Discrimination between cross-country and downhill skiers by pulmonary and local³¹pnmr evaluations

The purpose of the present study was to correlate data on calf muscle metabolism using³¹P nuclear magnetic resonance spectroscopy with measurements of whole body maximal oxygen consumption and maximal power output, and to determine whether the combination of these data could be used to predict athletic ability. Experiments were performed in a 2.35 Tesla, 35 cm diameter electromagnet on the leg muscle of sedentary human subjects (N = 6) and groups of athletes trained for endurance (cross-country skiers, N=7) or strength performance (downhill skiers, N = 5). The exercise protocol consisted of successive plantar flexions performed at graded fractions of the maximal voluntary contraction (MVC). The results obtained from NMR investigation (changes in content of inorganic phosphate: Pi, phosphocreatine: PC and muscle ATP, and intracel-luIar pH) were then compared with those of maximal O₂ consumption (VO_2max) and maximal power (MP). When the data on athletes were compared with those obtained on sedentary subjects, the curves illustrating the relationship between the imposed load and the Pi/PC ratio were significantly shifted toward high output power for a given Pi/PC value. It also appeared from this study that specific training in force development (downhill skiing) induced a slighter decrease in PC level than for endurance (cross-country skiers) despite improvement in physical performance. A slight but significant intracellular acidification was observed in the muscles of sedentary subjects and downhill skiers for contraction at, respectively, 50% and 80% of MVC, but not in the skeletal muscles of cross-country skiers. The comparison of the NMR results with those given by VO_2max and MP revealed that the energetic response of muscle to exercise was not always closely related to the global capacity for endurance or for short and intense effort. However, the breakdown of the population into specific training groups using principal components analysis showed that global and local parameters could be combined to discriminate.