Regulation of cardiomyocyte hypertrophy in diabetes at the transcriptional level
Bibliographic record
Abstract
Diabetic cardiomyopathy, structurally characterized by cardiomyocyte hypertrophy and increased extracellular matrix (ECM) protein deposition, eventually leads to heart failure. We investigated the role of transcriptional coactivator p300 and its interaction with myocyte enhancer factor 2 (MEF2) in diabetes-induced cardiomyocyte hypertrophy. Neonatal rat cardiomyocytes were exposed to variable levels of glucose. Cardiomyocytes were analyzed with respect to their size. mRNA expression of p300, MEF2A, MEF2C, atrial natriuretic polypeptide (ANP), brain natriuretic polypeptide (BNP), angiotensinogen (ANG), cAMP-responsive element binding protein-binding protein (CBP), and protein analysis of MEF2 were done with or without p300 blockade. We investigated the hearts of STZ-induced diabetic rats and compared them with age- and sex-matched controls after 1 and 4 mo of followup with or without treatment with p300 blocker curcumin. The results were that cardiomyocytes, exposed to 25 mM glucose for 48 h, showed cellular hypertrophy and augmented mRNA expression of ANP, BNP, and ANG, molecular markers of cardiac hypertrophy. Glucose caused a duration-dependent increase of mRNA and protein expression in MEF2A and MEF2C and transcriptional coactivator p300. Curcumin, a p300 blocker, and p300 siRNA prevented these abnormalities. Similarly, ANP, BNP, and ANG mRNA expression was significantly higher in the hearts of diabetic rats compared with the controls, in association with increased p300, MEF2A, and MEF2C expression. Treatment with p300 blocker curcumin prevented diabetes-induced upregulation of these transcripts. We concluded that data from these studies demonstrate a novel glucose-induced epigenetic mechanism regulating gene expression and cardiomyocyte hypertrophy in diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".