A second rest period of 40 min was enforced followed by the intervention and performance tests. The change in Tm elicited during cycling was matched in the hot bath and WBV interventions. Therefore cycling was performed first, proceeded by, in a random order of hot bath and acute WBV. The rate of Tm was significantly greater (P < 0.001) during acute WBV (0.30 degree C min(-1)) compared to cycle (0.15 degree C min(-1)) and hot bath (0.09 degree C min(-1)) however there was no difference between the cycle and hot bath, and the metabolic rate was the same in cycling and WBV (19 mL kg(-1) min(-1)). All three interventions showed a significant (P < 0.001) increase in countermovement jump peak power and height. For the 5 s maximal cycle test (MIC) there were no significant differences in peak power between the three interventions. In conclusion, acute WBV elevates Tm more quickly than traditional forms of cycling and passive warm-up. Given that all three warm-up methods yielded the same increase in peak power output, we propose that the main effect is caused by the increase in Tm
58-0.96). The variability in Ratio(1:2) was primarily due to differences between people in one-leg V(O2peak) (r = 0.71, P < 0.0005) and was not related to two-leg V(O2max) (r = 0.15, P = 0.209). Magnetic resonance imaging (n = 30) and muscle biopsy sampling (n = 20) revealed that one-leg V(O2peak) was mainly determined by muscle volume (r = 0.73, P < 0.0005) rather than muscle fibre type or oxidative capacity. A high one-leg V(O2peak) was associated with favourable lipoprotein profiles (P = 0.033, n = 24) but this was not the case for two-leg V(O2max). Calculations based on these data suggest that conventional two-leg exercise at 70% V(O2max) requires subjects with the lowest Ratio(1:2) to work their legs at 60% of single-leg V(O2peak), whilst those with the highest Ratio(1:2) work their legs at only 36% of maximum. It was concluded that endurance training carried out according to current guidelines will result in highly variable training stimuli for the leg muscles and variable magnitudes of adaptation. These conclusions have implications for the prescription of exercise to improve health and for investigations into the genetic basis of muscle adaptations
Both groups showed improvement but there were no significant differences between the groups. In neither trial was there any correlation between the extent of change in the subjects’ physical fitness due to aerobic exercise and the extent of the improvement of psychiatric scores
Bone scans were obtained by peripheral Quantitative Computed Tomography (pQCT) from the tibia and from the radius in 106 sprinters, 52 middle distance runners, 93 long distance runners and 49 race-walkers who were competing at master championships, and who were aged between 35 and 94 years. Seventy-five age-matched, sedentary people served as control group. Most athletes of this study had started to practice their athletic discipline after the age of 20, but the current training regime had typically been maintained for more than a decade. As hypothesised, tibia diaphyseal bone mineral content (vBMC), cortical area and polar moment of resistance were largest in sprinters, followed in descending order by middle and long distance runners, race-walkers and controls. When compared to control people, the differences in these measures were always >13% in male and >23% in female sprinters (p<0.001). Similarly, the periosteal circumference in the tibia shaft was larger in male and female sprinters by 4% and 8%, respectively, compared to controls (p<0.001). Epiphyseal group differences were predominantly found for trabecular vBMC in both male and female sprinters, who had 15% and 18% larger values, respectively, than controls (p<0.001). In contrast, a reverse pattern was found for cortical vBMD in the tibia, and only few group differences of lower magnitude were found between athletes and control people for the radius. In conclusion, tibial bone strength indicators seemed to be related to exercise-specific peak forces, whilst cortical density was inversely related to running distance. These results may be explained in two, non-exclusive ways. Firstly, greater skeletal size may allow larger muscle forces and power to be exerted, and thus bias towards engagement in athletics. Secondly, musculoskeletal forces related to running can induce skeletal adaptation and thus enhance bone strength
Force-velocity relationships were determined from isotonic contractions of maximally activated fibres at 15 degrees C. Mean (+/- s.d.) peak powers were 1.99 +/- 0.72 watts per litre (W L(-1)) for type I fibres and 6.92 +/- 2.41 W L(-1), for type IIA fibres. The most notable feature, however, was the very large, sevenfold, range of power outputs within a single fibre type. This wide range was a consequence of variations in each of the three components determining power: P(0), V(max) and a/P(0). Within a single fibre type, P(0) varied threefold, and V(max) and a/P(0) two- to threefold. There were no obvious relationships between P(0) and V(max) or between P(0) and a/P(0). However, there was a suggestion of an inverse relationship between a/P(0) and V(max), the effect being to reduce, somewhat, the impact of differences in V(max) on peak power. In searching for the causes of variation in peak power of fibres of the same type, it appears likely that there are two factors, one that affects P(0) and another that leads to variation in both V(max) and a/P(0).
There is no ideal preparation; rather the question to be answered will determine the most appropriate model in each case and sometimes a combination of approaches will be needed. In particular, it is important to understand how the mechanical output of whole muscle can be sustained to meet the demands of a task and to take into account the organized variability of the constituent motor units.