Abstract 571: A Novel High-Throughput Whole Blood Immuno-Counting Assay is Useful in the Assessment of Platelet Responses to Antiplatelet Therapy
Bibliographic record
Abstract
Background: The current gold standard in platelet function testing, light transmission aggregometry, is time- and labor-intensive, and uses platelet-rich plasma which makes it sub-optimal for high throughput testing. In order to reduce blood manipulation prior to platelet function testing and to study multiple platelet activation pathways simultaneously, we have developed a 96-well plate-based assay carried out in whole blood, where aggregation is measured as a decrease in the number of fluorescently-labeled single platelets by flow cytometry. Aim: To investigate whether a 96-well plate-based whole blood assay can be used to assess platelet function. Methods: Platelet function in response to 5 concentrations of lyophilized arachidonic acid (AA), ADP, collagen, epinephrine, TRAP, U46619, and ristocetin, was assessed in healthy volunteers (n=20) to establish normal ranges. The effect of antiplatelet drugs was assessed in vitro by incubation with aspirin (100 μM), cangrelor (1 μM) or both (n=20), and in patients on dual antiplatelet therapy (n=20). After addition of 40 μl of whole blood per well, the plate was shaken for 5 min at 1000 rpm at 37°C; a fixative solution (Platelet Solutions, Nottingham) was applied to stop platelet aggregation and allow analysis in a central laboratory. Fixed whole blood samples (stable for up to 9 days) were labeled with FITC-conjugated CD42a and assessed by flow cytometry. Aggregation was calculated as (Platelet count in vehicle-treated sample - Platelet count in agonist-stimulated sample) / Platelet count in vehicle-treated sample x 100. Results: Dose-response curves were readily assessable for all agonists and intra-individual variability was minimal in healthy volunteers (CV<10%). In vitro addition of aspirin alone resulted in inhibition of AA- and collagen-induced aggregation, whereas cangrelor induced a shift in dose-response to most agonists in addition to profound inhibition of ADP responses. In patients on dual antiplatelet therapy, the pattern of response was consistent with the results obtained with in vitro agents. Conclusions: A 96-well plate-based whole blood assay with a minimal blood volume requirement (<2 ml) could be used to provide a global portrait of platelet responses to antiplatelet agents.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.005 |
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".