Physiological adaptations to various types of prolonged and intensive physical activity, as seen in elite athletes from different sports, include changes in blood pressure (BP) response to acute exercise. Also, functional polymorphisms of the angiotensin I converting enzyme (ACE) and alfa-actinin-3 (ACTN3) genes are shown to be associated with BP parameters changes, both in athletes and sedentary population. In this study, an Alu insertion (I)/deletion (D) polymorphism in ACE gene, as well as nonsense mutation in the gene encoding ACTN3 have been scored in 107 elite Serbian athletes classified according to their sporting discipline to power/sprint (short distance runners/swimmers), endurance (rowers, footballers, middle-distance swimmers) or mixed sports (water polo, handball, volleyball players). Presence of nonfunctional allele in ACTN3 is associated with significantly increased maximal systolic BP (SBPmax, p = 0.04). Athletes with Alu insertion in ACE had significantly (p = 0.006) larger decline of systolic BP after 3 minutes of recovery (SBPR3), calculated as the percentage of maximal SBP response during exercise stress testing. Concomitant presence of non-functional variant in ACTN3 gene decreased this beneficiary effect of ACE mutation on SBPR3. Long term enrollment in power/sprint sports significantly increased resting diastolic BP (DBPrest: 74 mmHg) and SBPmax (197 mmHg) and improved SBPR3 (74.8%) compared to enrolment in endurance (72 mmHg; 178 mmHg; 81.1%) and mixed sports (69 mmHg; 185 mmHg; 80.0%). Lack of the effect of genotype by sport interaction on BP parameters suggests that the long-term effects of different disciplines on BP are not mediated by these two genes.

Objective: We sought to investigate the prevalence of smoking and lung function in the large cohort of elite athletes. Methods: This cross-sectional study included 804 athletes competing at international level who were consecutively examined from January to December 2017. Elite athletes were classified in four groups of sport disciplines (skill, power, endurance and mixed): skill (n = 141), power (n = 107), endurance (n = 105) and mixed sport disciplines (n = 451). All participants underwent pre-participation screening, including spirometry. Results: Study included 745 (92.7%) non-smokers, 20 (2.5%) former smokers and 39 (4.8%) active smokers. The percentage of body fat was higher and the percentage of muscle was lower in active smokers than in non-smokers and former smokers. Active smokers were more prevalent among skill and mixed than in power and endurance sports. FEV1 and FVC, as well as FEV1/FVC ratio, were significantly lower in active smokers than in non-smokers. There was no significant difference in PEF assessed in absolute values and in percentages. Forced expiratory flows, evaluated at the usual intervals (25%, 50% and 75% of FVC), were significantly lower in active smokers than in non-smokers. FEV1 and MEF25 were the lowest among active smokers in the skill sport group, whereas FEV1/FVC, MEF50 and MEF25 were the lowest among active smokers in the power sport group. In mixed and endurance disciplines there was no difference in pulmonary function between non-smokers, former smokers and active smokers. Conclusions: Pulmonary function was reduced in active smokers and these differences were the most prominent in skill and power sports. The percentage of body fat was the highest and percentage of muscle was the lowest in active smokers.

Purpose: The purpose of this study is to determine heart rate (HR) recovery after maximal test in elite athletes who compete in high dynamic, high static, and in mixed sport disciplines; to assess differences in HR recovery between these groups of athletes; and to measure the association of HR index (HRI) with heart adaptation variables to determine whether these values were correlated with the type of exercise. Methods: One hundred and ninety-four elite athletes were divided into three groups according to the predominant type of exercise performed: endurance (n = 40), strength-sprinter (n = 36), and ball-game players (n = 118). They performed maximal cardiopulmonary exercise testing on a treadmill and were subjected to echocardiography. The rate of decline (HR recovery) was calculated as the difference between maximum and recovery HRs (HRrec1 and HRrec3). The HRI was calculated as HR_max – 1-min post-exercise HR (HRrec1). Results: The most significant correlation of HRI was with posterior wall diameter and left ventricular (LV) mass index (r = 0.43 and r = 0.51; p = 0.012 and p = 0.003, respectively). LV mass index [Beta (B) = 0.354, p = 0.001] was an independent predictor of HRI and HRrec1. HRI may be an effective tool for discrimination of physiological and “gray zone” LV hypertrophy, with area under the curve of 0.545 (95% CI = 0.421–0.669, p = 0.0432). HRI displayed a sensitivity of 50% and specificity of 52.2% at the optimal cut-off value of 23.5. Conclusion: HR recovery pattern, especially HRI, may offer a timely and efficient tool to identify athletes with autonomous nervous system adaptive changes.

Aim The variety of individual basketball position shows that the determination of certain parameters such as aerobic and anaerobic threshold metabolic testing method helps to improve some parameters and sport performance. Basketball is a sport that requires a certain level of skills at both the individual and group level. This is a sport in which there is a constant change of rhythm, requiring a high level of aerobic power (because it allows training that lasts longer and on an elite level) as well as anaerobic power but also incorporates muscle strength, endurance and flexibility. The aim is to determine the ergospirometric parameters (VO2 max, levels of aerobic and anaerobic threshold) using one of the modified protocols for testing to assess current level of physical fitness and training prior to entering the competition season. Methods The total number of participants is 68 players (junior teams of Serbia), 15 to 18 years of age, body weight (range 66.3 kg/110.7 kg), body height (range 180 cm/213 cm), BMI (range 18.17/26.8 kg m-²). Ergospirometric parameters were examined in our laboratory for functional diagnostic: VO2max (ml/min/kg), HR VAT (RER ∼ 1), HR AT, RER max, AT HR (% HRmax) and compared among players of same and different team position. The test of maximum oxygen consumption was performed using a Treadmill T200 Cosmed, using method breath by breath pulmonary gas exchange (O2, CO2 and Quark CPET, COSMED). To assess VO2max we used Shvartz E. Reinbold RC (1990) tables for an adequate age (grades 1 to 7, as required by the tables). Results Maximum oxygen consumption by player position shows that it is the largest in positions 1 and 2 (as shown in the chart). VO2 (ml/min/kg) ranges between 44.55 - 52.85 (the highest in the point guard position (1), slightly lower for shooting guard (2), small forward (3) and power forwards (4) and the lowest in the centres (5). Conclusion By determining VO2max metabolic testing methods come to the conclusion that the players are currently estimated as follows: • moderate/average/good (grade 3 to 5 per Shvartz E.Rainbold RC) between the ages of 15 and 17 years • good/excellent (grade 4 to 5 per Shvartz E.Rainbold RC) at 18 years and by playing position, they are estimated by the following marks: 4 to 5 position point guard and shooting guard 3 to 5 at the small forward and power forwards position 2 to 4 at the centre position as the current and real value of positions that are played in the national team (keeping in mind the characteristics of the sport). Assessment of current level of physical fitness and training of basketball players shows that junior player fitness level can be categorised based on position on the team but also can be improve with professional training approach. Future studies should explore possibility of individual approach in relation to the requirements of the position they have in the team.