Circulating microparticles as biomarkers of stroke: A focus on the value of endothelial‐ and platelet‐derived microparticles
Bibliographic record
Abstract
Stroke is one of the leading causes of mortality and disability worldwide. Numerous pathophysiological mechanisms involving blood vessels, coagulation and inflammation contribute to the vascular occlusion. Perturbations in these pathways can be detected by numerous methods including changes in endoplasmic membrane remodeling and rearrangement leading to the shedding of microparticles (MPs) from various cellular origins in the blood. MPs are small membrane-derived vesicles that are shed from nearly all cells in the body in resting state or upon stimulation. MPs act as biological messengers to transfer information to adjacent and distant cells thus regulating various biological processes. MPs may be important biomarkers and tools for the identification of the risk and diagnosis of cerebrovascular diseases. Endothelial activation and dysfunction and altered thrombotic responses are two of the main features predisposing to stroke. Endothelial MPs (EMPs) have been recognized as both biomarkers and effectors of endothelial cell activation and injury while platelet-derived MPs (PMPs) carry a strong procoagulant potential and are activated in thrombotic states. Therefore, we reviewed here the role of EMPs and PMPs as biomarkers of stroke. Most studies reported high circulating levels of EMPs and PMPs in addition to other cell origins in stroke patients and have been linked to stroke severity, the size of infarction, and prognosis. The identification and quantification of EMPs and PMPs may thus be useful for the diagnosis and management of stroke.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".