Aged Gastrocnemius Muscle of Mice Positively Responds to a Late Onset Adapted Physical Training

FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY(2023)

引用 0|浏览23
摘要
Introduction: A regular physical training is known to contribute to preserve muscle mass and strength, maintaining structure and function of neural and vascular compartments and preventing muscle insulin resistance and inflammation. However, physical activity is progressively reduced during aging causing mobility limitations and poor quality of life. Although physical exercise for rehabilitation purposes (e.g., after fractures or cardiovascular events) or simply aiming to counteract the development of sarcopenia is frequently advised by physicians, nevertheless few data are available on the targets and the global effects on the muscle organ of adapted exercise especially if started at old age.Methods: To contribute answering this question for medical translational purposes, the proteomic profile of the gastrocnemius muscle was analyzed in 24-month-old mice undergoing adapted physical training on a treadmill for 12 weeks or kept under a sedentary lifestyle condition. Proteomic data were implemented by morphological and morphometrical ultrastructural evaluations.Results and Discussion: Data demonstrate that muscles can respond to adapted physical training started at old age, positively modulating their morphology and the proteomic profile fostering protective and saving mechanisms either involving the extracellular compartment as well as muscle cell components and pathways (i.e., mitochondrial processes, cytoplasmic translation pathways, chaperone-dependent protein refolding, regulation of skeletal muscle contraction). Therefore, this study provides important insights on the targets of adapted physical training, which can be regarded as suitable benchmarks for future in vivo studies further exploring the effects of this type of physical activity by functional/metabolic approaches.
更多
查看译文
关键词
ageing,skeletal muscle,physical training,matrix,proteomics,electron microscopy
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
0
您的评分 :

暂无评分

数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn