Introduction. Anthropometric and anaerobic profile of elite athletes are fundamental for the assessment of their respective performance. The present study was designed to evaluate the anthropometric parameters, body composition and anaerobic characteristics of elite male handball players and rowers, and to compare them in relation to specific sport demands. Material and Methods. The study group consisted of 41 elite national level athletes: 20 handball players (aged 23.7?3.72) and 21 rowers (aged 19.7?2.84). Anthropometric characteristics (body mass, body height, skinfold thickness, body circumferences), and body fat mass were evaluated, and Wingate anaerobic test for anaerobic power assessment was applied. Results. The significant differences were noted in chest, upper arm, waist and hip circumferences, and supraspinal and calf skinfolds between the two investigated groups. Rowers showed higher values of fat body mass (13.2?3.76 vs. 10.7?3.76%), but lower body mass index (22.0?1,92 vs. 25.7?2.31 kg/m2) compared to handball players. When analyzing the Wingate test parameters, significantly higher values of absolute anaerobic power (786?127 vs. 691?140 W), absolute explosive power in the handball players compared to the rowers were recorded (118?26.3 vs. 105?27.8 W/s), while rowers achieved higher relative anaerobic capacity (192?31.2 vs. 177?20.8 J/kg). Conclusion. Specific body composition and anthropometrical assessment as a part of morphological analysis should complement physiological profile of elite athletes. The analysis of the anaerobic performance shows that the handball players have greater alactic anaerobic and explosive power component, compared to the rowers in whom the anaerobic endurance and specific training have the greatest effect on the consumption of dominant metabolic substrate during the race.

Ann Indian Acad Neurol, Official Journal of Indian Academy of Neurology

Introduction. There is a great interest to identify factors that influence the value of maximum oxygen consumption. The goal of this research was to assess the body composition, pulmonary parameters, and maximum oxygen consumption in different types of sports and in non-athletes. Material and Methods. The research included 149 male participants: aerobic athletes (n = 55), anaerobic athletes (n = 53) and non-athletes (n = 41). The participants were tested at the Department of Physiology, Faculty of Medicine of the University of Novi Sad. Anthropometric parameters and body mass index were measured. Also, the body fat mass was determined by bioelectrical impedance. pulmonary parameters by spirometry and maximum oxygen consumption on a bicycle ergometer. Results. The body mass index values in non-athletes were the highest and significantly different compared to the aerobic athletes (p = 0.01). Also, non-athletes had significantly higher values of body fat mass compared to athletes (p < 0.001). The pulmonary parameters were not significantly different between the tested groups (p > 0.05). However. the values of maximum oxygen consumption were significantly different between all three tested groups (aerobic athletes 53.75 ± 7.82 ml/kg/min; anaerobic athletes 48.04 ± 6.79 ml/kg/min; non-athletes 41.95 ± 8.53 ml/kg/min) (p < 0.001). A low degree of correlation was found between maximum oxygen consumption and pulmonary parameters in the tested groups. Conclusion. Body composition has an impact on the pulmonary parameters. The values of maximum oxygen consumption depend on the type of sport and training. and the highest values are in aerobic sports. There is a low degree of correlation between maximum oxygen consumption and pulmonary parameters in the tested groups.

Background: Population aging is accompanied by progressive immune remodeling, chronic low-grade inflammation, and increased susceptibility to neurodegenerative diseases. Although the microbiota–gut–brain axis is increasingly recognized as a regulator of neuroimmune homeostasis, mechanisms linking age-associated dysbiosis with immunosenescence, barrier dysfunction, and brain aging remain incompletely understood. This review integrates current evidence into the proposed Gut–Immune–Brain Resilience Axis (GIBRA), a systems-level model describing how microbial signaling shapes neuroimmune resilience during aging. Methods: A structured narrative review was conducted using PubMed and the Web of Science Core Collection from database inception up to July 2026. Evidence from systematic reviews, meta-analyses, consensus statements, mechanistic and translational studies, longitudinal cohorts, randomized clinical trials, and observational studies was synthesized. Results: Current evidence supports an important role for the disruption of microbial functional signaling in neuroimmune aging, while microbial taxonomy and functional profiles provide complementary levels of biological information. Reduced short-chain fatty acid production, dysregulated tryptophan metabolism, microbial translocation, endotoxin-mediated innate immune activation, and gut-conditioned adaptive immune responses promote immunosenescence, inflammaging, barrier dysfunction, and microglial priming. The proposed Double-Barrier Hypothesis links intestinal and blood–brain barrier dysfunction as complementary mechanisms underlying chronic neuroinflammation. GIBRA highlights functional microbiome endotypes, biomarkers, multi-omics, and artificial intelligence as emerging tools for precision medicine. Conclusions: GIBRA provides an integrated systems biology perspective connecting microbial signaling, immune resilience, barrier integrity, and brain resilience during aging. Prioritizing functional resilience over microbial taxonomy may improve biomarker discovery, patient stratification, and microbiome-targeted interventions for neurodegenerative disease prevention. Prospective longitudinal studies integrating multi-omics are needed to support clinical translation.

Various biomarkers like certain complete blood cell count parameters and the derived ratios including neutrophil–lymphocyte ratio are commonly used to evaluate disease severity. Our study aimed to establish if baseline levels of complete blood cell count-derived biomarkers and CRP, measured before any treatment which can interfere with their values, could serve as a predictor of development of pneumonia and the need for hospitalization requiring oxygen therapy. We retrospectively analyzed the laboratory data of 200 consecutive patients without comorbidities, who denied usage of medications prior to blood analysis and visited a COVID-19 ambulance between October and December 2021. Multivariate regression analysis extracted older age, elevated CRP and lower eosinophil count as significant independent predictors of pneumonia (p = 0.003, p = 0.000, p = 0.046, respectively). Independent predictors of hospitalization were higher CRP (p = 0.000) and lower platelet count (p = 0.005). There was no significant difference in the neutrophil–lymphocyte and platelet–lymphocyte ratios between examined groups. Individual biomarkers such as platelet and eosinophil count might be better in predicting the severity of COVID-19 than the neutrophil–lymphocyte and platelet–lymphocyte ratios.

Introduction. The difference between 24-hour daily energy intake and total daily energy expenditure determines whether we lose or gain weight. The resting metabolic rate is the major component of daily energy expenditure, which depends on many different factors, but also on the level of physical activity. The aim of the study was to determine anthropometric and metabolic parameters of athletes engaged in different types of training, to compare obtained results and to examine whether there are statistically significant differences among them. Material and Methods. The study included a total of 42 young male athletes divided into two groups. The first group included 21 athletes who were predominantly engaged in aerobic type of training, and the other group of 21 athletes in anaerobic type of training. Anthropometric measurements were taken and resting metabolic rate was assessed using the indirect calorimetry method. The results were statistically analyzed and the differences in parameters between the two groups were compared. Results. Statistically significant differences were established in total body mass, amount of fat-free mass and muscle mass, body mass index, as well as in the relative metabolic indices between two groups of subjects. Conclusion. The percentage of fat-free body mass has the greatest impact on the resting metabolic rate. The rate of metabolic activity of this body compartment is higher in athletes engaged in aerobic than in athletes engaged in anaerobic type of training.