Angiopoietin‐Like 2 Promotes Atherogenesis in Mice
Bibliographic record
Abstract
BACKGROUND: Angiopoietin like-2 (angptl2), a proinflammatory protein, is overexpressed in endothelial cells (ECs) from patients with coronary artery disease (CAD). Whether angptl2 contributes to atherogenesis is unknown. We tested the hypothesis that angptl2 promotes inflammation and leukocyte adhesion onto ECs, thereby accelerating atherogenesis in preatherosclerotic dyslipidemic mice. METHODS AND RESULTS: In ECs freshly isolated from the aorta, basal expression of TNF-α and IL-6 mRNA was higher in 3-month-old severely dyslipidemic mice (LDLr(-/-); hApoB100(+/+) [ATX]) than in control healthy wild-type (WT) mice (P<0.05) and was increased in both groups by exogenous angptl2 (100 nmol/L). Angptl2 stimulated the adhesion of leukocytes ex vivo on the native aortic endothelium of ATX, but not WT mice, in association with higher expression of ICAM-1 and P-selectin in ECs (P<0.05). Antibodies against these endothelial adhesion molecules prevented leukocyte adhesion. Intravenous administration of angptl2 for 1 month in preatherosclerotic 3-month-old ATX mice increased (P<0.05) total cholesterol and LDL-cholesterol levels, strongly induced (P<0.05) the expression of endothelial proinflammatory cytokines and adhesion molecules while accelerating atherosclerotic lesion formation by 10-fold (P<0.05). Plasma and aortic tissue levels of angptl2 increased (P<0.05) with age and were higher in 6- and 12-month-old ATX mice than in age-matched WT mice. Angptl2 accumulated to high levels in the atherosclerotic lesions (P<0.05). Finally, angptl2 was greatly expressed (P<0.05) in ECs cultured from CAD patients, and circulating angptl2 levels were 6-fold higher in CAD patients compared with age-matched healthy volunteers. CONCLUSIONS: Angptl2 contributes to the pathogenesis of atherosclerosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".