Endothelial Progenitor Cells Bind and Inhibit Platelet Function and Thrombus Formation
Bibliographic record
Abstract
BACKGROUND: Interactions of endothelial progenitor cells (EPCs) with vascular and blood cells contribute to vascular homeostasis. Although platelets promote the homing of EPCs to sites of vascular injury and their differentiation into endothelial cells, the functional consequences of such interactions on platelets remain unknown. Herein, we addressed the interactions between EPCs and platelets and their impact on platelet function and thrombus formation. METHODS AND RESULTS: Cultured on fibronectin in conditioned media, human peripheral blood mononuclear cells differentiated, within 10 days of culture, into EPCs, which uptake acetylated low-density lipoprotein, bind ulex-lectin, lack monocyte/leukocyte markers (CD14, P-selectin glycoprotein ligand-1, L-selectin), express progenitor/endothelial markers (CD34, vascular endothelial growth factor receptor-2, von Willebrand factor, and vascular endothelial cadherin), and proliferate in culture. These EPCs bound activated platelets via CD62P and inhibited its translocation, glycoprotein IIb/IIIa activation, aggregation, and adhesion to collagen, mainly via prostacyclin secretion. Indeed, this was associated with upregulation of cyclooxygenase-2 and inducible nitric oxide synthase. However, the effects on platelets in vitro were reversed by cyclooxygenase and cyclooxygenase-2 inhibition but not by nitric oxide or inducible nitric oxide synthase inhibition. Moreover, in a ferric chloride-induced murine arterial thrombosis model, injection of EPCs led to their incorporation into sites of injury and impaired thrombus formation, leading to an incomplete occlusion with 50% residual flow. CONCLUSIONS: Peripheral blood mononuclear cell-derived EPCs bind platelets via CD62P and inhibit platelet activation, aggregation, adhesion to collagen, and thrombus formation, predominantly via upregulation of cyclooxygenase-2 and secretion of prostacyclin. These findings add new insights into the biology of EPCs and define their potential roles in regulating platelet function and thrombosis.
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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 | 0.001 |
| 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".