidence-based debate of the Critical Power (CP), or its analogous Critical Speed (CS), concept. Race times of top Spanish runners were utilized to calculate CS based on three (1500-m to 5000-m; CS_1.5-5km ) and four (1500-m to 10000-m; CS_1.5-10km ) distance performances. Male running world records from 1000 to 5000-m (CS_1-5km ), 1000 to 10,000-m (CS_1-10km ), 1000-m to half marathon (CS_{1km-half marathon} ), and 1000-m to marathon (CS_1km-marathon ) distance races were also utilized for CS calculations. CS_1.5-5km (19.62 km h^-1 ) and CS_1.5-10km (18.68 km h^-1 ) were different (p < 0.01), but both approached the average race speed of the longest distance chosen in the model, and were remarkably homogeneous among subjects (97% ±1% and 98% ±1%, respectively). Similar results were obtained using the world records. CS values progressively declined, until reaching a CS_1km-marathon value of 20.77 km h^-1 (10% lower than CS_1-5km ). Each CS value approached the average speed of the longest distance chosen in the model (96.4%-99.8%). A power function better fitted the speed-time relationship compared with the standardized hyperbolic function. However, the horizontal asymptote of a power function is zero. This better approaches the classical definition of CP: the power output that can be maintained almost indefinitely without exhaustion. Beyond any sophisticated mathematical calculation, CS corresponds to 95%-99% of the average speed of the longest distance chosen as an exercise trial. CP could be considered a mathematical artifact rather than an important endurance performance marker. In such a case, the consideration of CP as a physiological "gold-standard" should be reevaluated.

Vagal blockade suppresses the phase I heart rate response but not the phase I cardiac output response at exercise onset in humans

Purpose

We tested the vagal withdrawal concept for heart rate (HR) and cardiac output (CO) kinetics upon moderate exercise onset, by analysing the effects of vagal blockade on cardiovascular kinetics in humans. We hypothesized that, under atropine, the φ₁ amplitude (A₁) for HR would reduce to nil, whereas the A₁ for CO would still be positive, due to the sudden increase in stroke volume (SV) at exercise onset.

Methods

On nine young non-smoking men, during 0–80 W exercise transients of 5-min duration on the cycle ergometer, preceded by 5-min rest, we continuously recorded HR, CO, SV and oxygen uptake (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \dot{V} $$\end{document}V˙O₂) upright and supine, in control condition and after full vagal blockade with atropine. Kinetics were analysed with the double exponential model, wherein we computed the amplitudes (A) and time constants (τ) of phase 1 (φ₁) and phase 2 (φ₂).

Results

In atropine versus control, A₁ for HR was strongly reduced and fell to 0 bpm in seven out of nine subjects for HR was practically suppressed by atropine in them. The A₁ for CO was lower in atropine, but not reduced to nil. Thus, SV only determined A₁ for CO in atropine. A₂ did not differ between control and atropine. No effect on τ₁ and τ₂ was found. These patterns were independent of posture.

Conclusion

The results are fully compatible with the tested hypothesis. They provide the first direct demonstration that vagal blockade, while suppressing HR φ₁, did not affect φ₁ of CO.

Level, Uphill, and Downhill Running Economy Values Are Correlated Except on Steep Slopes

The aim of this study was first to determine if level, uphill, and downhill energy cost of running (ECR) values were correlated at different slopes and for different running speeds, and second, to determine the influence of lower limb strength on ECR. Twenty-nine healthy subjects completed a randomized series of 4-min running bouts on an instrumented treadmill to determine their cardiorespiratory and mechanical (i.e., ground reaction forces) responses at different constant speeds (8, 10, 12, and 14 km·h⁻¹) and different slopes (−20, −10, −5, 0, +5, +10, +15, and +20%). The subjects also performed a knee extensor (KE) strength assessment. Oxygen and energy costs of running values were correlated between all slopes by pooling all running speeds (all r² ≥ 0.27; p ≤ 0.021), except between the steepest uphill vs. level and the steepest downhill slope (i.e., +20% vs. 0% and −20% slopes; both p ≥ 0.214). When pooled across all running speeds, the ECR was inversely correlated with KE isometric maximal torque for the level and downhill running conditions (all r² ≥ 0.24; p ≤ 0.049) except for the steepest downhill slope (−20%), but not for any uphill slopes. The optimal downhill grade (i.e., lowest oxygen cost) varied between running speeds and ranged from −14% and −20% (all p < 0.001). The present results suggest that compared to level and shallow slopes, on steep slopes ~±20%, running energetics are determined by different factors (i.e., reduced bouncing mechanism, greater muscle strength for negative slopes, and cardiopulmonary fitness for positive slopes). On shallow negative slopes and during level running, ECR is related to KE strength.

Comparison of Energy Contributions and Workloads in Male and Female Badminton Players During Games Versus Repetitive Practices

Purpose

The aim of this study was to compare the energy contributions and workloads in men and women during badminton matches versus frequently used multi-ball smash practices.

Methods

Fourteen badminton players performed one badminton singles game and one session of smashing practice on separate days. The energy contributions were examined in terms of each individual’s three energy systems and substrate oxidation, while workloads included heart rate (HR), Player Load (PL), accelerations, decelerations, changes of direction, and jumps.

Results

(1) During games, male players exhibited higher adenosine triphosphate–phosphocreatine system contribution (E_PCr, kJ) (p = 0.008) and average rate of carbohydrate oxidation (R_CHO, g/min) (p = 0.044) than female players, while female players showed greater absolute PL (p = 0.029) and more accelerations (p = 0.005) than male players. Furthermore, players who lost performed higher relative PL (p = 0.017) than those who won. (2) Higher energy system contributions, including E_PCr (kJ) (p = 0.028), E_HLa (kJ) (p = 0.024), E_Aer (kJ) (p = 0.012), E_Tot (kJ) (p = 0.007), and R_CHO (g/min) (p = 0.0002), were seen in male players during repetitive spike practices. Male players also made greater number of jumps (p = 0.0002). (3) Players exhibited higher aerobic energy contribution (p < 0.001), mean HR (p = 0.002), and HRmax (p = 0.029) during games, while exhibiting greater anaerobic energy contribution (p < 0.001) and relative PL (p = 0.001) during repetitive practices.

Conclusion

The similarities between male and female badminton players in proportional use of the three energy systems during games and repetitive spike training indicate similar relative energy demands for both genders. However, considering the need for higher aerobic capacity in competition, it might be advisable to design appropriate work:rest ratios for repetitive practices in daily training.

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.

The Validity of an Updated Metabolic Power Algorithm Based upon di Prampero's Theoretical Model in Elite Soccer Players

The aim of this study was to update the metabolic power (MP) algorithm (PV˙O2, W·kg⁻¹) related to the kinematics data (P_GPS, W·kg⁻¹) in a soccer-specific performance model. For this aim, seventeen professional (Serie A) male soccer players (V˙O2max 55.7 ± 3.4 mL·min⁻¹·kg⁻¹) performed a 6 min run at 10.29 km·h⁻¹ to determine linear-running energy cost (C_r). On a separate day, thirteen also performed an 8 min soccer-specific intermittent exercise protocol. For both procedures, a portable Cosmed K4b² gas-analyzer and GPS (10 Hz) was used to assess the energy cost above resting (C). From this aim, the MP was estimated through a newly derived C equation (P_GPSn) and compared with both the commonly used (P_GPSo) equation and direct measurement (PV˙O2). Both P_GPSn and P_GPSo correlated with PV˙O2 (r = 0.66, p < 0.05). Estimates of fixed bias were negligible (P_GPSn = −0.80 W·kg⁻¹ and P_GPSo = −1.59 W·kg⁻¹), and the bounds of the 95% CIs show that they were not statistically significant from 0. Proportional bias estimates were negligible (absolute differences from one being 0.03 W·kg⁻¹ for P_GPSn and 0.01 W·kg⁻¹ for P_GPSo) and not statistically significant as both 95% CIs span 1. All variables were distributed around the line of unity and resulted in an under- or overestimation of P_GPSn, while P_GPSo routinely underestimated MP across ranges. Repeated-measures ANOVA showed differences over MP conditions (F_1,38 = 16.929 and p < 0.001). Following Bonferroni post hoc test significant differences regarding the MP between P_GPSo and PV˙O2/P_GPSn (p < 0.001) were established, while no differences were found between PV˙O2 and P_GPSn (p = 0.853). The new approach showed it can help the coaches and the soccer trainers to better monitor external training load during the training seasons.

Energy Demands in Well-Trained Alpine Ski Racers During Different Duration of Slalom and Giant Slalom Runs

Bottollier, V, Coulmy, N, Le Quellec, L, and Prioux, J. Energy demands in well-trained alpine ski racers during different duration of slalom and giant slalom runs. J Strength Cond Res 34(8): 2156-2164, 2020-The purpose of this study was to investigate the energy demands of different duration slalom (SL) and giant slalom (GS) events in well-trained alpine ski racers. Eight well-trained alpine ski racers (age: 18.2 ± 0.8 years; stature: 1.72 ± 0.10 m; body mass: 65.8 ± 12.0 kg) performed an incremental laboratory test on cycle ergometer and 4 standardized alpine ski runs: short (ST) and long (LG) versions of SL and GS (SLST, SLLG, GSST, and GSLG). Oxygen uptake (V[Combining Dot Above]O2) and heart rate (HR) were recorded continuously in all conditions. Blood lactate ([La]) was determined immediately before run and 3 and 5 minutes after run ([La]peak). The contribution of aerobic, glycolytic, and phosphagen energy systems was estimated. The aerobic system was the primary energy system involved in GSST (43.9 ± 5.7%) and GSLG (48.5 ± 2.5%). No significant difference in the contribution of aerobic and glycolytic systems was observed in SLST and SLLG. [La]peak was higher in SLLG (11.10 ± 2.41 mmol·L) than in GSST (8.01 ± 2.01 mmol·L). There was no difference in oxygen uptake peak between GSST and GSLG. Energetic training goals should focus on the improvement of both aerobic, glycolytic, and phosphagen systems for alpine ski racers who perform SL and GS. Giant slalom specialists might benefit from emphasizing the improvement of the aerobic system, without neglecting other systems.

Frictional internal work of damped limbs oscillation in human locomotion

Joint friction has never previously been considered in the computation of mechanical and metabolic energy balance of human and animal (loco)motion, which heretofore included just muscle work to move the body centre of mass (external work) and body segments with respect to it. This happened mainly because, having been previously measured ex vivo, friction was considered to be almost negligible. Present evidences of in vivo damping of limb oscillations, motion captured and processed by a suited mathematical model, show that: (a) the time course is exponential, suggesting a viscous friction operated by the all biological tissues involved; (b) during the swing phase, upper limbs report a friction close to one-sixth of the lower limbs; (c) when lower limbs are loaded, in an upside-down body posture allowing to investigate the hip joint subjected to compressive forces as during the stance phase, friction is much higher and load dependent; and (d) the friction of the four limbs during locomotion leads to an additional internal work that is a remarkable fraction of the mechanical external work. These unprecedented results redefine the partitioning of the energy balance of locomotion, the internal work components, muscle and transmission efficiency, and potentially readjust the mechanical paradigm of the different gaits.

Importance of dimensional changes on glycolytic metabolism during growth

PURPOSE

The aim of the present study was to investigate (i) how glycolytic metabolism assessed by accumulated oxygen deficit (AOD_gly) and blood metabolic responses (lactate and pH) resulting from high-intensity exercise change during growth, and (ii) how lean body mass (LBM) influences AOD_gly and its relationship with blood markers.

METHODS

Thirty-six 11- to 17-year olds performed a 60-s all-out test on a rowing ergometer. Allometric modelling was used to investigate the influence of LBM and LBM + maturity offset (MO) on AOD_gly and its relationship with the extreme post-exercise blood values of lactate ([La]_max) and pH (pH_min) obtained during the recovery period.

RESULTS

AOD_gly and [La]_max increased while pH_min decreased linearly with LBM and MO (r² = 0.46 to 0.72, p < 0.001). Moreover, AOD_gly was positively correlated with [La]_max (r² = 0.75, p < 0.001) and negatively correlated with pH_min (r² = 0.77, p < 0.001). When AOD_gly was scaled for LBM, the coefficients of the relationships with blood markers drastically decreased by three to four times ([La]_max: r² = 0.24, p = 0.002; pH_min: r² = 0.30, p < 0.001). Furthermore, by scaling AOD_gly for LBM + MO, the correlation coefficients with blood markers became even lower ([La]_max: r² = 0.12, p = 0.037; pH_min: r² = 0.18, p = 0.009). However, MO-related additional changes accounted much less than LBM for the relationships between AOD_gly and blood markers.

CONCLUSION

The results challenge previous reports of maturation-related differences in glycolytic energy turnover and suggest that changes in lean body mass are a more powerful influence than maturity status on glycolytic metabolism during growth.

Energetic Profile in Forehand Loop Drive Practice with Well-Trained, Young Table Tennis Players

The forehand loop drive is one of the primary attacking techniques in table tennis and is practiced at a large volume during training. The aim of this study was to investigate the energetic profile of the high-repetition forehand loop drive practice in table tennis. Twenty-six well-trained, young table tennis players performed a treadmill graded exercise test to determine their peak oxygen uptake as a measure of overall cardiorespiratory fitness and an incremental table tennis stroke test with 3-min intervals during the forehand loop drive with a ball-throwing robot at a frequency of 35 to 85 strokes∙min⁻¹. Pulmonary and blood parameters were measured and analyzed with a portable spirometry system and a blood lactate analyzer. Energy contributions were calculated from aerobic, anaerobic lactic, and anaerobic alactic pathways for each stroke frequency. Energy cost was defined as the amount of energy expended above resting levels for one stroke. Repeated-measures analyses of variance (ANOVA) with the stroke frequency (35,45,55,65,75, or 85 strokes/min⁻¹) as a within-subject factor were performed for the dependent variables. A Power regression was performed for the energy cost as a function of the stroke frequency. Findings demonstrated a function of Y = 91.566·x^−0.601 where Y is the energy cost and x is the stroke frequency, R² = 0.9538. The energy cost decreased at higher stroke frequencies. The energy contributions from aerobic, anaerobic lactic, and anaerobic alactic pathways at each stroke frequency ranged from 79.4%–85.2%, 0.6%–2.1%, and 12.9%–20.0%, respectively. In conclusion, the energy cost of the forehand loop drive decreased at higher stroke frequencies. The high-repetition forehand loop drive practice was aerobic dominant and the anaerobic alactic system played a vital role.

The Anaerobic Capacity of Cross-Country Skiers: The Effect of Computational Method and Skiing Sub-technique

Anaerobic capacity is an important performance-determining variable of sprint cross-country skiing. Nevertheless, to date, no study has directly compared the anaerobic capacity, determined using the maximal accumulated oxygen deficit (MAOD) method and gross efficiency (GE) method, while using different skiing sub-techniques.

Purpose: To compare the anaerobic capacity assessed using two different MAOD approaches (including and excluding a measured y-intercept) and the GE method during double poling (DP) and diagonal stride (DS) cross-country skiing.

Methods: After an initial familiarization trial, 16 well-trained male cross-country skiers performed, in each sub-technique on separate occasions, a submaximal protocol consisting of eight 4-min bouts at intensities between ~47–78% of V.O_2peak followed by a 4-min roller-skiing time trial, with the order of sub-technique being randomized. Linear and polynomial speed-metabolic rate relationships were constructed for both sub-techniques, while using a measured y-intercept (8+Y_LIN and 8+Y_POL) or not (8–Y_LIN and 8–Y_POL), to determine the anaerobic capacity using the MAOD method. The average GE (GE_AVG) of all eight submaximal exercise bouts or the GE of the last submaximal exercise bout (GE_LAST) were used to calculate the anaerobic capacity using the GE method. Repeated measures ANOVA were used to test differences in anaerobic capacity between methods/approaches.

Results: A significant interaction was found between computational method and skiing sub-technique (P < 0.001, η² = 0.51) for the anaerobic capacity estimates. The different methodologies resulted in significantly different anaerobic capacity values in DP (P < 0.001, η² = 0.74) and in DS (P = 0.016, η² = 0.27). The 8-Y_POL model resulted in the smallest standard error of the estimate (SEE, 0.24 W·kg⁻¹) of the MAOD methods in DP, while the 8-Y_LIN resulted in a smaller SEE value than the 8+Y_LIN model (0.17 vs. 0.33 W·kg⁻¹) in DS. The 8-Y_LIN and GE_LAST resulted in the closest agreement in anaerobic capacity values in DS (typical error 2.1 mL O₂eq·kg⁻¹).

Conclusions: It is discouraged to use the same method to estimate the anaerobic capacity in DP and DS sub-techniques. In DP, a polynomial MAOD method (8-Y_POL) seems to be the preferred method, whereas the 8-Y_LIN, GE_AVG, and GE_LAST can all be used for DS, but not interchangeable, with GE_LAST being the least time-consuming method.

Effect of Lower Body Negative Pressure on Phase I Cardiovascular Responses at Exercise Onset

We hypothesised that vagal withdrawal and increased venous return interact in determining the rapid cardiac output (CO) response (phase I) at exercise onset. We used lower body negative pressure (LBNP) to increase blood distribution to the heart by muscle pump action and reduce resting vagal activity. We expected a larger increase in stroke volume (SV) and smaller for heart rate (HR) at progressively stronger LBNP levels, therefore CO response would remain unchanged. To this aim ten young, healthy males performed a 50 W exercise in supine position at 0 (Control), −15, −30 and −45 mmHg LBNP exposure. On single beat basis, we measured HR, SV, and CO. Oxygen uptake was measured breath-by-breath. Phase I response amplitudes were obtained applying an exponential model. LBNP increased SV response amplitude threefold from Control to −45 mmHg. HR response amplitude tended to decrease and prevented changes in CO response. The rapid response of CO explained that of oxygen uptake. The rapid SV kinetics at exercise onset is compatible with an increased venous return, whereas the vagal withdrawal conjecture cannot be dismissed for HR. The rapid CO response may indeed be the result of two independent yet parallel mechanisms, one acting on SV, the other on HR.

Omics and the molecular exercise physiology

Exercise is a well-known non-pharmacologic agent used to prevent and treat a wide range of pathologic conditions such as metabolic and cardiovascular disease. In this sense, the classic field of exercise physiology has determined the main theoretical and practical bases of physiologic adaptations in response to exercise. However, the last decades were marked by significant advances in analytical laboratory techniques, where the field of biochemistry, genetics and molecular biology promoted exercise science to enter a new era. Regardless of its application, whether in the field of disease prevention or performance, the association of molecular biology with exercise physiology has been fundamental for unveiling knowledge of the molecular mechanisms related to the adaptation to exercise. This chapter will address the natural evolution of exercise physiology toward genetics and molecular biology, emphasizing the collection of integrated analytical approaches that composes the OMICS and their contribution to the field of molecular exercise physiology.

The energy cost of swimming and its determinants

The energy expended to transport the body over a given distance (C, the energy cost) increases with speed both on land and in water. At any given speed, C is lower on land (e.g., running or cycling) than in water (e.g., swimming or kayaking) and this difference can be easily understood when one considers that energy should be expended (among the others) to overcome resistive forces since these, at any given speed, are far larger in water (hydrodynamic resistance, drag) than on land (aerodynamic resistance). Another reason for the differences in C between water and land locomotion is the lower capability to exert useful forces in water than on land (e.g., a lower propelling efficiency in the former case). These two parameters (drag and efficiency) not only can explain the differences in C between land and water locomotion but can also explain the differences in C within a given form of locomotion (swimming at the surface, which is the topic of this review): e.g., differences between strokes or between swimmers of different age, sex, and technical level. In this review, the determinants of C (drag and efficiency, as well as energy expenditure in its aerobic and anaerobic components) will, thus, be described and discussed. In aquatic locomotion it is difficult to obtain quantitative measures of drag and efficiency and only a comprehensive (biophysical) approach could allow to understand which estimates are "reasonable" and which are not. Examples of these calculations are also reported and discussed.

Health Risks and Interventions in Exertional Heat Stress

BACKGROUND

With climate change, heat waves are expected to become more frequent in the near future. Already, on average more than 25 000 "heat deaths" are estimated to occur in Europe every year. However, heat stress and heat illnesses arise not just when ambient temperatures are high. Physical exertion increases heat production within the organism many times over; if not enough heat is lost, there is a risk of exertional heat stress. This review article discusses contributing factors, at-risk groups, and the diagnosis and treatment of heat illnesses.

METHODS

A selective literature search was carried out on PubMed. Current guidelines and expert recommendations were also included.

RESULTS

Apart from muscular heat production (>70% of converted energy), there are other factors that singly or in combination can give rise to heat stress: clothing, climate/acclimatization, and individual factors. Through its insulating properties, clothing reduces the evaporation of sweat (the most effective physiological cooling mechanism). A sudden heat wave, or changing the climate zone (as with air travel), increases the risk of a heat-related health event. Overweight, low fitness level, acute infections, illness, dehydration, and other factors also reduce heat tolerance. In addition to children, older people are particularly at risk because of their reduced physiological adaptability, (multi-)morbidity, and intake of prescription drugs. A heat illness can progress suddenly to life-threatening heat stroke. Successful treatment depends on rapid diagnosis and cooling the body down as quickly as possible. The aim is to reduce core body temperature to <40 °C within 30 minutes.

CONCLUSION

Immediately effective cooling interventions are the only causal treatment for heat stroke. Time once lost cannot be made up. Prevention (acclimatization, reduced exposure, etc.) and terminating the heat stress in good time (e.g., stopping work) are better than any cure.

Acute impact of an endurance race on cardiac function and biomarkers of myocardial injury in triathletes with and without myocardial fibrosis

AIMS

The aim of this study was to investigate the occurrence of myocardial injury and cardiac dysfunction after an endurance race by biomarkers and cardiac magnetic resonance in triathletes with and without myocardial fibrosis.

METHODS AND RESULTS

Thirty asymptomatic male triathletes (45 ± 10 years) with over 10 training hours per week and 55 ± 8 ml/kg per minute maximal oxygen uptake during exercise testing were studied before (baseline) and 2.4 ± 1.1 hours post-race. Baseline cardiac magnetic resonance included cine, T1/T2, late gadolinium enhancement (LGE) and extracellular volume imaging. Post-race non-contrast cardiac magnetic resonance included cine and T1/T2 mapping. Non-ischaemic myocardial fibrosis was present in 10 triathletes (LGE+) whereas 20 had no fibrosis (LGE-). At baseline, LGE + triathletes had higher peak exercise systolic blood pressure with 222 ± 21 mmHg compared to LGE- triathletes (192 ± 30 mmHg, P < 0.01). Post-race troponin T and creatine kinase MB were similarly increased in both groups, but there was no change in T2 and T1 from baseline to post-race with 54 ± 3 ms versus 53 ± 3 ms (P = 0.797) and 989 ± 21 ms versus 989 ± 28 ms (P = 0.926), respectively. However, post-race left atrial ejection fraction was significantly lower in LGE + triathletes compared to LGE- triathletes (53 ± 6% vs. 59 ± 6%, P < 0.05). Furthermore, baseline atrial peak filling rates were lower in LGE -  triathletes (121 ± 30 ml/s/m²) compared to LGE + triathletes (161 ± 34 ml/s/m², P < 0.01). Post-race atrial peak filling rates increased in LGE- triathletes to 163 ± 46 ml/s/m², P < 0.001), but not in LGE + triathletes (169 ± 50ml/s/m², P = 0.747).

CONCLUSION

Despite post-race troponin T release, we did not find detectable myocardial oedema by cardiac magnetic resonance. However, the unfavourable blood pressure response during exercise testing seemed to be associated with post-race cardiac dysfunction, which could explain the occurrence of myocardial fibrosis in triathletes.

Reproducibility of Blood Lactate Concentration Rate under Isokinetic Force Loads

(1) Background: Maximum isokinetic force loads show strongly increased post-load lactate concentrations and an increase in the maximum blood lactate concentration rate (V˙La_max), depending on load duration. The reproducibility of V˙La_max must be known to be able to better assess training-related adjustments of anaerobic performance using isokinetic force tests. (2) Methods: 32 subjects were assigned to two groups and completed two unilateral isokinetic force tests (210° s⁻¹, Range of Motion 90°) within seven days. Group 1 (n = 16; age 24.0 ± 2.8 years, BMI 23.5 ± 2.6 kg m⁻², training duration: 4.5 ± 2.4 h week⁻¹) completed eight repetitions and group 2 (n = 16; age 23.7 ± 1.9 years, BMI 24.6 ± 2.4 kg m⁻², training duration: 5.5 ± 2.1 h week⁻¹) completed 16 repetitions. To determine V˙La_max, capillary blood (20 µL) was taken before and immediately after loading, and up to the 9th minute post-load. Reproducibility and variability was determined using Pearson and Spearman correlation analyses, and variability were determined using within-subject standard deviation (S_w) and Limits of Agreement (LoA) using Bland Altman plots. (3) Results: The correlation of V˙La_max in group 1 was r = 0.721, and in group 2 r = 0.677. The S_w of V˙La_max was 0.04 mmol L⁻¹ s⁻¹ in both groups. In group 1, V˙La_max showed a systematic bias due to measurement repetition of 0.02 mmol L⁻¹ s⁻¹ in an interval (LoA) of ±0.11 mmol L⁻¹ s⁻¹. In group 2, a systematic bias of −0.008 mmol L⁻¹ s⁻¹ at an interval (LoA) of ±0.11 mmol L⁻¹ s⁻¹ was observed for repeated measurements of V˙La_max. (4) Conclusions: Based on the existing variability, a reliable calculation of V˙La_max seems to be possible with both short and longer isokinetic force loads. Changes in V˙La_max above 0.11 mmol L⁻¹ s⁻¹ due to training can be described as a non-random increase or decrease in V˙La_max.

Performance and Metabolic Demand of a New Repeated-Sprint Ability Test in Basketball Players: Does the Number of Changes of Direction Matter?

Zagatto, AM, Ardigò, LP, Barbieri, FA, Milioni, F, Dello Iacono, A, Camargo, BHF, and Padulo, J. Performance and metabolic demand of a new repeated-sprint ability test in basketball players: does the number of changes of direction matter? J Strength Cond Res 31(9): 2438-2446, 2017-This study compared 2 repeated-sprint ability (RSA) tests in basketball players. Both tests included 10 × 30-m sprints, with the difference that the previously validated test (RSA2COD) featured 2 changes of direction (COD) per sprint, whereas the experimental test (RSA5COD) featured 5 CODs per sprint. Test performances and metabolic demands were specifically assessed in 20 basketball players. First, RSA5COD test-retest reliability was investigated. Then, RSA2COD, RSA5COD sprint times, peak speeds, oxygen uptake (V[Combining Dot Above]O2) and posttest blood lactate concentration [La] were measured. The RSA5COD results showed to be reliable. RSA2COD performance resulted better than the RSA5COD version (p < 0.01), with shorter sprint times and higher peak speeds. Over sprints, the tests did not differ from each other in terms of V[Combining Dot Above]O2 (p > 0.05). Over whole bout, the RSA2COD was more demanding than the RSA5COD, considering overall metabolic power requirement (i.e., VO2-driven + [La]-driven components). Given that RSA5COD (a) mimics real game-play as sprint distance and action change frequency/direction and (b) has the same metabolic expenditure per task completion as metabolic cost, RSA5COD is a valuable option for players and coaches for training basketball-specific agility and assessing bioenergetic demands.

Method-Induced Differences of Energy Contributions in Women's Kayaking

CONTEXT

Different relative aerobic energy contribution (W_AER%) has been reported for the 2 women's Olympic kayaking disciplines (ie, 200 and 500 m).

PURPOSE

To investigate whether the adopted method of energy calculation influences the value of W_AER% during kayaking time trials.

METHODS

Eleven adolescent female kayakers (age 14 ± 1 y, height 172 ± 4 cm, body mass 65.4 ± 4.2 kg, VO₂peak 42.6 ± 4.9 mL·min^-1·kg^-1, training experience 1.5 ± 0.3 y) volunteered to participate in 1 incremental exercise test and 2 time trials (40 and 120 s) on the kayak ergometer. A portable spirometric system was used to measure gas metabolism. Capillary blood was taken from the ear lobe during and after the tests and analyzed for lactate afterward. The method of modified maximal accumulated oxygen deficit (m-MAOD) and the method based on the fast component of oxygen-uptake off-kinetics (PCr-La-O₂) were used to calculate the energy contributions.

RESULTS

The anaerobic energy portions from m-MAOD were lower than those from PCr-La-O₂ in the 40-s (41.9 ± 8.8 vs 52.8 ± 4.0 kJ, P > .05) and 120-s (64.1 ± 27.9 vs 68.2 ± 10.0 kJ, P > .05) time trials, which induced differences of W_AER% between m-MAOD and PCr-La-O₂ (36.0% vs 30.0% in 40 s, P > .05; 60.9% vs 57.5% in 120 s, P > .05).

CONCLUSIONS

The reported different W_AER% in women's Olympic kayaking could be partly attributed to the adopted method of energy calculation (ie, m-MAOD vs PCr-La-O₂). A fixed method of energy calculation is recommended during the longitudinal assessment on the relative energy contribution in women's Olympic kayaking.

The physiology of submaximal exercise: The steady state concept

The steady state concept implies that the oxygen flow is invariant and equal at each level along the respiratory system. The same is the case with the carbon dioxide flow. This condition has several physiological consequences, which are analysed. First, we briefly discuss the mechanical efficiency of exercise and the energy cost of human locomotion, as well as the roles played by aerodynamic work and frictional work. Then we analyse the equations describing the oxygen flow in lungs and in blood, the effects of ventilation and of the ventilation - perfusion inequality, and the interaction between diffusion and perfusion in the lungs. The cardiovascular responses sustaining gas flow increase in blood are finally presented. An equation linking ventilation, circulation and metabolism is developed, on the hypothesis of constant oxygen flow in mixed venous blood. This equation tells that, if the pulmonary respiratory quotient stays invariant, any increase in metabolic rate is matched by a proportional increase in ventilation, but by a less than proportional increase in cardiac output.

Effects of recovery interval duration on the parameters of the critical power model for incremental exercise

INTRODUCTION

We tested the linear critical power ([Formula: see text]) model for discrete incremental ramp exercise implying recovery intervals at the end of each step.

METHODS

Seven subjects performed incremental (power increment 25 W) stepwise ramps to subject's exhaustion, with recovery intervals at the end of each step. Ramps' slopes (S) were 0.83, 0.42, 0.28, 0.21, and 0.08 W s^-1; recovery durations (t _r) were 0 (continuous stepwise ramps), 60, and 180 s (discontinuous stepwise ramps). We determined the energy store component (W'), the peak power ([Formula: see text]), and [Formula: see text].

RESULTS

When t _r = 0 s, [Formula: see text] and W' were 187 ± 26 W and 14.5 ± 5.8 kJ, respectively. When t _r = 60 or 180 s, the model for ramp exercise provided inconsistent [Formula: see text] values. A more general model, implying a quadratic [Formula: see text] versus [Formula: see text] relationship, was developed. This model yielded, for t _r = 60 s, [Formula: see text] = 189 ± 48 W and W' = 18.6 ± 17.8 kJ, and for t _r = 180 s, [Formula: see text] = 190 ± 34 W, and W' = 16.4 ± 16.7 kJ. These [Formula: see text] and W' did not differ from the corresponding values for t _r = 0 s. Nevertheless, the overall amount of energy sustaining work above [Formula: see text], due to energy store reconstitution during recovery intervals, was higher the longer t _r, whence higher [Formula: see text] values.

CONCLUSIONS

The linear [Formula: see text] model for ramp exercise represents a particular case (for t _r = 0 s) of a more general model, accounting for energy resynthesis following oxygen deficit payment during recovery.