نوشین آزادپور

Purpose: Vigorous physical exercise causes notable alterations in the circulatory system, affecting stress hormones and plasma proteins. Cortisol serves as a primary glucocorticoid hormone, while albumin, globulin, and hemoglobin function as important carrier proteins. However, how cortisol levels after exercise interact with these proteins is not well understood. This research aimed to explore the association between serum cortisol and the levels of albumin, globulin, and hemoglobin following a single session of intense aerobic exercise in young male runners. Method: Twelve healthy young male runners (average age 21.38 ± 0.95 years; VO₂max 50.81 ± 2.35 ml/kg/min) completed a 15-minute Balke treadmill test. Blood samples were collected before exercise, immediately after, and three hours post-exercise (recovery) to assess serum cortisol, albumin, globulin, and hemoglobin concentrations. Hematocrit measurements were used to adjust for changes in plasma volume. Statistical analysis involved one-way repeated measures ANOVA with Tukey’s post hoc test and Pearson correlation. Results: Immediately after exercise, there were significant increases in cortisol (61.4%), albumin (7.5%), globulin (10.5%), and hemoglobin (10.5%) (p<0.05). After three hours of recovery, cortisol, albumin, and hemoglobin levels returned to baseline, whereas globulin remained significantly elevated (p<0.05). No significant correlations were detected between cortisol changes and any of the carrier proteins at any time point (p>0.05). Conclusion: A single session of intense aerobic exercise markedly raises serum cortisol and key carrier proteins in young runners. The absence of correlation between cortisol and these proteins suggests that their immediate post-exercise increases are likely driven by factors other than cortisol fluctuations, such as hemoconcentration and changes in hydrostatic pressure, rather than direct hormonal stimulation.

Background: The "athlete's heart" syndrome encompasses structural and functional cardiac adaptations to chronic exercise. These sports impose unique hemodynamic loads, potentially leading to distinct remodeling patterns. Objective: This study aimed to compare central cardiovascular adaptations, both structural and functional, in elite male athletes from basketball, volleyball, and handball to identify sport-specific differences. Methods: Thirty male athletes (aged 18-25; n=10 per sport group) participated in this cross-sectional study. All participants underwent comprehensive transthoracic echocardiography at rest and immediately following a maximal graded exercise test (GXT) on a treadmill. Key measured parameters included left ventricular (LV) dimensions, wall thickness, mass, ejection fraction (EF), stroke volume, and cardiac output. Data were analyzed using One-Way ANOVA or the Kruskal-Wallis test, with post-hoc analyses where appropriate. Results: While most parameters indicated a common adaptive athlete’s heart profile across all sports, significant sport-specific differences were found. Handball players exhibited a significantly higher heart rate post-GXT (180.11±9.45bpm) compared to both basketball and volleyball players (p<0.01). Furthermore, ejection fraction was significantly different between all groups at rest (p<0.05), with handball players also demonstrating a superior EF post-GXT compared to the other groups (p<0.05). A significant difference in left ventricular end-systolic dimension was also observed at rest between all three sports (p<0.001). Conclusion: The significant differences in post-exercise heart rate and ejection fraction, particularly in handball players, suggest that the pronounced upper-body and isometric components of handball impose a unique hemodynamic stress, leading to distinct functional adaptations. This underscores the importance of sport-specific interpretation of cardiac parameters in athletes.

Purpose: This study aimed to compare respiratory parameters and sleep quality between physically active and inactive young adult males, while exploring correlations between these domains. Method: In a semi-experimental design, 15 active males (aged 20–23 years; ≥8 hours/week moderate-to-vigorous activity; >2 years sports experience) and 15 inactive males (≤3 hours/week activity; no sports experience) were recruited. Anthropometric measures (height, weight, BMI, body fat percentage, heart rate) were assessed. Pulmonary function—including forced vital capacity (FVC), vital capacity (VC), maximum voluntary ventilation (MVV), forced expiratory volume in one second (FEV1), percentage predicted FEV1 (%FEV1), and maximum expiratory flows at 25% and 75% of FVC (MEF25%, MEF75%)—was evaluated via spirometry (Fukuda ST-95) per American Thoracic Society guidelines. Sleep quality was quantified using the Pittsburgh Sleep Quality Index (PSQI). Independent t-tests compared groups; Pearson correlations and multiple linear regressions examined associations (α = 0.05). Results: Active participants displayed superior respiratory metrics ( p < 0.05): higher FVC ( p = 0.023), VC ( p = 0.002), MVV ( p = 0.001), FEV1 ( p = 0.001), %FEV1 ( p = 0.001), MEF25% ( p = 0.026), and MEF75% ( p = 0.042). PSQI scores were significantly lower (better) in the active group (4.13 ± 1.18) versus inactive (6.53 ± 2.50; p = 0.002). No baseline differences emerged in age, height, weight, heart rate, fat percentage, or BMI ( p > 0.05). In the active group, each 1-unit increase in FEV1, MVV, VC, FVC, and MEF75% was associated with corresponding reductions in sleep quality scores of 0.217, 0.127, 0.370, 0.386, and 0.194 units, respectively (all p > 0.05). Regressions and correlations between respiratory indices and sleep quality were non-significant in both groups. Conclusion: Regular physical activity enhances sleep quality and respiratory function in young males, though direct mechanistic links were not evident in this cohort. These findings advocate exercise as a non-pharmacological strategy for addressing sleep and pulmonary health, warranting larger, diverse studies to elucidate interactions.