Effect of chronic contractile activity on mRNA stability in skeletal muscle
Bibliographic record
Abstract
Repeated bouts of exercise promote the biogenesis of mitochondria by multiple steps in the gene expression patterning. The role of mRNA stability in controlling the expression of mitochondrial proteins is relatively unexplored. To induce mitochondrial biogenesis, we chronically stimulated (10 Hz; 3 or 6 h/day) rat muscle for 7 days. Chronic contractile activity (CCA) increased the protein expression of PGC-1alpha, c-myc, and mitochondrial transcription factor A (Tfam) by 1.6-, 1.7- and 2.0-fold, respectively. To determine mRNA stability, we incubated total RNA with cytosolic extracts using an in vitro cell-free system. We found that the intrinsic mRNA half-lives (t(1/2)) were variable within control muscle. Peroxisome proliferator-activated receptor-gamma, coactivator-1alpha (PGC-1alpha) and Tfam mRNAs decayed more rapidly (t(1/2) = 22.7 and 31.4 min) than c-myc mRNA (t(1/2) = 99.7 min). Furthermore, CCA resulted in a differential response in degradation kinetics. After CCA, PGC-1alpha and Tfam mRNA half-lives decreased by 48% and 44%, respectively, whereas c-myc mRNA half-life was unchanged. CCA induced an elevation of both the cytosolic RNA-stabilizing human antigen R (HuR) and destabilizing AUF1 (total) by 2.4- and 1.8-fold, respectively. Increases in the p37(AUF1), p40(AUF1), and p45(AUF1) isoforms were most evident. Thus these data indicate that CCA results in accelerated turnover rates of mRNAs encoding important mitochondrial biogenesis regulators in skeletal muscle. This adaptation is likely beneficial in permitting more rapid phenotypic plasticity in response to subsequent contractile activity.
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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".