Lipoprotein-Associated Phospholipase A2: How Effective as a Risk Marker of Cardiovascular Disease and as a Therapeutic Target?
Bibliographic record
Abstract
Lipoprotein-associated phospholipase A2 (Lp-PLA2) has been studied extensively in terms of biology, pathophysiology, diagnostic and prognostic values. Lp-PLA2 is an enzyme produced in atherosclerotic plaque by inflammatory cells, linked to LDL, HDL and VLDL. The binding of Lp-PLA2 to a specific lipoprotein fraction renders it more atherogenic. Increasing evidence has demonstrated Lp-PLA2 as a novel "ideal" marker for CVD as of its high specificity for vascular inflammation and low biologic variability. Thus, determination of Lp-PLA2 in individuals may provide clinically relevant information about their future risk of CVD events. In addition, Lp-PLA2 has been considered as a therapeutic target, which has been acted upon indirectly (lipid lowering medications) and directly (Lp-PLA2 antagonists such as darapladib) in pharmacologic therapies. This review will provide an overview on biochemistry, biology, proatherogenic, proinflammatory and proapoptotic effects of Lp-PLA2. Clinical utility and its validity as an independent CVD biomarker as well as a diagnostic biomarker to be detected in the very early stages of atherosclerosis will be also discussed. Moreover, the role of Lp-PLA2 as a pharmacologic therapeutic target is another theme of this review.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".