Targeting platelets for prevention and treatment of cardiovascular disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Platelets play an important role in the development of thrombosis, atherosclerosis, hypertension, heart attack and stroke. As a result, pharmacologic interventions that influence platelet functions, such as adhesion, aggregation and the release of different factors, are considered useful for the prevention and treatment of cardiovascular disease. Although classical anti-platelet agents have proven beneficial effects for the treatment of some specific cardiovascular diseases, there are limitations for their use as these drugs target platelet function directly. In contrast, newly developed anti-platelet agents have broad applications for the treatment of cardiovascular disease as they not only influence platelet function but are also considered to affect cardiac and vascular smooth muscle cell functions. Natural food products and nutraceutical agents also appear to modify cardiovascular abnormalities by affecting various platelet functions; however, the mechanisms of their actions remain to be investigated. Accordingly, this article is focused to discuss emerging pharmacologic, nutritional and nutraceutical interventions that may influence the prevention or progression of a broad range of cardiovascular diseases.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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) | 0.000 | 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 it