The Influence of Propyl Pyrazole Triol on the Post-Exercise Alpha Estrogen Receptor-Mediated Activation of Satellite Cells in Skeletal Muscle of Ovariectomized Rats
Bibliographic record
Abstract
Estrogen has been shown to augment satellite cell activation, proliferation and total number and that this may occur through an estrogen receptor (ER) mediated mechanism. The purpose of this study was to investigate the role of ERs in the postexercise estrogen-induced augmentation of satellite cells in skeletal muscle of ovariectomized rats. Furthermore, the specific role of the ERα was examined through the use of an ERa agonist, propyl pyrazole triol (PPT). Ovariectomized rats were used (n=64) and separated into 4 groups: sham, estrogen supplemented, agonist supplemented and a combined estrogen and agonist supplemented group. These groups were further subdivided into control (unexercised) and exercise groups. Animals in the exercise group participated in an intermittent running protocol that involved animals running downhill on a motorized treadmill for 90 minutes. Surgical removal of white vastus and soleus muscles occurred 72 hours post-exercise. Muscle samples were immunostained for the satellite cell markers Pax7 and MyoD. Significant increases in total (Pax7-positive) and activated (MyoD-positive) satellite cells were found in all groups post-exercise. A further significant augmentation of total and activated satellite cells occurred in estrogen supplemented, agonist supplemented and the combined estrogen and agonist supplemented groups postexercise in white vastus and soleus muscles relative to unsupplemented animals. These results demonstrate that both estrogen and the ERα agonist, PPT, can significantly augment satellite cell number and activation following exercise-induced muscle damage. This suggests that estrogen acts through an ER-mediated mechanism to stimulate satellite cell activation and proliferation following exercise, with ERα playing a primary role.
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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 | 0.001 |
| 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".