Heat Shock Factor Activation in Skeletal Muscle Following Lengthening Contractions
Bibliographic record
Abstract
Heat shock proteins (HSPs) are integral for the maintenance of proteostasis and allowing cells to cope with episodes of stress. HSPs are regulated by transcription factors known as heat shock transcription factors (HSFs). Given that when skeletal muscles are subjected to lengthening contractions (LCs) both muscle damage and HSPs are increased, it was of interest to investigate the mechanism of the LC‐induced increase in HSPs and assess the role of HSFs in this process. Thus, the purpose of this study was to determine if HSF activation (HSF trimerization and DNA binding) is elevated in rat skeletal muscle following exposure to 60 LCs. 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) and removed at 0, 1, 3, or 24 hours after LCs, while the non‐stimulated contralateral TA served as a control. Hsp72 and Hsp25 content, HSF activation, muscle damage, and muscle glycogen content were assessed at various time points. Following 60 LCs, electrophoretic shift assay showed a transient increase in HSF activation (0–3 hours) that was followed by a significant (p<0.001) increase in Hsp72 (3.4±0.21 fold) and Hsp25 (3.2±1.2 fold) content 24 hours later as assessed by western blotting. Histological assessment of the TA muscle revealed evidence of muscle damage (measured as necrotic fibers and inflammatory infiltrates) and glycogen depletion. Taken together, the results suggest LCs induce structural and metabolic stress that results in muscle damage, increased HSF activation and the accumulation of Hsp72 and Hsp25. 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 | 0.000 | 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".