Roles of histone deacetylation and AMP kinase in regulation of cardiomyocyte <i>PGC-1α</i> gene expression in hypoxia
Bibliographic record
Abstract
The transcriptional coactivator peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) is a key determinant of cardiac metabolic function by regulating genes governing fatty acid oxidation and mitochondrial biogenesis. PGC-1α expression is reduced in many cardiac diseases, and gene deletion of PGC-1α results in impaired cardiomyocyte metabolism and function. Reduced fuel supply generally induces PGC-1α expression, but the specific role of oxygen deprivation is unclear, and the mechanisms governing PGC-1α gene expression in these situations are poorly understood. During hypoxia of primary rat cardiomyocytes up to 12 h, we found that PGC-1α expression was downregulated via a histone deacetylation-dependent mechanism. Conversely, extended hypoxia to 24 h concomitant with glucose depletion upregulated PGC-1α expression via an AMP-activated protein kinase (AMPK)-mediated mechanism. Our previous work demonstrated that estrogen-related receptor-α (ERRα) regulates PGC-1α expression, and we show here that overexpression of ERRα was sufficient to attenuate PGC-1α downregulation in hypoxia. We confirmed that chronic hypoxia downregulated cardiac PGC-1α expression in a hypoxic but nonischemic hypobaric rat model of pulmonary hypertension. Our data demonstrate that depletion of oxygen or fuel results in repression or induction, respectively, of PGC-1α expression via discrete mechanisms, which may contribute to cardiac energetic derangement during hypoxia, ischemia, and failure.
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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) | 0.000 | 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".