The spatial distribution and abundance of intimal myeloid cells in the normal mouse aorta correlate with the location and strain susceptibility to atherosclerosis
Bibliographic record
Abstract
Atherosclerotic lesions develop in regions of arterial curvature and branch points, which are exposed to disturbed blood flow and have unique gene expression patterns. We evaluated the abundance of monocytes/macrophages (mϕ) dendritic cells (DC) and T‐cells in normal aortas of normocholesterolemic mice using real‐time PCR and en face immunoconfocal microscopy. In C57BL/6 mice, abundant intimal mϕ and DC, but only occasional T‐cells, were found in the lesser curvature (LC) of the aortic arch, a region predisposed to atherosclerosis. In contrast, very few leukocytes were detected in the greater curvature (GC), a region resistant to lesion formation. Abundant mϕ were found in the adventitia of both the LC and GC. The recruitment of monocytes from the blood, as opposed to local proliferation, accounted for mϕ accumulation in the intima. Significantly lower numbers of intimal mϕ were found in atherosclerosis‐resistant inbred strains (C3H and BALB/c) relative to C57BL/6, indicating that the abundance of intimal mϕ correlates with the strain susceptibility to atherosclerosis. However, there were similar numbers of mϕ in the adventitia of all strains. Our data suggest that the spatial distribution and abundance of intimal leukocytes may influence atherogenesis induced by hypercholesterolemia and other proatherogenic stimuli.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".