Pathogenesis of atherosclerosis: A multifactorial process.
Bibliographic record
Abstract
Atherosclerosis is a leading cause of mortality and morbidity in the western world. It has been recognized for over a century, and the understanding of its pathogenesis has undergone many changes. Pathophysiological studies have unravelled the interactions of molecular and cellular elements involved in atherogenesis. The focus has shifted to the novel risk factors as well as characteristics and stability of atherosclerotic plaque; the genetic predisposition has further broadened the pathogenetic mechanisms. This review focuses on the molecular mechanisms involved in the evolution of the atherosclerotic plaque that may pave the way for selecting optimal therapies and preventing plaque complications. Atherosclerosis is no longer a disease attributed mainly to the high lipid content of the body. New insight into the disease pathology has shown it to be a disease of much greater ramifications. Endothelial damage and reactive oxygen species (and other free radicals) have predominantly emerged as factors in virtually all pathways leading to the development of atherosclerosis due to hyperlipidemia, diabetes, hypertension or smoking. Novel risk factors such as hyperhomocysteinemia, infections and systemic lupus erythematosus have emerged. Atherosclerosis has come to be regarded as a chronic inflammatory disease with an autoimmune component. The genetic basis of the disease assumes significance as candidate genes are identified and gene therapy becomes a promising new addition to the existing, less substantial conventional therapies.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".