Epigenetic Therapy for the Treatment of Hypertension-Induced Cardiac Hypertrophy and Fibrosis
Bibliographic record
Abstract
BACKGROUND: The development of heart failure is associated with changes in the size, shape, and structure of the heart that has a negative impact on cardiac function. These pathological changes involve excessive extracellular matrix deposition within the myocardial interstitium and myocyte hypertrophy. Alterations in fibroblast phenotype and myocyte activity are associated with reprogramming of gene transcriptional profiles that likely requires epigenetic alterations in chromatin structure. The aim of our work was to investigate the potential of a currently licensed anticancer epigenetic modifier as a treatment option for cardiac diseases associated with hypertension-induced cardiac hypertrophy and fibrosis. METHODS AND RESULTS: The effects of DNA methylation inhibition with 5-azacytidine (5-aza) were examined in a human primary fibroblast cell line and in a spontaneously hypertensive rat (SHR) model. The results from this work allude to novel in vivo antifibrotic and antihypertrophic actions of 5-aza. Administration of the DNA methylation inhibitor significantly improved several echocardiographic parameters associated with hypertrophy and diastolic dysfunction. Myocardial collagen levels and myocyte size were reduced in 5-aza-treated SHRs. These findings are supported by beneficial in vitro effects in cardiac fibroblasts. Collagen I, collagen III, and α-smooth muscle actin were reduced in a human ventricular cardiac fibroblast cell line treated with 5-aza. CONCLUSION: These findings suggest a role for epigenetic modifications in contributing to the profibrotic and hypertrophic changes evident during disease progression. Therapeutic intervention with 5-aza demonstrated favorable effects highlighting the potential use of this epigenetic modifier as a treatment option for cardiac pathologies associated with hypertrophy and fibrosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".