Skeletal muscle adaptation: training twice every second day vs. training once daily

Author:

Hansen Anne K.,Fischer Christian P.,Plomgaard Peter,Andersen Jesper Løvind,Saltin Bengt,Pedersen Bente Klarlund

Abstract

Low muscle glycogen content has been demonstrated to enhance transcription of a number of genes involved in training adaptation. These results made us speculate that training at a low muscle glycogen content would enhance training adaptation. We therefore performed a study in which seven healthy untrained men performed knee extensor exercise with one leg trained in a low-glycogen (Low) protocol and the other leg trained at a high-glycogen (High) protocol. Both legs were trained equally regarding workload and training amount. On day 1, both legs (Low and High) were trained for 1 h followed by 2 h of rest at a fasting state, after which one leg (Low) was trained for an additional 1 h. On day 2, only one leg (High) trained for 1 h. Days 1 and 2 were repeated for 10 wk. As an effect of training, the increase in maximal workload was identical for the two legs. However, time until exhaustion at 90% was markedly more increased in the Low leg compared with the High leg. Resting muscle glycogen and the activity of the mitochondrial enzyme 3-hydroxyacyl-CoA dehydrogenase increased with training, but only significantly so in Low, whereas citrate synthase activity increased in both Low and High. There was a more pronounced increase in citrate synthase activity when Low was compared with High. In conclusion, the present study suggests that training twice every second day may be superior to daily training.

Publisher

American Physiological Society

Subject

Physiology (medical),Physiology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3