This systematic review investigates the integration of artificial intelligence (AI) and information and communication technologies (ICT) in physical education across all educational levels. Physical education is uniquely centered on motor skill development, physical activity engagement, and health promotion—outcomes that require tailored technological approaches. Through the analysis of recent empirical studies, the main areas where digital technologies contribute to pedagogical innovation are highlighted—such as personalized learning, real-time feedback, student motivation, and educational inclusion. The findings show that AI-assisted tools facilitate differentiated instruction and self-regulated learning by adapting to students’ individual performance levels. Technologies such as wearables and augmented reality (AR)/virtual reality (VR) systems increase engagement and support the participation of students with special educational needs. Furthermore, AI contributes to more efficient and objective assessment of motor performance, coordination, and movement quality. However, significant structural and ethical challenges persist, such as unequal access to digital infrastructure, lack of teacher training, and concerns related to personal data protection. Teachers’ perceptions reflect both openness to the educational potential of AI and caution regarding its practical implementation. The review concludes that AI and ICT can substantially transform physical education, provided that coherent policies, clear ethical frameworks, and investments in teachers’ professional development are in place.

The aim of the study was to identify genetic variants associated with personal best scores in Turkish track and field athletes and to compare allelic frequencies between sprint/power and endurance athletes and controls using a whole-exome sequencing (WES) approach, followed by replication studies in independent cohorts. The discovery phase involved 60 elite Turkish athletes (31 sprint/power and 29 endurance) and 20 ethnically matched controls. The replication phase involved 1132 individuals (115 elite Russian sprinters, 373 elite Russian endurance athletes (of which 75 athletes were with VO_2max measurements), 209 controls, 148 Russian and 287 Finnish individuals with muscle fiber composition and cross-sectional area (CSA) data). None of the single nucleotide polymorphisms (SNPs) reached an exome-wide significance level (p < 2.3 × 10⁻⁷) in genotype–phenotype and case–control studies of Turkish athletes. However, of the 53 nominally (p < 0.05) associated SNPs, four functional variants were replicated. The SIRT1 rs41299232 G allele was significantly over-represented in Turkish (p = 0.047) and Russian (p = 0.018) endurance athletes compared to sprint/power athletes and was associated with increased VO_2max (p = 0.037) and a greater proportion of slow-twitch muscle fibers (p = 0.035). The NUP210 rs2280084 A allele was significantly over-represented in Turkish (p = 0.044) and Russian (p = 0.012) endurance athletes compared to sprint/power athletes. The TRPM2 rs1785440 G allele was significantly over-represented in Turkish endurance athletes compared to sprint/power athletes (p = 0.034) and was associated with increased VO_2max (p = 0.008). The AGRN rs4074992 C allele was significantly over-represented in Turkish sprint/power athletes compared to endurance athletes (p = 0.037) and was associated with a greater CSA of fast-twitch muscle fibers (p = 0.024). In conclusion, we present the first WES study of athletes showing that this approach can be used to identify novel genetic markers associated with exercise- and sport-related phenotypes.

The present study aimed to examine the vitamin D receptor (VDR), rs2228570 polymorphism, and its effect on elite athletes’ performance. A total of 60 elite athletes (31 sprint/power and 29 endurance) and 20 control/ physically inactive, aged 18–35, voluntarily participated in the study. The International Association of Athletics Federations (IAAF) score scale was used to determine the performance levels of the athletes’ personal best (PB). Whole exome sequencing (WES) was performed by the genomic DNA isolated from the peripheral blood of the participants. Sports type, sex, and competitive performance were chosen as the parameters to compare within and between the groups by linear regression models. The results showed no statistically significant difference between the CC, TC, and TT genotypes within and between the groups (p > 0.05). Additionally, our results underlined that there were no statistically significant differences for the association of rs2228570 polymorphism with PBs within the groups of the (p > 0.05) athletes. The genetic profile in the selected gene was similar in elite endurance, sprint athletes, and in controls, suggesting that rs2228570 polymorphism does not determine competitive performance in the analyzed athlete cohort.

Background/Objectives: This systematic review aimed to gather the most recent evidence regarding the link between genetic polymorphisms and physical performance in team sports, with a focus on the practical utility of this information for athlete selection, training personalization, and injury prevention. Methods: Sixteen studies published between 2018 and 2025 were analyzed and selected from six international databases, in accordance with the PRISMA guideline. Only English-language studies were included, which evaluated active athletes in team sports and investigated associations between genetic variations, such as Actinin Alpha 3 (ACTN3 R577X), Angiotensin I Converting Enzyme (ACE I/D), Peroxisome Proliferator-Activated Receptor Alpha (PPARA), Interleukin 6 (IL6), and Nitric Oxide Synthase 3 (NOS3), and physical performance parameters. The methodological quality of the studies was assessed using the Q-Genie tool, with all studies scoring over 45 across all 11 items, indicating high quality. Results: The ACTN3 and ACE genes stood out due to their consistent association with traits such as strength, speed, endurance, and recovery capacity. Other genes, such as PPARA, Fatty Acid Amide Hydrolase (FAAH), Angiotensinogen (AGT), and NOS3, complemented this genetic profile by being involved in the regulation of energy metabolism and injury predisposition. An increasing number of studies have begun to adopt cumulative genotype scores, suggesting a shift from a monogenic approach to complex predictive models. Conclusions: The integration of genetic profiling into the evaluation and management of athletes in team sports is becoming increasingly relevant. Although current evidence supports the applicability of these markers, robust future research conducted under standardized conditions is necessary to validate their use in sports practice and to ensure sound ethical standards.

According to some studies, muscle strength (F) is a predictor of health when this motor quality is associated with body mass index (BMI). Based on this statement, our study aims to find out if there is a significant relationship between the two variables, in the context in which the BMI was determined on 160 subjects, selected from students aged 12-15 and who were subsequently included in 4 subcategories: underweight, normal weight, overweight and obese. For the assessment of muscle strength, we used handgrip strength and standing long jump (broad jump) (respecting the EUROFIT methodology). The results show a moderate positive relationship between the level of muscle strength development and BMI (rho = .44, p ≤ .01; rho = .43, p ≤ .01). Our data shows that there is a significant, moderate-intensity connection between BMI and strength development, the subjects with excess weight (overweight and obese) having lower strength values compared to normal-weight subjects. Although some authors consider that only the relationship between BMI and strength does not provide conclusive data for predicting the health of adolescents, the results of our study still confirm the existence of an inverse relationship between BMI and muscle strength at overweight and obese subjects. Because the studies on this direction are not very numerous yet, we consider that other observational studies with a larger sample size, especially longitudinal and prospective studies, are necessary.

This study presents the implementation and results of the Annual Physical Training Program for Masters +45 Half Marathoners (PASm-12), focused on optimizing athletic performance through rigorous planning of training volume and intensity. PASm-12, structured over 12 mesocycles and 52 microcycles, was applied to 6 female runners with over 10 years of experience. The results indicate that the total running volume achieved (2347 km) was 90.2% of the volume proposed by PASm-12 (2603.2 km), with statistically significant differences in most mesocycles (Cohen’s f² = 6.24, t = −5.997, p = 0.002, indicating a large effect size). The training intensity was achieved at an average of 94.8% of what was proposed by PASm-12, with significant differences in several mesocycles (Cohen’s f² = 0.45, t = −1.972 to −3.984, p < 0.05, indicating a moderate to large effect size). The female runners’ performances in field tests generally showed faster times than the maximum and average values proposed in PASm-12, with the exception of the final competition, where performance was slightly lower due to external competitive factors (Cohen’s d = −0.53, t = −1.192, p = 0.3). This plan, demonstrating good practice, could serve as a guideline model for amateur runners who do not have specialist counseling. PASm-12 can reduce the risk of injury, prevent excessive fatigue, and support ongoing participation in sports activities. Additionally, the implementation of this plan could provide amateur runners with a safe and effective training structure, contributing to improved health and athletic performance.