The role of estrogen receptor-α in estrogen-mediated regulation of basal and exercise-induced Hsp70 and Hsp27 expression in rat soleus
Bibliographic record
Abstract
We examined the influence of estrogen receptor-alpha (ERα) activation on estrogen-mediated regulation of heat shock proteins 70 (Hsp70) and 27 (Hsp27) in soleus. Ovariectomized rats received estrogen (EST), an ERα agonist (propyl pyrazole triol, PPT), both (EST+PPT), or a sham, and they served as either unexercised controls or were subjected to exercise by having to run downhill (17 m/min, -13.5° grade) for 90 min. At 72 h postexercise, soleus muscles were removed and either immunohistochemically stained for Hsp70 and myosin heavy chain or homogenized for Western blotting for Hsp70 and Hsp27. Elevated (p < 0.05) basal Hsp70 in both type I and II fibres in the unexercised EST, PPT, and EST+PPT groups relative to unexercised sham animals was noted. Compared with Hsp70 levels in the unexercised animals, that in exercised animals was elevated (p < 0.05) in both sham and PPT groups but not in EST and EST+PPT groups. Western blot determined that Hsp27 levels were not significantly different between groups. Hence, the ability of estrogen to augment resting type I and type II muscle fibre Hsp70 content is primarily mediated via muscle ERα. However, the blunted Hsp70 response following damaging exercise in estrogen-supplemented animals does not appear to be fully accounted for by ERα-mediated effects.
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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".