Altered Gene Expression in Early Atherosclerosis Is Blocked by Low Level Apolipoprotein E
Bibliographic record
Abstract
BACKGROUND: Mice deficient in apolipoprotein E (apoE(-/-)) develop atherosclerosis. The possible linkage between expression of adhesion molecules/cofactors and atherosclerosis was probed at the level of mRNA and protein expression. The hypothesis of a linkage between changes of adhesion molecules/cofactors and atherosclerosis was tested further by suppression of aortic lesion formation in apoE(-/-) mice by expression of very low levels of transgenic apolipoprotein E. METHODOLOGY/PRINCIPAL FINDINGS: We show that at 8.5 months of age, the apoE(-/-) mice display elevated expression of mRNA for LFA-1, MAC-1, VCAM-1, ICAM-1, and for CD44, as well as MCP-1, cathepsin B, and COX-2 (but not that for eNOS) in atherosclerotic aortic arches. At earlier age, (10-13 week old) apoE(-/-) mice already display elevated expression of mRNA of CD44, LFA-1, MAC-1, VCAM-1, ICAM-1, cathepsin, and of COX-2 in lesioned aortic arches. Expressing very low levels of transgenic apolipoprotein E suppresses both aortic lesions and the expression of mRNA of LFA-1, VCAM-1, MCP-1, cathepsin B, and of ICAM-1 in ApoE(-/-) mice. We tested at the level of protein, the observations obtained for mRNA expression. CD11a (a component of LFA-1), VCAM-1 and cathepsin B expression was found to be elevated in apoE(-/-) aortas at 8-9 months; low level expression of transgenic apolipoprotein E rectifies these changes. CONCLUSIONS/SIGNIFICANCE: Atherosclerotic lesions in apoE(-/-) mice are detected as early as 4 weeks of age. Expression of low levels of apoE is shown to be both atheroprotective and to suppress these changes in key adhesion and inflammatory molecules observed in early atherosclerotic lesions.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".