Characterization of Thrombin-Induced Leukocyte Rolling and Adherence: A Potential Proinflammatory Role for Proteinase-Activated Receptor-4
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Bibliographic record
Abstract
It is commonly accepted that thrombin exerts its proinflammatory properties through the activation of proteinase-activated receptor (PAR)-1, although two other thrombin receptors have been discovered: PAR-3 and PAR-4. In this study, we have investigated the mechanisms and the receptors involved in thrombin-induced leukocyte/endothelial cell interactions by using selective agonists and antagonists of thrombin receptors in an in vivo intravital microscopy system. Topical addition of selective PAR-1 agonists to rat mesenteric venules failed to reproduce the increased leukocyte rolling and adhesion observed after thrombin topical addition. When added together with the selective PAR-1 antagonist RWJ-56110, thrombin was still able to provoke increased leukocyte rolling and adherence. The thrombin-induced leukocyte rolling and adherence was not affected by pretreatment of rats with an anti-platelet serum. Selective PAR-4-activating peptide was able to reproduce the effects of thrombin on leukocyte rolling and adhesion. Intraperitoneal injection of PAR-4-activating peptide also caused a significant increase in leukocyte migration into the peritoneal cavity. In rat tissues, PAR-4 expression was detected both on endothelium and isolated leukocytes. Taken together, these results showed that in rat mesenteric venules, thrombin exerts proinflammatory properties inducing leukocyte rolling and adherence, by a mechanism independent of PAR-1 activation or platelet activation. However, PAR-4 activation either on endothelial cells or on leukocytes might be responsible for the thrombin-induced effects. These findings suggest that PAR-4 activation could contribute to several early events in the inflammatory reaction, including leukocyte rolling, adherence and recruitment, and that in addition to PAR-1, PAR-4 could be involved in proinflammatory properties of thrombin.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it