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Metabolic and neuromuscular adaptations to endurance training in professional cyclists: a longitudinal study

, : Metabolic and neuromuscular adaptations to endurance training in professional cyclists: a longitudinal study. Japanese Journal of Physiology 50(3): 381-388

The aim of this longitudinal study was to analyze the changes in several metabolic and neuromuscular variables in response to endurance training during three defined periods of a full sports season (rest, precompetition and competition). The study population was formed by thirteen professional cyclists (age +/- SEM: 24+/-1 years; mean V(O2 max) approximately 74 ml kg(-1) min(-1)). In each testing session, subjects performed a ramp test until exhaustion on a cycle ergometer (workload increases of 25 W min(-1)). The following variables were recorded every 100 W until the tests: oxygen consumption (V(O2) in l min(-1)), respiratory exchange ratio (RER in V(CO2) V(O2)(-1)) and blood lactate, pH and bicarbonate concentration [HCO3(-)]. Surface electromyography (EMG) recordings were also obtained from the vastus lateralis to determine the variables: root mean square voltage (rms-EMG) and mean power frequency (MPF). RER and lactate values both showed a decrease (p<0.05) throughout the season at exercise intensities corresponding to submaximal workloads. In contrast, no significant differences were found in mean pH or [HCO(3-)]. Finally, rms-EMG tended to increase during the season, with significant differences (p<0.05) observed mainly between the competition and rest periods at most workloads. In contrast, precompetition MPF values increased (p<0.05) with respect to resting values at most submaximal workloads but fell (p<0.05) during the competition period. Our findings suggest that endurance conditioning induces the following general adaptations in elite athletes: (1) lower circulating lactate and increased reliance on aerobic metabolism at a given submaximal intensity, and possibly (2) an enhanced recruitment of motor units in active muscles, as suggested by rms-EMG data.


PMID: 11016988

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