The diversity of platelet microparticles
Bibliographic record
Abstract
PURPOSE OF REVIEW: Platelet microparticles are small extracellular vesicles abundant in blood. The present review will introduce the mechanisms underlying the generation of microparticles, and will describe the diverse microparticle subtypes identified to date. The most appropriate methodologies used to distinguish microparticle subtypes will be also presented. RECENT FINDINGS: Both the megakaryocytes and platelets can generate microparticles. Circulating microparticles originating from megakaryocytes are distinguished from those derived from activated platelets by the presence of CD62P, LAMP-1, and immunoreceptor-based activation motif receptors. Close examination of platelet activation has shed light on a novel mechanism leading to microparticle production. Under physiologic flow, microparticles bud off from long membrane strands formed by activated platelets. Furthermore, mounting evidence supports the notion of microparticle heterogeneity. Platelet microparticles are commonly characterized by the expression of surface platelet antigens and phosphatidylserine. In fact, only a fraction of platelet microparticles harbor phosphatidylserine, and a distinct subset contains respiratory-competent mitochondria. During disease, the microparticle surface may undergo posttranslational modifications such as citrullination, further supporting the concept of microparticle diversity. SUMMARY: An appreciation of the microparticle heterogeneity will support their development as potential biomarkers and may reveal functions unique to each microparticle subtype in health and disease.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".