Variability in Estimating Eccentric Contraction-Induced Muscle Damage and Inflammation in Humans
Bibliographic record
Abstract
We studied five young healthy volunteers who performed a "damage protocol" consisting of 240 (24 sets x 10 repetitions/set) maximal isokinetic eccentric muscle contractions (30 degrees/s) on each leg one week apart. Biopsies were taken from the vastus lateralis on two occasions. Two biopsies were taken from within the same muscle 24h following the damage protocol. On a second occasion a single biopsy was taken from the contralateral leg at 24h following the same damage protocol. Biopsies at all three sites showed Z-band disruption, much greater (i.e., approximately 14-fold) than is typically observed in resting biopsies, with no significant differences (ANOVA) according to site location (within legs or between legs). The within-leg coefficient of variation (CV) was, however, 41 +/- 30%, and the between-leg CVs were 57 +/- 36% and 68 +/- 36%. Macrophage cells were also detected within the muscle, and cell numbers were not statistically different between biopsy sites. However, the within-biopsy CV = 52 +/- 19% and the between-biopsy CVs of 34 +/- 24% and 48 +/- 27%. We conclude that eccentric contraction-induced Z-band streaming and inflammatory cell response, as detected in muscle biopsy samples from humans, is highly variable with a CV of 40-70%.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".