Sex alters impact of repeated bouts of sprint exercise on neuromuscular activity in trained athletes
Bibliographic record
Abstract
This study characterized the effect of sex on neuromuscular activity during repeated bouts of sprint exercise. Thirty-three healthy male and female athletes performed twenty 5-s cycle sprints separated by 25 s of rest. Mechanical work and integrated electromyograhs (iEMG) of 4 muscles of the dominant lower limb were calculated in every sprint. The iEMG signals from individual muscles were summed to represent overall electrical activity of these muscles (sum-iEMG). Neuromuscular efficiency (NME) was calculated as the ratio of mechanical work and sum-iEMG for every sprint. Arterial oxygen saturation was estimated (SpO2) with pulse oximetry throughout the protocol. The sprint-induced work decrement (18.9% vs. 29.6%; p < 0.05) and sum-iEMG reduction (11.4% vs. 19.4%; p < 0.05) were less for the women than for the men. However, the sprints decreased NME (10.1%; p < 0.05) and SpO2 (3.4%; p < 0.05) without showing sex dimorphism. Changes in SpO2 and sum-iEMG were strongly correlated in both sexes (men, R2 = 0.87; women, R2 = 0.91; all p < 0.05), although the slope of this relationship differed (6.3 +/- 2.9 vs. 3.8 +/- 1.6, respectively; p < 0.05). It is suggested that the sex difference in fatigue during repeated bouts of sprint exercise is not likely to be explained by a difference in muscle contractility impairment in men and women, but may be due to a sex difference in muscle recruitment strategy. We speculate that women would be less sensitive to arterial O2 desaturation than men, which may trigger lower neuromuscular adjustments to exhaustive exercise.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".