Abstract 2: Aorta Intima-Resident Macrophages Contribute to Atherosclerotic Lesion Initiation
Bibliographic record
Abstract
Atherosclerosis is an underlying cause of cardiovascular disease and a leading cause of mortality worldwide. Macrophage accumulation in atherosclerotic plaque, their uptake of cholesterol, and subsequent local death drive disease progression. Lipid-laden plaque macrophages are thought to be exclusively derived from blood monocyte progenitors that are recruited following endothelial damage induced by cholesterol exposure. In our current study, we focused on characterization of resident vascular macrophages that reside in the aortic intima in plaque-prone areas, previously identified as ‘vascular dendritic cells’. Using en face whole-mount confocal microscopy of aortas, we confirm a uniform resident CD64 + CD11c + CX3CR1 + MHCII + macrophage population, which is present in C57/BL6 mice resistant to atherosclerosis. Importantly, they do not express dendritic cell restricted genes zBTB46 or L-myc. We find aortic macrophages require M-CSF and Flt3 signaling for survival, but are independent of CCR2, CCR7, and GM-CSF receptor signaling, making them a distinct myeloid population. Lineage-tracing and parabiosis approaches suggest these cells derive from definitive hematopoiesis and are then self-maintained independent of blood-progenitors. Using these characterization data, we developed a labeling strategy to identify resident from recruited macrophages during kinetic studies of lesion progression. We find that resident aortic macrophages are the first cells to take up lipid following high fat diet exposure and expand within the arterial wall to form the initial lesion bed. In the absence of resident macrophages early lipid deposition in the aortic arch is ablated. Finally, utilizing an intravital carotid artery imaging approach, we identify resident aortic macrophages to be potential mediators of monocyte recruitment through direct interactions with rolling monocytes on the endothelial surface under diseased and steady-states. Overall, these results shift our understanding of the cellular mechanisms responsible for plaque construction and maintenance.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".