Role of von Willebrand factor in tumour cell‐induced platelet aggregation: differential regulation by NO and prostacyclin
Bibliographic record
Abstract
1. We have studied the effects of a novel agonist, solid-phase von Willebrand Factor (sVWF), on tumour cell-induced platelet aggregation (TCIPA). 2. Washed platelet suspensions were obtained from human blood and the effects of HT-1080 human fibrosarcoma cells and sVWF on platelets were studied using aggregometry, phase-contrast microscopy, and flow cytometry. 3. Incubation of platelets with sVWF (1.2 microg ml(-1)) and HT-1080 cells (5 x 10(3) ml(-1)) resulted in a two-phased reaction characterized first by the adhesion of platelets to sVWF, then by aggregation. 4. TCIPA in the presence of sVWF was inhibited by S-nitroso-glutathione (GSNO, 100 microM) and prostacyclin (PGI(2), 30 nM). 5. Platelet activation in the presence of tumour cells and sVWF resulted in the decreased surface expression of platelet glycoprotein (GP)Ib and up-regulation of GPIIb/IIIa receptors. 6. Pre-incubation of platelets with PGI(2) (30 nM) resulted in inhibition of sVWF-tumour cell-stimulated platelet surface expression of GPIIb/IIIa as measured by flow cytometry using antibodies directed against both non-activated and activated receptor. In contrast, GSNO (100 microM) did not affect sVWF-tumour cell-stimulated platelet surface expression of GPIIb/IIIa. 7. Flow cytometry performed with PAC-1 antibodies that bind only to the activated GPIIb/IIIa revealed that GSNO (100 microM) caused inhibition of activation of GPIIb/IIIa. 8. The inhibitors exerted no significant effects on TCIPA-mediated changes in GPIb. 9. Thus, sVWF potentiates the platelet-aggregatory activity of HT-1080 cells and these effects appear to be mediated via up-regulation of platelet GPIIb/IIIa. 10. Prostacyclin and NO inhibit TCIPA-sVWF-mediated platelet aggregation. The mechanisms of inhibition of this aggregation by PGI(2) differ from those of NO.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".