Fry Andrew C, Housh Terry J, Cramer Joel B, Weir Joseph P, Beck Travis W, Schilling Brian K, Miller Jonathan D, Nicoll Justin X
1Osness Human Performance Laboratories, Department of Health, Sport & Exercise Sciences, University of Kansas, Lawrence, Kansas; 2Department of Nutrition and Health Sciences, University of Nebraska-Lincoln, Lincoln, Nebraska; 3Department of Health and Exercise Science, University of Oklahoma, Norman, Oklahoma; and 4Department of Kinesiology and Nutrition Sciences, University of Nevada-Las Vegas, Las Vegas, Nevada.
J Strength Cond Res. 2017 Sep;31(9):2355-2362. doi: 10.1519/JSC.0000000000001645.
Fry, AC, Housh, TJ, Cramer, JB, Weir, JP, Beck, TW, Schilling, BK, Miller, JD, and Nicoll, JX. Noninvasive assessment of skeletal muscle myosin heavy chain expression in trained and untrained men. J Strength Cond Res 31(9): 2355-2362, 2017-Numerous conditions and types of physical activity (e.g., exercise, aging, and muscle-related diseases) can influence muscle fiber types and the proteins expressed. To date, muscle fibers can only be characterized by actually obtaining a tissue sample using the invasive muscle biopsy procedure. Mechanomyography (MMG) is the assessment of the vibration properties of contracting skeletal muscle and has been proposed as a possible noninvasive method for muscle fiber analysis. Therefore, the purpose of this project was to examine the feasibility of using MMG and muscle performance measures to noninvasively assess muscle fiber characteristics. Fifteen men (5 endurance-trained, 5 weight-trained, and 5 sedentary) provided muscle samples from their vastus lateralis muscle. These samples were analyzed for relative myosin heavy chain (MHC) protein expression, which is highly correlated with % muscle fiber type areas. Additionally, each subject performed several muscle performance tests, and MMG of the quadriceps was assessed during a knee extension exercise. Multiple regression was used to develop prediction equations for determining relative muscle content of MHC types I, IIa, and IIx. A combination of MMG and knee extension performance variables estimated types I, IIa, and IIx MHCs with approximately 80% accuracy. Although preliminary, these data suggest that muscle performance tests in addition to MMG assessments during a simple muscle performance task (knee extension) can be used to estimate muscle fiber type composition in a healthy male population. Such methods could ultimately be used to noninvasively monitor muscle health and fitness.
弗莱，AC，豪什，TJ，克莱默，JB，韦尔，JP，贝克，TW，席林，BK，米勒，JD和尼科尔，JX。训练有素和未经训练男性骨骼肌肌球蛋白重链表达的无创评估。《力量与体能研究杂志》31(9): 2355 - 2362，2017年 - 许多情况和类型的体力活动（如运动、衰老和肌肉相关疾病）会影响肌纤维类型和所表达的蛋白质。迄今为止，肌纤维只能通过使用侵入性肌肉活检程序实际获取组织样本进行表征。机械肌电图（MMG）是对收缩骨骼肌振动特性的评估，并已被提议作为一种可能的无创肌纤维分析方法。因此，本项目的目的是研究使用MMG和肌肉性能指标无创评估肌纤维特征的可行性。15名男性（5名耐力训练者、5名力量训练者和5名久坐者）提供了股外侧肌的肌肉样本。对这些样本进行了相对肌球蛋白重链（MHC）蛋白表达分析，其与肌纤维类型面积百分比高度相关。此外，每位受试者进行了多项肌肉性能测试，并在膝关节伸展运动期间评估了股四头肌的MMG。使用多元回归建立了用于确定I型、IIa型和IIx型MHC相对肌肉含量的预测方程。MMG和膝关节伸展性能变量的组合以约80%的准确率估计了I型、IIa型和IIx型MHC。尽管是初步的，但这些数据表明，在简单的肌肉性能任务（膝关节伸展）期间，除了MMG评估外，肌肉性能测试可用于估计健康男性人群的肌纤维类型组成。此类方法最终可用于无创监测肌肉健康和体能。
