AMP‐activated protein kinase‐regulated activation of the PGC‐1α promoter in skeletal muscle cells
Bibliographic record
Abstract
PGC‐1α is an important regulator of mitochondrial biogenesis in skeletal muscle. However, the transcriptional mechanisms controlling PGC‐1α expression in muscle remain to be clearly defined. We have isolated the proximal 2kb sequence of the PGC‐1α promoter from human genomic DNA. Analysis reveals that it contains putative binding sites for Sp1, ATF2/CREB, FKHR, GATA, SRF, MEF2, p53 and NF‐κB as well as multiple E Boxes. Using truncated deletions of the PGC‐1α promoter, we investigated the effect of AMPK activation by AICAR, a known mitochondrial biogenesis‐stimulating agent. AICAR treatment (1mM, 24hrs) increased promoter activity within the 848bp fragment of the PGC‐1α promoter activity by 3.4‐fold (p<0.001) in C 2 C 12 muscle cells. This occurred concomitantly with 1.8‐ (p<0.05) and 2.2‐fold (p<0.05) increases in GATA‐EBox DNA‐binding and PGC‐1α mRNA expression, respectively. The AICAR effect, which is mediated via overlapping GATA/EBox binding sites, requires the cooperative actions of GATA‐4 and USF‐1. GATA‐4 overexpression increased PGC‐1α promoter activity 3.2‐fold (p<0.05), and was further enhanced by 1.4‐fold in the presence of AICAR. Our data define a novel pathway by which AMPK activation regulates PGC‐1α promoter activity via GATA‐4 and USF‐1, ultimately resulting in the induction of PGC‐1α mRNA expression. They also suggest that the modulation of the AMPK signaling pathway via GATA‐4 and/or USF‐1 could represent a potential therapeutic target to control PGC‐1α expression in skeletal muscle. This work was funded by NSERC and CIHR.
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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 | 0.001 |
| 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 | 0.001 |
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".