Plasma derived extracellular vesicle biomarkers of microglia activation in an experimental stroke model
Bibliographic record
Abstract
Abstract Chronic microglia activation post-stroke is associated with worse neurological and cognitive outcomes. However, measurement of microglia activation in vivo is currently limited. Plasma derived extracellular vesicles (EVs) are cell-specific indicators that may allow for non-invasive measurement of microglia phenotype. The aim of this study was to identify activation-state specific microglia EVs (MEVs) in vitro followed by validation in an experimental stroke model. Following pro-inflammatory activation, MEVs contain the microglia protein TMEM119 alongside increased expression of the Toll-like receptor 4 co-receptor CD14. Immunoprecipitation followed by fluorescent nanoparticle tracking analysis (ONI Nanoimager) was used to confirm the isolation of TMEM119 + /CD14 + EVs from rat plasma. Electron microscopy confirmed that TMEM119 and CD14 localize to the MEV membrane. To model ischemia, plasma was collected from 3-month wildtype Fischer344 rats prior to, 7 and 28 days after endothelin-1 or saline injection into the dorsal right striatum. Fluorescently labelled MEVs were directly measured in the plasma using nanoflow cytometry (Apogee A60 Microplus). We report a significant increase in circulating TMEM119 + /CD14 + EVs 28-days post-stroke in comparison to baseline levels and saline-injected rats, which correlated weakly with stroke volume. TMEM119 + /MHC-II + EVs were also increased post-stroke in comparison to baseline and saline-injected animals. This study is the first to describe an EV biomarker of activated microglia detected directly in plasma following stroke and represents a future tool for the measurement of microglia activity in vivo .
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".