Expression of mRNA species affecting growth and membrane homeostasis in skeletal muscle following eccentric exercise
Bibliographic record
Abstract
Eccentric exercise leads to muscle damage with our recent work suggesting an early response of components of membrane repair and remodeling at the transcriptome level. Estradiol has been reported to have membrane stabilizing properties but it is unclear if these are mediated at the transcriptome or post‐translational level. We measured skeletal muscle expression of mRNA for enzymes involved in membrane homeostasis (FOXO1, Caveolin 1 and SREBP‐2) and growth (DSCR1, DMPK and CapZα1) in healthy males following 8 days of either placebo (n=9) or 17‐beta‐estradiol (n=9) supplementation. Muscle biopsies were collected pre and post supplementation as well as 3 and 48 hours following an exercise protocol of 150 eccentric contractions. Quantification of mRNA expression was determined by RT‐PCR. FOXO1, Caveolin 1, SREBP‐2 and DSCR1 were elevated at 3h post exercise by 2.7, 1.4, 1.6 and 16.6 fold respectively, with no effect of supplementation. DMPK and CapZα1 were elevated at 48h post exercise by 2.6 and 1.8 fold respectively, with no effect of supplementation. These findings indicate an early and later temporal pattern in steady‐state mRNA content for genes involved in membrane synthesis (3h) and growth (3 and 48h) following eccentric exercise that is not influenced by17beta‐estradiol. (This research was funded by NSERC)
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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) | 0.003 | 0.001 |
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".