Health and Exercise Sciences Research Group, School of Sport, University of Stirling, Stirling, Scotland, UK.
J Appl Physiol (1985). 2013 Feb 15;114(4):461-71. doi: 10.1152/japplphysiol.00652.2012. Epub 2012 Dec 20.
This study was undertaken to investigate physiological adaptation with two endurance-training periods differing in intensity distribution. In a randomized crossover fashion, separated by 4 wk of detraining, 12 male cyclists completed two 6-wk training periods: 1) a polarized model [6.4 (±1.4 SD) h/wk; 80%, 0%, and 20% of training time in low-, moderate-, and high-intensity zones, respectively]; and 2) a threshold model [7.5 (±2.0 SD) h/wk; 57%, 43%, and 0% training-intensity distribution]. Before and after each training period, following 2 days of diet and exercise control, fasted skeletal muscle biopsies were obtained for mitochondrial enzyme activity and monocarboxylate transporter (MCT) 1 and 4 expression, and morning first-void urine samples were collected for NMR spectroscopy-based metabolomics analysis. Endurance performance (40-km time trial), incremental exercise, peak power output (PPO), and high-intensity exercise capacity (95% maximal work rate to exhaustion) were also assessed. Endurance performance, PPOs, lactate threshold (LT), MCT4, and high-intensity exercise capacity all increased over both training periods. Improvements were greater following polarized rather than threshold for PPO [mean (±SE) change of 8 (±2)% vs. 3 (±1)%, P < 0.05], LT [9 (±3)% vs. 2 (±4)%, P < 0.05], and high-intensity exercise capacity [85 (±14)% vs. 37 (±14)%, P < 0.05]. No changes in mitochondrial enzyme activities or MCT1 were observed following training. A significant multilevel, partial least squares-discriminant analysis model was obtained for the threshold model but not the polarized model in the metabolomics analysis. A polarized training distribution results in greater systemic adaptation over 6 wk in already well-trained cyclists. Markers of muscle metabolic adaptation are largely unchanged, but metabolomics markers suggest different cellular metabolic stress that requires further investigation.
本研究旨在探究两种不同强度分布的耐力训练周期的生理适应性。采用随机交叉设计,在 4 周停训期后,12 名男性自行车运动员分别完成了两个 6 周的训练周期:1)极化模式[6.4(±1.4SD)小时/周;训练时间在低、中、高强度区的比例分别为 80%、0%和 20%];2)阈模式[7.5(±2.0SD)小时/周;训练强度分布的比例分别为 57%、43%和 0%]。在每个训练周期前后,经过 2 天的饮食和运动控制,空腹采集骨骼肌活检标本,用于线粒体酶活性和单羧酸转运蛋白(MCT)1 和 4 的表达分析,并采集早晨第一次排空尿液进行基于 NMR 光谱的代谢组学分析。还评估了耐力表现(40km 计时赛)、递增运动、最大功率输出(PPO)和高强度运动能力(95%最大工作率至力竭)。耐力表现、PPO、乳酸阈(LT)、MCT4 和高强度运动能力在两个训练周期都有所提高。与阈模式相比,极化模式下的 PPO[平均(±SE)变化 8(±2)%比 3(±1)%,P<0.05]、LT[9(±3)%比 2(±4)%,P<0.05]和高强度运动能力[85(±14)%比 37(±14)%,P<0.05]的改善更大。训练后线粒体酶活性或 MCT1 没有变化。在代谢组学分析中,获得了阈模式的多水平偏最小二乘判别分析模型,但极化模式没有。在已经训练有素的自行车运动员中,极化的训练分布在 6 周内会导致更大的全身适应性。肌肉代谢适应性的标志物基本不变,但代谢组学标志物表明存在不同的细胞代谢应激,需要进一步研究。