Bibliographic record
Abstract
Cardiovascular disease (CVD) accounts for almost half of all deaths worldwide and has now surpassed infectious disease as the leading cause of death and disability in developing countries. At present, therapies such as low-density lipoprotein-lowering statins and antihypertensive drugs have begun to bend the morality curve for coronary artery disease (CAD); yet, as we come to appreciate the more complex pathophysiological processes in the vessel wall, there is an opportunity to fine-tune therapies to more directly target mechanisms that drive CAD. MicroRNAs (miRNAs) have been identified that control vascular cell homeostasis,(1-3) lipoprotein metabolism,(4-9) and inflammatory cell function.(10) Despite the importance of these miRNAs in driving atherosclerosis and vascular dysfunction, therapeutic modulation of miRNAs in a cell- and context-specific manner has been a challenge. In this review, we summarize the emergence of miRNA-based therapies as an approach to treat CAD by specifically targeting the pathways leading to the disease. We focus on the latest development of nanoparticles (NPs) as a means to specifically target the vessel wall and what the future of these nanomedicines may hold for the treatment of CAD.
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 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) | 0.001 | 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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".