Instrument and technique for the <i>in vitro</i> screening of platelet activation from whole blood samples
Bibliographic record
Abstract
The measurement of platelet activation is very difficult to accomplish clinically as platelets are readily activated by in vitro manipulations. Although techniques such as platelet aggregation and flow cytometry exist to estimate platelet function, important limitations prevent these techniques to be widely accepted. In this study, low-fouling surfaces used to limit ex vivo platelet activation were locally bioactivated to rapidly detect platelet activation from whole blood through the selective local adhesion and aggregation of artificially activated platelets. To achieve this result, a fabrication method was developed to create arrays of anti-CD62 and anti-CD61 proteins covalently immobilized on substrates covered by low-fouling graft layers. Moreover, to further limit ex vivo platelet activation and to obtain reproducible results, a custom-made flow chamber was designed and fabricated with the help of computer-assisted mathematical modeling to create defined shear environments. This diagnostic instrument has the potential to allow the rapid estimation of platelet activation levels in whole blood.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".