Cyclooxygenase-2 Promotes Early Atherosclerotic Lesion Formation in LDL Receptor–Deficient Mice
Bibliographic record
Abstract
BACKGROUND: Atherosclerosis has features of an inflammatory disease. Because cyclooxygenase (COX)-2 is expressed in atherosclerotic lesions and promotes inflammation, we tested the hypotheses that selective COX-2 inhibition would reduce early lesion formation in LDL receptor-deficient (LDLR-/-) mice and that macrophage COX-2 expression contributes to atherogenesis in LDLR-/- mice. METHODS AND RESULTS: Treatment of male LDLR-/- mice fed the Western diet with rofecoxib or indomethacin for 6 weeks resulted in significant reductions in atherosclerosis in the proximal aorta (25% and 37%) and in the aorta en face (58% and 57%), respectively. Rofecoxib treatment did not inhibit platelet thromboxane production, a COX-1-mediated process, but it significantly reduced the urinary prostacyclin metabolite 2,3-dinor-6-keto-PGF1alpha. Fetal liver cell transplantation was used to generate LDLR-/- mice null for expression of the COX-2 gene by macrophages. After 8 weeks on the Western diet, COX-2-/- --> LDLR-/- mice developed significantly less (33% to 39%) atherosclerosis than control COX-2+/+ --> LDLR-/- mice. In both the inhibitor studies and the transplant studies, serum lipids did not differ significantly between groups. CONCLUSIONS: The present studies provide strong pharmacological and genetic evidence that COX-2 promotes early atherosclerotic lesion formation in LDLR-/- mice in vivo. These results support the potential of anti-inflammatory approaches to the prevention of atherosclerosis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".