Inhibition of the phosphotidylinositol 3‐kinase (PI3K) pathway attenuates post‐exercise increases in soleus muscle satellite cells in estrogen supplemented ovariectomized rats
Bibliographic record
Abstract
17β‐Estradiol (E2) enhances the activation, proliferation and differentiation of muscle satellite cells (SC) following eccentric exercise via activation of estrogen receptor‐α. Insulin‐like Growth Factor‐1 (IGF‐1) is known to cause SC proliferation and differentiation via phosphatidylinositol 3‐kinase (PI3K) signaling. To determine if E2 regulates SC activity via the PI3K pathway, 64, nine‐week old, ovariectomized Sprague‐Dawley rats were divided into eight treatments groups based on: estrogen status (0.25 mg estrogen pellet or sham), exercise status (90 min run @ 17 m/min, −13.5° or unexercised), PI3K signaling inhibition (0.7 mg Wortmannin/kg Body Weight or saline control). Significant increases in total SCs in soleus muscle (immunofluorescent colocalization of nuclei with Pax7) were seen at 72 hr post‐exercise in rats who were E2‐supplemented (t(62) = 1.89, p = 0.063), exercised (t(62) = 5.723, p < 0.001), and whose PI3K pathway was not inhibited (t(62) = 3.460, p = 0.001). PI3K pathway inhibited animals, regardless of estrogen or exercise status showed no significant enhancement of SC number. Preliminary data suggests that an increase in SC population following exercise in estrogen supplemented females may be mediated via PI3K pathway signaling.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".