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Rafaela Nehme, Flávia M.S. de Branco, Públio F. Vieira, Ana Vitória C. Guimarães, Gederson K. Gomes, Gabriela P. Teixeira, Pedro H. Rodrigues, Leonardo M. de Castro Junior, Guilherme M. Puga, Bryan Saunders, and Erick P. de Oliveira

Carbohydrate (CHO) mouth rinsing seems to improve performance in exercises lasting 30–60 min. However, its effects on intermittent exercise are unclear. It is also unknown whether serial CHO mouth rinses can promote additional ergogenic effects when compared with a single mouth rinse. The aim of this study was to evaluate the effect of single and serial CHO mouth rinses on Yo-Yo Intermittent Recovery Test Level 1 (Yo-Yo IR1) performance in soccer players. In a randomized, crossover, double-blind, placebo-controlled design, 12 male (18.9 ± 0.5 years) soccer players performed eight serial mouth rinses under three different conditions: placebo solution only (noncaloric juice), seven placebo mouth rinses plus a single CHO mouth rinse (8% maltodextrin), or eight CHO mouth rinses (8-CHO). Following the final mouth rinse, individuals performed the Yo-Yo IR1 test to evaluate the maximal aerobic endurance performance measured via total distance covered. There were no differences in Yo-Yo IR1 performance between sessions (p = .32; single CHO mouth rinse (8% maltodextrin): 1,198 ± 289 m, eight CHO mouth rinses: 1,256 ± 253 m, placebo: 1,086 ± 284 m). In conclusion, single and serial CHO mouth rinsing did not improve performance during the Yo-Yo IR1 for soccer players. These data suggest that CHO mouth rinsing is not an effective ergogenic strategy for intermittent exercise performance irrespective of the number of rinses.

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Philip Friere Skiba and David C. Clarke

Since its publication in 2012, the W′ balance model has become an important tool in the scientific armamentarium for understanding and predicting human physiology and performance during high-intensity intermittent exercise. Indeed, publications featuring the model are accumulating, and it has been adapted for popular use both in desktop computer software and on wrist-worn devices. Despite the model’s intuitive appeal, it has achieved mixed results thus far, in part due to a lack of clarity in its basis and calculation. Purpose: This review examines the theoretical basis, assumptions, calculation methods, and the strengths and limitations of the integral and differential forms of the W′ balance model. In particular, the authors emphasize that the formulations are based on distinct assumptions about the depletion and reconstitution of W′ during intermittent exercise; understanding the distinctions between the 2 forms will enable practitioners to correctly implement the models and interpret their results. The authors then discuss foundational issues affecting the validity and utility of the model, followed by evaluating potential modifications and suggesting avenues for further research. Conclusions: The W′ balance model has served as a valuable conceptual and computational tool. Improved versions may better predict performance and further advance the physiology of high-intensity intermittent exercise.

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Paulius Kamarauskas, Inga Lukonaitienė, Aaron T. Scanlan, Davide Ferioli, Henrikas Paulauskas, and Daniele Conte

Purpose: To assess weekly fluctuations in hormonal responses and their relationships with load and well-being during a congested in-season phase in basketball players. Methods: Ten semiprofessional, male basketball players were monitored during 4 congested in-season phase weeks consisting of 3 weekly matches. Salivary hormone variables (testosterone [T], cortisol [C], and T:C ratio) were measured weekly, and external load (PlayerLoad™ and PlayerLoad per minute), internal load session rating of perceived exertion, percentage of maximum heart rate (HR), summated HR zones, and well-being were assessed for each training session and match. Results: Significant (P < .05) moderate to large decreases in T were found in the third and fourth weeks compared with the first week. Nonsignificant moderate to large decreases in C were apparent in the last 2 weeks compared with previous weeks. Summated HR zones and perceived sleep significantly (P < .05) decreased in the fourth week compared with the first week; whereas, percentage of maximum HR significantly (P < .05) decreased in the fourth week compared with the second week. No significant relationships were found between weekly changes in hormonal responses and weekly changes in load and overall wellness. Conclusions: A congested schedule during the in-season negatively impacted the hormonal responses of players, suggesting that T and C measurements may be useful to detect fluctuations in hormone balance in such scenarios. The nonsignificant relationships between weekly changes in hormonal responses and changes in load and well-being indicate that other factors might induce hormonal changes across congested periods in basketball players.

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Vincenzo Rago, Adrian Muschinsky, Kasper Deylami, Magni Mohr, and Jeppe F. Vigh-Larsen

Purpose: The aim of this study was to compare training load (TL) between practice and games across in-season microcycles in elite Danish male ice hockey. Methods: Practice sessions and game data were collected using a wearable 200-Hz accelerometer, heart rate (HR) recording, and rating of perceived exertion (RPE) throughout 23 practice sessions and 8 competitive games (n = 427 files) and examined in relation to the number of days before the game (game day minus). Results: Total accelerations, accelerations >2 m·s−1 (Acc2), total decelerations, decelerations less than −2 m·s−1 (Dec2), time >85% maximum heart rate (t85HRmax), Edwards TL, modified training impulse (TRIMPMOD), session-RPE, peak HR (HRpeak), and RPE were greater during competition than during practice (r = .19–.91; P < .05), whereas total accelerations per minute and total decelerations per minute were lower (r = .27–.36; P < .001). Acc2, t85HRmax, Edwards TL and TRIMPMOD, % t85HRmax, mean HR (HRmean), and RPE progressively decreased toward game day (r = .13–.63; P < .001). Positive correlations were found between Acc2, Dec2, Acc2 per minute, and Dec2 per minute during practice and during competition (r = .66–.84; P < .001). Conclusions: Evident within-week decreases in internal TL but not external TL were observed as the game day approached. Day-to-day variations were more pronounced in HR- and RPE-based parameters than accelerations and decelerations. Finally, the amount of intense accelerations and decelerations performed during practice was associated to the amount performed during competition, whereas physiological and perceptual demands showed no such relationship.

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Arilene M.S. Santos, Alberto J. Maldonado, Antônio V.M. de Sousa Junior, Susi O.S. Brito, Rayane C. de Moura, Caique Figueiredo, Paula A. Monteiro, Lucas M. Neves, Ismael F. Freitas Junior, Marcos A.P. dos Santos, Sergio L.G. Ribeiro, and Fabrício E. Rossi

Purpose: To analyze peripheral brain-derived neurotrophic factor (BDNF) levels and psychophysiological parameters in youth badminton athletes during the season and to determine the relationship between variables. Methods: Fourteen young badminton athletes were assessed over the season (preseason, middle season, and final season). Serum BDNF (sBDNF) was determined during the preseason and final season. Sleep time, total physical activity, and time in vigorous activity were measured using an accelerometer. The fat-free mass, skeletal muscle mass, fat mass, handgrip strength, cardiorespiratory fitness (VO2max), and dietary intake were evaluated during the season. The Stroop Color and Word Test was employed to assess cognitive tasks. To evaluate the mood, the Brunel Mood Scale was used. Results: There  were lower sBDNF levels (−16.3% [46.8%]; P = .007) and sleep time (final season = 5.7 [1.1] vs preseason = 6.6 [1.1] h·night−1, P = .043) during the end of the season. The total calories and carbohydrate intake decreased across the season (P < .05). Conversely, better cognitive function was found in the final season with respect to the preseason (P < .05). There were significant correlations between BDNF and VO2max only in the preseason (r = .61, P = .027), but no significant relationship was found among sBDNF and cognitive performance, sleep time, and percentage of won games. Conclusions: Youth badminton athletes decreased their sBDNF levels, sleep time, carbohydrate, and calorie intake across the season. The athletes improved in cognitive function; however, only the females improved in body composition, and the males improved their VO2max in the middle season. The sBDNF levels were positively correlated with the VO2max in the preseason, and no correlations were observed among the sBDNF and psychological parameters, sleep time, and sport performance during the season.

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Jacob N. Kisiolek, Kyle A. Smith, Daniel A. Baur, Brandon D. Willingham, Margaret C. Morrissey, Samantha M. Leyh, Patrick G. Saracino, Cheri D. Mah, and Michael J. Ormsbee

The relationship between sleep duration, sleep quality, and race completion time during each stage of a 3-day ultra-endurance triathlon (stage 1: 10-km swim, 146-km cycle; stage 2: 276-km cycle; and stage 3: 84.4-km run) was investigated. Seventeen triathletes partook in sleep analysis throughout the ultra-endurance multiday triathlon using an actigraphy wristband. The participants wore the band to record objective sleep outcomes for approximately 4 days (1–2 d prerace, 3 race days, and 1 d postrace), except while racing. The total sleep time (TST; prerace: 414.1 [95.3] min, prestage 1: 392.2 [138.3] min, prestage 2: 355.6 [62.5] min, and prestage 3: 299.7 [107.0] min) significantly decreased over time (P < .05). Significant Pearson moment–product correlations were found between TST and subsequent race–day performance for race stage 1 (r = −.577; P = .019) and stage 3 (r = −.546; P = .035), with further analysis revealing that TST explained 33% and 30% of the variation in performance for stages 1 and 3, respectively. During a 3-day ultra-endurance triathlon, the TST was reduced and had a significant negative correlation to exercise performance, indicating that sleep loss was associated with slower performances. Sleep onset latency, wake episodes, and sleep efficiency did not significantly change over the course of this investigation, which may stem from the close proximity of exercise to sleep.

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Matthew J. McAllister, Joni A. Mettler, Kyle Patek, Matthew Butawan, and Richard J. Bloomer

This study investigated the effects of 6 mg/day of astaxanthin supplementation on markers of oxidative stress and substrate metabolism during a graded exercise test in active young men. A double-blind, randomized, counterbalanced, cross-over design was used. Fourteen men (age = 23 ± 2 years) supplemented with 6 mg/day of astaxanthin and a placebo for 4 weeks, with a 1 week washout period between treatments. Following each supplementation period, a fasting blood sample was obtained to measure markers of oxidative stress: glutathione, hydrogen peroxide, advanced oxidation protein products, and malondialdehyde. Participants also completed a graded exercise test after each treatment to determine substrate utilization during exercise at increasing levels of intensity. Glutathione was ∼7% higher following astaxanthin compared with placebo (1,233 ± 133 vs. 1,156 ± 185 μM, respectively; p = .02, d = 0.48). Plasma hydrogen peroxide and malondialdehyde were not different between treatments (p > .05). Although not statistically significant (p = .45), advanced oxidation protein products were reduced by ∼28%. During the graded exercise test, mean fat oxidation rates were not different between treatments (p > .05); however, fat oxidation decreased from 50 to 120 W (p < .001) and from 85 to 120 W (p = .004) in both conditions. Astaxanthin supplementation of 6 mg/day for 4 weeks increased whole blood levels of the antioxidant glutathione in active young men but did not affect oxidative stress markers or substrate utilization during exercise. Astaxanthin appears to be an effective agent to increase endogenous antioxidant status.

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Shahin Minaei, Morteza Jourkesh, Richard B. Kreider, Scott C. Forbes, Tacito P. Souza-Junior, Steven R. McAnulty, and Douglas Kalman

The purpose was to investigate the effects of CYP1A2 −163C > A polymorphism on the effects of acute caffeine (CAF) supplementation on anaerobic power in trained males. Sixteen trained males (age: 21.6 ± 7.1 years; height: 179.7 ± 5.6 cm; body mass: 72.15 ± 6.8 kg) participated in a randomized, double-blind, placebo (PLA) controlled crossover design. Participants supplemented with CAF (6 mg/kg of body mass) and an isovolumetric PLA (maltodextrin) in random order and separated by 7 days, before an all-out 30-s anaerobic cycling test to determine peak, average, and minimum power output, and fatigue index. Genomic deoxyribonucleic acid was extracted to identify each participants CYP1A2 genotype. Six participants expressed AA homozygote and 10 expressed C alleles. There was a treatment by genotype interaction for peak power output (p = .041, η2 = .265, observed power = 0.552) with only those expressing AA genotype showing improvement following CAF supplementation compared with PLA (CAF: 693 ± 108 watts vs. PLA: 655 ± 97 watts; p = .039), while no difference between treatments was noted in those expressing C alleles (CAF: 614 ± 92 watts vs. PLA: 659 ± 144 watts; p = .135). There were no other interaction or main effects for average or minimum power output, or fatigue index (p > .05). In conclusion, the ingestion of 6 mg/kg of CAF improved peak power output only in participants with the AA genotype compared with PLA; however, expression of the CYP1A2 did not influence average or minimum power output or fatigue index.

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Rune K. Talsnes, Roland van den Tillaar, and Øyvind Sandbakk

Purpose: To compare the effects of increased load of low- versus high-intensity endurance training on performance and physiological adaptations in well-trained endurance athletes. Methods: Following an 8-week preintervention period, 51 (36 men and 15 women) junior cross-country skiers and biathletes were randomly allocated into a low-intensity (LIG, n = 26) or high-intensity training group (HIG, n = 25) for an 8-week intervention period, load balanced using the overall training impulse score. Both groups performed an uphill running time trial and were assessed for laboratory performance and physiological profiling in treadmill running and roller-ski skating preintervention and postintervention. Results: Preintervention to postintervention changes in running time trial did not differ between groups (P = .44), with significant improvements in HIG (−2.3% [3.2%], P = .01) but not in LIG (−1.5% [2.9%], P = .20). There were no differences between groups in peak speed changes when incremental running and roller-ski skating to exhaustion (P = .30 and P = .20, respectively), with both modes being significantly improved in HIG (2.2% [3.1%] and 2.5% [3.4%], both P < .01) and in roller-ski skating for LIG (1.5% [2.4%], P < .01). There was a between-group difference in running maximal oxygen uptake changes (P = .04), tending to improve in HIG (3.0% [6.4%], P = .09) but not in LIG (−0.7% [4.6%], P = .25). Changes in roller-ski skating peak oxygen uptake differed between groups (P = .02), with significant improvements in HIG (3.6% [5.4%], P = .01) but not in LIG (−0.1% [0.17%], P = .62). Conclusion: There was no significant difference in performance adaptations between increased load of low- versus high-intensity training in well-trained endurance athletes, although both methods improved performance. However, increased load of high-intensity training elicited better maximal oxygen uptake adaptations compared to increased load of low-intensity training.