Oestrogen‐dependent satellite cell activation and proliferation following a running exercise occurs via the <scp>PI</scp>3K signalling pathway and not <scp>IGF</scp>‐1
Bibliographic record
Abstract
AIM: The purpose of this study was to determine whether 17β-estradiol (E2) enhances the activation, proliferation and differentiation of muscle satellite cells (SC) following eccentric exercise either via insulin-like growth factor-1 (IGF-1) or through phosphatidylinositol 3-kinase (PI3K) signalling. METHODS: This study used 64, 9-week-old, ovariectomized Sprague-Dawley rats that were divided into eight treatments groups based on oestrogen status (0.25 mg oestrogen pellet or sham), exercise status (90 min run @ 17 m min(-1), -13.5° or unexercised) and PI3K signalling inhibition (0.7 mg wortmannin kg(-1) body weight or DMSO control). RESULTS: Significant increases in total SCs were found in both soleus and white gastrocnemius muscles (immunofluorescent co-localization of Pax7(+) nuclei) 72 h following eccentric exercise (P < 0.05). Oestrogen supplementation caused a further enhancement in total SCs in exercised rats (P < 0.05). In animals where the PI3K pathway was inhibited, regardless of oestrogen or exercise status, there was no significant enhancement of SC number in both the soleus or white gastrocnemius muscles. Interestingly, oestrogen supplementation lowered muscle levels of IGF-1 with this effect being most prominent in the soleus muscle. While IGF-1 was increased following exercise (P < 0.05), oestrogen supplementation abrogated this increase back to sedentary levels. CONCLUSION: These data suggest that the increase in SC population following exercise in oestrogen-supplemented females may be mediated via PI3K pathway signalling and not IGF-1.
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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".