Heat Shock Proteins as Markers of Contraction‐Induced Muscle Damage
Bibliographic record
Abstract
Angular contraction velocity has been proposed as a determinant in the severity of lengthening contraction‐induced muscle damage, yet empirical evidence is equivocal. We measured heat shock protein (HSP) content as a marker of muscle damage severity following lengthening contractions (LCs) at multiple angular velocities (slow; 63°/sec, medium; 127°/sec, fast; 190°/sec) to determine the relationship between angular velocity and muscle damage. To do this, male sprague‐dawley rats were anaesthetized and one tibialis anterior (TA) muscle was subjected to 60 LCs (3 sets of 20 LCs with 5 minutes rest between sets) at three velocities, while the contralateral TA served as a control. Twenty‐four hours after the last LC, intramuscular Hsp72 content, as assessed by western blotting, was significantly (p<0.001) increased in the stimulated TA regardless of the angular velocity. Similarly, Hsp25 content was also elevated but only considered significant (p<0.05) after LCs at the slow velocity (63°/sec). Interestingly, TA muscle function (ability to generate torque) was affected greatest following slow LCs. When compared to fast LCs (190°/sec), slow LCs caused significantly (p<0.05) greater loss of muscle torque with each set of 20 LCs, suggesting muscle damage and/or fatigue was greater after slow LCs. However, histological assessment of TA cross‐sections suggest the severity of muscle damage (measured as necrotic fibers and inflammatory infiltrates) and metabolic fatigue (measured as glycogen depletion) was similar between velocities. Taken together, the results suggest Hsp72 content may be a novel marker for determining the severity of LC‐induced muscle damage. Support or Funding Information No external funding
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".