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Objectives: Assess the effect of water dousing on heat strain and performance during self- and fixed-paced exercise in the heat. Design: Crossover, block-randomized controlled trial. Methods: Thirteen trained runners completed a 10-km time trial (TT) and 60-minute fixed-pace run (60% velocity of $\dot{\mathrm{V}}{\mathrm{O}}_2\text{max}$ ) in a 30.4 °C, 47.4% relative humidity environment using either water dousing (DOUSE) or no dousing (CON). Results: Ten-kilometer TT performance was faster in DOUSE compared to CON (44:11 [40:48, 47:34] vs 44:38 [41:21, 47:56] min:s; P = .033). Change in core temperature (T _c ) was not different between groups during the TT (+0.02 [−0.04, 0.07] °C in DOUSE; P = .853) or fixed-pace run (+0.02 [−0.15, 0.18] °C; P = .848). Change in mean skin temperature was lower in DOUSE during the TT (−1.80 [−2.15, −1.46] °C; P < .001) and fixed-pace run (−1.38 [−1.81, −0.96] °C; P < .001). Heart rate was lower for DOUSE during the fixed-pace run (−3.5 [−6.8, −0.2] beats/min; P = .041) but not during the TT (−0.2 [−2.5, 2.1] beats/min; P = .853). Thermal sensation was lower for DOUSE during the TT (−49.3 [−72.1, −26.1] mm; P < .001) and fixed-pace run (−44.7 [−59.7, −29.6] mm; P < .001). Rating of perceived exertion was not different between groups for the TT (−0.2 [−0.7, 0.3]; P = .390) or fixed-pace run (−0.2 [−0.8, 0.4]; P = .480). Sweat rate was lower for DOUSE for the TT (−0.37 [−0.53, −0.22] L/h; P < .001) and fixed-pace run (−0.37 [−0.48, −0.26] L/h; P < .001). Conclusion: Water dousing improves 10-km TT performance in the heat but does not affect T _c . The positive change in thermal perception (via lower skin temperature) during the TT likely drives this benefit.

Purpose: We investigated the effects of manipulating running velocity and hypoxic exposure on vastus lateralis muscle oxygenation levels during treadmill running. Methods: Eleven trained male distance runners performed 7 randomized runs at different velocities (8, 10, 12, 14, 16, 18, and 20 km·h⁻¹), each lasting 45 seconds on an instrumented treadmill in normoxia (fraction of inspired oxygen [FiO₂] = 20.9%), moderate hypoxia (FiO₂ = 16.1%), high hypoxia (FiO₂ = 14.1%), and severe hypoxia (FiO₂ = 13.0%). Continuous assessment of Tissue Saturation Index (TSI) in the vastus lateralis muscle was conducted using near-infrared spectroscopy. Subsequently, changes in TSI (ΔTSI) data over the final 20 seconds of each run were compared between velocities and conditions. Results: There was a significant velocity × condition interaction for ΔTSI% (P < .001, ${\eta }_{\mathrm{p}}^2=.19$ ), with a smaller ΔTSI% decline in normoxia compared with high hypoxia and severe hypoxia at 8 km·h⁻¹ (g = 1.30 and 1.91, respectively), 10 km·h⁻¹ (g = 0.75 and 1.43, respectively), and 12 km·h⁻¹ (g = 1.47 and 1.95, respectively) (pooled values for all conditions: P < .037). The ΔTSI% decline increased with each subsequent velocity increment from 8 km·h⁻¹ (−9.2% [3.7%]) to 20 km·h⁻¹ (−22.5% [4.1%]) irrespective of hypoxia severity (pooled values for all conditions: P < .048). Conclusions: Running at slower velocities in conjunction with high and severe hypoxia reduces vastus lateralis muscle oxygenation levels. Muscle ΔTSI% proves to be a sensitive indicator, underscoring the potential use of near-infrared spectroscopy as a reference index of internal load during treadmill runs.

Purpose: Antarctic expeditions are exceptional physiological challenges. Sleep plays a critical role in athletic performance, recovery, and wellness, with sleep disturbances having a negative impact on health and performance. Methods: The authors investigated sleep, fatigue, and recovery profiles of the longest solo unsupported one-way polar ski journey across Antarctica. A 33-year-old woman covered 1484.53 km from Hercules Inlet to the South Pole, finishing at the Ross Ice Shelf, in 70 days and 16 hours. Questionnaires on sleep (Pittsburgh Insomnia Rating Scale and Karolinska Sleepiness Scale), fatigue (Subjective Assessment of Fatigue), recovery (Total Quality Recovery), and wellness were completed at different time points (before, during, and after the expedition). Results: Average daily sleep time was between 4 and 5 hours, increasing to 7 hours for the final part of the expedition. Satisfaction of sleep and lack of energy deteriorated as the expedition progressed, alongside signs of clinical insomnia. Fatigue and muscle soreness increased with increasing milage, with extreme levels and very poor recovery toward the end of the expedition. Despite this, the adventurer continued to perform on extremely high levels. Postexpedition scores returned to baseline, demonstrating the incredible adaptation and ability to recovery. The postexpedition interview showed that prior experience of an Antarctic expedition may have prepared the athlete and made her more resilient for this challenge. Conclusions: The data provide unique insights into Antarctic expeditions and may help us understand the limits of human performance when planning future expeditions of this nature. Female athletes are capable of extreme challenges, breaking established performance boundaries.

Purpose: The purpose of this study was to investigate the effects of acute ischemic preconditioning (IPC) on tennis skill and physical exercise performance, as well as to explore whether 7-day repeated IPC (RIPC) accelerated fatigue recovery after a simulated tennis match. Methods: Twenty-nine male tennis-specific current students were randomly allocated into 1 of 2 groups: SHAM (n = 14, 3 × 5 min at 20 mm Hg) and IPC (n = 15, 3 × 5 min at 220 mm Hg). Participants in both groups engaged in acute IPC and RIPC interventions. After the first acute IPC intervention, assessments were conducted to evaluate tennis-specific skills and overall physical exercise capacity. Following completion of chronic RIPC interventions, all participants competed in a simulated tennis match specifically designed to induce fatigue. To evaluate recovery from this induced fatigue, physical exercise capacity tests were conducted at 24 and 48 hours postmatch, allowing for an assessment of the participants’ recovery capabilities over time. Results: After the first acute intervention, notable differences were observed between the IPC and SHAM groups in their performance on the repeated-sprint ability test. Specifically, the total times recorded were significantly shorter in the IPC group compared with the SHAM group (IPC: 109.05 [2.70] vs SHAM: 114.57 [7.45] s, P = .012), and this trend was also reflected in their best times (IPC: 4.20 [0.18] s vs SHAM: 4.39 [0.30] s, P = .042), indicating an immediate benefit of the IPC intervention on sprint performance. After a 7-day RIPC intervention, significant changes were noted in the SHAM group’s performance metrics postmatch. There was an increase (P < .001) in fatigue index from 22% (8%) to 30% (9%) during repeated-sprint ability test and a decrease in serve speed from 120.2 (17.5) to 106.7 (13.0) km/h (P = .002) and knee peek torque from 196.0 (49.0) to 162.7 (39) N (extension, 60°/s, P < .001) in the SHAM group 24 hours postmatch, relative to the IPC group. Moreover, compared with the SHAM group, the IPC group showed a lower rate of perceived exertion during the match (P < .001) and a decrease in visual analog scale score (P = .026) 24 hours postmatch, suggesting enhanced recovery and reduced perception of pain relative to the SHAM group. Conclusion: IPC could serve as a strategy to generate an ergogenic effect and recovery during training and competition.

Purpose: To gather information on practices and perceptions of high-performance experts regarding their athletes’ muscle fiber-type composition (MFTC) and its estimation. Methods: A questionnaire on the noninvasive versus invasive estimation of MFTC was completed by 446 experts including coaches and sport-science/sports-medicine staff. Moreover, the perceived importance of MFTC for training and performance optimization was assessed. Differences between sport types (individual and team sports) were analyzed using chi-square tests. Results: Forty percent of the experts implemented MFTC assessment in pursuit of performance optimization, while 50% did not know their athletes’ MFTC but expressed a desire to implement it if they would be able to assess MFTC. Ten percent did not perceive value in MFTC assessment. Only 18% of experts believed that their athletes would undergo a muscle biopsy, leading to the adoption of alternative noninvasive techniques. Experts primarily relied on their experience to estimate MFTC (65%), with experts working in individual sports using their experience more frequently than those working in team sports (68% vs 51%; P = .009). Jump tests emerged as the second-most commonly employed method for estimating MFTC (56%). When only considering experts who are currently using MFTC, 87% use MFTC to individualize training volume and 84% to individualize training intensity. Conclusions: Experts value MFTC assessment primarily to individualize training but mainly rely on noninvasive methods to estimate MFTC. Some of these methods lack scientific validity, suggesting a continuing need for education and further research in this area.

Purpose: Jump and linear sprint performances both correlate with pro-agility performance. However, correlation does not imply causation, and potential confounders may affect the correlation. Therefore, this study aimed to determine the relationship between change-of-direction (COD) performance and COD deficits (COD-D) in linear-sprint and countermovement-jump (CMJ) -related performance using multiple stepwise linear-regression models. Methods: The study included 42 female national-level intercollegiate athletes. The 10- and 20-m linear-sprint and pro-agility times, COD-D, CMJ height, and phase-specific force production and rate of force development during eccentric unloading, eccentric braking, and the concentric phases of CMJ were measured. Stepwise linear-regression analyses were used to predict the factors related to COD and COD-D. Results: CMJ height was the sole predictor in the 10-m pro-agility model (adjusted R ² = .234, P = .001). Modified Reactive Strength Index (standardized coefficient, −.710) and the lowest center-of-mass depth during the CMJ (standardized coefficient, .323) were predictors in the 20-m pro-agility model (adjusted R ² = .330, P < .001). For the 10- and 20-m COD-D models, the rate of force development at 30 and 60 milliseconds, respectively, during the concentric phase was the only predictor of performance (adjusted R ² = .183, P = .003 and .237, P = .001, respectively). Conclusions: These results suggest that athletes should concentrate on improving their CMJ height, increasing their ability to lower their center of mass more deeply, and increasing their instantaneous force-production abilities immediately after the eccentric braking phase of CMJ to improve their COD performance.