Analysis of procoagulant phosphatidylserine‐exposing platelets by imaging flow cytometry
Bibliographic record
Abstract
BACKGROUND: Upon platelet activation, a subpopulation of procoagulant platelets is formed, characterized by the exposure of the anionic aminophospholipid phosphatidylserine (PS) on the surface membrane. OBJECTIVE: To evaluate procoagulant PS-exposing platelets by imaging flow cytometry. METHODS: Platelet ultrastructure was examined by transmission electron microscopy, and a comprehensive analysis of procoagulant platelets was performed using imaging flow cytometry; platelets were fluorescently labeled for the markers glycoprotein (GP)IX, activated integrin αIIbβ3, CD62P, and PS exposure. RESULTS: A subpopulation of platelets stimulated in suspension by the physiological agonists thrombin+collagen, and all platelets stimulated by the calcium ionophore A23187, had a distinct round morphology. These platelets were PS-exposing, larger in size, had an increased circularity index, and had reduced internal complexity compared with non-PS-exposing platelets. They expressed CD62P and αIIbβ3 in an inactive conformation on the surface, and demonstrated depolarized inner mitochondrial membranes. For the first time, using imaging flow cytometry, a large proportion of PS-exposing platelets possessing platelet-associated extracellular vesicles (EVs) was observed, which demonstrated heterogeneous platelet marker expression that was different from free released EVs. CONCLUSIONS: Innovative imaging flow cytometry allowed detailed fluorescence-based, quantitative morphometric analysis of PS-exposing platelets; in becoming procoagulant, platelets undergo remarkable morphological changes, transforming into spherical "balloons," almost devoid of their normal internal architecture. Almost all PS-exposing platelets have associated EVs that are not detectable by traditional flow cytometry. While their functions have yet to be fully elucidated, the heterogeneity of platelet-associated and released EVs suggests that they may contribute to different aspects of hemostasis and of thrombosis.
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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 | 0.001 | 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 | 0.000 |
| 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".