Abstract 334: A Novel Model For Tracking Endothelial-derived Extracellular Vesicles In Murine Atherosclerotic Disease
Bibliographic record
Abstract
Introduction: An early marker of atherosclerosis is endothelial cell (EC) dysfunction. ECs are uniquely positioned as a boundary layer of the vessel wall capable of communicating with the circulating blood and the vessel wall. Extracellular vesicles (EVs), nanoparticles that carry cargo capable of governing cellular function and/or signalling disease have emerged as a novel communication paradigm. While in vitro models have shown EC-EV crosstalk with monocytes and vascular smooth muscle cells, animal models interrogating EC-EVs in atherosclerosis are lacking. We therefore created a model that allowed us to detect, quantify and visualize fluorescent EC-EVs in a murine model of atherosclerosis. Methods: Nine-week-old mice (LCE Gr ; Ldlr -/- :Cdh5Cre ERT2 :CD63-emGFP l/s/l and LE Gr ; Ldlr -/- :CD63-emGFP l/s/l ) were injected with tamoxifen (3 mg i.p., 3 doses, male & female) to induce green fluorescent EC-EVs. Mice received high-cholesterol diet (HCD, 12 wks) to promote atherosclerotic lesion formation or normal chow. EVs were enriched by size exclusion chromatography from plasma, quantified, and characterized by nanoparticle tracking analysis (NTA). Flow cytometry was performed to detect EC-EVs in cells isolated from whole blood. EC-EVs were visualized within atherosclerotic plaques using confocal microscopy. Results: As anticipated, HCD-fed mice developed atherosclerotic plaques compared to mice fed normal chow (n=3/grp). Fluorescent (GFP+) EVs were visualized in plasma of tamoxifen treated LCE Gr mice (NTA, 488nm laser; EVs pooled from 3 mice) and detected in blood cells of tamoxifen treated LCE Gr mice, but not in LE Gr mice (flow cytometry, n=2-4/grp). NTA demonstrated total plasma EVs were increased in HCD-fed mice compared to mice on chow diet (2.21x10 12 vs 2.40x10 11 particles/ml; p<0.0001; n=3/grp). Using confocal imaging we observed tissue-based EC communication in atherosclerotic plaques, where EC-EVs colocalize within leukocytes (GFP+CD45+; n=2/grp). Conclusions: This mouse model enabled detection of fluorescent (GFP+) EC-EVs in the circulating blood and visualization in leukocytes within atherosclerotic plaques. Further characterization of this model will help assess the role of EC-EVs in atherosclerotic plaque development.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".