Expression of Platelet-Activating Factor Receptor in Human Carotid Atherosclerotic Plaques
Bibliographic record
Abstract
BACKGROUND: Human monocyte-derived macrophages synthesize numerous proinflammatory and prothrombotic substances, including lipid mediators, such as platelet-activating factor (PAF), which may play a major role in the onset and perpetuation of atherosclerotic lesions. In addition, both monocytes and macrophages express PAF receptors (PAF-R). The expression of PAF-R is transcriptionally downregulated by oxidized LDL in in vitro primary cultures of monocyte/macrophages. In this study, we evaluated the expression of PAF-R in human carotid plaque tissue, in foam cells isolated from human carotid plaques, and in primary cultures of umbilical smooth muscle cells (SMCs). METHODS AND RESULTS: We show that PAF-R was expressed at low levels in foam cells compared with monocyte/macrophages in plaques, as assessed by immunohistochemical staining and in situ hybridization. In addition, low levels of mRNA were also detected by RT-PCR in isolated human carotid foam cells. A prominent finding of our study was the demonstration that contractile SMCs were positive for PAF-R, and its mRNA was extracted from primary cultures of umbilical SMCs. CONCLUSIONS: As macrophages loose their inflammatory phenotype on transformation into foam cells, they may equally loose their capacity of defense against aggression. We postulate that the diminished expression of PAF-R may be deleterious in the context of plaque formation and progression. The observation that arterial SMCs of contractile phenotype express PAF-R opens new avenues concerning the migration of these cells from media to intima and atherosclerotic plaque formation.
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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) | 0.002 | 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".