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Short-term fatigue protocols simulating sports participation are scarce and not well-documented in jumplanding sports. Therefore, this study investigated physiological and physical responses following high-intensity, intermittent exercise protocols (HIIPs) with a standardized level of subjective exhaustion (Borg ≥18/20) and a modified fixed version of five circuits (HIIP-5) for future inclusion in biomechanical screening protocols. Twenty male volleyball and basketball players participated in this study to complete the HIIP and the HIIP-5. Physiological and physical variables were assessed before and up to 30 min after cessation of both protocols. Regarding physiological variables, heart rate values increased (+104 bpm, p < 0.001) and remained elevated up to 30 min (+34 bpm, p < 0.001), and blood lactate levels increased (+17 mmol/l, p < 0.001) compared to baseline. Regarding physical variables, decreased jump height (-4 cm, p = 0.001-0.009) and quadriceps muscle strength (p = 0.001-0.050) were observed up to 30 min compared to baseline. The type of the fatigue protocol did not have an effect on the investigated variables (p > 0.05). To conclude, both the HIIP and the HIIP-5 seem valuable tools to induce acute and long-lasting responses, providing a sufficiently large time window of 30 min within which biomechanical markers of injury can be assessed under fatigued conditions in future risk factor screenings. In practice, the fatigue protocol can be terminated after only five circuits if athletes had not yet been stopped at that point due to exhaustion (Borg ≥18/20). [ABSTRACT FROM AUTHOR]

Purpose: Apnea duration is dependent on three factors: oxygen storage, oxygen consumption, hypoxia and hypercapnia tolerance. While current literature focuses on maximal apneas to improve apnea duration, apnea trained individuals use timed-repeated submaximal apneas, called "O2 and CO2 tables". These tables claim to accommodate the body to cope with hypoxia and hypercapnia, respectively. The aim of this study was twofold. First, to investigate the determinants of maximal apnea duration in apnea novices. Second, to compare physiologic responses to maximal apneas, O2 and CO2 tables. Methods: After medical screening, lung function test and hemoglobin mass measurement, twenty-eight apnea novices performed three apnea protocols in random order: maximal apneas, O2 table and CO2 table. During apnea, peripheral oxygen saturation (SpO2), heart rate (HR), muscle (mTOI) and cerebral (cTOI) tissue oxygenation index were measured continuously. End-tidal carbon dioxide (EtCO2) was measured before and after apneas. Results: Larger lung volumes, higher resting cTOI and lower resting EtCO2 levels correlated with longer apnea durations. Maximal apneas induced greater decreases in SpO2 (− 16%) and cTOI (− 13%) than O2 (− 8%; − 8%) and CO2 tables (− 6%; − 6%), whereas changes in EtCO2, HR and mTOI did not differ between protocols. Conclusion: These results suggest that, in apnea novices, O2 and CO2 tables did not induce a more profound hypoxia and hypercapnia, but a similar reduction in oxygen consumption than maximal apneas. Therefore, apnea novices should mainly focus on maximal apneas to improve hypoxia and hypercapnia tolerance. The use of specific lung training protocols can help to increase oxygen storage capacity. [ABSTRACT FROM AUTHOR]

Purpose: To examine the differences in training load (TL) metrics when quantifying training sessions differing in intensity and duration. The relationship between the TL metrics and the acute performance decrement measured immediately after the sessions was also assessed. Methods: Eleven male recreational cyclists performed 4 training sessions in a random order, immediately followed by a 3-km time trial (TT). Before this period, participants performed the time TT in order to obtain a baseline performance. The difference in the average power output for the TTs following the training sessions was then expressed relative to the best baseline performance. The training sessions were quantified using 7 different TL metrics, 4 using heart rate as input, 2 using power output, and 1 using the rating of perceived exertion. Results: The load of the sessions was estimated differently depending on the TL metrics used. Also, within the metrics using the same input (heart rate and power), differences were found. TL using the rating of perceived exertion was the only metric showing a response that was consistent with the acute performance decrements found for the different training sessions. The Training Stress Score and the individualized training impulse demonstrated similar patterns but overexpressed the intensity of the training sessions. The total work done resulted in an overrepresentation of the duration of training. Conclusion: TL metrics provide dissimilar results as to which training sessions have higher loads. The load based on TL using the rating of perceived exertion was the only one in line with the acute performance decrements found in this study. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the physical profile and training program of a world-class lightweight double sculls rowing crew toward the Tokyo 2020 Olympics. Method: A case study in which both rowers performed physical testing in November 2020 and April 2021 (anthropometrics, incremental rowing test, and power profiling). The training program (38 wk) in the buildup to the Olympics was analyzed, providing insight into training characteristics (volume; contribution of rowing, alternative, and strength training; prescribed and recorded [heart rate] training-intensity distribution). The entire period was split into 3 phases: preparation period (8 wk), competition period 1 (11 wk), and competition period 2 (9 wk), and training characteristics were compared. Results: In the April 2021 testing, rower A (1.89 m, 74.6 kg, 4.4% body fat) had a peak oxygen uptake of 5.8 L·min−1 (77.8 mL·min−1·kg−1) and a peak power output of 491 W. Rower B (1.82 m, 70.6 kg, 7.8% body fat) had a peak oxygen uptake of 5.5 L·min−1 (77.9 mL·min−1·kg−1) and a peak power output of 482 W. The mean weekly training volume was 14 hours 47 minutes (4 h 5 min), of which 58.5% (14.6%) consisted of rowing, 13.4% (6.8%) strength training, and 28.1% (2.6%) alternative training. Heart-rate training-intensity distribution was 77.8% (4.2%) in zone 1, 16.6% (3.7%) in zone 2, and 5.6% (2.8%) in zone 3 with a lower contribution of zone 1 in competition period 1 (P =.029) and competition period 2 (P =.023) compared with the preparation period, and a higher contribution of zone 3 in competition period 1 (P =.018) and competition period 2 (P =.011) compared with the preparation period. Conclusion: The crew combined a high volume of rowing, alternative, and strength training in a pyramidal heart-rate training-intensity distribution throughout the year. [ABSTRACT FROM AUTHOR]

The article focuses on evaluating the performance of metabolic carts, MetaLyzer 3B and Oxycon Pro, for cardiopulmonary exercise testing under different climatic conditions. Topics discussed include the comparison of these carts, their accuracy and reliability, and their suitability for use in various environmental settings.

Standards may create market power for the holders of standard essential patents (SEPs). To address these concerns, the literature advocates price commitments, whereby SEP holders commit to the maximum royalty they would charge were their technology included in the standard. We consider a setting in which a technology implementer holds private information about profitability. In this setting, price commitments increase efficiency not only by curbing SEP holders' market power, but also by alleviating distortions in the design of the royalty scheme. We derive conditions under which price commitments can be implemented using a simple royalty cap as used in practice. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this commentary is to outline some of the pitfalls when using the fitness–fatigue model to unravel the interaction between training load and performance. By doing so, we encourage sport scientists and coaches to interpret the parameters from the model with some extra caution. Conclusions: Caution is needed when interpreting the fitness–fatigue model since the parameter values are influenced by the starting parameter values, the modeling technique, and the input of the model. Also, the use of general constants should be avoided since they do not account for interindividual differences and differences between training-load methods. Therefore, we advise sport scientists and coaches to use the model as a way to work more data-informed rather than working data-driven. [ABSTRACT FROM AUTHOR]

Purpose: This study aimed to determine the influencing factors of potential differences in sleep architecture between elite (EG) and nonelite (NEG) female artistic gymnasts. Methods: Twelve EG (15.1 [1.5] y old) and 10 NEG (15.3 [1.8] y old) underwent a nocturnal polysomnography after a regular training day (5.8 [0.8] h vs 2.6 [0.7] h), and, on a separate test day, they performed an incremental treadmill test after a rest day in order to determine physical fitness status. A multiple linear regression assessed the predictive value of training and fitness parameters toward the different sleep phases. Total sleep time and sleep efficiency (proportion of time effectively asleep to time in bed), as well as percentage of nonrapid eye movement sleep phase 1 (NREM1) and 2 (NREM2), slow wave sleep (SWS), and rapid eye movement sleep (REM), during a single night were compared between EG and NEG using an independent-samples t test. Results: Peak oxygen uptake influenced NREM1 (β = 1.035, P =.033), while amount of weekly training hours predicted SWS (β = 1.897, P =.032). No differences were documented between EG and NEG in total sleep time and sleep efficiency. SWS was higher in EG (36.9% [11.4%]) compared with NEG (25.9% [8.3%], P =.020), compensated by a lower proportion of NREM2 (38.7% [10.2%] vs 48.4% [6.5%], P =.017), without differences in NREM1 and REM. Conclusions: The proportion of SWS was only predicted by weekly training hours and not by training hours the day of the polysomnography or physical fitness, while NREM1 was linked with fitness level. Sleep efficiency did not differ between EG and NEG, but in EG, more SWS and less NREM2 were identified. [ABSTRACT FROM AUTHOR]

Purpose: Numerous methods exist to quantify training load (TL). However, the relationship with performance is not fully understood. Therefore the purpose of this study was to investigate the influence of the existing TL quantification methods on performance modeling and the outcome parameters of the fitness-fatigue model. Methods: During a period of 8 weeks, 9 subjects performed 3 interval training sessions per week. Performance was monitored weekly by means of a 3-km time trial on a cycle ergometer. After this training period, subjects stopped training for 3 weeks but still performed a weekly time trial. For all training sessions, Banister training impulse (TRIMP), Lucia TRIMP, Edwards TRIMP, training stress score, and session rating of perceived exertion were calculated. The fitness-fatigue model was fitted for all subjects and for all TLmethods. Results: The error in relating TL to performance was similar for all methods (Banister TRIMP: 618 [422], Lucia TRIMP: 625 [436], Edwards TRIMP: 643 [465], training stress score: 639 [448], session rating of perceived exertion: 558 [395], and kilojoules: 596 [505]). However, the TL methods evolved differently over time, which was reflected in the differences between the methods in the calculation of the day before performance on which training has the biggest positive influence (range of 19.6 d). Conclusions: The authors concluded that TL methods cannot be used interchangeably because they evolve differently. [ABSTRACT FROM AUTHOR]