Tukey mean difference plot suggested there was no bias, with a mean difference (SD) of -0.16 (1.8) and respective 95% confidence interval of 3.5. The kappa agreement for the descriptive ratings between the two approaches was found to be moderate (k = 0.54, p less then 0.01). Overall, the results suggest the VCS could potentially be an alternative to the conventional TGMD-2 assessment approach for assessing children's locomotor skills without the necessity of the presence of an experienced rater for the administration.Bioelectrical impedance analysis (BIA) is a common practice to assess body composition in athletes, however, when measuring athletes with specific body geometry, its accuracy may decrease. In this study we examined how length dimensions affect body composition estimation and we compared BIA and dual-energy X-ray absorptiometry (DXA) assessments in three sports. 738 male adolescent athletes (15.8 ± 1.4 years) from three sports (soccer, basketball, and handball) were measured. Body composition was estimated by BIA (InBody 720) and by DXA (Lunar Prodigy). Differences between the two methods were tested by Bland-Altman analysis and by paired t-test. ANOVA was used for inter-group comparisons. Pearson correlation and multivariate linear regression was used to look for the relationship between segmental lean body mass and length dimensions. BIAInBody 720 consistently underestimated percent body fat (PBF) and overestimated lean body mass (LBM) than DXA. The magnitude of the differences between the two methods varied among the examined sports. Handball (PBF = 8.3 ± 2.4 %; LBM = -5.0 ± 2.1 kg) and basketball players (PBF = 8.8 ± 2.3 %; LBM = -5.3 ± 1.8 kg) had significantly larger differences between the two methods than soccer players (PBF = 6.4 ± 2.2 %; LBM = -3.1 ± 1.4 kg). There was a negative correlation between differences in segmental LBM estimation and length sizes (trunk length, upper extremity length, lower extremity length). The highest correlation was found for lower extremity (r = -0.4). Longer lower extremity resulted in greater difference in LBM estimation. The differences between the sport disciplines are most probably attributed to body height differences. Length dimensions result in overestimation of LBM with BIA, thus body composition assessment with BIAInBody 720 needs to be carefully interpreted in athletes with extreme length sizes, especially, with basketball players.After lower extremity injury, only half of the injured athletes return to their pre-injury sports level. Even though functional performance tests are often used to make return to sport decisions, it is unknown whether functional performance is associated with return to performance after such injuries. The aim of this systematic review was to identify, critically appraise, and analyze studies that investigated the association of functional performance tests with return to performance after lower extremity injuries in athletes participating in high-impact sports. MEDLINE, Embase, Web of Science, and CINAHL were systematically searched for relevant studies. Articles were independently screened by two authors and data were obtained from each included study using a data extraction form. Two authors independently scored methodological quality using the Quality In Prognosis Studies tool. A qualitative best evidence synthesis was conducted. Eight studies reported the association of functional performance with return ociated with return to performance after lower extremity injuries in athletes practicing high-impact sports.  https://www.selleckchem.com/products/BIBF1120.html  Low quality evidence suggests small associations after anterior and posterior cruciate ligament reconstruction. No evidence exists for lower extremity injuries other than after anterior or posterior cruciate ligament reconstruction. Therefore, research on functional performance associated with return to performance is recommended in high-quality prospective cohort studies including athletes with any type of lower extremity injury.To elucidate the fluid regulation in different menstrual cycle phases during exercise. Sex hormones affect fluid regulation in different ways. Moreover, the renin angiotensin-aldosterone system is activated in the luteal phase in rest. However, there are limited studies on fluid regulation affected by such hormone excretion in the menstrual cycle during exercise, especially during a light walking exercise. A non-invasive method using urine samples to determine menstrual cycle phases was used, and the follicular and luteal phases were successfully confirmed in 10 participants (age, 21 ± 1 years; body mass index, 20.5 ± 2.1 kg/m2). The experimental exercise sessions consisted of 5-min standing and 15-min walking at 2 km/h on 15% slope (approximately 8.3°) on a treadmill. Each participant carried a backpack weighing 5% of her own weight, and performed three sessions of walking exercise. Urine aldosterone excretion was significantly higher in the luteal than in the follicular phase before and after walking (p less then 0.05). Urinary excretion of aldosterone was five times higher in the luteal than in the follicular phase before and after walking exercise. Heart rates during walking, after rest, and after recovery were all significantly higher in the luteal than in the follicular phase (p less then 0.05). The participants' ratings of perceived exertion during the first and third session of walking in the luteal phase was not higher than that at the follicular phase. The results of our study suggested that increased activity of the renin-angiotensin-aldosterone system in the luteal phase of the menstrual cycle might be further activated during exercise. This may increase the circulatory load, which is reflected as increased heart rate. These results suggested that premenopausal women may better take into account a possibility of an increased circulatory load in the luteal phase even when they perform light exercise.The purpose of this study was (a) to determine the effects of an 8-week jump training program on measures of neuromuscular performance in 12-14-year-old boys before and after peak height velocity (PHV), and (b) to compare the effects of the jump training program to the effects of the regular physical education program. One hundred and twenty-six participants were categorized into two maturity groups (pre- or post-PHV) and then randomly assigned to either a jump training (pre-PHV, n = 26; post-PHV, n = 24) or a control (pre-PHV, n = 33; post-PHV, n = 19) group. Jump training consisted of twice-weekly training for 8 weeks, while control groups continued with their regular physical education lessons. Squat jump and countermovement jump height (cm), reactive strength index (the ratio between jump height and ground contact time (mm/ms)), 20-m sprint time (s), and isokinetic knee extensors muscle strength (peak toque (Nm)) were assessed pre- and post-intervention. Following the 8-week intervention, both pre- and post-PHV jump training groups made significant gains in measures of neuromuscular performance irrespective of the maturity (where p less then 0.