Transient adhesion refractoriness of circulating platelets under shear stress: the role of partial activation and microaggregate formation by suboptimal ADP concentration
Bibliographic record
Abstract
Exposure of whole blood (WB) to subendothelial extracellular matrix (ECM) under shear stress in the cone and plate(let) analyser (CPA) results in platelet adhesion, followed by release reaction and aggregation of circulating platelets on the adherent platelets. The properties of circulating non-adhered platelets in the CPA was studied by exposure of WB to ECM at a high shear rate (1300/s) for 2 min (1st run), followed by transfer of the suspension to a new ECM-coated well for a second run (2nd run) under similar conditions. The results of the 2nd run demonstrated transient adhesion refractoriness associated with platelet microaggregate formation in the suspension. The adhesion refractoriness was dependent on platelet activation during the 1st run and was prevented by addition of apyrase (ADP scavenger) or ADP receptor inhibitor, suggesting a role for ADP in mediating this response. Furthermore, exposure of WB samples to suboptimal concentrations of ADP (0.4-1 micromol/l) or a thrombin receptor activating peptide (TRAP) (5 micromol/l) for 2 min resulted in a similar transient platelet adhesion refractoriness to ECM under flow conditions. The transient platelet refractoriness and microaggregate formation induced by ADP was associated with a transient reduction in glycoprotein (GP)Ib, increased P-selectin expression and increased fibrinogen binding by circulating platelets. These data suggest a role for platelet agonists at suboptimal concentrations in modulating platelet function and limiting the expansion of the thrombus.
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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) | 0.001 | 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".