Bibliographic record
Abstract
Platelets play a pivotal role in primary hemostasis where their rapid response to vascular injury prevents excessive bleeding. To accomplish this, platelets are enriched in membrane receptors and cytoplasmic enzymes with often redundant and self-amplifying functions leading to platelet activation, release into the bloodstream of hemostatically active compounds and culminating with thrombus formation. However, the same process in the pathological state of atherosclerosis can lead to thrombotic complications such as an acute coronary syndrome or stroke. The role of platelets in this process is more extensive than previously believed. Several lines of evidence suggest that platelets contribute not only to the acute thrombotic events in atherosclerosis, but also to disease initiation and progression. This review focuses on the role of platelet heterogeneity and turnover in atherothrombotic disease. Specifically, this article covers (a) the regulation of platelet formation; (b) the role of the heterogeneity of platelets in atherothrombotic diseases; (c) the disease-modifying effect of platelets on the development of atherosclerosis; and (d) the modifying effect of atherosclerotic disease on platelet production and function; (e) the platelet indices influencing platelet responsiveness to antiplatelet therapies; and finally (f) the potential novel therapeutic modalities that could be applied in atherothrombosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".