Human fast-twitch muscle fibers generate high power in a short amount of time but are easily fatigued, whereas slow-twitch fibers are more fatigue resistant. The transfer of this knowledge to coaching is hampered by the invasive nature of the current evaluation of muscle typology by biopsies. Therefore, a noninvasive method was developed to estimate muscle typology through proton magnetic resonance spectroscopy in the gastrocnemius. The aim of this study was to investigate whether male subjects with an a priori-determined fast typology (FT) are characterized by a more pronounced Wingate exercise-induced fatigue and delayed recovery compared with subjects with a slow typology (ST). Ten subjects with an estimated higher percentage of fast-twitch fibers and 10 subjects with an estimated higher percentage of slow-twitch fibers underwent the test protocol, consisting of three 30-s all-out Wingate tests. Recovery of knee extension torque was evaluated by maximal voluntary contraction combined with electrical stimulation up to 5 h after the Wingate tests. Although both groups delivered the same mean power across all Wingates, the power drop was higher in the FT group (−61%) compared with the ST group (−41%). The torque at maximal voluntary contraction had fully recovered in the ST group after 20 min, whereas the FT group had not yet recovered 5 h into recovery. This noninvasive estimation of muscle typology can predict the extent of fatigue and time to recover following repeated all-out exercise and may have applications as a tool to individualize training and recovery cycles. NEW & NOTEWORTHY A one-fits-all training regime is present in most sports, though the same training implies different stimuli in athletes with a distinct muscle typology. Individualization of training based on this muscle typology might be important to optimize performance and to lower the risk for accumulated fatigue and potentially injury. When conducting research, one should keep in mind that the muscle typology of participants influences the severity of fatigue and might therefore impact the results.
Purpose: The aims of this study were 1) to model the temporal profile of W′ recovery after exhaustion, 2) to estimate the contribution of changing V ˙O2 kinetics to this recovery, and 3) to examine associations with aerobic fitness and muscle fiber type (MFT) distribution. Methods: Twenty-one men (age = 25 ± 2 yr, V ˙O2peak = 54.4 ± 5.3 mL•min −1 •kg −1 ) performed several constant load tests to determine critical power and W′ followed by eight trials to quantify W′ recovery. Each test consisted of two identical exhaustive work bouts (WB1 and WB2), separated by a variable recovery interval of 30, 60, 120, 180, 240, 300, 600, or 900 s. Gas exchange was measured and muscle biopsies were collected to determine MFT distribution. W′ recovery was quantified as observed W′ recovery (W′ OBS ), model-predicted W′ recovery (W′ BAL ), and W′ recovery corrected for changing V ˙O2 kinetics (W′ ADJ ). W′ OBS and W′ ADJ were modeled using mono-and biexponential fitting. Root-mean-square error (RMSE) and Akaike information criterion (ΔAIC C ) were used to evaluate the models' accuracy. Results: The W′ BAL model (τ = 524 ± 41 s) was associated with an RMSE of 18.6% in fitting W′ OBS and underestimated W′ recovery for all durations below 5 min (P < 0.002). Monoexponential modeling of W′ OBS resulted in τ = 104 s with RMSE = 6.4%. Biexponential modeling of W′ OBS resulted in τ 1 = 11 s and τ 2 = 256 s with RMSE = 1.7%. W′ ADJ was 11% ± 1.5% lower than W′ OBS (P < 0.001). ΔAIC C scores favored the biexponential model for W′ OBS , but not for W′ ADJ . V ˙O2peak (P = 0.009) but not MFT distribution (P = 0.303) was associated with W′ OBS . Conclusion: We showed that W′ recovery from exhaustion follows a two-phase exponential time course that is dependent on aerobic fitness. The appearance of a fast initial recovery phase was attributed to an enhanced aerobic energy provision resulting from changes in V ˙O2 kinetics.
Purpose: The present study identified the physiological and performance characteristics that are deterministic during a maximal 1500-m time trial and in paced 1500-m time trials, with an all-out last lap. Methods: Thirtytwo trained middle-distance runners (n=21 male, VO2peak: 72.1±3.2; n=11, female, VO2peak: 61.2±3.7 mL•kg -1 •min -1 ) completed a 1500-m time trial in the fastest time possible (1500FAST) as well as a 1500MOD and 1500SLOW trial whereby mean speed was reduced during the 0-1100-m by 5% and 10%, respectively. Anaerobic speed reserve (ASR), running economy (RE), the velocity corresponding with VO2peak (VVO2peak), maximal sprint speed (MSS) and maximal accumulated oxygen deficit (MAOD) were determined during additional testing. Carnosine content was quantified by proton magnetic resonance spectroscopy in the gastrocnemius and expressed as a Zscore to estimate muscle fibre typology. Results: 1500FAST time was best explained by RE and VVO2peak in female runners (adjusted r 2 =0.80, P<0.001), in addition to the 0-1100-m speed relative to VVO2peak in male runners (adjusted r 2 =0.72, P<0.001). Runners with a higher gastrocnemius carnosine Z-score (i.e., higher estimated percentage of type II fibres) and greater MAOD, reduced their last lap time to a greater extent in the paced 1500m trials. Neither ASR nor MSS were associated with last lap time in the paced trials. Conclusion: These findings suggest that VVO2 peak and RE are key determinants of 1500-m running performance with a sustained pace from the start, while a higher carnosine Z-score and MAOD are more important for last lap speed in tactical 1500-m races.
The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.
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