Transcranial direct current stimulation (tDCS) is a non-invasive neuromodulation technique that applies a stable, low-intensity (1–2 mA) direct current to modulate neuronal activity in the cerebral cortex. This technique is effective, simple to operate, affordable, and widely employed across various fields. tDCS has been extensively used in clinical and translational research, with growing applications in military and competitive sports domains. In recent years, the use of tDCS in sports science has garnered significant attention from researchers. Numerous studies have demonstrated that tDCS can enhance muscle strength, explosive power, and aerobic metabolism, reduce fatigue, and improve cognition, thereby serving as a valuable tool for enhancing athletic performance. Additionally, recent research has shed light on the physiological mechanisms underlying tDCS, including its modulation of neuronal resting membrane potential to alter cortical excitability, enhancement of synaptic plasticity to regulate long-term potentiation, modulation of neurovascular coupling to improve regional cerebral blood flow, and improvement of cerebral network functional connectivity, which activates and reinforces specific brain regions. tDCS also enhances the release of excitatory neurotransmitters, further regulating brain function. This article, after outlining the role of tDCS in improving physical performance, delves into its mechanisms of action to provide a deeper understanding of how tDCS enhances athletic performance and offers novel approaches and perspectives for physical performance enhancement.

Exercise training can lead to changes in the metabolic composition of an athlete’s blood, the magnitude of which depends largely on the intensity and duration of exercise. A variety of behavioral, biochemical, hormonal, and immunological biomarkers are commonly used to assess an athlete’s physical condition during exercise training. However, traditional invasive muscle biopsy testing methods are unable to comprehensively detect physiological differences and metabolic changes in the body. Metabolomics technology is a high-throughput, highly sensitive technique that provides a comprehensive assessment of changes in small molecule metabolites (molecular weight <1,500 Da) in the body. By measuring the overall metabolic characteristics of biological samples, we can study the changes of endogenous metabolites in an organism or cell at a certain moment in time, and investigate the interconnection and dynamic patterns between metabolites and physiological changes, thus further understanding the interactions between genes and the environment, and providing possibilities for biomarker discovery, precise training and nutritional programming of athletes. This paper summaries the progress of research on the application of exercise metabolomics in sports science, and looks forward to the future development of exercise metabolomics, with a view to providing new approaches and perspectives for improving human performance, promoting exercise against chronic diseases, and advancing sports science research.

We aimed to investigate the impact of a single bout of endurance exercise on the brain-derived neurotrophic factor (BDNF) in humans and analyze how a single bout of endurance exercise impacts the peripheral BDNF types by age group. We performed a systematic literature review by searching PubMed, Elsevier, and Web of Science for studies that included a single bout of endurance exercise in the experimental group and other exercise types in the control group. Eight interventions were included in the study. Overall, a single bout of endurance exercise significantly increased BDNF expression (SMD = 0.30; 95% CI = [0.08, 0.52]; p = 0.001), which was confirmed in the serum BDNF (SMD = 0.30; 95% CI = [0.04, 0.55]; p < 0.001). A non-significant trend was observed in the plasma BDNF (SMD = 0.31; 95% CI = [−0.13, 0.76]; p = 0.017). The serum and plasma BDNF levels significantly increased regardless of age (SMD = 0.35; 95% CI = [0.11, 0.58]; p = 0.004; I² = 0%). In conclusion, a single bout of endurance exercise significantly elevates BDNF levels in humans without neurological disorders, regardless of age. The serum BDNF is a more sensitive index than the plasma BDNF in evaluating the impact of a single bout of endurance exercise on the BDNF.

This investigation aimed to explore the relationship between Chinese elite wrestlers and the polymorphic loci of explosive strength genes, and to further explore the feasibility of its application to athlete selection. The snapshot technique was used to resolve the polymorphic loci of explosive power genes in the wrestler group (59 elite wrestlers) and the control group (180 ordinary college students), and to analyze the genotype frequencies and allele frequencies of each group. A chi-square test was performed on the genotype and allele distribution data of each group to analyze the loci of explosive power genes that were associated with elite wrestlers. The loci that had an association with elite wrestlers were combined with the genotyping data, and the dominance ratios of the genotypes were calculated using the chi-square test to determine the dominant genotypes associated with elite wrestlers. The VDR gene rs2228570 locus exhibited statistically significant differences in genotype and allele distributions between elite wrestlers and the general population (p < 0.01). At the rs2228570 locus of the VDR gene, the difference between the CC genotype and other genotypes was statistically significant (p < 0.05). The rs2228570 locus of the VDR gene was identified as the locus associated with Chinese elite wrestlers. The polymorphism of the VDR gene can be used as a biomarker for Chinese wrestlers, and the CC genotype can be used as a molecular marker for the selection of Chinese elite athletes in this sport. However, expanding the sample size of elite athletes is necessary to further validate the scientific validity and feasibility of these findings.

The stable flight posture that affects sports performance during flight is usually formed by the multiple angles of the athlete-ski posture. At present, research on the flight phase is mainly based on the single-factor impact analysis based on computational fluid dynamics simulation technology, but studies on the multi-factor coupling relationship of two or more factors is less. This study aims to determine the best optimal-level combination based on the simulation model of this work through comprehensive evaluation from the optimisation perspective of multi-factor coupling. Here, a refined model of the athlete-ski system with the characteristics of ski jumping was established. Reynolds time-averaged method was used for the simulation. A three-factor and five-level simulation test was conducted on the relative inclination between skis, the angle between the body and the ski and the ski V-angle through orthogonal experiment design. Our results show that the optimal-level combination of the relative inclination between skis of 120°, the angle between the body and the ski of 20°, and the ski V-angle of 30° is relatively best in terms of aerodynamic characteristics. Simulation results were similar to the results of the winter field data from video analysis, and the results were effective.