A major role for VCAM-1, but not ICAM-1, in early atherosclerosis
Bibliographic record
Abstract
VCAM-1 and ICAM-1 are endothelial adhesion molecules of the Ig gene superfamily that may participate in atherogenesis by promoting monocyte accumulation in the arterial intima. Both are expressed in regions predisposed to atherosclerosis and at the periphery of established lesions, while ICAM-1 is also expressed more broadly. To evaluate functions of VCAM-1 in chronic disease, we disrupted its fourth Ig domain, producing the murine Vcam1(D4D) allele. VCAM-1(D4D) mRNA and protein were reduced to 2-8% of wild-type allele (Vcam1(+)) levels but were sufficient to partially rescue the lethal phenotype of VCAM-1-null embryos. After crossing into the LDL receptor-null background, Vcam1(+/+) and Vcam1(D4D/D4D) paired littermates were generated from heterozygous intercrosses and fed a cholesterol-enriched diet for 8 weeks. The area of early atherosclerotic lesions in the aorta, quantified by en face oil red O staining, was reduced significantly in Vcam1(D4D/D4D) mice, although cholesterol levels, lipoprotein profiles, and numbers of circulating leukocytes were comparable to wild-type. In contrast, deficiency of ICAM-1 either alone or in combination with VCAM-1 deficiency did not alter nascent lesion formation. Therefore, although expression of both VCAM-1 and ICAM-1 is upregulated in atherosclerotic lesions, our data indicate that VCAM-1 plays a dominant role in the initiation 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".