Exercise‐induced benefits are being increasingly recognized in promoting health and preventing diseases. However, initial adaption to exercise response can have different effects on cells, including an increase in the formation of oxidants and inflammatory mediators that ultimately leads to oxidative stress, but this scenario depends on the exercise type and intensity and training status of the individual. Therefore, we aimed to understand the effect of different types of exercise on oxidative stress. Indeed, exercise‐induced minimum oxidative stress is required for regulating signaling pathways. According to the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) statement, a search for relevant articles was carried out on PubMed/Medline, ISI Web of Science, and Google Scholar using a broad range of synonyms such as oxidants, reactive oxygen species (ROS), oxidative stress, exercise, physical training, aerobic exercise, and strength exercise until 2019. This study selected a total of 18 articles for assessing the oxidative damage using various parameters such as malondialdehyde (MDA), protein carbonyl (PCO), and F1‐isoprostanes and enzymatic antioxidants. We observed that any type of exercise can increase the oxidative damage in an exercise type and intensity manner. Further, the training status of the individual and specific oxidative damage marker plays a crucial role in predicting earlier oxidative damage in the exercise condition. However, some of the studies that we included for review did not perform follow‐up evaluations. Therefore, follow‐up programs using larger numbers need to be performed to confirm our findings.

Running gait patterns have implications for revealing the causes of injuries between higher-mileage runners and low-mileage runners. However, there is limited research on the possible relationships between running gait patterns and weekly running mileages. In recent years, machine learning algorithms have been used for pattern recognition and classification of gait features to emphasize the uniqueness of gait patterns. However, they all have a representative problem of being a black box that often lacks the interpretability of the predicted results of the classifier. Therefore, this study was conducted using a Deep Neural Network (DNN) model and Layer-wise Relevance Propagation (LRP) technology to investigate the differences in running gait patterns between higher-mileage runners and low-mileage runners. It was found that the ankle and knee provide considerable information to recognize gait features, especially in the sagittal and transverse planes. This may be the reason why high-mileage and low-mileage runners have different injury patterns due to their different gait patterns. The early stages of stance are very important in gait pattern recognition because the pattern contains effective information related to gait. The findings of the study noted that LRP completes a feasible interpretation of the predicted results of the model, thus providing more interesting insights and more effective information for analyzing gait patterns.

Single-leg landing (SL) is often associated with a high injury risk, especially anterior cruciate ligament (ACL) injuries and lateral ankle sprain. This work investigates the relationship between ankle motion patterns (ankle initial contact angle [AICA] and ankle range of motion [AROM]) and the lower limb injury risk during SL, and proposes an optimized landing strategy that can reduce the injury risk. To more realistically revert and simulate the ACL injury mechanics, we developed a knee musculoskeletal model that reverts the ACL ligament to a nonlinear short-term viscoelastic mechanical mechanism (strain rate-dependent) generated by the dense connective tissue as a function of strain. Sixty healthy male subjects were recruited to collect biomechanics data during SL. The correlation analysis was conducted to explore the relationship between AICA, AROM, and peak vertical ground reaction force (PVGRF), joint total energy dissipation (TED), peak ankle knee hip sagittal moment, peak ankle inversion angle (PAIA), and peak ACL force (PAF). AICA exhibits a negative correlation with PVGRF ( r = −0.591) and PAF ( r = −0.554), and a positive correlation with TED ( r = 0.490) and PAIA ( r = 0.502). AROM exhibits a positive correlation with TED ( r = 0.687) and PAIA ( r = 0.600). The results suggested that the appropriate increases in AICA (30° to 40°) and AROM (50° to 70°) may reduce the lower limb injury risk. This study has the potential to offer novel perspectives on the optimized application of landing strategies, thus giving the crucial theoretical basis for decreasing injury risk.

The health benefits of regular exercise are well established. Nonetheless, the molecular mechanism(s) responsible for exercise-induced health benefits remain a topic of debate. One of the key cell-signaling candidates proposed to provide exercise-induced benefits is sirtuin 3 (SIRT3). SIRT3, an NAD+ dependent mitochondrial deacetylase, positively modulates many cellular processes, including energy metabolism, mitochondrial biogenesis, and protection against oxidative stress. Although the exercise-induced change in SIRT3 signaling is a potential mechanism contributing to the health advantages of exercise on aging, studies investigating the impact of exercise on SIRT3 abundance in cells provide conflicting results. To resolve this conundrum, this narrative review provides a detailed analysis of the role that exercise-induced changes in SIRT3 play in providing the health and aging benefits associated with regular physical activity. We begin with an overview of SIRT3 function in cells followed by a comprehensive review of the impact of exercise on SIRT3 expression in humans and other mammalians. We then discuss the impact of SIRT3 on aging, followed by a thorough analysis of the cell-signaling links between SIRT3 and exercise-induced adaptation. Notably, to stimulate future research, we conclude with a discussion of key unanswered questions related to exercise, aging, and SIRT3 expression.