<i>Hesr2</i> Knockout Mice Develop Aortic Valve Disease With Advancing Age
Bibliographic record
Abstract
OBJECTIVE: Acquired heart diseases, such as valve disease, are major causes of human morbidity and mortality. However, the pathological mechanisms underlying these diseases are largely unknown. Our aim is to identify the role of the hairy and enhancer of split-related (Hesr)-2 gene in the adult heart. METHODS AND RESULTS: Echocardiography detected heart dysfunctions indicative of aortic valve anomalies, stenosis, and regurgitation, in ≈59% of >12-month-old Hesr2 knockout survivor mice. Morphological and histological analyses revealed thickened semilunar valves with increased fibrotic areas, indicating that sclerotic degeneration of valves is the main cause of aortic valve disease. The expression of osteogenic genes, such as osteopontin and sclerostin, were upregulated in the mutants, and the overexpression of sclerostin in endothelial cells resulted in thickened semilunar valves with increased fibrotic areas, similar to that seen in the Hesr2 knockout mice, suggesting that Hesr2 can regulate osteogenic gene expression in valves. Reduced left ventricular function, which may be caused by increased ventricular interstitial fibrosis, and enlarged myocardial cell size without ventricular wall thickening were found in both aortic valve stenosis/regurgitation-positive (33%) and aortic valve stenosis/regurgitation-negative (38%) subpopulations in 12-month-old survivor mice. Dilated left ventricular internal dimensions were specifically detected in the aortic valve stenosis/regurgitation-positive subpopulation, thus suggesting that the degeneration of cardiomyocytes is influenced by irregular hemodynamics. CONCLUSIONS: These data revealed that survivor mice lacking the Hesr2 gene exhibit fibrosis in the aortic valve and ventricle in adulthood, thus suggesting that Hesr2 plays an important role in maintaining the homeostasis of the aortic valve and ventricle.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".