Allometric Scaling of Force-velocity Test Output Among Pre-pubertal Basketball Players.

Basketball is characterized by high-intensity episodes predominantly reliant on anaerobic metabolism. The force-velocity test enables individual determination of an optimal braking force and emerged as appropriate to estimate optimal peak power. It has rarely been used in youth basketball. This study aimed to examine the contribution of body size, composition, and biological maturation to interindividual variation in force-velocity test output among pre-pubertal basketball players. The sample consisted of 64 male participants (8.4-12.3 years). Stature, sitting height, body mass and two skinfolds were measured, and leg length estimated. Fat-free mass and lower limb volume were estimated from anthropometry. Age at peak height velocity was predicted from maturity offset. Optimal peak power was correlated with all body size descriptors (correlation: 0.541-0.700). Simple allometric models explained 30-47% of inter-individual variance, with fat-free mass being the best predictor of performance. Whole-body fat-free mass (as a surrogate for active muscle mass) plus the indicator of maturation emerged as the best proportional allometric model (53% explained variance). Even at pre-pubertal ages, the interpretation of the force-velocity test requires assessing the metabolically active component of body mass.

Diferenças em populações de células exterminadoras naturais (Natural Killers-NK) sanguíneas periféricas entre atletas de caiaque e não atletas / Differences in peripheral blood Natural Killer cell populations between elite kayakers and non-athletes

INTRODUÇÃO: O exercício estressante prolongado tem sido associado a uma depressão transitória da função imune, com rotinas de treinamento e competição intensas e prolongadas capazes de levar os atletas a uma deficiência imune. OBJETIVO: O objetivo deste estudo foi observar se o treinamento cr ônico foi capaz de produzir diferenças sustentáveis no sangue periférico (SP) subpopulações de leucócitos (LEU, granulócitos, monócitos, linfócitos totais, linfócitos B e T, e células CD4+ e CD8+T e células natural killers) de atletas de caiaque de elite quando comparados com não atletas. MÉTODOS: A amostra incluiu 13 homens atletas de caiaque de elite, 20 ± 3 anos, 75,0kg ± 7,9 peso e 177,3 ± 7,1 cm estatura. O VO2max foi 58,3 ± 7,8mL.kg.min-1. O grupo de não atletas incluiu sete homens saudáveis, idade 18 ± 1 ano de idade, 81,3 ± 13,8Kg de peso corporal e 171,9 ± 4,5cm de estatura. As amostras de sangue dos atletas foram coletadas no início da temporada de treinamento, após um período fora do treinamento de seis semanas. Populações de células sanguíneas periféricas foram identificadas por análise de citometria de fluxo. Para identificar as diferenças entre os grupos de atletas e não atletas, o teste U de Mann-Whitney foi utilizado. RESULTADOS: N ão foram identificadas diferenças entre os atletas de caiaque treinados e não atletas em repouso, exceto para células natural killers (CD3-CD56+) e os valores da subpopulação CD3-CD56+CD8+ os quais foram mais baixos nos atletas. CONCLUSÃO: Nosso estudo encontrou que, após um período prolongado sem treinamento (seis semanas), somente a população de NK CD3-CD56+ e, em especial, a subpopulação de altamente citotóxica CD3-CD56+CD8+ apresentou níveis mais baixos nos atletas de elite quando comparados com os homens destreinados.

INTRODUCTION: Prolonged strenuous exercise has been associated with a transient depression of immune function, with prolonged intense training schedules and competition able to lead to immune impairment in athletes. OBJETIVE: The objective of this study was to see if chronic training was able to produce sustained differences in the peripheral blood (PB) leukocyte subpopulations (WBC, granulocytes, monocytes, total lymphocytes, B and T lymphocytes, CD4+ and CD8+ T cells and Natural Killer cells) of elite kayakers when compared to non-athletes. METHODS: The sample comprised 13 elite male kayakers, 20 ± 3 years old, 75.0 kg ±7.9 weight and 177.3±7.1 cm stature. The VO2max was 58.3±7.8 mL.kg.min-1. The Non-athlete group comprised 7 health males, aged 18±1 years old, 81.3±13.8 kg of weight and 171.9±4.5cm stature. The athlete's blood samples were collected at the beginning of the training season, after an off period of six weeks of training. Peripheral blood cell populations were identified by flow cytometry analysis. To verify the differences between the athlete and non-athlete groups the Mann-Whitney U Test was used. RESULTS: No differences between the trained kayakers and the non-athletes were found at rest except for Natural Killer cells (CD3-CD56+) and the CD3-CD56+CD8+ subset values that were lower in the athletes. CONCLUSION: Our study found that after a prolonged time without training (six weeks) only the NK CD3-CD56+ population and particularly the highly cytotoxic CD3-CD56+CD8+ subpopulation had lower levels in the elite athletes when compared to the untrained men.

Haematological changes in elite kayakers during a training season.

This study monitored haematological markers in response to training load in elite kayakers during a training season. The sample comprised eight elite kayakers aged 22 ± 4.2 years with a 77.2 ± 6.7 kg body mass and a 177.5 ± 5.6 cm stature. The initial [Formula: see text]O(2max) was 61.2 ± 5.5 mL·kg(-1)·min(-1). The control group consisted of six healthy males, aged 18.6 ± 1.1 years, with an 81.3 ± 13.8 kg body mass and a 171.9 ± 4.5 cm stature. Blood samples were collected at the beginning of the training season after an off-training period of six weeks (t(0)), at the 11th week after the application of high training volumes (t(1)), at the 26th week after an intense training cycle (t(2)), and at the 31st week at the end of a tapering phase (t(3)). Differences between time points were detected using ANOVA and the Bonferroni post hoc test. Significant changes were found after the intense training cycle (t(2)), lymphocytes decreased while haemoglobin, mean corpuscular volume, mean corposcular haemoglobin, mean concentration of corpuscular hemoglobin concentration, platelets distribution width, and red blood cell distribution width values increased when compared with baseline values. At t(3), a reduction in monocyte numbers and an increase in mean platelet volume compared with baseline values were seen. By reducing the volume and intensity of training, many variables returned to values close to those at baseline. Although many athletes had accumulated responses over time due to training, they still suffered transient changes that appear to be influenced by training load. Haemorheology monitoring may help detect health risks, especially during times of intensified training.