Effect of contractile activity on PGC-1α transcription in young and aged skeletal muscle
Bibliographic record
Abstract
Mitochondrial impairments are often noted in aged skeletal muscle. The transcriptional coactivator peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) is integral to maintaining mitochondria, and its expression declines in aged muscle. It remains unknown whether this is due to a transcriptional deficit during aging. Our study examined PGC-1α transcription in muscle from young and old F344BN rats. Using a rat PGC-1α promoter-reporter construct, we found that PGC-1α transcription was reduced by ∼65% in aged TA muscle, accompanied by decreases in PGC-1α mRNA and transcript stability. Altered expression patterns in PGC-1α transcription regulatory factors, including nuclear respiratory factor 2, upstream transcription factor 1, activating transcription factor 2, and yin yang 1, were noted in aged muscle. Acute contractile activity (CA) followed by recovery was employed to examine whether PGC-1α transcription could be activated in aged muscle similar to that observed in young muscle. AMPK and p38 signaling was attenuated in aged muscle. CA evoked an upregulation of PGC-1α transcription in both young and aged groups, whereas mRNAs encoding PGC-1α and cytochrome oxidase subunit IV were induced during the recovery period. Global DNA methylation, an inhibitory event for transcription, was enhanced in aged muscle, likely a result of elevated methyltransferase enzyme Dnmt3b in aged muscle. Successive bouts of CA for 7 days to evaluate longer-term consequences resulted in a rescue of PGC-1α and downstream mRNAs in aged muscle. Our data indicate that diminished mitochondria in aged muscle is due partly to a deficit in PGC-1α transcription, a result of attenuated upstream signaling. Contractile activity is an appropriate countermeasure to restore PGC-1α expression and mitochondrial content in aged muscle. NEW & NOTEWORTHY PGC-1α is a regulator of mitochondrial biogenesis in muscle. We demonstrate that PGC-1α expression is reduced in aging muscle due to decreases in transcriptional and posttranscriptional mechanisms. The transcriptional deficit is due to alterations in transcription factor expression, reduced signaling, and DNA methylation. Acute exercise can initiate signaling to reverse the transcriptional defect, restoring PGC-1α expression toward young values, suggesting a mechanism whereby aged muscle can respond to exercise for the promotion of mitochondrial biogenesis.
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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) | 0.001 | 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".