Activation of platelets by in vitro whole blood contact with materials: Increases in microparticle, procoagulant activity, and soluble P-selectin blood levels
Bibliographic record
Abstract
Non-adherent platelets and plasma were analyzed for evidence of platelet activation after whole blood contact with materials under conditions of low shear for one hour at 37 degrees C. The contact involved adding heparinized whole blood to small diameter tubes that were connected to two arms extending from a rocking platform. For all surfaces (polyethylene, polypropylene, Silastic, PVA hydrogel) tested there was strong evidence of platelet activation in the bulk blood: platelet-derived microparticles, procoagulant platelet membranes and soluble P-selectin levels. Flow cytometric quantification of microparticles (MPs) was highly sensitive and entailed the direct determination of microparticle concentrations as opposed to the traditional quantification of microparticle percentages (relative to total number of MPs and platelets). Whole blood contact with polypropylene surfaces led to the greatest drops in bulk platelet counts and also to the lowest increases in microparticle concentrations. Flow cytometry was also used to assess procoagulant levels (annexin V binding) within a light scatter region known to contain platelets and some large microparticles. All surfaces were noted to generate a significant procoagulant population that was, based on forward light scatter, mostly very small platelets or large microparticles. In contrast, most of the P-selectin positive platelets were averaged sized. Lastly. all surfaces generated soluble P-selectin levels that were approximately double the level (25 ng ml(-1)) noted in the resting whole blood samples. In addition to our previous reports, these findings support the observation that there is strong evidence of platelet activation in the bulk that we anticipate will ultimately lead to more relevant in vitro testing of the compatibility of platelets towards materials.
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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) | 0.001 | 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) | 0.002 | 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".