Influence of training status on cardiac and vascular functioning in young recreational and competitive male rowers.

Introduction: The aim of the study was to investigate the influence of training status on cardiovascular function in young male recreational and competitive rowers. Methods: Ejection duration in percentage to the heart rate period (ED%), subendocardial viability ratio (SEVR), augmentation index at 75 bpm (AIx75) and carotid to femoral pulse wave velocity (cf-PWV) of competitive rowers (CR) (age 17.6 ± 4.1 years), recreational rowers (RR) (age 16.7 ± 2.70 years) and athletes practicing other recreational sports (ORS) (age 15.3 ± 1.4 years) were assessed. Results: ED% was lower in CR compared to ORS (31.9 ± 3.9% vs. 38.4 ± 4.8%; p = 0.026) and cf-PWV was higher in CR compared to ORS (5.5 ± 1.0 m/s vs. 4.7 ± 0.5 m/s; p = 0.032). SEVR was higher in CR compared to RR and ORS (165.8 ± 33.7% vs. 127.4 ± 30.4% and 128.3 ± 27.8%; p = 0.022) and AIx75 was lower in CR compared to RR and ORS (-15.7 ± 8.6% vs. 1.2 ± 9.9% and 1.5 ± 9.1; p = 0.001). Discussion: Healthy, young competitive male rowers reported higher myocardial performance and better cardiovascular health than recreational athletes. Interpretations of cf-PWV in competitive rowers should be performed alongside other cardiovascular indicators.

Acute Effects of Fitlight Training on Cognitive-Motor Processes in Young Basketball Players.

Cognitive-motor training could be used to improve open-skill sport performances, increasing cognitive demands to stimulate executive function (EF) development. Nevertheless, a distributed training proposal for the improvement of EFs is increasingly difficult to combine with seasonal sport commitments. This study aimed to investigate whether a massed basketball training program enriched with Fitlight training can improve EFs and motor performance. Forty-nine players (age = 15.0 ± 1.5 yrs) were assigned to the control and Fitlight-trained (FITL) groups, which performed 3 weeks of massed basketball practice, including 25 min per day of shooting sessions or Fitlight training, respectively. All athletes were tested in cognitive tasks (Flanker/Reverse Flanker; Digit Span) and fitness tests (Agility T-test; Yo-Yo IR1). During the intervention, exercise/session perceived effort (eRPE/sRPE) and enjoyment were collected. RM-ANOVA showed significant EFs scores increased in both groups over time, without differences between the groups. Moreover, an increased sRPE and eRPE appeared in the FITL group (p = 0.0001; p = 0.01), with no group differences in activity enjoyment and fitness tests. Three weeks of massed basketball training improved EFs and motor performance in young players. The additional Fitlight training increased the perceived cognitive effort without decreasing enjoyment, even if it seems unable to induce additional improvements in EFs.

Live Streaming vs. Pre-Recorded Training during the COVID-19 Pandemic in Italian Rhythmic Gymnastics.

The SARS-CoV-2 outbreak led to an inevitable and drastic transition to online training systems. This study aimed to analyze the differences between live-streaming and pre-recorded training modalities in rhythmic gymnastics (RG) with coaches and gymnasts of different technical levels. A total of 238 coaches and 277 athletes affiliated with the Italian Gymnastics Federation (FGI) participated in the study. The data collection tool was a self-collected questionnaire structured in three sections: participant's information, characteristics of live-streaming training, and characteristics of pre-recorded training. A 2 × 2 ANOVA was used for each numeric variable. A Pearson's chi-squared test was used for each categorical variable. For the athletes, training frequency, motivation, and efficacy were significantly higher (p < 0.05) with live streaming (3.7 ± 1.5 day/week, 3.8 ± 0.9 score and 3.8 ± 0.8 score, respectively) than with a pre-recorded modality (2.2 ± 1.7 day/week, 3.1 ± 1.2 score and 3.7 ± 0.9 score, respectively), while for coaches, significant differences (p < 0.005) were found between the two modalities only for training frequency (live streaming, 3.6 ± 1.8 days/week vs. pre-recorded, 2.1 ± 1.7 days/week). The adherence (number of No:Yes) was significantly higher (p < 0.05) for the live-streaming modality than for the pre-recorded modality in gold athletes (1:74 vs. 14:61, respectively), silver athletes (12:190 vs. 28:174, respectively), and gold coaches (3:63 vs. 11:55, respectively), but it was not for silver coaches. Physical preparation was performed significantly (p < 0.005) more often (number of No:Yes) for live streaming than for the pre-recorded modality by gold athletes (9:66 vs. 34:41, respectively), silver athletes (25:177 vs. 77:125, respectively), gold coaches (8:58 vs. 37:29), and silver coaches (33:139 vs. 85:87, respectively). Free body technical preparation was performed significantly (p < 0.005) more often (number of No:Yes) for live streaming than for the pre-recorded modality by gold athletes (15:60 vs. 39:36, respectively), silver athletes (84:118 vs. 121:81, respectively), gold coaches (10:56 vs. 38:28), and silver coaches (60:112 vs. 105:67, respectively), while no differences were found for silver athletes' and coaches' technical preparations for apparatus training between the two modalities. In conclusion, live streaming had greater positive effects on RG training during home confinement. However, pre-recorded training could be more effective for some types of training, depending on the technical level of the athletes.

Detecting Metabolic Thresholds from Nonlinear Analysis of Heart Rate Time Series: A Review.

Heart rate time series are widely used to characterize physiological states and athletic performance. Among the main indicators of metabolic and physiological states, the detection of metabolic thresholds is an important tool in establishing training protocols in both sport and clinical fields. This paper reviews the most common methods, applied to heart rate (HR) time series, aiming to detect metabolic thresholds. These methodologies have been largely used to assess energy metabolism and to identify the appropriate intensity of physical exercise which can reduce body weight and improve physical fitness. Specifically, we focused on the main nonlinear signal evaluation methods using HR to identify metabolic thresholds with the purpose of identifying a method which can represent a useful tool for the real-time settings of wearable devices in sport activities. While the advantages and disadvantages of each method, and the possible applications, are presented, this review confirms that the nonlinear analysis of HR time series represents a solid, robust and noninvasive approach to assess metabolic thresholds.

Nutrition and Physical Activity-Induced Changes in Gut Microbiota: Possible Implications for Human Health and Athletic Performance.

The gut microbiota is a complex heterogeneous microbial community modulated by endogenous and exogenous factors. Among the external causes, nutrition as well as physical activity appear to be potential drivers of microbial diversity, both at the taxonomic and functional level, likely also influencing endocrine system, and acting as endocrine organ itself. To date, clear-cut data regarding which microbial populations are modified, and by which mechanisms are lacking. Moreover, the relationship between the microbial shifts and the metabolic practical potential of the gut microbiota is still unclear. Further research by longitudinal and well-designed studies is needed to investigate whether microbiome manipulation may be an effective tool for improving human health and, also, performance in athletes, and whether these effects may be then extended to the overall health promotion of general populations. In this review, we evaluate and summarize the current knowledge regarding the interaction and cross-talks among hormonal modifications, physical performance, and microbiota content and function.

Recurrence quantification analysis of heart rate variability to detect both ventilatory thresholds.

Aims of this study were: to verify if Recurrence Quantification Analysis (RQA) of Heart Rate Variability (HRV) time series could determine both ventilatory thresholds in individuals with different fitness levels, and to assess the validity of RQA method compared to gas-exchange method (GE). The two thresholds were estimated in thirty young individuals during incremental exercise on cycle-ergometer: Heart rate (HR), Oxygen consumption (VO2) and Workload were measured by the two methods (RQA and GE). Repeated measures ANOVA was used to assess main effects of methods and methods-by-groups interaction effects for HR, VO2 and Workload at aerobic (AerT) and anaerobic (AnT) thresholds. Validity of RQA at both thresholds was assessed for HR, VO2 and Workload by Ordinary Least Products (OLP) regression, Typical Percentage Error (TE), Intraclass Correlation Coefficients (ICC) and the Bland Altman plots. No methods-by-groups interaction effects were detected for HR, VO2 and Workload at AerT and AnT. The OLP analysis showed that at both thresholds RQA and GE methods had very strong correlations (r >0.8) in all variables (HR, VO2 and Workload). Slope and intercept values always included the 1 and the 0, respectively. At AerT the TE ranged from 4.02% (5.48 bpm) to 10.47% (8.53 Watts) (HR and Workload, respectively) and in all variables ICC values were excellent (≥0.85). At AnT the TE ranged from 2.53% (3.98 bpm) to 6.64% (7.81 Watts) (HR and Workload, respectively) and in all variables ICC values were excellent (≥0.90). Therefore, RQA of HRV time series is a new valid approach to determine both ventilatory thresholds in individuals with different physical fitness levels, it can be used when gas analysis is not possible or not convenient.