Biology of Sport最新文献

The aims were to I. assess the differences in unforced errors between men's and women's professional padel players, II. assess the differences in unforced errors between winners and losers of the set in professional padel players, III. analyse the evolution of unforced errors in professional padel. To do this, the unforced errors (which are provided by World Padel Tour (WPT)) were collected from 2,567 sets (1,476 men's sets and 1,091 women's sets) corresponding to matches from the final draw (round of 32, round of 16, quarterfinals, semi-finals and finals) of tournaments on the WPT men's and women's circuits during 2016 to 2022 seasons, which are available on the WPT YouTube channel and on the WPT TV website. The results with respect to the first aim indicate that the number of unforced errors was higher in women's padel than in men's, regardless of the set number, tournament round, season and court. With respect to the second aim, not committing unforced errors is a fundamental factor in professional padel to win the sets. Finally, regarding the third aim, the number of unforced errors decreased as the seasons progressed; therefore, to win, players should not only have to pass the ball without missing, but they might have to hit winners or generate forced errors of the opponent.

This study aims to utilize Genome-Wide Association Analysis (GWAS) to identify genetic markers associated with enhanced power resulting from resistance training. Additionally, we analyze the potential biological effects of these markers and establish a predictive model for training outcomes. 193 Han Chinese adults (age: 20 ± 1 years) underwent resistance training involving squats and bench presses at 70% 1RM, twice weekly, 5 sets × 10 repetitions, for 12 weeks. Whole-genome genotyping was conducted, and participants' countermovement jump (CMJ) height, lower limb muscle strength, and body muscle mass were assessed. CMJ height change was used to assess changes in power and subjected to Genome-Wide Association Analysis (GWAS) against genotypes. Employing Polygenic Score (PGS) calculations and stepwise linear regression, a predictive model for training effects was constructed. The results revealed a significant increase in CMJ height among participants following the resistance training intervention (Δ% = 16.53%, p < 0.01), with individual differences ranging from -35.90% to 125.71%. 38 lead SNPs, including PCTP rs9907859 (p < 1 × 10^-8), showed significant associations with the percentage change in CMJ height after training (p < 1 × 10^-5). The explanatory power of the predictive model for training outcomes, established using PGS and phenotypic indicators, was 62.6%, comprising 13.0% from PGS and 49.6% from phenotypic indicators. SNPs associated with power resistance training were found to participate in the biological processes of musculoskeletal movement and the Striated muscle contraction pathway. These findings indicate that individual differences in the training effect of CMJ exist after resistance training, partially explained by genetic markers and phenotypic indicators (62.6%).

Exercise mechanical efficiency typically falls within the range of approximately 20 to 25%. This means that a great part of the metabolic energy converted to generate movement is released as heat. Therefore, the rise in core temperature during endurance exercise in humans is proportional to generated work. Cutaneous vasodilation occurs when the core temperature threshold is reached. The rise in heart rate in response to thermal stress is a cardiovascular response that increases cardiac output and skin blood flow. The cardiovascular response during endurance exercise is a complex phenomenon potentially influenced by the involvement of nitric oxide in active thermoregulatory vasodilation. Excessive exercise can create high oxidative stress by disrupting the balance between free radicals' production and scavenging, resulting in impaired cardiovascular function. The above considerations are related to the severity and duration of endurance exercise. The first focus of this narrative review is to provide an updated understanding of cardiovascular function during endurance exercise. We aim to explore the potential role of oxidative stress in causing cardiovascular dysfunction during endurance exercise from a fresh perspective. Additionally, we aim to identify the primary factors contributing to cardiovascular risk during strenuous prolonged exercise by highlighting recent progress in this area, which may shed light on previously unexplained physiological responses. To ascertain the effect of endurance exercise on cardiovascular function and dysfunction, a narrative review of the literature was undertaken using PubMed, ScienceDirect, Medline, Google Scholar, and Scopus. The review highlighted that high oxidative stress (due to high levels of catecholamines, shear stress, immune system activation, and renal dysfunction) leads to a rise in platelet aggregation during endurance exercise. Importantly, we clearly revealed for the first time that endothelial damage, vasoconstriction, and blood coagulation (inducing thrombosis) are potentially the primary factors of cardiovascular dysfunction and myocardial infarction during and/or following endurance exercise.

The present study aimed to investigate the effects of 12 weeks of resistance training (RT) on body composition [fat mass (FM), lean body mass (LBM)], muscle quality upper and lower (MQU, MQL), muscle size [cross sectional area (CSA), quadriceps cross-sectional area (QCSA)], biomarkers of neuromuscular junctions [C-terminal agrin fragment (CAF)], and muscle protein turnover [N-terminal peptide (P3NP), 3-methylhistidine (3MH), skeletal muscle-specific isoform of troponin T (sTnT)] in older men. Thirty elderly men (age 66.23 ± 0.57 years) were randomly divided into two groups: resistance training group (RT, n=15) and control group (CON, n=15). Participants in RT performed resistance training protocols with the intensity of 60% one-repetition maximum (3 × /week, 4 sets of the six exercise circuits). Blood samples were assessed before (pre-test) and after (post-test) a 12-week intervention. The ANCOVA (2 × 2; group × time; with the baseline variable as the covariate) revealed significant interaction effects; the greater increases for LBM (P < 0.001), CSA (P < 0.001), QCSA (P < 0.001), MQU (P < 0.05), MQL (P < 0.01), 3MH (P < 0.05) were noted in RT than CON, and greater decreases for FM (P < 0.001) and CAF (P < 0.001) in RT than CON. No interaction effect was found for P3NP and sTnT. The time effect was found for all variables besides P3NP in RT, but no time effect was revealed in CON. The 12-week RT was an effective strategy for improving the concentrations of neuromuscular junction biomarkers such as 3-MH and CAF in older adults, and may lead to favourable changes in body composition, muscle quality, and muscle size.

[This corrects the article DOI: 10.5114/biolsport.2024.132991.].

In sport, the awakening responses of cortisol (CAR) and testosterone (TAR) have been used as evaluative tools. Research findings are, however, inconsistent and the mechanisms involved are unclear. This study investigated the CAR and TAR in male athletes across light and heavy training weeks, focusing on skeletal muscle damage as a mediating factor. Twenty elite male judokas were assessed across consecutive weeks of light and heavy training (i.e., 6 days, 9-10 weekly sessions). Plasma cortisol and testosterone concentrations were measured post-awakening (+3, +30, +60 mins), along with creatine kinase (CK) at +3 mins. The CAR and TAR were indexed by baseline-corrected change scores (Δb30, Δb60) and area under the curve (AUCb30, AUCb60). The early-morning surge in plasma cortisol concentration (CAR_Δb30, CAR_Δb60, CAR_AUCb30, CAR_AUCb60) was significantly larger after light versus heavy training with effect-size differences of 2.14-2.64. The post-awakening decline in plasma testosterone (TAR_Δb30, TAR_AUCb30, TAR_AUCb60) was found to be significantly less pronounced, whilst CK level was elevated, after heavy than light training with effect-size differences of 0.95-1.04 and 4.70, respectively. Causal mediation analysis confirmed that CK mediated, in part, the training effect on the CAR, but not TAR, measures. In summary, male judokas, upon rising after a light training block, displayed a rising CAR (36%, 22%) and declining TAR (-11%, -15%) at +30 and +60 mins. A high-intensity training block suppressed the CAR (21%, 8%) and attenuated the TAR (-7%, -13%) with accompanying muscle damage offering one mechanism to partly explain the CAR differences.

The aims of this study were to: a) examine the relationships between high-intensity distances covered above generic and relative speed thresholds in English Premier League (EPL) matches across two consecutive seasons and b) analyze the effects of playing position and team possession. Sixteen elite male soccer players (seven defenders, six midfielders and three forwards) participated in this study (age 27.8 ± 3.5 years, height 183.7 ± 5.4 cm, body mass 83.9 ± 7.1 kg). An Optical Tracking System was used to collect the following variables: total distance covered; high-speed running distance (HSRD) (> 5.5 m/s); high-intensity running distance (HIRD) (5.5-7 m/s); sprint distance (> 7 m/s); total distance covered above Maximal Aerobic Speed (MAS); distance covered > 85% peak speed (PS); and distance > 30% Anaerobic Speed Reserve (ASR). All measures were analyzed as whole match totals and as distances covered in the periods of the team in possession (TIP), opponent team in possession (OTIP), and ball out of play (BOP). Analysis by position based on defenders, midfielders and forwards was also performed. Distance > 30% ASR was almost perfectly correlated with HSRD (r = 0.98), while distances > MAS were highly correlated with both HIRD (r = 0.91) and HSRD (r = 0.91), and distance > 85% PS were highly correlated with SD (r = 0.70). Although the generic and relative speed thresholds show almost perfect correlation, the differences between HSRD, HIRD and distance > MAS indicate that players may be exposed to more HIRD when using relative thresholds.

The aim of this study was to determine the effects of linear and change of direction high-intensity interval training (HIIT) on physical performance in elite female soccer players. Thirty elite female soccer players (age: 19.6 ± 4.6 years; height: 166.5 ± 4.8 cm; body weight: 60.5 ± 8.3 kg; BMI: 21.9 ± 2.9 kg/m²) were randomly allocated to HIIT linear (HIIT_LIN) and HIIT change of direction (HIIT_COD) training groups. The HIIT_LIN group performed linear running for 15, 20 or 25 s by keeping constant pace during the entire distance. In contrast, the HIIT_COD group performed three changes of direction (COD) with a 180° turn during each interval run at 15, 20 or 25 s. Physical performance was assessed using sprinting, agility, vertical jumps, repeated sprint ability (RSA) and 30-15 Intermittent Fitness Test (30-15 IFT). In both groups, all physical performance measurements improved (p ≤ 0.05), except RSAbest in HIIT_LIN (p = 0.45). Both interventions significantly improved speed over 10 m, 20 m, 30 m, Pro-agility, Zig-zag, RSAavg, fatigue index, maximal oxygen uptake, and velocity at 30-15 IFT, while moderate improvements were observed in countermovement jump (CMJ), CMJ with arm swing and squat jump. However, HIIT_COD did not achieve superior improvements in any of the aforementioned measurements compared to HIIT_LIN. Based on the obtained results, we concluded that different types of HIIT training have a positive effect on physical performance in elite female soccer players.

We evaluated the effects of post-activation performance enhancement through flywheel exercise with varying inertial loads compared to traditional resistance exercise on countermovement jump performance and muscle recruitment. In a randomized crossover design, 13 trained men completed four main experimental trials after three familiarization sessions. These conditions included a traditional trial consisting of 5 sets of 1 repetition using the Smith machine (SM) squat at 90% 1RM, and three flywheel ergometer trials. Each flywheel protocol consisted of 3 sets of 8 repetitions with 3-minute rest intervals between sets, utilizing one of three inertial loads (0.0465, 0.0784, and 0.1568 kg · m² for light, moderate, and heavy, respectively). Participants performed countermovement jumps before (baseline), immediately after (0 minute), and at the fourth (+4 minutes), eighth (+8 minutes), and twelfth (+12 minutes) minute following exercise. Compared to baseline, jump height was higher at +4 minutes for SM squats (p = 0.009). All flywheel conditions exhibited higher jump heights at +4 minutes (p < 0.05), +8 minutes (p < 0.001), and +12 minutes (p < 0.001) compared to baseline. Additionally, moderate and heavy loads resulted in higher jump heights at 0 minute (both p < 0.001). Integrated electromyographic activity values, a proxy for muscle recruitment, were significantly higher for the gluteus maximus muscle at both +8 minutes and +12 minutes for moderate (both p = 0.004) and heavy loads (p ≤ 0.002) compared to SM squats. Overall, flywheel protocols produce greater post-activation performance enhancement, extend the time window for improvement, and recruit more active musculature compared to heavy-load SM squats, particularly with heavier loads acting as a stronger preload stimulus.

This study aimed to compare the predictive accuracy of absolute and relative external load indices (ELI) across three machine learning models, and predict the rating of perceived exertion (RPE) of elite Gaelic football players using ELI, personal characteristics, wellness scores, and training workloads. ELI and related variables were collected from 49 elite Gaelic football players over three competitive seasons resulting in 1617 observations. ELI included total distance, high speed running distance (≥ 4.72 m · s^-1), and number of accelerations and decelerations (n ± 3 m · s^-2), expressed in both absolute and relative terms. Variables related to personal characteristics, wellness scores, and training workloads were also included. Data were analysed using decision tree, random forest (RF), and bootstrap aggregation (BS) models. The RF model had the highest predictive accuracy using absolute and relative ELI only, at 54.3% and 48.3%, respectively. Total and relative distance were the strongest predictors of RPE in the RF model, accounting for 38.8% and 27.9% of the normalised importance. The BS model had the highest accuracy at 67.0% and 65.2% for absolute and relative ELI when performed in conjunction with the related variables, respectively. The current models demonstrate potential to predict RPE and subsequently optimise training load in Gaelic football.