Contribution of Bone Morphogenetic Protein-2 to Aortic Valve Calcification in Aged Rat
Bibliographic record
Abstract
Although aging is well established as an important risk factor for aortic stenosis, the mechanism of age-related aortic valve calcification is yet unknown. Here, we investigated this mechanism in tissue and cellular levels using middle-aged rats. Aortic valve specimens were obtained by dissecting from 9-week-old (young) and 30-week-old (aged) male Wistar rats. In the aged rats, the main risk factors for aortic stenosis in plasma were still in the normal range; however, their number of calcified specimens was significantly increased in comparison with the young rats. Aortic valve interstitial cells (AVICs) obtained from explants of aortic valve specimens were cultured for 14 days after reaching confluence. Spontaneous calcification, the expressions of calcigenic genes, that is, BMP-2, alkaline phosphatase (ALP), and osterix (osteogenic transcription factor) and ALP enzyme activity in AVICs from aged rats were enhanced in comparison with those from young rats. However, neither typical calcification inducing reagents (dexamethasone, β-glycerophosphate, and high concentration of phosphate) nor tumor necrosis factor-α (an inflammatory cytokine) accelerated the spontaneous calcification of AVICs from aged rats. These results suggest that aortic valve calcification progresses with age partly through an activation of the BMP-2 pathway.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".