Two maximal isometric contractions attenuate the magnitude of eccentric exercise-induced muscle damage
Bibliographic record
Abstract
This study investigated whether maximal voluntary isometric contractions (MVC-ISO) would attenuate the magnitude of eccentric exercise-induced muscle damage. Young untrained men were placed into one of the two experimental groups or one control group (n = 13 per group). Subjects in the experimental groups performed either two or 10 MVC-ISO of the elbow flexors at a long muscle length (20° flexion) 2 days prior to 30 maximal isokinetic eccentric contractions of the elbow flexors. Subjects in the control group performed the eccentric contractions without MVC-ISO. No significant changes in maximal voluntary concentric contraction peak torque, peak torque angle, range of motion, upper arm circumference, plasma creatine kinase (CK) activity and myoglobin concentration, muscle soreness, and ultrasound echo intensity were evident after MVC-ISO. Changes in the variables following eccentric contractions were smaller (P < 0.05) for the 2 MVC-ISO group (e.g., peak torque loss at 5 days after exercise, 23% ± 3%; peak CK activity, 1964 ± 452 IU·L(-1); peak muscle soreness, 46 ± 4 mm) or the 10 MVC-ISO group (13% ± 3%, 877 ± 198 IU·L(-1), 30 ± 4 mm) compared with the control (34% ± 4%, 6192 ± 1747 IU·L(-1), 66 ± 5 mm). The 10 MVC-ISO group showed smaller (P < 0.05) changes in all variables following eccentric contractions compared with the 2 MVC-ISO group. Therefore, two MVC-ISO conferred potent protective effects against muscle damage, whereas greater protective effect was induced by 10 MVC-ISO, which can be used as a strategy to minimize muscle damage.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".