Striking muscle adaptations induced by volume-dependent repeated bouts of low-intensity eccentric exercise of the elbow flexors
Bibliographic record
Abstract
We investigated the effects of repeating 30 low-intensity eccentric contractions with a dumbbell corresponding to 10% maximal isometric strength (10%EC) on muscle strength and hypertrophy, and muscle damage after 30 maximal eccentric contractions (MaxEC) of the elbow flexors. Young men were placed into 1 of 3 experimental groups that performed 10%EC either once, twice a week for 4 (8 bouts) or 8 weeks (16 bouts) before MaxEC, or a control group that performed 2 bouts of MaxEC separated by 2 weeks (n = 13/group). Repeating 16 bouts of 10%EC increased (P < 0.05) maximal voluntary contraction strength (30 ± 21%) and muscle thickness (4.2 ± 2.3%) greater than 8 bouts (16 ± 4%, 1.9 ± 1.3%). Changes in the muscle damage markers after MaxEC were smaller (P < 0.05) for the experimental groups than the control group, and the magnitude of muscle damage protection was greater (P < 0.05) after 16 bouts (65 ± 30%) than 8 bouts (55 ± 33%), followed by 1 bout (34 ± 27%). The protection by 16 bouts was similar (P = 0.81) to that shown by the second MaxEC of the control group. These results showed that 10%EC produced potent muscle adaptation effects accumulatively and conferred muscle damage protection, but 1 bout of 10%EC was still effective for conferring approximately 20% of the protection of that by 16 bouts. Novelty: Repeating low-intensity eccentric exercise induces large increases in muscle strength and hypertrophy. Low-intensity eccentric exercise protects muscle damage induced by maximal eccentric contractions, and the protection is reinforced by repeating it. These are especially beneficial for individuals who are frail and cannot tolerate high-intensity resistance training.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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 teacher head, 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".