Sarcopenia is an aging-induced syndrome characterized by a progressive reduction of skeletal muscle mass and strength. Increasing evidence has attested that appropriate and scientific exercise could induce autophagy or optimize the functional status of autophagy, which plays a critical role in senescent muscular dystrophy. As a publicly recognized strategy for extending lifespan and improving the health of the elderly, the underlying mechanisms of lifelong regular aerobic exercise for the prevention of sarcopenia have not been fully elucidated. To explore the role of lifelong aerobic exercise in the beneficial regulation of autophagic signaling pathways in senescent skeletal muscle, the natural aging mice were used as the sarcopenia model and subjected to lifelong treadmill running to evaluate corresponding parameters related to skeletal muscle atrophy and autophagic signaling pathways. Compared with the young control mice, the aged mice showed a significant reduction in skeletal muscle mass, gastrocnemius muscle weight/body weight (GMW/BW) ratio, and cross-sectional areas (CSA) of skeletal muscle fibers (p < 0.01). In contrast, lifelong aerobic exercise effectively rescued these reduced biomarkers associated with muscle atrophy. Moreover, as shown in the activated AMPK/PGC-1α signaling pathway, lifelong aerobic exercise successfully prevented the aging-induced impairment of the ubiquitin-proteasome system (UPS), excessive apoptosis, defective autophagy, and mitochondrial dysfunction. The exercise-induced autophagy suppressed the key regulatory components of the UPS, inhibited excessive apoptosis, and optimized mitochondrial quality control, thereby preventing and delaying aging-induced skeletal muscle atrophy.

Introduction: Running is one of the most popular sports in the world, but it also increases the risk of injury. The purpose of this study was to establish a modeling approach for IMU-based subdivided action pattern evaluation and to investigate the classification performance of different deep models for predicting running fatigue.Methods: Nineteen healthy male runners were recruited for this study, and the raw time series data were recorded during the pre-fatigue, mid-fatigue, and post-fatigue states during running to construct a running fatigue dataset based on multiple IMUs. In addition to the IMU time series data, each participant’s training level was monitored as an indicator of their level of physical fatigue.Results: The dataset was examined using single-layer LSTM (S_LSTM), CNN, dual-layer LSTM (D_LSTM), single-layer LSTM plus attention model (LSTM + Attention), CNN, and LSTM hybrid model (LSTM + CNN) to classify running fatigue and fatigue levels.Discussion: Based on this dataset, this study proposes a deep learning model with constant length interception of the raw IMU data as input. The use of deep learning models can achieve good classification results for runner fatigue recognition. Both CNN and LSTM can effectively complete the classification of fatigue IMU data, the attention mechanism can effectively improve the processing efficiency of LSTM on the raw IMU data, and the hybrid model of CNN and LSTM is superior to the independent model, which can better extract the features of raw IMU data for fatigue classification. This study will provide some reference for many future action pattern studies based on deep learning.

Background: The related functions of skeletal muscle and brain decrease significantly with age, and muscle-brain-related diseases are primarily associated with each other. Exercise can promote the secretion of myokines in skeletal muscle, showing a beneficial effect on the function of both, reflecting muscle-brain crosstalk. However, the key mechanism of action of exercise-regulated myokines in muscle-brain diseases remains unclear. Summary: This review is intended to sort out and explore the key mechanism of the effect of exercise regulatory myokines on muscle-brain diseases through summarizing the relevant literature on the level of motor regulatory myokines in recent years and pay special attention to the impact of exercise type, intensity, and duration on myokine expression levels. Key Messages: The mechanism by which exercise regulates myokine levels in muscle-brain diseases is explained, and an effective exercise prescription for myokine expression that is more suitable for the elderly based on relevant literature is proposed. This work may hold certain value for subsequent exercise treatment of chronic diseases in the elderly and for further research on muscle-brain crosstalk.

Visual cognition plays a pivotal role in sports. It is widely recognized that there is an intriguing coupling that they could affect each other through interaction between visual cognition and motor control, but few studies linked the effects of visual cognitive tasks on landing stability to postural control and injury risk. Whether visual cognitive tasks affect the landing stability and lower limb injury risk of professional soccer players? The current study used a three-dimensional Multiple Object Tracking (MOT) task to simulate visual cognitive difficulties experienced in soccer matches. Fifteen male high-level soccer athletes (height: 181.43 ± 7.36 cm, weight: 75.37 ± 10.67 kg, training years: 10.07 ± 2.98 yr) from our school team were recruited and completed a landing action from a high platform with and without MOT tasks. Vicon infrared high-speed motion capture system and three-dimensional force measuring platform were used to collect various outcomes simultaneously. The Time to Stabilization (TTS) during landing was significantly prolonged, while the Medial-Lateral Stability Index (MLSI), Anterior-Posterior Stability (APSI), Dynamic Postural Index Stability Index (DPSI), the trajectory lengths, and envelope area of COP during landing were also increased during MOT dual-task. The decline of these indicators reflected the deterioration in postural stability and greater requirements for maintaining balance which could increase the risk of injury in soccer athletes. We advocate that adequate visual attention and visual information processing might play critical roles in maintaining dynamic balance through the supraspinal neural network.

Background. This review aims to investigate the efficacy of Tai Chi Chuan on subjective sleep quality among adults. Methods. We systematically searched PubMed, Embase, Cochrane Library, Scopus, CNKI (China National Knowledge Infrastructure), and the Wanfang Database from their inception to August 2019 and identified 25 eligible studies that were published in both English and Chinese. Results. 24 out of 25 studies were identified to be high‐quality studies according to the PEDro scale. The pooled results confirmed that Tai Chi Chuan elicited moderate improvements in subjective sleep quality (SMD = −0.512, 95% CI [−0.767, −0.257], P < 0.001). Notably, Tai Chi Chuan yielded more significant effects on sleep quality among the healthy population (SMD = −0.684, 95% CI [−1.056, −0.311], P < 0.001) than the clinical population (SMD = −0.395, 95% CI [−0.742, −0.047], P = 0.026) and more benefits among the Asian population (SMD = −0.977, 95% CI [−1.446, −0.508], P < 0.001) than the American population (SMD = −0.259, 95% CI [−0.624, 0.105], P = 0.164). After controlling the methodological quality of studies, it has been noted that Asians could achieve the most significant sleep‐promoting benefit when Tai Chi Chuan was practiced between 60 and 90 min per session. Conclusions. Available data implied that subjective sleep quality was improved via Tai Chi training, but more thorough studies must be executed to ascertain our findings and optimize Tai Chi practices accordingly toward various populations.