Identifying physiological determinants of 800 m running performance using post-exercise blood lactate kinetics.

PURPOSE: The aims of the present study were to investigate blood lactate kinetics following high intensity exercise and identify the physiological determinants of 800 m running performance. METHODS: Fourteen competitive 800 m runners performed two running tests. First, participants performed a multistage graded exercise test to determine physiological indicators related to endurance performance. Second, participants performed four to six 30-s high intensity running bouts to determine post-exercise blood lactate kinetics. Using a biexponential time function, lactate exchange ability (γ1), lactate removal ability (γ2), and the quantity of lactate accumulated (QLaA) were calculated from individual blood lactate recovery data. RESULTS: 800 m running performance was significantly correlated with peak oxygen consumption (r = -0.794), γ1 and γ2 at 800 m race pace (r = -0.604 and -0.845, respectively), and QLaA at maximal running speed (r = -0.657). V ˙ O2peak and γ2 at 800 m race pace explained 83% of the variance in 800 m running performance. CONCLUSION: Our results indicate that (1) a high capacity to exchange and remove lactate, (2) a high capacity for short-term lactate accumulation and, (3) peak oxygen consumption, are critical elements of 800 m running performance. Accordingly, while lactate has primarily been utilized as a performance indicator for long-distance running, post-exercise lactate kinetics may also prove valuable as a performance determinant in middle-distance running.

Stride-to-stride variability and fluctuations at intensities around lactate threshold in distance runners.

Stride-to-stride variability and fluctuations in running have been widely investigated in relation to fatigue, injury, and other factors. However, no studies have examined the relationship of stride-to-stride variability and fluctuations with lactate threshold (LT), a well-known performance indicator for distance runners that represents the threshold at which fast-twitch muscle fibers are activated and the glycolytic system is hyperactivated. In this study, we examined a relationship between LT and stride-to-stride variability and fluctuations in trained middle- and long-distance runners (n = 33). All runners were asked to perform multistage graded exercise tests while wearing accelerometers on the upper surface of their shoes. The LT was determined by measuring blood lactate concentrations after each stage. Three gait parameters for each step were calculated based on the acceleration data: stride time (ST), ground contact time (CT), and peak acceleration (PA). The coefficient of variation (CV) and the long-range correlations (α) for each parameter were also calculated. The effects of the runner's group and the relative intensity for CV and α on gait parameters were evaluated using a two-way repeated measures analysis of variance. Although no significant effect was observed in the CV and α of ST, significant intensity main effects were observed for the CV and α of CT and PA. The lack of significant changes in ST might be the result of runners' adequate control of ST to minimize energy cost. All the parameters showing significant changes with increasing intensity decreased dramatically when they were close to LT. This might have been caused by an increase in physiological load near LT and be interpreted as a variation in motor control because of alternations in the mobilized muscle fibers and physiological changes around the LT. The α should be useful for non-invasive LT detection.

Effect of endurance training and PGC-1α overexpression on calculated lactate production volume during exercise based on blood lactate concentration.

Lactate production is an important clue for understanding metabolic and signal responses to exercise but its measurement is difficult. Therefore, this study aimed (1) to develop a method of calculating lactate production volume during exercise based on blood lactate concentration and compare the effects between endurance exercise training (EX) and PGC-1α overexpression (OE), (2) to elucidate which proteins and enzymes contribute to changes in lactate production due to EX and muscle PGC-1α OE, and (3) to elucidate the relationship between lactate production volume and signaling phosphorylations involved in mitochondrial biogenesis. EX and PGC-1α OE decreased muscle lactate production volume at the absolute same-intensity exercise, but only PGC-1α OE increased lactate production volume at the relative same-intensity exercise. Multiple linear regression revealed that phosphofructokinase, monocarboxylate transporter (MCT)1, MCT4, and citrate synthase equally contribute to the lactate production volume at high-intensity exercise within physiological adaptations, such as EX, not PGC-1α OE. We found that an exercise intensity-dependent increase in the lactate production volume was associated with a decrease in glycogen concentration and an increase in P-AMPK/T-AMPK. This suggested that the calculated lactate production volume was appropriate and reflected metabolic and signal responses but further modifications are needed for the translation to humans.

No Influence of Acute Moderate Normobaric Hypoxia on Performance and Blood Lactate Concentration Responses to Repeated Wingates.

BACKGROUND: Training in hypoxia versus normoxia often induces larger physiological adaptations, while this does not always translate into additional performance benefits. A possible explanation is a reduced oxygen flux, negatively affecting training intensity and/or volume (decreasing training stimulus). Repeated Wingates (RW) in normoxia is an efficient training strategy for improving both physiological parameters and exercise capacity. However, it remains unclear whether the addition of hypoxia has a detrimental effect on RW performance. PURPOSE: To test the hypothesis that acute moderate hypoxia exposure has no detrimental effect on RW, while both metabolic and perceptual responses would be slightly higher. METHODS: On separate days, 7 male university sprinters performed 3 × 30-s Wingate efforts with 4.5-min passive recovery in either hypoxia (FiO2: 0.145) or normoxia (FiO2: 0.209). Arterial oxygen saturation was assessed before the first Wingate effort, while blood lactate concentration and ratings of perceived exertion were measured after each bout. RESULTS: Mean (P = .92) and peak (P = .63) power outputs, total work (P = .98), and the percentage decrement score (P = .25) were similar between conditions. Arterial oxygen saturation was significantly lower in hypoxia versus normoxia (92.0% [2.8%] vs 98.1% [0.4%], P < .01), whereas blood lactate concentration (P = .78) and ratings of perceived exertion (P = .51) did not differ between conditions. CONCLUSION: In sprinters, acute exposure to moderate hypoxia had no detrimental effect on RW performance and associated metabolic and perceptual responses.

Short-Term Repeated Wingate Training in Hypoxia and Normoxia in Sprinters.

Repeated Wingate efforts (RW) represent an effective training strategy for improving exercise capacity. Living low-training high altitude/hypoxic training methods, that upregulate muscle adaptations, are increasingly popular. However, the benefits of RW training in hypoxia compared to normoxia on performance and accompanying physiological adaptations remain largely undetermined. Our intention was to test the hypothesis that RW training in hypoxia provides additional performance benefits and more favorable physiological responses than equivalent training in normoxia. Twelve male runners (university sprinters) completed six RW training sessions (3 × 30-s Wingate "all-out" efforts with 4.5-min recovery) in either hypoxia (FiO2: 0.145, n = 6) or normoxia (FiO2: 0.209, n = 6) over 2 weeks. Before and after the intervention, participants underwent a RW performance test (3 × 30-s Wingate "all-out" efforts with 4.5-min recovery). Peak power output, mean power output, and total work for the three exercise bouts were determined. A capillary blood sample was taken for analyzing blood lactate concentration (BLa) 3 min after each of the three efforts. Peak power output (+ 11.3 ± 23.0%, p = 0.001), mean power output (+ 6.6 ± 6.8%, p = 0.001), and total work (+ 6.3 ± 5.4% p = 0.016) significantly increased from pre- to post-training, independently of condition. The time × group × interval interaction was significant (p = 0.05) for BLa. Compared to Pre-tests, BLa values during post-test were higher (+ 8.7 ± 10.3%) after about 2 in the normoxic group, although statistical significance was not reached (p = 0.08). Contrastingly, BLa values were lower (albeit not significantly) during post- compared to pre-tests after bout 2 (-9.3 ± 8.6%; p = 0.08) and bout 3 (-9.1 ± 10.7%; p = 0.09) in the hypoxic group. In conclusion, six RW training sessions over 2 weeks significantly improved RW performance, while training in hypoxia had no additional benefit over normoxia. However, accompanying BLa responses tended to be lower in the hypoxic group, while an opposite pattern was observed in the normoxic group. This indicates that different glycolytic and/or oxidative pathway adaptations were probably at play.