"Vulnerable plaques" — ticking of the time bomb
Bibliographic record
Abstract
Atherosclerosis and its sequelae are one of the leading causes of morbidity and mortality, especially in the developed nations. Over the years, treatment protocols have changed with the changing understanding of the disease process. Inflammatory mechanisms have emerged as key players in the formation of the atherosclerotic plaque. For the majority of its life span, the plaque develops silently and only some exhibit overt clinical manifestations. The purpose of this review is to examine the inherent properties of some of these "vulnerable" or symptomatic plaques. Rupture of the plaque is related to the thickness of the fibrous cap overlying the necrotic lipid core. A thin cap is more likely to lead to rupture. Multiple factors broadly grouped as the "determinants of vulnerability" are responsible for directly or indirectly influencing the plaque dynamics. Apoptosis is considered an important underlying mechanism that contributes to plaque instability. Inflammatory reactions within the plaque trigger apoptosis by cell-cell contact and intra cellular death signaling. Once started, the apoptotic process affects all of the components that make up the plaque, including vascular smooth muscle cells, endothelial cells, and macrophages. Extensive research has identified many of the key cellular and molecular regulators that play a part in apoptosis within the atherosclerotic lesion. This information will help us to gain a better understanding of the underlying mechanisms at the cellular and molecular level and enable us to formulate better therapeutic strategies to combat this disease.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".