Measurement of the activation of equine platelets by use of fluorescent-labeled annexin V, anti-human fibrinogen antibody, and anti-human thrombospondin antibody
Bibliographic record
Abstract
OBJECTIVE: To investigate the potential use of fluorescent-labeled annexin V, anti-human fibrinogen antibody, and anti-human thrombospondin antibody for detection of the activation of equine platelets by use of flow cytometry. SAMPLE POPULATION: Platelets obtained from 6 Thoroughbreds. PROCEDURE: Flow cytometry was used to assess platelet activation as indicated by detection of binding of fluorescent-labeled annexin V, anti-human fibrinogen antibody, and anti-thrombospondin antibody to unactivated and ADP-, collagen-, platelet activating factor (PAF)-, and A23187-activated equine platelets. Human platelets were used as control samples. Determination of 14C-serotonin uptake and release was used to assess the extent of platelet secretion. RESULTS: Anti-human thrombospondin antibody failed to bind to equine platelets. Annexin V bound to platelets activated with PAF or A23187 when platelets had undergone secretion. Anti-human fibrinogen antibody bound to ADP-, PAF-, and A23817-activated platelets, but binding was not dependent on platelet secretion. The extent of binding of anti-fibrinogen antibody was less in equine platelets, compared with that for human platelets, despite maximal stimulation. CONCLUSIONS AND CLINICAL RELEVANCE: Activation of equine platelets can be detected by use of fluorescent-labeled annexin V and anti-human fibrinogen antibody but not by use of anti-human thrombospondin antibody. These flow cytometric techniques have the potential for detection of in vivo platelet activation in horses at risk of developing thrombotic disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".