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The aim of this study was to evaluate the mediation role of muscle quantity in the relationship between physical fitness and cardiometabolic risk factors (CMRF) in adolescents. This cross-sectional study conducted with 120 adolescents of both sexes, aged between 10 and 17 years. Body mass, height, fat mass (FM), lean mass, blood pressure, high-density lipoprotein, low-density lipoprotein, triglycerides, glucose, insulin, cardiorespiratory fitness (CRF) and 1 repetition maximum strength (1-RM) with evaluation of the leg press 45° (RM-leg), bench press (RM-bench) and arm curl (RM-arm). Body mass index z-score, appendicular skeletal muscle mass, appendicular skeletal muscle mass index, lean mass index (LMI), muscle-to-fat ratio (MFR), age at peak height velocity, and CMRF z-score were calculated. The direct relation between FM and CMRF was mediated by the LMI (26%) and inverse relation between CRF and CMRF was mediated by the LMI (26%). For girls, the direct relation between FM and CMRF was mediated by the LMI (32%); the inverse relation between CRF, RM-leg, RM-arm and CMRF was mediated by the LMI (32%, 33%, and 32%, respective). For boys, the indirect effect was not significant, indicating that LMI is not a mediator in the relation between FM, CRF, 1-RM with CMRF. The direct relation between RM-leg and CMRF was mediated by the MRF (16%). This finding evidenced the importance of promoting a healthy lifestyle to improve physical fitness levels and the quantity of muscle mass in adolescents., (© 2024. The Author(s).)

Boltzmann-Gibbs statistical mechanics applies satisfactorily to a plethora of systems. It fails however for complex systems generically involving nonlocal space-time entanglement. Its generalization based on nonadditive q-entropies adequately handles a wide class of such systems. We show here that scale-invariant networks belong to this class. We numerically study a d-dimensional geographically located network with weighted links and exhibit its 'energy' distribution per site at its quasi-stationary state. Our results strongly suggest a correspondence between the random geometric problem and a class of thermal problems within the generalised thermostatistics. The Boltzmann-Gibbs exponential factor is generically substituted by its q-generalisation, and is recovered in the [Formula: see text] limit when the nonlocal effects fade away. The present connection should cross-fertilise experiments in both research areas.

Exercise training and a healthy diet are the main non-pharmacological strategies for treating chronic conditions, such as obesity and insulin resistance (IR), in adolescents. However, the isolated metabolic changes caused by exercise training without dietary intervention have not yet been established. We investigated how combined training (CT) without dietary intervention altered the concentrations of serum metabolites, biochemical, anthropometric and functional parameters in overweight and obese adolescents. Thirty-seven adolescents (14.6 ± 1.05 years), of both sexes, were randomly assigned to the control group (CG, n = 19) or the training group (TG, n = 18). The CT was composed by resistance training and aerobic training performed in the same session (~ 60 min), three times a week, for 12 weeks. All assessments were performed pre and post-intervention. Metabolomics analyses were conducted using nuclear magnetic resonance spectroscopy ( 1 H NMR) in a 600 MHz spectrometer. There was a decrease in body weight (BW), body mass index (BMI), waist circumference (WC), % body fat (%BF), fasting glucose, insulin levels, and insulin resistance (IR), by HOMA-IR, in the TG. An increase in fat-free mass (FFM) was also observed in the CG. The metabolic changes were given mainly by changes in the levels of metabolites 2-oxoisocaproate (↓TG), 3-hydroxyisobutyrate (↑CG and ↓TG), glucose (↓TG), glutamine (↓CG and ↑TG) and pyruvate (↓TG). These findings demonstrate the positive effects of CT program without dietary intervention on metabolomic profile, body composition, biochemical markers, and glucose metabolism in overweight and obese adolescents.

Deep connections are known to exist between scale-free networks and non-Gibbsian statistics. For example, typical degree distributions at the thermodynamical limit are of the form , where the q-exponential form optimizes the nonadditive entropy Sq (which, for q → 1, recovers the Boltzmann-Gibbs entropy). We introduce and study here d-dimensional geographically-located networks which grow with preferential attachment involving Euclidean distances through . Revealing the connection with q-statistics, we numerically verify (for d = 1, 2, 3 and 4) that the q-exponential degree distributions exhibit, for both q and k, universal dependences on the ratio αA/d. Moreover, the q = 1 limit is rapidly achieved by increasing αA/d to infinity.