Power loss is attenuated following a second bout of high-intensity eccentric contractions due to the repeated bout effect’s protection of rate of torque and velocity development
Bibliographic record
Abstract
High-intensity unaccustomed eccentric contractions result in weakness and power loss because of fatigue and muscle damage. Through the repeated bout effect (RBE), adaptations occur, then damage and weakness are attenuated following a subsequent bout. However, it is unclear whether the RBE protects peak power output. We investigated the influence of the RBE on power production and estimated fatigue- and damage-induced neuromuscular impairments following repeated high-intensity eccentric contractions. Twelve healthy adult males performed 5 sets of 30 maximal eccentric elbow flexions and repeated an identical bout 4 weeks later. Recovery was tracked over 7 days following both bouts. Reduced maximum voluntary isometric contraction torque, and increased serum creatine kinase and self-reported soreness indirectly inferred muscle damage. Peak isotonic power, time-dependent measures — rate of velocity development (RVD) and rate of torque development (RTD) — and several electrophysiological indices of neuromuscular function were assessed. The RBE protected peak power, with a protective index of 66% 24 h after the second eccentric exercise bout. The protection of power also related to preserved RVD (R2 = 0.61, P < 0.01) and RTD (R2 = 0.39, P < 0.01). Furthermore, the RBE’s protection against muscle damage permitted the estimation of fatigue-associated neuromuscular performance decrements following eccentric exercise. Novelty: The repeated bout effect protects peak isotonic power. Protection of peak power relates to preserved rates of torque and velocity development, but more so rate of velocity development. The repeated bout effect has little influence on indices of neuromuscular fatigue.
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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) | 0.002 | 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".