Activated platelets promote an osteogenic programme and the progression of calcific aortic valve stenosis
Bibliographic record
Abstract
AIMS: Calcific aortic valve stenosis (CAVS) is characterized by a fibrocalcific process. Studies have shown an association between CAVS and the activation of platelets. It is believed that shear stress associated with CAVS promotes the activation of platelets. However, whether platelets actively participate to the mineralization of the aortic valve (AV) and the progression of CAVS is presently unknown. To identify the role of platelets into the pathobiology of CAVS. METHODS AND RESULTS: Explanted control non-mineralized and mineralized AVs were examined by scanning electron microscope (SEM) for the presence of activated platelets. In-depth functional assays were carried out with isolated human valve interstitial cells (VICs) and platelets as well as in LDLR-/- apoB100/100 IGFII (IGFII) mice. Scanning electron microscope and immunogold markings for glycoprotein IIb/IIIa (GPIIb/IIIa) revealed the presence of platelet aggregates with fibrin in endothelium-denuded areas of CAVS. In isolated VICs, collagen-activated platelets induced an osteogenic programme. Platelet-derived adenosine diphosphate induced the release of autotaxin (ATX) by VICs. The binding of ATX to GPIIb/IIIa of platelets generated lysophosphatidic acid (LysoPA) with pro-osteogenic properties. In IGFII mice with CAVS, platelet aggregates were found at the surface of AVs. Administration of activated platelets to IGFII mice accelerated the development of CAVS by 2.1-fold, whereas a treatment with Ki16425, an antagonist of LysoPA receptors, prevented platelet-induced mineralization of the AV and the progression of CAVS. CONCLUSIONS: These findings suggest a novel role for platelets in the progression of CAVS.
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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 | 0.000 |
| 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".