Exploring sex differences in blood-based biomarkers following exhaustive exercise using bioinformatics analysis.

This study examined the acute effects of exercise testing on immunology markers, established blood-based biomarkers, and questionnaires in endurance athletes, with a focus on biological sex differences. Twenty-four healthy endurance-trained participants (16 men, age: 29.2± 7.6 years, maximal oxygen uptake ( V ˙ O 2 max ): 59.4 ± 7.5 ml · min-1 · kg-1; 8 women, age: 26.8 ± 6.1 years, V ˙ O 2 max : 52.9 ± 3.1 ml · min-1 · kg-1) completed an incremental submaximal exercise test and a ramp test. The study employed exploratory bioinformatics analysis: mixed ANOVA, k-means clustering, and uniform manifold approximation and projection, to assess the effects of exhaustive exercise on biomarkers and questionnaires. Significant increases in biomarkers (lymphocytes, platelets, procalcitonin, hemoglobin, hematocrit, red blood cells, cell-free DNA (cfDNA)) and fatigue were observed post-exercise. Furthermore, differences pre- to post-exercise were observed in cytokines, cfDNA, and other blood biomarkers between male and female participants. Three distinct groups of athletes with differing proportions of females (Cluster 1: 100% female, Cluster 2: 85% male, Cluster 3: 37.5% female and 65.5% male) were identified with k-means clustering. Specific biomarkers (e.g., interleukin-2 (IL-2), IL-10, and IL-13, as well as cfDNA) served as primary markers for each cluster, potentially informing individualized exercise responses. In conclusion, our study identified exercise-sensitive biomarkers and provides valuable insights into the relationships between biological sex and biomarker responses.

Predicting Injury and Illness with Machine Learning in Elite Youth Soccer: A Comprehensive Monitoring Approach over 3 Months.

The search for monitoring tools that provide early indication of injury and illness could contribute to better player protection. The aim of the present study was to i) determine the feasibility of and adherence to our monitoring approach, and ii) identify variables associated with up-coming illness and injury. We incorporated a comprehensive set of monitoring tools consisting of external load and physical fitness data, questionnaires, blood, neuromuscular-, hamstring, hip abductor and hip adductor performance tests performed over a three-month period in elite under-18 academy soccer players. Twenty-five players (age: 16.6 ± 0.9 years, height: 178 ± 7 cm, weight: 74 ± 7 kg, VO2max: 59 ± 4 ml/min/kg) took part in the study. In addition to evaluating adherence to the monitoring approach, data were analyzed using a linear support vector machine (SVM) to predict illness and injuries. The approach was feasible, with no injuries or dropouts due to the monitoring process. Questionnaire adherence was high at the beginning and decreased steadily towards the end of the study. An SVM resulted in the best classification results for three classification tasks, i.e., illness prediction, illness determination and injury prediction. For injury prediction, one of four injuries present in the test data set was detected, with 96.3% of all data points (i.e., injuries and non-injuries) correctly detected. For both illness prediction and determination, there was only one illness in the test data set that was detected by the linear SVM. However, the model showed low precision for injury and illness prediction with a considerable number of false-positives. The results demonstrate the feasibility of a holistic monitoring approach with the possibility of predicting illness and injury. Additional data points are needed to improve the prediction models. In practical application, this may lead to overcautious recommendations on when players should be protected from injury and illness.

Adding LIT to HIIT: Is Low-Intensity Training Vital for Endurance-Trained Athletes during a 7-day HIIT Shock Microcycle?

PURPOSE: This study aimed to investigate the effects of a 7-d high-intensity interval training shock microcycle (HIIT-SM) with or without additional low-intensity training (LIT) on aerobic fitness and endurance performance compared with a control group (CG). METHODS: Thirty-three endurance-trained athletes (7 women, 26 men, mean ± SD: age, 30.2 ± 6.9 yr; maximal oxygen uptake (V̇O 2max ), 59.8 ± 4.9 mL·min -1 ·kg -1 ) performed exercise testing at T1 and were randomly assigned to one of three groups: i) HSM, 10 running-based HIIT sessions (5 × 4 min at 90%-95% maximal heart rate) over 7 d; ii) HSM + LIT, equal to HSM with additional 30 min of LIT after each HIIT; iii) CG, regular training. Exercise testing was repeated 3 d (T2), 7 d (T3), and 14 d (T4) after the intervention. A 5-km time trial (TT 5km ) was performed 3-4 d before T1 and 10-11 d after the intervention. Data were analyzed by two-way repeated-measures ANOVA. RESULTS: No interaction effect was found for V̇O 2max ( P = 0.170, pη2 = 0.09), peak power output ( P = 0.734, pη2 = 0.04), and work economy ( P = 0.804, pη2 = 0.03). There was an interaction for velocity at lactate threshold ( P = 0.006, pη2 = 0.18) with increased velocity in HSM at T2 (3.2%, P = 0.030), T3 (4%, P = 0.006), T4 (4%, P = 0.003), as well as in HSM + LIT for T2 (3.2%, P = 0.011), whereas CG showed no change. There was an interaction for TT 5km ( P = 0.044, pη2 = 0.19), with HSM improving 2.7% ( P = 0.003) and HSM + LIT 2.3% ( P = 0.010), whereas CG was, on average, -0.3% ( P = 0.821) slower. CONCLUSIONS: HIIT-SM with or without additional LIT has negligible effects on V̇O 2max but improves other key endurance variables in endurance-trained athletes. No superiority of either intervention group was demonstrated. Therefore, additional LIT during HIIT-SM is not beneficial.

A training goal-oriented categorization model of high-intensity interval training.

There are various categorization models of high-intensity interval training (HIIT) in the literature that need to be more consistent in definition, terminology, and concept completeness. In this review, we present a training goal-oriented categorization model of HIIT, aiming to find the best possible consensus among the various defined types of HIIT. This categorization concludes with six different types of HIIT derived from the literature, based on the interaction of interval duration, interval intensity and interval:recovery ratio. We discuss the science behind the defined types of HIIT and shed light on the possible effects of the various types of HIIT on aerobic, anaerobic, and neuromuscular systems and possible transfer effects into competition performance. We highlight various research gaps, discrepancies in findings and not yet proved know-how based on a lack of randomized controlled training studies, especially in well-trained to elite athlete cohorts. Our HIIT "toolbox" approach is designed to guide goal-oriented training. It is intended to lay the groundwork for future systematic reviews and serves as foundation for meta-analyses.

Unraveling the mystery of isocaloric endurance training - Influence of exercise modality, biological sex, and physical fitness.

BACKGROUND: A sedentary lifestyle with low energy expenditure (EE) is associated with chronic diseases and mortality. Barriers such as "lack of time" or "lack of motivation" are common reasons why physical exercise is neglected in the general population. To optimize EE in the time available, time-efficient but also enjoyable types of exercise are required. We therefore used an isocaloric approach to systematically investigate the effects of six different endurance exercise modalities on metabolic, mechanical, cardiorespiratory, and subjective variables in relation to biological sex and physical fitness. METHODS: Out of 104, 92 healthy participants (21 recreationally trained and 18 trained females, 25 recreationally trained and 28 trained males) were subjected to physiological exercise testing to determine the exercise intensities for six exercise modalities, i.e., three different high-intensity interval training (HIIT) protocols (5 × 4 min, 15 × 1 min, 30 × 30 sec intervals), threshold (THR), speed endurance production (SEP), and low-intensity continuous endurance training (LIT). One of three HIIT sessions served as the reference for the subsequent isocaloric exercise modalities which were completed in randomized order. Metabolic and mechanical variables, i.e., EE during exercise, time to isocaloric EE (Tiso), relative and absolute fat contribution, post-exercise oxygen consumption (EPOC), mechanical energy, as well as cardiorespiratory and subjective variables, i.e., heart rate, oxygen uptake response, rating of perceived exertion, and enjoyment were assessed. Data were analyzed using a 6 × 2 × 2 repeated-measures ANOVA. RESULTS: All three versions of HIIT and THR achieved the same EE during exercise for the same training duration. We found that LIT had a 1.6-fold (p < 0.001) and SEP a 1.3-fold (p < 0.001) longer Tiso compared to HIIT with no effects of biological sex (p = 0.42, pη2 = 0.01) or physical fitness (p = 0.09, pη2 = 0.04). There was a main effect of exercise modality on EPOC (p < 0.001, pη2 = 0.76) with highest values for HIIT 30 × 30 (p = 0.032) and lowest for LIT (p < 0.001). The highest relative and absolute amounts of fatty acids were measured during LIT (p < 0.001), and the lowest values were obtained during HIIT modalities. HIIT 30 × 30 was the most enjoyable version of HIIT (p = 0.007), while THR was the least enjoyable exercise modality (p = 0.008). CONCLUSION: HIIT modalities are time-saving and enjoyable, regardless of sex and physical fitness. The results illustrate the relationship between exercise modality and metabolic, physiological, and subjective responses, and are thus of great interest to healthy individuals seeking time-saving and enjoyable exercise options.

Videos using different message strategies to promote the interruption of sedentary behavior in university students during online lectures - A pilot study.

Background: Sedentary behavior (SB) is highly prevalent among university students and has increased during COVID-19 pandemic. As SB is associated with negative health outcomes, appropriate prevention measures in the university setting are needed. Objective: This pilot study aimed at investigating the effects of videos using different message strategies to interrupt SB in the collective of university students during online lectures. Methods: During online lectures, university students (N = 96) were shown one of three videos on the interruption of SB. The videos differed in their message strategies with regard to evidence type (statistical vs. narrative) and vividness (static vs. animated images). Demographics, health variables (SB intentions, SB attitudes) and selected media reception variables (identification, homophily, counterarguing) were examined as possible influence factors on the interruption of SB evoked by watching the video. Results: Approximately half of the students interrupted sedentary behavior during watching the videos and students of the older age group (cut-off: median = 22 years) interrupted SB significantly more often (p = 0.046). The interruption of SB was predicted by SB intentions (p < 0.05). Identification with characters significantly predicted the intentions to reduce SB (p < 0.001), with a large effect of the overall regression model (R2corr = 0.47). Conclusion: Considering the increased digitalization in general and restrictions due to COVID-19 pandemic, videos seem to be a useful tool to interrupt SB among university students during online lectures. Narrative formats could facilitate the intention to reduce SB, which in turn could have a positive impact on the interruption of SB. However, further research on effective communication and message strategies is needed.

Comprehensive training load monitoring with biomarkers, performance testing, local positioning data, and questionnaires - first results from elite youth soccer.

Load management, i.e., prescribing, monitoring, and adjusting training load, is primarily aimed at preventing injury and maximizing performance. The search for objective monitoring tools to assess the external and internal load of athletes is of great interest for sports science research. In this 4-week pilot study, we assessed the feasibility and acceptance of an extensive monitoring approach using biomarkers, neuromuscular performance, and questionnaires in an elite youth soccer setting. Eight male players (mean ± SD: age: 17.0 ± 0.6 years, weight: 69.6 ± 8.2 kg, height: 177 ± 7 cm, VO2max: 62.2 ± 3.8 ml/min/kg) were monitored with a local positioning system (e.g., distance covered, sprints), biomarkers (cell-free DNA, creatine kinase), questionnaires, neuromuscular performance testing (counter-movement jump) and further strength testing (Nordic hamstring exercise, hip abduction and adduction). Feasibility was high with no substantial impact on the training routine and no adverse events such as injuries during monitoring. Adherence to the performance tests was high, but adherence to the daily questionnaires was low, and decreased across the study period. Occasional significant correlations were observed between questionnaire scores and training load data, as well as between questionnaire scores and neuromuscular performance. However, due to the small sample size, these findings should be treated with caution. These preliminary results highlight the feasibility of the approach in elite soccer, but also indicate that modifications are needed in further large-scale studies, particularly in relation to the length of the questionnaire.

The Salzburg 10/7 HIIT shock cycle study: the effects of a 7-day high-intensity interval training shock microcycle with or without additional low-intensity training on endurance performance, well-being, stress and recovery in endurance trained athletes-study protocol of a randomized controlled trial.

BACKGROUND: Performing multiple high-intensity interval training (HIIT) sessions in a compressed period of time (approximately 7-14 days) is called a HIIT shock microcycle (SM) and promises a rapid increase in endurance performance. However, the efficacy of HIIT-SM, as well as knowledge about optimal training volumes during a SM in the endurance-trained population have not been adequately investigated. This study aims to examine the effects of two different types of HIIT-SM (with or without additional low-intensity training (LIT)) compared to a control group (CG) on key endurance performance variables. Moreover, participants are closely monitored for stress, fatigue, recovery, and sleep before, during and after the intervention using innovative biomarkers, questionnaires, and wearable devices. METHODS: This is a study protocol of a randomized controlled trial that includes the results of a pilot participant. Thirty-six endurance trained athletes will be recruited and randomly assigned to either a HIIT-SM (HSM) group, HIIT-SM with additional LIT (HSM + LIT) group or a CG. All participants will be monitored before (9 days), during (7 days), and after (14 days) a 7-day intervention, for a total of 30 days. Participants in both intervention groups will complete 10 HIIT sessions over 7 consecutive days, with an additional 30 min of LIT in the HSM + LIT group. HIIT sessions consist of aerobic HIIT, i.e., 5 × 4 min at 90-95% of maximal heart rate interspersed by recovery periods of 2.5 min. To determine the effects of the intervention, physiological exercise testing, and a 5 km time trial will be conducted before and after the intervention. RESULTS: The feasibility study indicates good adherence and performance improvement of the pilot participant. Load monitoring tools, i.e., biomarkers and questionnaires showed increased values during the intervention period, indicating sensitive variables. CONCLUSION: This study will be the first to examine the effects of different total training volumes of HIIT-SM, especially the combination of LIT and HIIT in the HSM + LIT group. In addition, different assessments to monitor the athletes' load during such an exhaustive training period will allow the identification of load monitoring tools such as innovative biomarkers, questionnaires, and wearable technology. TRIAL REGISTRATION: clinicaltrials.gov, NCT05067426. Registered 05 October 2021-Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT05067426 . Protocol Version Issue date: 1 Dec 2021. Original protocol. Authors: TLS, NH.