Purinergic receptors and atherosclerosis: emerging role for vessel wall P2Y12
Bibliographic record
Abstract
This editorial refers to ‘Vessel wall, not platelet, P2Y12 potentiates early atherogenesis’ by L.E. West et al., pp. 429–435, this issue. Platelets play a key role in primary haemostasis and also represent an important interface between thrombosis, immunity, and atherogenesis.1 Platelet-triggered inflammatory pathways contribute to the formation of atherosclerotic lesions and atherothrombosis. Platelets express receptors for a variety of agonists that initiate platelet activation, which is then amplified and sustained by activation of the G-protein-coupled purinergic receptor P2Y12. P2Y12 mediates platelet aggregation and secretion of platelet granule contents in response to ADP.2 P2Y12 is also a well-established target for anti-thrombotic drugs, such as the thienopyridine compounds ticlopidine, clopidogrel, and prasugrel or the direct, reversible antagonists ticagrelor, cangrelor, and elinogrel.2 Clinical studies have shown that in addition to preventing arterial thrombus formation in patients with coronary artery syndromes or after stent implantation, anti-thrombotic/anti-platelet therapy is also associated with systemic anti-inflammatory effects.3 While these findings imply an important role for P2Y12 in the regulation of platelet functions, P2Y12 expression is not restricted to platelets. Indeed, accumulating data indicate that P2Y12 may directly mediate pro-inflammatory and atherogenic actions in the vessel wall apparently independently of platelet activation. West et al.4 provide evidence supporting this notion by describing a role for vessel wall, but not platelet, P2Y12 in the development of early atherosclerotic lesions.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".