The effect of heat stress on skeletal muscle contractile properties
Bibliographic record
Abstract
An elevated heat-shock protein (HSP) content protects cells and tissues, including skeletal muscles, from certain stressors. We determined if heat stress and the elevated HSP content that results is correlated with protection of contractile characteristics of isolated fast and slow skeletal muscles when contracting at elevated temperatures. To elevate muscle HSP content, one hindlimb of Sprague-Dawley rats (21-28 days old, 70-90 g) was subjected to a 15 min 42 °C heat-stress. Twenty-four hours later, both extensor digitorum longus (EDL) and soleus muscles were removed, mounted in either 20 °C or 42 °C Krebs-Ringer solution, and electrically stimulated. Controls consisted of the same muscles from the contra-lateral (non-stressed) hindlimbs as well as muscles from other (unstressed) animals. Isolated muscles were twitched and brought to tetanus every 5 min for 30 min. As expected, HSP content was elevated in muscles from the heat-stressed limbs when compared with controls. Regardless of prior treatment, both EDL and soleus twitch tensions were lower at 42 °C when compared with 20 °C. In addition, when incubated at 42 °C, both muscles showed a drop in twitch tension between 5 and 30 min. For tetanic tension, both muscles also showed an increase in tension between 5 and 30 min when stimulated at 20 °C regardless of treatment but when stimulated at 42 °C no change was observed. No protective effect of an elevated HSP content was observed for either muscle. In conclusion, although heat stress caused an elevation in HSP content, no protective effects were conferred to isolated contracting muscles.
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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) | 0.001 | 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".