Three Simulated Goalball Games in the Same Day Cause Central Fatigue and Can Impair Game Technical Performance.

The purpose of this study was to investigate the effects of three simulated goalball games on neuromuscular, physiological, perceptual, and technical parameters. Ten male players underwent assessments before and immediately after each game. Heart rate was recorded at rest and during all games that were entirely filmed for further technical performance analysis. Exercise significantly decreased knee extensor muscles peak force and percentage of voluntary activation after the second and third games, indicating the presence of central fatigue. Heart rate responses remained predominantly in a range equivalent to moderate activity intensity in all games. In addition, perceptual parameters were associated with reduced frequency of throws and density of actions. These findings suggest significant implications for the management of physical training, game strategy during a competition, and fixture change from three to two games per day.

Metformin anticipates peak of lactate during high-intensity interval training but no changes performance or neuromuscular response in amateur swimmers.

BACKGROUND & AIMS: Metformin demonstrated potential to improve metabolic efficiency in short-intense and prolonged-continuous efforts. The present study investigates the acute effects of metformin intake on performance, rating of perceived exertion (RPE), blood lactate, blood glucose and neuromuscular parameters related to swimming high-intensity interval series. METHODS: A double-blind, crossover, randomized and placebo-controlled study was carried out. Seven healthy swimmers ingested metformin (500 mg) or placebo capsules on different days and performed a typical high-intensity training series (10 bouts of 50 m with a 3-min interval). Performance, RPE, neuromuscular parameters (lower and upper limbs), blood lactate and glucose were analyzed by the Wilcoxon Signed-Rank and Friedman's tests between supplementation situations and moments, respectively (p > 0.05), the moment where glucose and blood lactate peak were found were analyzed by a Student t-test (p > 0.05) and a Bayesian repeated-measures ANOVA for effects analysis (BFincl). RESULTS: The anticipation of blood glucose and peak lactate was signaling by the interaction effect (metformin increased and placebo decreased) between the eighth and the last bout (BFincl: 4.230 and 5.188 respectively). The second interaction effect of blood glucose and lactate (metformin maintained and placebo increased) during recoveries between 5 min and 7 min (BFincl: 3.825 and 3.806 respectively) also signaling the anticipatory behavior of both physiological parameters. The anticipation of blood lactate peak concentration after metformin intake confirms the anticipatory behavior of blood lactate (p: 0.015). CONCLUSIONS: The anticipatory behavior of glucose was not confirmed. Although the anticipatory peak of blood lactate, metformin does not affect neuromuscular responses, RPE and performance. REGISTRATION OF CLINICAL TRIAL: RBR-67wxdw8 Effects of metformin during swimmer training performance.

Corrigendum: Proposal of a Conditioning Activity Model on Sprint Swimming Performance.

[This corrects the article DOI: 10.3389/fphys.2020.580711.].

Determination of Maximum Accumulated Oxygen Deficit Using Backward Extrapolation.

This study aimed to compare the Maximum Accumulated Oxygen Deficit determined by the conventional method (MAODC) with that determined by the backward extrapolation technique (MAODEXTR) in runners. Fourteen runners underwent a maximal incremental test for determination of iVO2MAX, ten submaximal efforts (50-95% of iVO2MAX for 7 min). During the submaximal efforts oxygen consumption (VO2) values were obtained conventionally and through the backward extrapolation technique (~ 3 s after the end of each effort). A supramaximal effort (110% of iVO2MAX) (tLimC) and five supramaximal bouts (tLimEXTR) were performed. MAODC and MAODEXTR were determined from the difference between the VO2 accumulated during tLimC and tLimEXTR and the predicted values. The tLimC was lower than tLimEXTR (164.06±36.32 s, 200.23±63.78 s, p<0.05). No significant differences were found between absolute and relative MAODC and MAODEXTR values, however, low intraclass correlations (0.26 and 0.24), high typical errors (2.03 L and 24 mL∙kg-1) were observed, and coefficients of variation (46 and 48%), respectively. The graphical analysis of the differences showed agreement and correlation between the methods (r=0.86 and 0.85). Thus, it can be concluded that the MAODEXTR is not a valid method for estimating the anaerobic capacity of runners, moreover, unreliable.

Proposal of a Conditioning Activity Model on Sprint Swimming Performance.

This study aimed to propose a conditioning activity (CA) model to stimulate improvement on neuromuscular responses, mechanical parameters and for the 50-m freestyle swimming. Thirteen male swimmers (19 ± 3 years and performances of 77% in relation to World Championship records) performed four CA protocols followed by a maximum performance in the 50-m freestyle. In the first protocol (P1) swimmers performed a standard warm-up (∼15 min); in the second protocol (P2) lunges (3 × 85% of the one-repetition maximum); in the third (P3) pull-ups (3 maximum repetitions) and box jumps 40 cm high and 60 cm deep (1 × 5 with 10% of the corporal weight); and in the fourth protocol (P4) a combination of exercises from the second and third protocols. CA protocols had no effect on the standard warm-up. However, P2 performance (27.01 ± 1.25 s) was similar to P1 (27.01 ± 1.18 s) and presented higher positive effects in mechanical parameters for the swim start performance in comparison to other protocols, contributing to improvements in the 50-m freestyle. In addition, turnaround time also had a negative effect, mainly in P3 (3.12 ± 0.28 s), signaling the improvement of this variable in all protocols (P1: 3.30 ± 0.38 s; P2: 3.17 ± 0.30 s; P4: 3.17 ± 0.34 s). P2 (after: 80 ± 11%; before: 82.7 ± 9.9%) and P3 (after: 82.7 ± 9.9%; before: 85.1 ± 9.7%) presented a possible positive effect on the percentage of voluntary activation in relation to P1 (after: 79.3 ± 10.7%; before: 76.3 ± 12%). In conclusion, the proposed conditioning activity protocols were not efficient for performance improvement in the 50-m freestyle compared to the standard model and seem to specifically influence each phase of the event.

A New Approach to Evaluate Neuromuscular Fatigue of Extensor Elbow Muscles.

Neuromuscular fatigue evaluation is widely performed on different muscles through the conventional protocol using maximum voluntary contraction (MVC) with electrical stimuli in the analyzed muscle. In an attempt to use this protocol on elbow extensor musculature, previous studies and pilot studies showed co-contraction effects from antagonist musculature during muscular stimulations. The aim of this study was to propose a new neuromuscular fatigue protocol evaluation on elbow extensor musculature. Twenty participants preformed exercises to induce central (CenFat) and peripheral fatigue (PerFat). Neuromuscular fatigue was evaluated on knee extensor muscles by a conventional protocol that provides Twitch Superimposed (TSK) and Twitch Potentiated (TPK), central and peripheral parameters respectively. For elbow extensor muscles, the protocol used sustained submaximal contraction at 10, 20, 30, 40, and 50% of MVC. The neuromuscular fatigue in upper limbs was identified by Twitch Potentiated (TPE) and multiple Twitch Superimposed (TSE) parameters. Using the relationship between MVC (%) and evoked force, the proposed protocol used several TSE to provide slope, y-intercept and R 2. It is proposed that slope, R 2, and y-intercept change may indicate peripheral fatigue and the identified relationship between y-intercept and R 2 may indicate central fatigue or both peripheral and central fatigue. The results were compared using the non-parametric analyzes of Friedmann and Wilcoxon and their possible correlations were verified by the Spearmann test (significance level set at p < 0.05). After PerFat a decrease in TPE (57.1%, p < 0.001) was found but not in any TSE, indicating only peripheral fatigue in upper limbs. After CenFat a decrease in TPE (21.4%, p: 0.008) and TPK (20.9%, p < 0.001) were found but not in TSK, indicating peripheral fatigue in upper and lower limbs but not central fatigue. A non-significant increase of 15.3% after CenFat and a statistical reduction (80.1%, p: 0.001) after PerFat were found by slope. Despite R 2 showing differences after both exercises (p < 0.05), it showed a recovery behavior after CenFat (p: 0.016). Although PerFat provided only peripheral fatigue, CenFat did not provide central fatigue. Considering the procedural limitations of CenFat, parameters resulting from the proposed protocol are sensitive to neuromuscular alteration, however, further studies are required.