Ghazi Racil

Dynamic postural control in Canadian canoeing depends on coordinated load distribution and center of pressure regulation across three support points in a highly asymmetrical kneeling posture. However, the integrated organization of these biomechanical domains under varying stability demands remains poorly characterized. This exploratory study examined 13 Canadian canoeing athletes using three synchronized strain-gauge force platforms during a standardized canoe-specific kneeling position under stable and unstable support conditions. Three dynamic variables, percentage load distribution (%DCA), dynamic force (N.kg⁻¹), and center-of-pressure displacement (Dynamic SigmaPath), were assessed simultaneously. Principal component analysis showed that PC1 (62.5% variance) and PC2 (24.1% variance) captured the main structure of postural control, with Dynamic SigmaPath displaying loading patterns opposite to the percentage load distribution and force. Exploratory K-means clustering (k=2) suggested moderate organization into two biomechanical patterns. Correlation analyses revealed significant associations between load-distribution metrics and Dynamic SigmaPath (ρ=0.657 and p=0.015), and between force production and load-distribution asymmetry (ρ=−0.635 and p=0.020). These findings indicate that biomechanical affinity, quantified through multivariate analysis, characterizes athlete-specific postural-control strategies. A Composite Biomechanical Index is proposed as an exploratory framework for describing postural-control strategies and generating hypotheses regarding athlete monitoring and crew compatibility in paddling sports.

Background/Objectives: Standard plyometric, flexibility and balance drills are central to youth rhythmic gymnastics but can be limited by repetitive monotony and reduced engagement. This study evaluated whether embedding plyometric or flexibility exercises within traditional games improves physical performance and lower-limb flexibility in young female gymnasts. Methods: Forty-two female gymnasts (age 13.7 ± 1.5 years) were randomly assigned (1:1:1, permuted-block randomization with allocation concealment) to a game-based plyometric group (PECG), a game-based flexibility group (FECG), or a standard gymnastics control (GE). Over 8 weeks (five sessions per week) the experimental groups performed their protocols immediately before regular training, with load recalibrated every two weeks. Squat jump (SJ), countermovement jump (CMJ) and hip flexibility were pre-specified primary outcomes; agility, Stork balance and Y-Balance were exploratory. Linear mixed models tested Group × Time interactions, with within-group effect sizes expressed as Cohen’s d. Results: Significant Group × Time interactions emerged for the squat jump (F_2,39 = 6.09, p = 0.005) and countermovement jump (F_2,39 = 6.77, p = 0.003), favoring PECG (SJ β = 1.90; CMJ β = 1.86). FECG produced the largest flexibility gains, with significant Group × Time interactions for hip abduction and left hip flexion; a marked within-group increase in right hip extension (β = 2.65) was not accompanied by a significant interaction and is interpreted with caution. PECG also improved agility (p = 0.001), static balance and several Y-Balance directions. No injuries or dropouts were recorded. Conclusions: An 8-week game-based intervention enhanced physical performance in adolescent rhythmic gymnasts, with effects largely specific to the training modality: plyometric games improved explosive power, agility and dynamic balance, whereas flexibility games improved range of motion. Given the small sample, the findings should be regarded as preliminary and hypothesis-generating.

Purpose: Static spirometry parameters may offer practical alternatives to estimate maximum oxygen consumption (V̇O _2max ) in athletic populations. This study evaluated forced vital capacity (FVC) as a predictor of V̇O _2max across different sports, developing prediction equations for field-based assessment. Methods: Four hundred twenty-two athletes (324 males, 98 females; age 22.9 ± 8.5 years) from cycling ( n = 123), swimming ( n = 68), triathlon ( n = 60), multisport ( n = 83), and other sports ( n = 88) performed spirometry and maximal incremental testing. V̇O _2max was directly measured using breath-by-breath gas analysis. LASSO regression identified predictors, with Bland–Altman analysis assessing agreement. Results: FVC and gender emerged as significant predictors ( R ² = 0.690, P < 0.001). The equation V̇O _2max (L·min ⁻¹ ) = (FVC × 0.61) + (Gender × 0.86) yielded SEE = 0.65 L·min ⁻¹ . Including additional variables (Maximum voluntary ventilation, body weight, age) marginally improved prediction ( R ² = 0.712) but reduced practical utility. Coefficient of variation between measured and predicted values was 12.1%. Sport-specific analysis revealed highest predictive accuracy in swimmers ( R ² = 0.893). Conclusion: FVC provides reasonable population-level V̇O _2max estimates in athletes, though individual predictions require caution given substantial unexplained variance (31%). Sport-specific equations, particularly for swimming populations, enhance predictive accuracy. These findings offer practical screening tools for coaches lacking access to metabolic testing equipment, though direct measurement remains the gold standard for individual assessment.

Background: Marathon running has evolved into a global phenomenon, with rising participation across age and experience groups. Training for a marathon requires adherence to well-established principles involving pacing, training volume, and periodization. With the increasing integration of artificial intelligence (AI) into healthcare and fitness, it remains unclear whether AI can reliably prescribe evidence-based training programs for such demanding endurance events. Sources of data: We conducted a descriptive study using outputs from leading AI models: Claude 3.5 Sonnet, Claude 3.5 Haiku (Free), ChatGPT 4.0 (o-model), ChatGPT 0.1, ChatGPT 4 (free), Gemini 2.0 Flash, Gemini 2.0 Flash Thinking, and DeepSeek R1. Each was prompted to generate a 6-month marathon training plan tailored to three athlete levels: Beginner, Intermediate, and Advanced. Outputs were compared with peer-reviewed literature on the determinants of marathon training. Areas of agreement: Most AI systems identified key training components: weekly mileage progression, tapering, and intensity distribution (>80% at low intensity), which aligns with current endurance training theory. Areas of controversy: AI responses varied in accuracy and completeness. Some engines omitted key details (e.g. weekly mileage), failed to differentiate clearly between athlete levels (intermediate and advanced have been merged as if they were the same level), or offered inconsistent pacing data, especially for advanced runners. This descriptive analysis evaluated qualitative adherence to evidence-based training principles rather than quantitative outcomes requiring statistical inference. Growing points: AI demonstrates strong potential in accessible, structured training content. When properly prompted, outputs often align with contemporary training principles, though significant limitations regarding personalization and professional oversight necessitate further validation before clinical implementation. Areas timely for developing research: Future studies should evaluate the real-world outcomes of AI-generated programs in randomized trials including the integration of personal physiological data. Inizio moduloFine modulo.

Background: Adipose tissue secretes bioactive substances, adipokines, which affect cardiovascular health. The secretion of adinopectines is associated with decreases in metabolic and cardiovascular diseases risk-factors such as obesity and type 2 diabetes. High-intensity interval training (HIIT) exerts beneficial effects on cardiometabolic health, but its effect on adipokines is unclear. Sources of data: This systematic review and meta-analysis, aimed to report the effects of HIIT on adiponectin levels in overweight and obese individuals, was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The literature search was conducted in Web of Science, PubMed, ScienceDirect, and Google Scholar. The quality of the articles was evaluated using the Downs and Black checklist. Areas of agreement: HIIT training generally did not affect adiponectin levels in overweight and obese individuals. Most likely, this effect can result from the lack of weight loss of the subjects in some studies. Areas of controversy: One notable constraint within the scope of these investigations pertains to the relatively modest sample sizes employed. Consequently, future research endeavours should employ larger cohorts to enhance the generalizability of findings. Growing points: HIIT focused on weight loss and fat percentage may effectively enhance the impact of HIIT on adiponectin levels. Areas timely for developing research: Future research should implement rigorous dietary controls to isolate the independent effects of HIIT on adiponectin modulation. PROSPERO Registration: CRD42024580266.

Purpose: The integration of visual feedback (VFB) has become essential in physical education (PE), particularly with theemergence in artificial intelligence (AI) technologies. However, tackling techniques in youth soccer training have receivedlimited empirical attention, even though they represent a complex and high-risk defensive skill. The purpose of the studywas to analyse the effects of AI-enhanced VFB, using 3D animated motion capture, on the acquisition of tackling skills amongyouth soccer players.Methods: Twenty-three participants were randomly assigned to an experimental group (EG; n = 12), utilizing AI-animatedVFB, or to a control group (CG; n = 11) which received only verbal feedback. Technical performance was evaluated throughfour validated success criteria at the 1st, 6th, and 12th training lessons, while biomechanical efficiency was measured bycomparing the trunk-leg angle to a model angle (167.3°). Motivation was evaluated using the Situational Motivation Scale.Results: The findings show that the EG achieved a significantly greater improvement in technical performance (+179%)compared to the CG (+96%), with very marked effects for leg-knee positioning (Criteria 3) and ball contact (Criteria 4).The leg-trunk angle of the EG also improved significantly (+23.84%), approaching the expert model, while the CG showedonly a modest increase (+9.63%). Furthermore, intrinsic motivation increased significantly in the EG (P = .001; d = 1.44),accompanied by a significant reduction in amotivation (P = .004; d = 1.07).Conclusions: The AI-enhanced VFB allowed players to analyse their performance through 3D animations, facilitating skillimprovement. These findings highlight the potential of AI-driven visual feedback in sports training, through further researchneeded to optimize its application in skill acquisition.

Purpose: This study examines the impact of video use in three different formats: continuous playback without interruption,self-paced control, and feedback-based format, on situational interest, self-efficacy, and the development of tactical knowledgein handball among students in physical education.Methods: Sixty secondary school students, (age 14.47±0.44 years) were divided into three groups of 20 students each, with10 girls and 10 boys per group: The Continuous Video Group (CVG; n=20), the Video Control Group (CTR; n= 20), and theVideo Feedback Group (VFB; n=20). Students viewed a handball video scenario and then completed recall and transfer tests,as well as situational interest and self-efficacy questionnaires.Results: Non-parametric analyses (Mann-Whitney U tests) showed that the Video Control Group had significantly betterrecall than the Video Continuous (U= 52, P< .001) and Video Feedback groups (U= 71.5, P< .001). For transfer and efficacytests, both the Control and Feedback groups outperformed the Continuous group (transfer: U=4 7, P< .001; U= 73, P< .001;efficacy: U=118.5, P= .026; U= 110, P= .014). Situational interest was significantly higher in the Continuous group comparedto the Feedback group (P= .027), suggesting continuous video exposure elicits greater interest than delayed feedback.Conclusions: These results suggest that, although the continuous reading group demonstrated higher situational interest, theirmemorization and transfer performance was lower than that of the groups using video control or video feedback. Therefore,video control and video feedback appear to promote both self-efficacy and performance. Therefore, to optimize results, the useof these teaching tools should be progressively structured and adapted to the cognitive abilities of physical education students.

This study aimed to develop predictive equations for unilateral (1-leg) half-squat exercise loads that would elicit equivalent neuromuscular activation, velocity, and force outputs as bilateral (2-leg) half-squat exercise loads. Twelve male soccer players (age 22.9±1.8 y, stature 1.8±0.1 m, and body mass 76.5±6.2 kg) performed both 1-leg and 2-leg half-squats using a Smith-machine. Surface electromyography of vastus lateralis and vastus medialis, barbell velocity and force outputs were measured across incremental loads. Linear regression analyses were conducted to develop predictive equations for 1-leg loads that would match 2-leg exercise outcomes. Three predictive equations were developed: (1) Equivalent muscle activation: 1-leg external load=50% of 2-leg external load –2 kg (r=0.923–0.997, p<0.05). (2) Equivalent barbell velocity: 1-leg external-load=71% of 2-leg external load –17.6 kg (r= –0.916 to 0.994, p<0.05). (3) Equivalent force-output: 1-leg external load=41% of 2-leg external load – 28 kg (r=0.937–0.998, p<0.05). This preliminary investigation provides initial predictive equations for equating unilateral and bilateral half-squat exercises, though validation on independent populations remains necessary. These tools enable practitioners to estimate equivalent loads between exercise modalities using a single one-repetition maximum assessment, facilitating targeted training and rehabilitation program development through accurate load prescription and performance comparisons. Further research is needed to validate these equations on large population and in different sports.

Systemic inflammation has been recognized as an extrapulmonary manifestation of chronic obstructive pulmonary disease (COPD). Recent studies have indicated that exercise training can reduce the levels of inflammatory cells and mediators in both healthy individuals and those with heart diseases. However, the impact of combining resistance training (RT) with aerobic training (AT) on inflammatory biomarkers in COPD patients remains unclear. This study aims to analyze the effects of adding RT to AT on inflammatory markers in patients with COPD. Thirty-one patients diagnosed with COPD were randomly assigned to either a combined resistance and aerobic training group (RATG; n = 16) or an aerobic training group (ATG; n = 15). Both groups participated in their respective exercise regimens three times per week for a duration of 3 months. Anthropometric characteristics were recorded, and all patients underwent lung function testing as well as a six-minute walk test. Additionally, levels of IL-6, IL-17, and IL-32 were measured to assess inflammation. The 6-min walking distance, dyspnea levels, and oxygen saturation (SpO2) all showed significant improvement in the intervention group. In both groups, the concentrations of IL-6, IL-17, and IL-32 decreased significantly (p < .05) following the rehabilitation program. Notably, IL-6 levels exhibited a more significant decrease in the intervention group compared to the control group. Both exercise regimens led to reductions in IL-6, IL-17, and IL-32 levels. However, the combined training appears to exert a synergistic effect, potentially offering greater anti-inflammatory and functional benefits in COPD patients.