Mechanisms and Biomarker Potential of Extracellular Vesicles in Stroke
Bibliographic record
Abstract
Stoke is a prevalent and devastating neurologic condition with limited options for therapeutic management. Since brain tissue is rarely accessible clinically, peripheral biomarkers for the central nervous system's (CNS's) cellular response to stroke may prove critical for increasing our understanding of stroke pathology and elucidating novel therapeutic targets. Extracellular vesicles (EVs) are cell-derived, membrane-enclosed vesicles secreted by all cell types within the CNS that can freely pass the blood-brain barrier (BBB) and contain unique markers and content linked to their cell of origin. These unique qualities make brain-derived EVs novel candidates for non-invasive blood-based biomarkers of both cell specificity and cell physiological state during the progression of stroke and recovery. While studies are continuously emerging that are assessing the therapeutic potential of EVs and profiling EV cargo, a vast minority of these studies link EV content to specific cell types. A better understanding of cell-specific EV release during the acute, subacute, and chronic stages of stroke is needed to further elucidate the cellular processes responsible for stroke pathophysiology. Herein, we outline what is known about EV release from distinct cell types of the CNS during stroke and the potential of these EVs as peripheral biomarkers for cellular function in the CNS during 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 | 0.000 | 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".