Which laboratory variable is related with time trial performance time in the Tour de France?

Measuring submaximal performance parameters to monitor fatigue and predict cycling performance: a case study of a world-class cyclo-cross cyclist

Recently a novel submaximal test, known as the Lamberts and Lambert submaximal cycle test (LSCT), has been developed with the purpose of monitoring and predicting changes in cycling performance. Although this test has been shown to be reliable and able to predict cycling performance, it is not known whether it can measure changes in training status. Therefore, the aim of this study was to determine whether the LSCT is able to track changes in performance parameters, and objective and subjective markers of well-being. A world class cyclo-cross athlete (31 years) volunteered to participate in a 10-week observational study. Before and after the study, a peak power output (PPO) test with respiratory gas analysis (VO(2max)) and a 40-km time trial (40-km TT) test were performed. Training data were recorded in a training logbook with a daily assessment of well-being, while a weekly LSCT was performed. After the training period all performance parameters had improved by a meaningful amount (PPO +5.2%; 40-km TT time -2.5%; VO(2max) +1.4%). Increased training loads during weeks 2 and 6 and the subsequent training-induced fatigue was reflected in the increased well-being scores. Changes during the LSCT were most clearly notable in (1) increased power during the first minute of third stage, (2) increased rating of perceived exertion during second and third stages, and (3) a faster heart rate recovery after the third stage. In conclusion, these data suggest that the LSCT is able to track changes in training status and detect the consequences of sharp increases in training loads which seem to be associated with accumulating fatigue.

Practical application of fundamental concepts in exercise physiology

The collection of primary data in laboratory classes enhances undergraduate practical and critical thinking skills. The present article describes the use of a lecture program, running in parallel with a series of linked practical classes, that emphasizes classical or standard concepts in exercise physiology. The academic and practical program ran under the title of a particular year II module named Sports Performance: Physiology and Assessment, and results are presented over a 3-yr period (2004-2006), based on an undergraduate population of 31 men and 34 women. The module compared laboratory-based indexes of endurance (e.g., ventilatory threshold and exercise economy) and high-intensity exercise (e.g., anaerobic power), respectively, with measures of human performance (based on 20-m shuttle run tests). The specific experimental protocols reinforced the lecture content to improve student understanding of the physiological and metabolic responses (and later adaptations) to exercise. In the present study, the strongest relationship with endurance performance was the treadmill velocity at maximal aerobic power (r = +0.88, P < 0.01, n = 51); in contrast, the strongest relationship with high-intensity exercise performance was the mean power output (in W/kg) measured during a 30-s all-out cycle ergometer sprint (r = +0.80, P < 0.01, n = 48). In class student data analysis improved undergraduate indepth or critical thinking during seminars and enhanced computer and data presentation skills. The endurance-based laboratories are particularly useful for examining the underlying scientific principles that determine aerobic performance but could equally well be adapted to investigate other topics, e.g., differences in the exercise response between men and women.

Strength training reduces freely chosen pedal rate during submaximal cycling

The freely chosen pedal rate is relatively high and energetically inefficient during submaximal cycling, which is a paradox since the rate of energy expenditure is considered important for voluntary motor behavior in other cyclical activities as, e.g., running. For example, it has been suggested that subjects pedal fast to reduce the perception of force. In this study, we investigated the hypothesis that strength training would cause subjects to pedal at a slower rate during low to moderate submaximal cycling. Fourteen healthy subjects performed supervised heavy (2-12 RM) strength training 4 days/week for 12 weeks, including 2 days/week with leg-extensor and knee-flexor exercises. Seven healthy subjects formed the control group. The training group increased strength (one repetition maximum, 1 RM) in both squat [20%(3), mean (SEM)] and leg curl [12%(1)] exercises from the beginning to the end of the study period (p<0.01). At the same time, freely chosen pedal rate was reduced by 8 (2) and 10 (2) rpm, respectively, during cycling at 37 and 57% of maximal power output (Wmax) (p<0.01). In addition, rate of energy expenditure is 3% (2) lower at 37% of Wmax (p<0.05) and tended to be lower at 57% Wmax (p=0.07) at the end of the study. Values for strength, freely chosen pedal rate, and rate of energy expenditure, were unchanged for the control group from the beginning to the end of the study. In conclusion, strength training caused subjects to choose an approximately 9 rpm lower pedal rate during submaximal cycling. This was accompanied by a approximately 3% lower rate of energy expenditure.

Distribution of Power Output During Cycling

We aim to summarise the impact and mechanisms of work-rate pacing during individual cycling time trials (TTs). Unlike time-to-exhaustion tests, a TT provides an externally valid model for examining how an initial work rate is chosen and maintained by an athlete during self-selected exercise. The selection and distribution of work rate is one of many factors that influence cycling speed. Mathematical models are available to predict the impact of factors such as gradient and wind velocity on cycling speed, but only a few researchers have examined the inter-relationships between these factors and work-rate distribution within a TT. When environmental conditions are relatively stable (e.g. in a velodrome) and the TT is >10 minutes, then an even distribution of work rate is optimal. For a shorter TT (< or = 10 minutes), work rate should be increased during the starting effort because this proportion of total race time is significant. For a very short TT (< or = 2 minutes), the starting effort should be maximal, since the time saved during the starting phase is predicted to outweigh any time lost during the final metres because of fatigue. A similar 'time saving' rationale underpins the advice that work rate should vary in parallel with any changes in gradient or wind speed during a road TT. Increasing work rate in headwind and uphill sections, and vice versa, decreases the variability in speed and, therefore, the total race time. It seems that even experienced cyclists naturally select a supraoptimal work rate at the start of a longer TT. Whether such a start can be 'blunted' through coaching or the monitoring of psychophysiological variables is unknown. Similarly, the extent to which cyclists can vary and monitor work rate during a TT is unclear. There is evidence that sub-elite cyclists can vary work rate by +/-5% the average for a TT lasting 25-60 minutes, but such variability might be difficult with high-performance cyclists whose average work rate during a TT is already extremely high (>350 watts). During a TT, pacing strategy is regulated in a complex anticipatory system that monitors afferent feedback from various physiological systems, and then regulates the work rate so that potentially limiting changes do not occur before the endpoint of exercise is reached. It is critical that the endpoint of exercise is known by the cyclist so that adjustments to exercise work rate can be made within the context of an estimated finish time. Pacing strategies are thus the consequence of complex regulation and serve a dual role: they are both the result of homeostatic regulation by the brain, as well as being the means by which such regulation is achieved. The pacing strategy 'algorithm' is sited in the brain and would need afferent input from interoceptors, such as heart rate and respiratory rate, as well as exteroceptors providing information on local environmental conditions. Such inputs have been shown to induce activity in the thalamus, hypothalamus and the parietal somatosensory cortex. Knowledge of time, modulated by the cerebellum, basal ganglia and primary somatosensory cortex, would also input to the pacing algorithm as would information stored in memory about previous similar exercise bouts. How all this information is assimilated by the different regions of the brain is not known at present.

Changes in Ventilatory Threshold at High Altitude

PURPOSE

To investigate the effects of prolonged hypoxia and antioxidant supplementation on ventilatory threshold (VT) during high-altitude (HA) exposure (4300 m).

METHODS

Sixteen physically fit males (25 +/- 5 yr; 77.8 +/- 8.5 kg) performed an incremental test to maximal exertion on a cycle ergometer at sea level (SL). Subjects were then matched on VO2peak, ventilatory chemosensitivity, and body mass and assigned to either a placebo (PL) or antioxidant (AO) supplement group in a randomized, double-blind manner. PL or AO (12 mg of beta-carotene, 180 mg of alpha-tocopherol acetate, 500 mg of ascorbic acid, 100 mug of selenium, and 30 mg of zinc daily) were taken 21 d prior to and for 14 d at HA. During HA, subjects participated in an exercise program designed to achieve an energy deficit of approximately 1400 kcal.d(-1). VT was reassessed on the second and ninth days at HA (HA2, HA9).

RESULTS

Peak power output (Wpeak) and VO2peak decreased (28%) in both groups upon acute altitude exposure (HA2) and were unchanged with acclimatization and exercise (HA9). Power output at VT (WVT) decreased from SL to HA2 by 41% in PL, but only 32% in AO (P < 0.05). WVT increased in PL only during acclimatization (P < 0.05) and matched AO at HA9. Similar results were found when VT was expressed in terms of % Wpeak and % VO2peak.

CONCLUSIONS

VT decreases upon acute HA exposure but improves with acclimatization. Prior AO supplementation improves VT upon acute, but not chronic altitude exposure.

Optimal power-to-mass ratios when predicting flat and hill-climbing time-trial cycling

The purpose of this article was to establish whether previously reported oxygen-to-mass ratios, used to predict flat and hill-climbing cycling performance, extend to similar power-to-mass ratios incorporating other, often quick and convenient measures of power output recorded in the laboratory [maximum aerobic power (W(MAP)), power output at ventilatory threshold (W(VT)) and average power output (W(AVG)) maintained during a 1 h performance test]. A proportional allometric model was used to predict the optimal power-to-mass ratios associated with cycling speeds during flat and hill-climbing cycling. The optimal models predicting flat time-trial cycling speeds were found to be (W(MAP)m(-0.48))(0.54), (W(VT)m(-0.48))(0.46) and (W(AVG)m(-0.34))(0.58) that explained 69.3, 59.1 and 96.3% of the variance in cycling speeds, respectively. Cross-validation results suggest that, in conjunction with body mass, W(MAP) can provide an accurate and independent prediction of time-trial cycling, explaining 94.6% of the variance in cycling speeds with the standard deviation about the regression line, s=0.686 km h(-1). Based on these models, there is evidence to support that previously reported VO2-to-mass ratios associated with flat cycling speed extend to other laboratory-recorded measures of power output (i.e. Wm(-0.32)). However, the power-function exponents (0.54, 0.46 and 0.58) would appear to conflict with the assumption that the cyclists' speeds should be proportional to the cube root (0.33) of power demand/expended, a finding that could be explained by other confounding variables such as bicycle geometry, tractional resistance and/or the presence of a tailwind. The models predicting 6 and 12% hill-climbing cycling speeds were found to be proportional to (W(MAP)m(-0.91))(0.66), revealing a mass exponent, 0.91, that also supports previous research.

Correlations between physiological variables and performance in high level cross country off road cyclists

OBJECTIVES

To examine the relations between maximal and submaximal indices of aerobic fitness and off road cycling performance in a homogeneous group of high level mountain bikers.

METHODS

12 internationally competitive mountain bikers completed the study. Maximum oxygen uptake (Vo(2max)), peak power output (PPO), power output (PO), and oxygen uptake (Vo(2)) at first (VT) and second (RCT) ventilatory thresholds were measured in the laboratory, and correlated with race time during a cross country circuit race.

RESULTS

The only physiological indices of aerobic fitness correlated with off road cycling performance were PO and Vo(2) at RCT when normalised to body mass (r = -0.63 and r = -0.66, respectively; p<0.05). VT, Vo(2max), and PPO were not correlated to performance in this homogeneous group of high level mountain bikers.

CONCLUSIONS

The results of this study suggest that submaximal indices of aerobic fitness such as PO and Vo(2) at RCT are more important determinants of off road cycling performance than maximal indices such as PPO and Vo(2max). This study confirms the importance of body mass for mountain biking performance. As aerobic fitness explained only 40% of the variance, other physiological and technical factors should be investigated, as they may be important determinants of cross country performance among elite mountain bikers.

PPARGC1A genotype (Gly482Ser) predicts exceptional endurance capacity in European men

Animal and human data indicate a role for the peroxisome proliferator-activated receptor-gamma coactivator 1alpha (PPARGC1A) gene product in the development of maximal oxygen uptake (V(O2 max)), a determinant of endurance capacity, diabetes, and early death. We tested the hypothesis that the frequency of the minor Ser482 allele at the PPARGC1A locus is lower in World-class Spanish male endurance athletes (cases) [n = 104; mean (SD) age: 26.8 (3.8) yr] than in unfit United Kingdom (UK) Caucasian male controls [n = 100; mean (SD) age: 49.3 (8.1) yr]. In cases and controls, the Gly482Ser genotype met Hardy-Weinberg expectations (P > 0.05 in both groups tested separately). Cases had significantly higher V(O2 max) [73.4 (5.7) vs. 29.4 ml x kg(-1) x min(-1) (3.8); P < 0.0001] and were leaner [body mass index: 20.6 (1.5) vs. 27.6 kg/m2 (3.9); P < 0.0001] than controls. In unadjusted chi2 analyses, the frequency of the minor Ser482 allele was significantly lower in cases than in controls (29.1 vs. 40.0%; P = 0.01). To assess the possibility that genetic stratification could confound these observations, we also compared Gly482Ser genotype frequencies in Spanish (n = 164) and UK Caucasian men (n = 381) who were unselected for their level of fitness. In these analyses, Ser482 allele frequencies were very similar (36.9% in Spanish vs. 37.5% in UK Caucasians, P = 0.83), suggesting that confounding by genetic stratification is unlikely to explain the association between Gly482Ser genotype and endurance capacity. In summary, our data indicate a role for the Gly482Ser genotype in determining aerobic fitness. This finding has relevance from the perspective of physical performance, but it may also be informative for the targeted prevention of diseases associated with low fitness such as Type 2 diabetes.