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Summary Introduction This aim of the present study was to compare metabolic rates at critical running speed vs. critical power in cycling. Summary of facts Eight participants (33.6 ± 12.1 years) performed a series of constant-intensity exhaustive trials to model the speed–time -1 (treadmill; 1% gradient) and power time -1 relationship (cycle ergometry) for intercept of the two relationships to be determined (Critical Speed [CS], Critical Power [CP]). A time to exhaustion (tlim) at CS and CP then followed. tlim did not differ between conditions (CS: 30.2 ± 4.7 min, CP: 26.8 ± 1.4 min, p = 0.58). The mean VO 2 values at minute 3 of the tlim were not significantly different with a strong relationship between the two sets of data ( r = 0.87, p 2 max (CP) at end exercise, with no difference between the two sets of data ( p Conclusion There is a metabolic, critical intensity (i.e. CS and CP) that induces similar metabolic stress, thus independent of the muscular contraction regimens.

Summary Introduction This study investigated the effect of a change in muscle contraction regimen via the manipulation of treadmill gradient on critical running speed. Summary of facts Ten participants performed a series of constant-speed exhaustive trials to model the speed–time −1 relationship using a 2-parameter equation (intercept: critical speed, CS). The treadmill gradient was either 0% (CS 0% ) or 10% (CS 10% ). A time to exhaustion ( t lim ) at both CS then followed in a randomised order. CS 10% was lower by ∼35% (2.57 ± 0.10 vs. 3.95 ± 0.15 m.s −1 ) yet the mean VO 2 values at minute 3 of t lim did not differ significantly. There was no difference in the t lim at CS 0% and CS 10% (∼30 minutes). However, there were some differences in the physiological responses between minute 3 and end exercise, and consequently the pattern between the two time points. Conclusion CS is affected by a change in treadmill gradient while its associated metabolic rate isn’t. But when exercising at CS, differences in the metabolic stress over time suggests for the development of fatigue, and therefore the sustainability of CS, to be dependent on the muscular contraction regimens.

The Wingate cycle test (WAnT) is a 30-s test commonly used to estimate anaerobic work capacity (AWC). However, the test may be too short to fully deplete anaerobic energy reserves. We hypothesized that a 90-s all-out isokinetic test (ISO_90) would be valid to assess both aerobic and anaerobic capacities in young females. Eight girls (11.9 ± 0.5 y) performed an exhaustive incremental test, a WAnT and an ISO_90. Peak VO2 attained during the ISO_90 was significantly greater than VO2peak. Mean power, end power, fatigue index, total work done and AWC were not significantly different between the WAnT and after 30 s of the 90-s test (i.e., ISO_30). However, 95% limits of agreement showed large variations between the two tests when comparing all anaerobic parameters. It is concluded that an ISO-90 may be a useful test to assess aerobic capacity in young girls. However, since the anaerobic parameters derived from the ISO_30 did not agree with those derived from a traditional WAnT, the validity of using an ISO_90 to assess anaerobic performance and capacity within this population group remains unconfirmed.

This study aimed to examine if the faster pulmonary oxygen uptake (VO2p) phase 2 in children could be explained by increased O2 availability or extraction at the muscle level. For that purpose, O2 availability and extraction were assessed using deoxyhemoglobin (HHb) estimated by near-infrared spectroscopy during moderate-intensity constant load cycling exercise in children and young adults. Eleven prepubertal boys and 12 men volunteered to participate in the study. They performed one maximal graded exercise to determine the power associated with the gas exchange threshold (GET) and four constant load exercises at 90% of GET. VO2p and HHb were continuously monitored. VO2p , HHb, and estimated capillary blood flow (Qcap) kinetics were modelled after a time delay and characterized by the time to achieve 63% of the amplitude (τ) and by mean response time (MRT: time delay + τ), respectively. Mean values of τ for VO2p (P < 0.001), of MRT for HHb (P < 0.01) and of MRT for Qcap (P < 0.001) were significantly shorter in children. Faster VO2p kinetics have been shown in children; these appear due to both faster O2 extraction and delivery kinetics as indicated by faster HHb and Qcap kinetics, respectively.

A 3D cycling model is presented that combines bicycle dynamics, a tyre model, rider biomechanics and environmental factors into a single dynamic system. The system is constructed using Matlab toolboxes (SimMechanics/Simulink) with the aim of identifying mechanical mechanisms that can influence performance in a road cycling time trial. Initial conditions are specified and a variable step ODE solver numerically integrates solutions to the equations of motion. Initial validation compared rider-less self-stability presented in a published “benchmark” with model simulation and found an error of

There has been much debate in the recent scientific literature regarding the possible ability to increase gross efficiency in cycling via training. Using cross-sectional study designs, researchers have demonstrated no significant differences in gross efficiency between trained and untrained cyclists. Reviewing this literature provides evidence to suggest that methodological inadequacies may have played a crucial role in the conclusions drawn from the majority of these studies. We present an overview of these studies and their relative shortcomings and conclude that in well-controlled and rigorously designed studies, training has a positive influence upon gross efficiency. Putative mechanisms for the increase in gross efficiency as a result of training include, muscle fibre type transformation, changes to muscle fibre shortening velocities and changes within the mitochondria. However, the specific mechanisms by which training improves gross efficiency and their impact on cycling performance remain to be determined.

To examine the impact of low-intensity and a mixture of low- and high-intensity training on physiological and performance responses in rowing.Eighteen experienced rowers undertook a 12-wk program of 100%or = lactate threshold (LT) training (LOW) or 70% training ator = LT and 30% at halfway (50%Delta) between the V O2 at LT and V O2peak (MIX). Responses were assessed before and after training by a progressive exercise test to exhaustion; multiple "square-wave" rest-to-exercise transitions of 6-min duration at 50%Delta; and a maximal 2000-m ergometer time trial.Improvements (P0.001) in 2000-m ergometer performance and V O2peak occurred independently of groups (P = 0.8 and 0.42, respectively). LOW improved the power at LT (23.5 +/- 12.2 vs 5.1 +/- 5.0 W, P = 0.013) and power at a [blood lactate] of 4 mM (32.3 +/- 6.9 vs 13.1 +/- 3.7 W, P = 0.03) compared with MIX. The time constant and gain of the primary component were unchanged with training, whereas the gain of the V O2 slow component was reduced with training, but independently of group.Both LOW and MIX training programs improved performance and V O2peak by the same magnitude, whereas LOW attenuated the blood lactate response to a given exercise intensity more so than MIX.

The aim of this study was to compare .VO2 kinetics of highly- versus recreationally-trained subjects during a constant velocity test of supramaximal intensity. Eighteen trained male subjects were recruited to one of two groups: highly trained (HT, n = 8, .VO(2max) = 70.1 +/- 6.5 ml . min (-1) . kg (-1)) and recreationally trained (RT, n = 10, .VO(2max) = 63.2 +/- 6.4 ml . min (-1) . kg (-1)). All subjects performed an incremental test to exhaustion for the determination of .VO(2max) and peak treadmill velocity (PTV), two constant velocity tests at 110 % of PTV to determine .VO2 kinetics and oxygen deficit (O(2)def), and a 800-m time trial to determine running performance (mean velocity over the distance, V (800 m)). We found significant differences between HT and RT for the on-transient of the .VO2 response (tau, 24.7 +/- 3.3 and 30.9 +/- 7.0 s, respectively), the amplitude of the .VO2 response (60.0 +/- 5.0 and 53.5 +/- 5.7 ml . min (-1) . kg (-1), respectively) and V (800 m) (6.27 +/- 2.1 and 5.45 +/- 0.38 m . s (-1), respectively). O(2)def (24.6 +/- 2.7 and 27.7 +/- 7.8 ml . kg (-1), respectively) and the gain of the .VO2 response (193 +/- 14 and 194 +/- 13 ml . kg (-1) . m (-1), respectively) were similar between groups. tau was associated with O(2)def (r = 0.90, p0.05), but not with V (800 m) (r = 0.30, p0.05). It was concluded that HT subjects exhibited faster on-kinetics and higher amplitude than their RT counterparts. The higher amplitude was not thought to reflect any difference in underlying physiological mechanisms. The faster tau, whose exact mechanisms remain to be elucidated, may have practical implications for coaches.

Purpose: To test the hypothesis that elite rowers would possess a faster, more economic oxygen uptake response than club standard rowers. Methods: Eight Olympic champion (ELITE) rowers were compared with a cohort of eight club standard (CLUB) rowers. Participants completed a progressive exercise test to exhaustion, repeated 6-min moderate and heavy square-wave transitions, and a maximal 2000-m ergometer time trial. Results: The time constant (t) of the primary component (PC) was faster for the ELITE group compared with CLUB for moderate-intensity (13.9 vs 19.4 s, P = 0.02) and heavy-intensity (18.7 vs 22.4 s, P = 0.005) exercise. ELITE rowers consumed less oxygen for moderate (14.2 vs 15.6 mL·min-1·W-1; P = 0.009) and heavy (12.1 vs 13.7 mL·min-1·W-1; P = 0.01) exercise. A greater absolute slow component was observed in the ELITE group (P = 0.009), but no differences were noted when the slow component was expressed relative to work rate performed (P = 0.14). Intergroup correlation with time trial performance speed was significant for tPC during heavy-intensity exercise (r = -0.59, P = 0.02). Conclusions: Compared with CLUB rowers, the shorter time constant response and greater economy observed in ELITE rowers may suggest advantageous adjustment of oxidative processes from rest to work. Training status or performance level do not seem to be associated with a smaller slow component when comparing CLUB and ELITE oarsmen.

The purpose of this study was to establish the validity of a 90-s all-out test for the estimation of maximal oxygen uptake (V.O (2max)) and submaximal aerobic ability as represented by critical power. We hypothesized that the fall in power output by the end of the 90-s all-out test (end power) would represent the exhaustion of anaerobic work capability, and as such, would correspond with the critical power. Sixteen active individuals (mean +/- SD: 30 +/- 6 years; 69.6 +/- 9.9 kg) carried out a series of tests: (i) an incremental ramp test to determine V.O (2max), (ii) three fixed-work rate trials to exhaustion to determine critical power, and (iii) two 90-s all-out tests to measure end power and peak V.O (2). End power (292 +/- 65 W) was related to (r=0.89) but was significantly higher (p

We analyse the evolution of the slope (critical speed) and the y-intercept (anaerobic distance capacity) of the linear distance-time relationship over a century of Olympic running performances. The distance-time relationship of each Olympic Games (1920-2004) was plotted using the performances in the 800-, 1500- and 5000-m track events. Values for critical speed and anaerobic distance capacity were determined by linear modelling. Mean performances for the 800, 1500 and 5000 m were 104.9 +/- 1.5 s (1.4%), 217.2 +/- 2.8 s (1.3%) and 808.9 +/- 18.4 s (2.3%), respectively. Critical speed improved during the first three-quarters of the twentieth century to reach a plateau in 1984. This is in accordance with the literature (Peronnet & Thibault, 1989) and suggests that "human aerobic endurance" has improved within the century (+13.4%) and tends to stabilize. Anaerobic distance capacity was highly variable over the century (coefficient of variation = 9.4%) and did not show a linear improvement over the years as has previously been suggested (Peronnet & Thibault, 1989). This could be due to an artefact in the application of the two-parameter model to only three Olympic performances. A limitation to the use of this linear mathematical model to fit physiological data may have been demonstrated.

Accurate classification of VO2 kinetics is essential to correctly interpret its control mechanisms. The purpose of this study was to examine VO2 kinetics in severe and supra-maximal intensity running exercise using two modelling techniques. Nine subjects (mean +/- S.D: age, 27 +/- 7 years; mass, 69.8 +/- 9.0 kg; VO2max, 59.1 +/- 1.8 mL x kg x min(-1)) performed a series of "square-wave" exercise transitions to exhaustion at running speeds equivalent to 80% of the difference between the VO2 at LT and VO2max (delta), and at 100%, 110% and 120% VO2max. The VO2 response was modelled with an exponential model and with a semi-logarithmic transformation, the latter assuming a certain steady state VO2. With the exponential model there was a significant reduction in the "gain" of the primary component in supra-maximal exercise (167 +/- 5 mL x kg(-1) x km(-1) at 80% delta to 142 +/- 5 mL x kg(-1) x km(-1) at 120% VO2max, p = 0.005). The time constant of the primary component also reduced significantly with increasing intensity (17.8 +/- 1.1 s at 80% delta to 12.5 +/- 1.2 s at 120% VO2max, p < 0.05). However, in contrast, using the semi-log model, the time constant significantly increased with intensity (30.9 +/- 13.5 s at 80% delta to 72.2 +/- 23.9 s at 120% VO2max, p < 0.05). Not withstanding the need for careful interpretation of mathematically modelled data, these results demonstrate that neither the gain nor the time constant of the VO2 primary component during treadmill running are invariant across the severe and supra-maximal exercise intensity domains when fit with an exponential model. This suggests the need for a reappraisal of the VO2/work rate relationship in running exercise.

The curvature of the power-time (P-t) relationship (W') has been suggested to be constant when exercising above critical power (CP) and to represent the anaerobic work capacity (AWC). The aim of this study was to compare W' to (1) the total amount of work performed above CP (W (90s)') and (2) the AWC, both determined from a 90s all-out fixed cadence test. Fourteen participants (age 30.5 +/- 6.5 years; body mass 67.8 +/- 10.3 kg), following an incremental VO(2max) ramp protocol, performed three constant load exhaustion tests set at 103 +/- 3, 97 +/- 3 and 90 +/- 2% P-VO(2max) to calculate W' from the P-t relationship. Two 90s all-out efforts were also undertaken to determine W (90s)' (power output-time integral above CP) and AWC (power output-time integral above the power output expected from the measured VO(2)). W' (13.6 +/- 1.3 kJ) and W (90s)' (13.9 +/- 1.1 kJ; P = 0.96) were not significantly different but were lower than AWC (15.9 +/- 1.2 kJ) by 24% (P = 0.03) and 17%, respectively (P = 0.04). All these variables were correlated (P < 0.001) but great extents of disagreement were reported (0.2 +/- 6.4 kJ between W' and W (90s)', 2.3 +/- 7.2 kJ between W' and AWC, and 2.1 +/- 4.3 kJ between W (90s)' and AWC). The underestimation of AWC from both W' and W (90s)' can be explained by the aerobic inertia not taking into consideration when determining the two latter variables. The low extents of agreement between W', W (90s)' and AWC mean the terms should not be used interchangeably.

The aim of the present study was to ascertain whether the intensity of prior exercise altered the time to exhaustion at critical power (CP).Eleven participants volunteered to take part in the study (mean +/- SD: VO2max 4.1 +/- 0.5 L x min(-1); age 30.1 +/- 7.2 yr; body mass 74.6 +/- 9.1 kg) and completed three trials to exhaustion at their CP under differing prior exercise conditions: 1) a control trial (CON); 2) a trial preceded by three 60-s efforts at 110% CP (severe); and 3) a trial preceded by three 73-s efforts at 90% CP (heavy). All trials followed a 5-min baseline at 50 W.Time to exhaustion was significantly lengthened after prior heavy exercise (1071 +/- 18 s) when compared with CON (973 +/- 16 s, F = 9.53, P = 0.006). However, there was no effect on TTE after prior severe exercise (967 +/- 16 s). Oxygen deficit was significantly reduced from that in CON (3.8 +/- 0.2 L) after prior heavy (3.2 +/- 0.3 L) and prior severe exercise (3.1 +/- 0.3 L, F = 10.95, P = 0.001). Concurrently, there was a significant reduction in the magnitude of the VO2 slow component (SC) in the trials with prior exercise (197 +/- 34 and 126 +/- 19 mL x min(-1) after heavy and severe exercise, respectively) when compared with CON (223 +/- 31 mL x min(-1), F = 9.62, P = 0.006).Prior heavy exercise does appear to improve the time to exhaustion at CP by approximately 10% and is associated with a reduction in the VO2 SC. However, the reduction in the SC, with no change in performance after prior severe exercise, suggests that a reduced SC may not necessarily lead to improved TTE.

The performance of prior high intensity constant work rate (CWR) exercise significantly influences the gain of the fundamental oxygen uptake (VO2) response during subsequent high intensity CWR exercise. The purpose of the present study was to investigate whether equivalent effects could be elicited in the second of two bouts of exhaustive ramp exercise. We therefore hypothesised that a prior bout of exhaustive ramp exercise would increase the VO2-work rate (DeltaVO2/DeltaWR) slope during subsequent ramp exercise. Nine healthy males performed two ramp exercise tests to exhaustion on an electrically braked cycle ergometer separated by a 10-min period of cycling at 20 W. Pulmonary VO2 was measured breath-by-breath throughout both tests, and the mean response time (MRT) and the DeltaVO2/DeltaWR slope for exercise below the gas exchange threshold (GET) (S1), above the GET (S2), and over the S1 + S2 region (ST) were determined. Paired t-tests were used to analyse the data with significance accepted at p < 0.05. Blood [lactate] was higher at the onset of the second ramp test compared to the first (mean +/- SEM 1.2 +/- 0.1 vs. 6.2 +/- 0.7 mM; p < 0.01), but baseline VO2 was not significantly different between tests (0.93 +/- 0.05 vs. 0.99 +/- 0.06 L. min (-1)). The MRT (42 +/- 4 vs. 40 +/- 5 s) did not differ between tests, but the DeltaVO2/DeltaWR slope was steeper in the second ramp test for S2 (9.1 +/- 0.4 vs. 9.8 +/- 0.5 ml. min (-1). W (-1); p < 0.01) and ST (9.0 +/- 0.4 vs. 9.6 +/- 0.5 ml. min (-1). W (-1); p < 0.05). The demonstration that prior ramp exercise increases the DeltaVO2/DeltaWR slope during subsequent ramp exercise is consistent with the results of previous CWR studies and indicates that exercise economy is sensitive to the prior activity of the engaged muscles.

The purpose of the present study was to test the hypothesis that muscle fibre type influences the oxygen uptake (.VO(2)) on-kinetic response (primary time constant; primary and slow component amplitudes) during moderate, heavy and severe intensity sub-maximal cycle exercise. Fourteen subjects [10 males, mean (SD) age 25 (4) years; mass 72.6 (3.9) kg; .VO(2peak) 47.9 (2.3) ml kg(-1) min(-1)] volunteered to participate in this study. The subjects underwent a muscle biopsy of the vastus lateralis for histochemical determination of muscle fibre type, and completed repeat "square-wave" transitions from unloaded cycling to power outputs corresponding to 80% of the ventilatory threshold (VT; moderate exercise), 50% (heavy exercise) and 70% (severe exercise) of the difference between the VT and .VO(2peak). Pulmonary .VO(2) was measured breath-by-breath. The percentage of type I fibres was significantly correlated with the time constant of the primary .VO(2) response for heavy exercise (r=-0.68). Furthermore, the percentage of type I muscle fibres was significantly correlated with the gain of the .VO(2) primary component for moderate (r=0.65), heavy (r=0.57) and severe (r=0.57) exercise, and with the relative amplitude of the .VO(2) slow component for heavy (r=-0.74) and severe (r=-0.64) exercise. The influence of muscle fibre type on the .VO(2) on-kinetic response persisted when differences in aerobic fitness and muscle capillarity were accounted for. This study demonstrates that muscle fibre type is significantly related to both the speed and the amplitudes of the .VO(2) response at the onset of constant-load sub-maximal exercise. Differences in contraction efficiency and oxidative enzyme activity between type I and type II muscle fibres may be responsible for the differences observed.

Purpose: The purpose of this study was to assess the relationship between pulmonary O2 and running speed over a range of exercise intensities. During constant-load cycle exercise above the lactate threshold (Tlac), it has been shown that O2 does not attain a steady state within 3 min but continues to rise until either a delayed but elevated steady-state O2 is attained or exhaustion occurs. Since this greater oxygen cost of exercise ( O2 slow component) has only been demonstrated at discrete exercise intensities above Tlac, it was hypothesised that the onset of the O2 slow component would coincide with Tlac during an incremental test if the stage durations were of sufficient length. Methods: Five male subjects (mean +/- SD age 31 +/- 2 yr; O2peak 60.1 +/- 5.8 mL[middle dot]kg-1[middle dot]min-1) performed four identical treadmill tests within an 8-d period. The tests involved the completion of six stages of 7-min duration. Running speed was increased by 0.5 km[middle dot]h-1 between stages. In the first test, fingertip capillary blood was sampled at the end of each stage for determination of Tlac. For all tests expired air was collected into Douglas bags from 3.0 to 3.75 min and from 6.0 to 6.75 min of each stage to determine any increase in O2 (ΔO2) over the duration of the stage. Results: The mean Δ O2 for each stage over the four tests was determined for each subject. Repeated measures ANOVA with post-hoc Tukey tests revealed a significant increase in Δ O2 at running speeds above, but not below, Tlac. Conclusions: The results of this study confirm the close association between the O2 slow component and the onset of lactic acidosis and demonstrate alinearity in the O2-exercise intensity relationship above Tlac for incremental treadmill exercise.

PURPOSE The purpose of this study was to investigate the effect of altering the initial running speed (RS) in the incremental portion of the lactate minimum test on the lactate minimum speed (LMS). METHODS Eight well-trained endurance runners (mean +/- SD age 29.0 +/- 5.4 yr, body mass 72.0 +/- 5.6 kg, VO2max 63.1 +/- 3.8 mL x kg(-1) min(-1)) completed a standard incremental treadmill test for the assessment of the lactate threshold (LT) and VO2max, and eight lactate minimum tests. Following a period of supramaximal exercise, subjects were allowed 8 min of recovery to allow blood [lactate] to peak. Subjects then undertook eight randomly-assigned incremental treadmill tests from different initial running speeds (3.0, 2.5, 2.0, 1.5, 1.0, and 0.5 km x h(-1) below the predetermined RS-LT, at the RS-LT, and at 1.0 km x h(-1) above the RS-LT) with RS increased by 1.0 km x h(-1) every 5 min until volitional fatigue. Blood samples for the determination of blood [lactate] were taken at the end of each stage and the LMS was determined by fitting a spline function to the data. RESULTS No LMS could be determined for the two highest initial RS conditions. For the other conditions, the LMS was significantly affected by the initial RS used in the incremental test and varied from 13.8 +/- 0.7 km x h(-1) with an initial RS of 3.0 km x h(-1) below the RS-LT, to 15.8 +/- 0.8 km x h(-1) with an initial RS of 0.5 km x h(-1) below the RS-LT. The LMS was significantly different from the RS-LT (15.4 +/- 0.8 km x h(-1)) (P < 0.05), except when the incremental test started at 1.0 or 1.5 km x h(-1) below the RS-LT. CONCLUSIONS These results suggest that the LMS test is not a valid method for estimation of the LT since it is profoundly influenced by the starting speed selected for the incremental portion of the test.

The aim of this study was to determine whether the amplitude of the V˙O (2) slow component was dependent from Critical Power (CP; the slope of the linear time - distance relationship) in individuals matched for V˙O (2) peak. 30 moderately-trained endurance athletes completed a maximal graded exercise test, 2 randomly ordered constant power tests at 90 and 100% of peak power output (PPO), and 2 constant duration test of 6 min at 30% of the difference between CP and PPO. Afterwards, participants were ranked according to their relative CP (%PPO; a direct measure of aerobic endurance). The median third was excluded to form a low aerobic endurance group (LEG) and a high aerobic endurance group (HEG). A t-test revealed no difference between LEG and HEG in peak oxygen consumption, but a large difference in their relative CP (p

International audience; The aim of the study was to compare time spent at a high percentage of VO2max (>90% of VO2max) (ts90%), time to achieve 90% of VO2max (ta90%), and time to exhaustion (TTE) for exercise in the severe intensity domain in children and adults. Fifteen prepubertal boys (10.3 ± 0.9 years) and 15 men (23.5 ± 3.6 years) performed a maximal graded exercise to determine VO2max, maximal aerobic power (MAP) and power at ventilatory threshold (PVTh). Then, they performed 4 constant load exercises in a random order at PVTh plus 50 and 75% of the difference between MAP and PVTh (PΔ50 and PΔ75) and 100 and 110% of MAP (P100 and P110). VO2max was continuously monitored. The P110 test was used to determine maximal accumulated oxygen deficit (MAOD). No significant difference was found in ta90% between children and adults. ts90% and TTE were not significantly different between children and adults for the exercises at PΔ50 and PΔ75. However, ts90% and TTE during P100 (p < 0.05 and p < 0.01, respectively) and P110 (p < 0.001) exercises were significantly shorter in children. Children had a significantly lower MAOD than adults (34.3 ± 9.4 ml · kg vs. 53.6 ± 11.1 ml · kg). A positive relationship (p < 0.05) was obtained between MAOD and TTE values during the P100 test in children. This study showed that only for intensities at, or higher than MAP, lower ts90% in children was linked to a reduced TTE, compared to adults. Shorter TTE in children can partly be explained by a lower anaerobic capacity (MAOD). These results give precious information about exercise intensity ranges that could be used in children's training sessions. Moreover, they highlight the implication of both aerobic and anaerobic processes in endurance performances in both populations.

It has been reported that performance in cycling time-trials is enhanced when power is varied in response to gradient although such a mechanical pacing strategy has never been confirmed experimentally in the field. The aim of this study was, therefore, to assess the efficacy of mechanical pacing by comparing a constant power strategy of 255 W with a variable power strategy that averaged to 255 W over an undulating time-trial course. 20 experienced cyclists completed 4 trials over a 4 km course with 2 trials at an average constant power of 253 W and 2 trials where power was varied in response to gradient and averaged 260 W. Time normalised to 255 W was 411±31.1 s for the constant power output trials and 399±29.5 s for the variable power output trials. The variable power output strategy therefore reduced completion time by 12±8 s (2.9%) which was significant ( P

The aim of this study was to compare maximal accumulated oxygen deficit (hereafter O2 deficit) estimated from the methods of Whipp et al. (1986), Medbo et al. (1988), and Hill et al. (1998) to determine whether they agree sufficiently to be used interchangeably. Nineteen moderately to highly trained endurance runners first performed an incremental test to exhaustion for the determination of maximal oxygen uptake ([Vdot]O(2max)) and peak treadmill speed, followed by six randomly ordered constant-speed tests at 95, 100, 105, 110, 110, and 120% of peak treadmill speed. All tests were separated by at least 72 h and were performed within 4 weeks. The method of Whipp produced an O(2) deficit estimate that was lower than that derived from the method of Hill or Medbo (bias +/- 95% limits of agreement: -29.6 +/- 36.6 and -26.1 +/- 32.8 ml . kg(-1), respectively; P0.001). The O2 deficit did not differ between the methods of Hill and Medbo (bias +/- 95% limits of agreement: 3.5 +/- 41.6 ml . kg(-1); n.s.). However, poor correlations (0.21r0.33; n.s.) together with wide limits of agreement between O2 deficit estimates (70 - 80% of the mean response) clearly question using these methods interchangeably.

The present study examined the use of the maximal lactate steady state (MLSS) as an exercise training stimulus in moderately trained runners. Fourteen healthy individuals (12 male, 2 female; age 25 +/- 6 years, height 1.76 +/- 0.05 m, body mass 76 +/- 8 kg mean +/- SD) took part in the study. Following determination of the lactate threshold (LT), VO2max, running velocity at MLSS (vMLSS) and a control period of 4 weeks, participants were pair matched and split into two cohorts performing either continuous (CONT: 2 sessions/week at vMLSS) or intermittent treadmill running (INT: 2 sessions/week, 3-min repetitions 0.5 km . h (-1) above and below vMLSS). vMLSS increased in CONT by 8 % from 12.3 +/- 1.5 to 13.4 +/- 1.6 km . h (-1) (p < 0.05) and in INT by 5 % from 12.2 +/- 1.9 km . h (-1) to 12.9 +/- 1.9 km . h (-1) (p < 0.05). Running speed at the LT increased by 7 % in the CONT group (p < 0.05) and by 9 % in the INT group (p < 0.05). VO2max increased by 10 % in the CONT group (p < 0.05) and by 6 % in INT (p < 0.05). Two sessions per week at vMLSS are capable of eliciting improvements in the physiological responses at LT, MLSS, and VO2max in moderately trained runners.

To test the hypothesis that muscle fiber recruitment patterns influence the oxygen uptake (VO2) kinetic response, constant-load exercise was performed after glycogen depletion of specific fiber pools.After validation of protocols for the selective depletion of Type I and II muscle fibers, 19 subjects performed square-wave exercise at 80% VT (moderate) and at 50% of the difference between VT and VO2max (heavy) without any prior depleting exercise (CON), after HIGH (10 x 1-min exercise bouts at 120% VO2max), and after LOW (3 h of exercise at 30% VO2max) exercise.Differences in VO2 kinetic parameters were only observed in heavy exercise AFTER HIGH: the VO2 primary component was higher (1.75 +/- 0.12 L x min) compared with CON (1.65 +/- 0.11 L x min, P0.05), and the VO2 slow component was lower (0.18 +/- 0.03 L x min) compared with CON (0.24 +/- 0.04 L x min, P0.05).The results indicate that the VO2 response to heavy constant-load exercise can be altered by depletion of glycogen in the Type II muscle fibers, lending support to the theory that muscle fiber recruitment influences both the VO2 primary and slow component amplitudes during heavy intensity exercise.

The aim of this study was to examine the variability of the oxygen uptake (VO2) kinetic response during moderate- and high-intensity treadmill exercise within the same day (at 06:00, 12:00 and 18:00 h) and across days (on five occasions). Nine participants (age 25 +/- 8 years, mass 70.2 +/- 4.7 kg, VO2max 4137 +/- 697 ml x min(-1); mean +/- s) took part in the study. Six of the participants performed replicate 'square-wave' rest-to-exercise transitions of 6 min duration at running speeds calculated to require 80% VO2 at the ventilatory threshold (moderate-intensity exercise) and 50% of the difference between VO2 at the ventilatory threshold and VO2max (50% delta; high-intensity exercise) on 5 different days. Although the amplitudes of the VO2 response were relatively constant (coefficient of variation approximately 6%) from day to day, the time-based parameters were more variable (coefficient of variation approximately 15 to 30%). All nine participants performed replicate square-waves for each time of day. There was no diurnal effect on the time-based parameters of VO2 kinetics during either moderate- or high-intensity exercise. However, for high-intensity exercise, the amplitude of the primary component was significantly lower during the 12:00 h trial (2859 +/- 142 ml x min(-1) vs 2955 +/- 135 ml x min(-1) at 06:00 h and 2937 +/- 137 ml x min(-1) at 18:00 h; P0.05), but this effect was eliminated when expressed relative to body mass. The results of this study indicate that the amplitudes of the VO2 kinetic responses to moderate- and high-intensity treadmill exercise are similar within and across test days. The time-based parameters, however, are more variable from day to day and multiple transitions are, therefore, recommended to increase confidence in the data.

The aim of this study was to examine the effect of increasing the ratio of concentric to eccentric muscle activation on oxygen uptake (VO(2)) kinetics during treadmill running. Nine subjects [2 women; mean (SD) age 29 (7) years, height 1.77 (0.07) m, body mass 73.0 (7.5) kg] completed incremental treadmill tests to exhaustion at 0% and 10% gradients to establish the gradient-specific ventilatory threshold (VT) and maximal oxygen uptake (VO(2max)). Subsequently, the subjects performed repeated moderate intensity (80% of gradient-specific VT) and heavy intensity (50% of the difference between the gradient specific VT and VO(2max)) square-wave runs with the treadmill gradient set at 0% and 10%. For moderate intensity exercise, there were no significant differences between treadmill gradients for VO(2) kinetics. For heavy intensity exercise, the amplitude of the primary component of VO(2) was not significantly different between 0% and 10% treadmill gradients [mean (SEM) 2,940 (196) compared to 2,869 (156) ml x min(-1), respectively], but the amplitude of the VO(2) slow component was significantly greater at the 10% gradient [283 (43) compared to 397 (37) ml x min(-1); P < 0.05]. These results indicate that the muscle contraction regimen (i.e. the relative contribution of concentric and eccentric muscle action) significantly influences the amplitude of the VO(2) slow component.

The purpose of the present study was to examine comprehensively the kinetics of oxygen uptake ( % MathType!MTEF!2!1!+- % feaaeaart1ev0aqatCvAUfKttLearuavP1wzZbqedmvETj2BSbWexL % MBbXgBcf2CPn2qVrwzqf2zLnharyWqVvNCPvMCG4uz3bqee0evGueE % 0jxyaibaieYlf9irVeeu0dXdh9vqqj-hEeeu0xXdbba9frFj0-OqFf % ea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs0dXdbPYxe9vr0-vr % 0-vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaiqbdAfawzaaca % Gaee4ta80aaSbaaSqaaiabbkdaYaqabaaaaa!386A! $$\dot V{\rm O}_{\rm 2} $$ ) during treadmill running across the moderate, heavy and severe exercise intensity domains. Nine subjects [mean (SD age, 27 (7) years; mass, 69.8 (9.0) kg; maximum % MathType!MTEF!2!1!+- % feaaeaart1ev0aqatCvAUfKttLearuavP1wzZbqedmvETj2BSbWexL % MBbXgBcf2CPn2qVrwzqf2zLnharyWqVvNCPvMCG4uz3bqee0evGueE % 0jxyaibaieYlf9irVeeu0dXdh9vqqj-hEeeu0xXdbba9frFj0-OqFf % ea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs0dXdbPYxe9vr0-vr % 0-vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaiqbdAfawzaaca % Gaee4ta80aaSbaaSqaaiabbkdaYaqabaaaaa!386A! $$\dot V{\rm O}_{\rm 2} $$ , % MathType!MTEF!2!1!+- % feaaeaart1ev0aqatCvAUfKttLearuavP1wzZbqedmvETj2BSbWexL % MBbXgBcf2CPn2qVrwzqf2zLnharyWqVvNCPvMCG4uz3bqee0evGueE % 0jxyaibaieYlf9irVeeu0dXdh9vqqj-hEeeu0xXdbba9frFj0-OqFf % ea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs0dXdbPYxe9vr0-vr % 0-vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaiqbdAfawzaaca % Gaee4ta80aaSbaaSqaaiabbkdaYiabb2gaTjabbggaHjabbIha4bqa % baaaaa!3C8B! $$\dot V{\rm O}_{{\rm 2max}} $$ , 4,137 (697) ml·min–1] performed a series of "square-wave" rest-to-exercise transitions of 6 min duration at running speeds equivalent to 80% and 100% of the % MathType!MTEF!2!1!+- % feaaeaart1ev0aqatCvAUfKttLearuavP1wzZbqedmvETj2BSbWexL % MBbXgBcf2CPn2qVrwzqf2zLnharyWqVvNCPvMCG4uz3bqee0evGueE % 0jxyaibaieYlf9irVeeu0dXdh9vqqj-hEeeu0xXdbba9frFj0-OqFf % ea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs0dXdbPYxe9vr0-vr % 0-vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaiqbdAfawzaaca % Gaee4ta80aaSbaaSqaaiabbkdaYaqabaaaaa!386A! $$\dot V{\rm O}_{\rm 2} $$ at lactate threshold (LT; moderate exercise); and at 20%, 40%, 60%, 80% and 100% of the difference between the % MathType!MTEF!2!1!+- % feaaeaart1ev0aqatCvAUfKttLearuavP1wzZbqedmvETj2BSbWexL % MBbXgBcf2CPn2qVrwzqf2zLnharyWqVvNCPvMCG4uz3bqee0evGueE % 0jxyaibaieYlf9irVeeu0dXdh9vqqj-hEeeu0xXdbba9frFj0-OqFf % ea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs0dXdbPYxe9vr0-vr % 0-vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaiqbdAfawzaaca % Gaee4ta80aaSbaaSqaaiabbkdaYaqabaaaaa!386A! $$\dot V{\rm O}_{\rm 2} $$ at LT and % MathType!MTEF!2!1!+- % feaaeaart1ev0aqatCvAUfKttLearuavP1wzZbqedmvETj2BSbWexL % MBbXgBcf2CPn2qVrwzqf2zLnharyWqVvNCPvMCG4uz3bqee0evGueE % 0jxyaibaieYlf9irVeeu0dXdh9vqqj-hEeeu0xXdbba9frFj0-OqFf % ea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs0dXdbPYxe9vr0-vr % 0-vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaiqbdAfawzaaca % Gaee4ta80aaSbaaSqaaiabbkdaYiabb2gaTjabbggaHjabbIha4bqa % baaaaa!3C8B! $$\dot V{\rm O}_{{\rm 2max}} $$ (Δ, heavy and severe exercise). Critical velocity (CV) was also determined using four maximal treadmill runs designed to result in exhaustion in 2–15 min. The % MathType!MTEF!2!1!+- % feaaeaart1ev0aqatCvAUfKttLearuavP1wzZbqedmvETj2BSbWexL % MBbXgBcf2CPn2qVrwzqf2zLnharyWqVvNCPvMCG4uz3bqee0evGueE % 0jxyaibaieYlf9irVeeu0dXdh9vqqj-hEeeu0xXdbba9frFj0-OqFf % ea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs0dXdbPYxe9vr0-vr % 0-vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaiqbdAfawzaaca % Gaee4ta80aaSbaaSqaaiabbkdaYaqabaaaaa!386A! $$\dot V{\rm O}_{\rm 2} $$ response was modelled using non-linear regression techniques. As expected, the amplitude of the % MathType!MTEF!2!1!+- % feaaeaart1ev0aqatCvAUfKttLearuavP1wzZbqedmvETj2BSbWexL % MBbXgBcf2CPn2qVrwzqf2zLnharyWqVvNCPvMCG4uz3bqee0evGueE % 0jxyaibaieYlf9irVeeu0dXdh9vqqj-hEeeu0xXdbba9frFj0-OqFf % ea0dXdd9vqaq-JfrVkFHe9pgea0dXdar-Jb9hs0dXdbPYxe9vr0-vr % 0-vqpWqaaeaabiGaciaacaqabeaadaqaaqaaaOqaaiqbdAfawzaaca % Gaee4ta80aaSbaaSqaaiabbkdaYaqabaaaaa!386A! $$\dot V{\rm O}_{\rm 2} $$ primary component increased with exercise intensity [from 1,868 (136) ml·min–1 at 80% LT to 3,296 (218) ml·min–1 at 100% Δ, P

Endurance exercise training results in profound adaptations of the cardiorespiratory and neuromuscular systems that enhance the delivery of oxygen from the atmosphere to the mitochondria and enable a tighter regulation of muscle metabolism. These adaptations effect an improvement in endurance performance that is manifest as a rightward shift in the ‘velocity-time curve’. This shift enables athletes to exercise for longer at a given absolute exercise intensity, or to exercise at a higher exercise intensity for a given duration. There are 4 key parameters of aerobic fitness that affect the nature of the velocity-time curve that can be measured in the human athlete. These are the maximal oxygen uptake (V . O2max), exercise economy, the lactate/ventilatory threshold and oxygen uptake kinetics. Other parameters that may help determine endurance performance, and that are related to the other 4 parameters, are the velocity at V . O2max(V-V . O2max )a nd the maximal lactate steady state or critical power. This review considers the effect of endurance training on the key parameters of aerobic (endurance) fitness and attempts to relate these changes to the adaptations seen in the body’s physiological systems with training. The importance of improvements in the aerobic fitness parameters to the enhancement of endurance performance is highlighted, as are the training methods that may be considered optimal for facilitating such improvements. LEADING ARTICLE

The aim of this study was to assess the responses of blood lactate and pyruvate during the lactate minimum speed test. Ten participants (5 males, 5 females; mean +/- s: age 27.1+/-6.7 years, VO2max 52.0+/-7.9 ml x kg(-1) x min(-1)) completed: (1) the lactate minimum speed test, which involved supramaximal sprint exercise to invoke a metabolic acidosis before the completion of an incremental treadmill test (this results in a 'U-shaped' blood lactate profile with the lactate minimum speed being defined as the minimum point on the curve); (2) a standard incremental exercise test without prior sprint exercise for determination of the lactate threshold; and (3) the sprint exercise followed by a passive recovery. The lactate minimum speed (12.0+/-1.4 km x h(-1)) was significantly slower than running speed at the lactate threshold (12.4+/-1.7 km x h(-1)) (P < 0.05), but there were no significant differences in VO2, heart rate or blood lactate concentration between the lactate minimum speed and running speed at the lactate threshold. During the standard incremental test, blood lactate and the lactate-to-pyruvate ratio increased above baseline values at the same time, with pyruvate increasing above baseline at a higher running speed. The rate of lactate, but not pyruvate, disappearance was increased during exercising recovery (early stages of the lactate minimum speed incremental test) compared with passive recovery. This caused the lactate-to-pyruvate ratio to fall during the early stages of the lactate minimum speed test, to reach a minimum point at a running speed that coincided with the lactate minimum speed and that was similar to the point at which the lactate-to-pyruvate ratio increased above baseline in the standard incremental test. Although these results suggest that the mechanism for blood lactate accumulation at the lactate minimum speed and the lactate threshold may be the same, disruption to normal submaximal exercise metabolism as a result of the preceding sprint exercise, including a three- to five-fold elevation of plasma pyruvate concentration, makes it difficult to interpret the blood lactate response to the lactate minimum speed test. Caution should be exercised in the use of this test for the assessment of endurance capacity.

The aim of this study was to assess the sensitivity of the lactate minimum speed test to changes in endurance fitness resulting from a 6 week training intervention. Sixteen participants (mean +/- s: age 23+/-4 years; body mass 69.7+/-9.1 kg) completed 6 weeks of endurance training. Another eight participants (age 23+/-4 years; body mass 72.7+/-12.5 kg) acted as non-training controls. Before and after the training intervention, all participants completed: (1) a standard multi-stage treadmill test for the assessment of VO2max, running speed at the lactate threshold and running speed at a reference blood lactate concentration of 3 mmol x l(-1); and (2) the lactate minimum speed test, which involved two supramaximal exercise bouts and an 8 min walking recovery period to increase blood lactate concentration before the completion of an incremental treadmill test. Additionally, a subgroup of eight participants from the training intervention completed a series of constant-speed runs for determination of running speed at the maximal lactate steady state. The test protocols were identical before and after the 6 week intervention. The control group showed no significant changes in VO2max, running speed at the lactate threshold, running speed at a blood lactate concentration of 3 mmol x l(-1) or the lactate minimum speed. In the training group, there was a significant increase in VO2max (from 47.9+/-8.4 to 52.2+/-2.7 ml x kg(-1) x min(-1)), running speed at the maximal lactate steady state (from 13.3+/-1.7 to 13.9+/-1.6 km x h(-1)), running speed at the lactate threshold (from 11.2+/-1.8 to 11.9+/-1.8 km x h(-1)) and running speed at a blood lactate concentration of 3 mmol x l(-1) (from 12.5+/-2.2 to 13.2+/-2.1 km x h(-1)) (all P0.05). Despite these clear improvements in aerobic fitness, there was no significant difference in lactate minimum speed after the training intervention (from 11.0+/-0.7 to 10.9+/-1.7 km x h(-1)). The results demonstrate that the lactate minimum speed, when assessed using the same exercise protocol before and after 6 weeks of aerobic exercise training, is not sensitive to changes in endurance capacity.

Modelling has been utilised in competitive road cycling to identify performance optimisations that would conventionally require extensive experimental testing. However, the validity of current models is limited by incomplete representation of the cycling environment and insufficient frequency of simulation. A three dimensional road cycling model has been developed that extends existing models by combining bicycle mechanics, rider biomechanics and environmental conditions into a single dynamic system. A system of rigid bodies linked by joints and driven by actuators has been built using the MATLAB toolboxes Simulink and SimMechanics. Each body is defined in respect of mass, inertia tensor, dimension and centre of gravity. The system operates in forward dynamics mode such that a simulation inputs forces to the equations of motion which are numerically integrated at