Microparticles From Human Atherosclerotic Plaques Promote Endothelial ICAM-1–Dependent Monocyte Adhesion and Transendothelial Migration
Bibliographic record
Abstract
RATIONALE AND OBJECTIVE: Membrane-shed submicron microparticles (MPs) released following cell activation or apoptosis accumulate in atherosclerotic plaques, where they stimulate endothelial proliferation and neovessel formation. The aim of the study was to assess whether or not MPs isolated from human atherosclerotic plaques contribute to increased endothelial adhesion molecules expression and monocyte recruitment. METHOD AND RESULTS: Human umbilical vein and coronary artery endothelial cells were exposed to MPs isolated from endarterectomy specimens (n=62) and characterized by externalized phosphatidylserine. Endothelial exposure to plaque, but not circulating, MPs increased ICAM-1 levels in a concentration-dependant manner (3.4-fold increase) without affecting ICAM-1 mRNA levels. Plaque MPs harbored ICAM-1 and transferred this adhesion molecule to endothelial cell membrane in a phosphatidylserine-dependent manner. MP-borne ICAM-1 was functionally integrated into cell membrane as demonstrated by the increased ERK1/2 phosphorylation following ICAM-1 ligation. Plaque MPs stimulated endothelial monocyte adhesion both in culture and in isolated perfused mouse carotid. This effect was also observed under flow condition and was prevented by anti-LFA-1 and anti-ICAM-1 neutralizing antibodies. MPs isolated from symptomatic plaques were more potent in stimulating monocyte adhesion than MPs from asymptomatic patients. Plaque MPs did not affect the release of interleukin-6, interleukin-8, or MCP-1, nor the expression of VCAM-1 and E-selectin. CONCLUSION: These results demonstrate that MPs isolated from human atherosclerotic plaques transfer ICAM-1 to endothelial cells to recruit inflammatory cells and suggest that plaque MPs promote atherosclerotic plaque progression.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".