Adenosine derived from ecto-nucleotidases in calcific aortic valve disease promotes mineralization through A2a adenosine receptor
Bibliographic record
Abstract
AIMS: In this study, we sought to determine the role of ecto-nucleotidases and adenosine receptors in calcific aortic valve disease (CAVD). The expression of ecto-nucleotidases, which modify the levels of extracellular nucleotides/nucleosides, may control the mineralization of valve interstitial cells (VICs). We hypothesized that expression of ectonucleotide pyrophosphatase/phosphodiesterase 1 (NPP1), which generates AMP, and 5'-nucleotidase (CD73), an enzyme using AMP as a substrate to produce adenosine, may co-regulate the mineralization of the aortic valve. METHODS AND RESULTS: We have investigated the expression of NPP1 and 5'-nucleotidase in CAVD tissues and determined the role of these ecto-nucleotidases on the mineralization of isolated VICs. In CAVD tissues (stenotic and sclerotic), we documented that NPP1 and 5'-nucleotidase were overexpressed by VICs. In isolated VICs, we found that mineralization induced by adenosine triphosphate was decreased by silencing NPP1 and 5'-nucleotidase, suggesting a role for adenosine. Adenosine and specific A2a adenosine receptor (A2aR) agonist increased the mineralization of VICs. Silencing of A2aR in human VICs and the use of A2aR(-/-) mouse VICs confirmed that A2aR promotes the mineralization of cells. Also, A2aR-mediated mineralization was negated by the transfection of a mutant dominant-negative Gαs vector. Through several lines of evidence, we next documented that adenosine stimulated the mineralization of VICs through a cAMP/protein kinase A (PKA)/cAMP response element-binding protein (CREB) pathway, and found that CREB positively regulated the expression of NPP1 in a positive feedback loop by physically interacting with the promoter. CONCLUSION: Expression of NPP1 and 5'-nucleotidase by VICs promotes the mineralization of the aortic valve through A2aR and a cAMP/PKA/CREB 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 | 0.001 | 0.000 |
| 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".