Role of Matrix Metalloproteinase-2 in the Development of Atherosclerosis among Patients with Coronary Artery Disease
Bibliographic record
Abstract
Coronary artery disease (CAD) is a caused by atherosclerotic plaque buildup in the coronary arteries that supply blood and oxygen to the heart. Matrix metalloproteinase (MMP) is a family of zinc-dependent endopeptidase that is involved in various stages of atherosclerosis as demonstrated in in vitro and in vivo studies. MMP-2 is associated with both stable and unstable atherosclerotic plaque formation. The current review aimed to identify the role of MMP-2 in atherosclerosis development among CAD patients. Literature search was conducted through four online databases and only studies that were published from 2018 until February 2023 were included. The risk of bias was assessed by using the Newcastle–Ottawa Scale. A total of 10,622 articles were initially identified, and only eight studies that fulfilled the selection criteria were included in this review. The results showed that MMP-2 levels and activity were higher in patients with unstable CAD than those with stable CAD and healthy subjects. There was a significant association between MMP-2 levels and cardiovascular disease with MMP-14 levels, which is a pro-MMP-2 activator. In addition, two single nucleotide polymorphisms of the MMP-2 gene (rs243865 and rs243866) were significantly associated with the development of atherosclerosis. In conclusion, MMP-2 plays a crucial role in the development of atherosclerosis among patients with CAD and could be a potential target for CAD therapy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".