Abstract 3046: Macrophage-smooth Muscle Cell Interactions In Atherosclerotic Foam Cell Formation
Bibliographic record
Abstract
Background: A hallmark of atherosclerosis is uncontrolled uptake of atherogenic lipoproteins by artery wall cells that accumulate large amounts of cholesteryl esters (“foam cells”). While smooth muscle cells (SMCs) and macrophages are in close proximity in lesions and contribute to cholesterol accumulation, whether these cells influence each other’s tendency to form foam cells is not clearly established. Hypothesis: Direct and indirect interactions between SMCs and macrophages promote foam cell formation by both cell types. Method: Human vascular SMCs were seeded onto macrophages to mimic direct macrophage-SMC interactions (n=5). Alternatively, conditioned media generated from human macrophages or SMCs with or without lipoprotein exposure was incubated with the alternate cell type (n=3). Aggregated lipoproteins were added in both models to induce cellular cholesterol accumulation. Intracellular cholesterol was quantified to compare lipoprotein uptake in cocultures relative to monocultures. Crosstalk based on CellChat analysis using single-cell RNA sequencing data from human coronary samples was performed to identify potential factors responsible for foam cell development (n=3). One-way ANOVA was used for statistical analysis. Result: SMCs showed a 4-fold (+/-0.3, p=0.002) increase in cell cholesterol accumulation when in direct contact with macrophages and a 3-fold (+/- 0.3, p<0.0001) increase when exposed to the conditioned media from macrophage foam cells. In contrast, macrophages showed a 3-fold reduction (+/- 0.3, p=0.001) in intracellular cholesterol accumulation when in direct contact with SMCs and a 2-fold reduction (+/-0.2, p=0.0005) when exposed to SMC foam cell-conditioned media. CellChat analysis suggested macrophage foam cells but not macrophage non-foam cells promote SMC foam cell formation by secretion of inflammatory cytokines, and that SMCs promote macrophage foam cell formation by secretion of extracellular matrix components. Conclusion: Our study provides novel understanding of how macrophage-SMC interactions influence macrophage and SMC foam cell formation. Further studies will be presented examining the role of SMC extracellular matrix proteins and macrophage-secreted cytokines on foam cell formation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.015 | 0.007 |
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".