Complementary Roles for Fibrin(ogen), Thrombospondin and vWF in Mediating Shear-dependent Aggregation of Platelets Stimulated at Threshold Thrombin Concentrations
Bibliographic record
Abstract
We have evaluated the relative contribution of the adhesive ligands, von Willebrand factor (vWF), fibrinogen (Fg) and thrombospondin (TSP), all surface-expressed on washed platelets (WP) activated with a threshold thrombin concentration (approximately 0.04 U/ml), to platelet microaggregation (PA) at shear rates (G) from 300-2000 s(-1). In suspensions of thrombin-activated WP sheared immediately (tau0), all three ligands were required for optimal aggregation at all G, as shown by a 50-70% inhibition of capture efficiencies of PA (measured from initial rates of PA), by antibodies (Abs) directed against each protein. This aggregation involved both GPIb and GPIIbIIIa, as indicated by approximately 80% and 100% inhibition by Ab 6D1 and Ab 10E5, respectively. For WP preexposed to thrombin for 10 min to ensure maximal surface expression of secreted ligands and activated GPIIbIIIa (tau0), vWF was predominantly required at all G (63-75% inhibition by anti-vWF Ab), together with TSP (35-50% inhibition by anti-TSP Ab). Under these conditions, Fg was extensively converted to fibrin, so that fibrin, rather than Fg, could participate in microaggregation, with GPIb less required than GPIIbIIIa as indicated by a 30-60% inhibition by Ab 6D1 as compared to 100% inhibition by Ab 10E5. Our results show that interactions between multiple ligands and receptors favour microaggregation depending on shear and thrombin activation conditions.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".