Thrombin induces endothelial cell-surface exposure of the plasminogen receptor annexin 2
Bibliographic record
Abstract
Cell-surface annexin 2 (A2) and its ligand p11 have been implicated in fibrinolysis because of their ability to accelerate tissue plasminogen activator (tPA)-mediated activation of plasminogen to plasmin. Because thrombin is a potent cell modulator obligately produced at the site of clot formation, we hypothesized that the amount of cell-surface A2 and p11 might be altered by thrombin with consequent effects on plasmin generation. In support of this hypothesis, immunofluorescence microscopy and hydrophilic biotinylation experiments showed that both A2 and p11 were significantly increased on the surface of human umbilical vein endothelial cells (HUVECs) treated with thrombin (0.8-8 nM) for 5 minutes followed by 1 hour at 37 degrees C. Intracellular immunofluorescence microscopy and immunoblot analyses of whole cell extracts revealed increased p11 but unchanged A2 in response to thrombin, suggesting that transbilayer trafficking of A2 might be controlled by p11. The thrombin receptor-activating peptide (TRAP) similarly affected cells, demonstrating that cell signaling at least involved the type-1 protease activated receptor (PAR-1). An effect on the fibrinolysis pathway after treatment of HUVECs with thrombin was shown by increased fluorescein-labeled plasminogen binding to cells, which was inhibited by an antibody specific for p11. This was confirmed by observing that thrombin pretreatment of HUVECs increased biotin-modified plasminogen binding. Utilizing a chromogenic assay, pretreatment of HUVECs by thrombin further enhanced activation of the Glu and Lys forms of plasminogen by tPA. These data suggest a novel mechanism that links the coagulation and fibrinolysis pathways by thrombin-mediated feedback.
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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) | 0.003 | 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".