Directional Endothelial Communication by Polarized Extracellular Vesicle Release
Bibliographic record
Abstract
BACKGROUND: Extracellular vesicles (EVs) contain bioactive cargo including miRNAs and proteins that are released by cells during cell-cell communication. Endothelial cells (ECs) form the innermost lining of all blood vessels, interfacing with cells in the circulation and vascular wall. It is unknown whether ECs release EVs capable of governing recipient cells within these 2 separate compartments. Given their boundary location, we propose ECs use bidirectional release of distinct EV cargo in quiescent (healthy) and activated (atheroprone) states to communicate with cells within the circulation and blood vessel wall. METHODS: EVs were isolated from primary human aortic ECs (plate and transwell grown; ±IL [interleukin]-1β activation), quantified, visualized, and analyzed by miRNA transcriptomics and proteomics. Apical and basolateral EC-EV release was determined by miRNA transfer, total internal reflection fluorescence and electron microscopy. Vascular reprogramming (RNA sequencing) and functional assays were performed on primary human monocytes or smooth muscle cells±EC-EVs. RESULTS: Activated ECs increased EV release, with miRNA and protein cargo related to atherosclerosis. EV-treated monocytes and smooth muscle cells revealed activated EC-EV altered pathways that were proinflammatory and atherogenic. ECs released more EVs apically, which increased with activation. Apical and basolateral EV cargo contained distinct transcriptomes and proteomes that were altered by EC activation. Notably, activated basolateral EC-EVs displayed greater changes in the EV secretome, with pathways specific to atherosclerosis. In silico analysis determined compartment-specific cargo released by the apical and basolateral surfaces of ECs can reprogram monocytes and smooth muscle cells, respectively, with functional assays and in vivo imaging supporting this concept. CONCLUSIONS: Demonstrating that ECs are capable of polarized EV cargo loading and directional EV secretion reveals a novel paradigm for endothelial communication, which may ultimately enhance the design of endothelial-based therapeutics for cardiovascular diseases such as atherosclerosis where ECs are persistently activated.
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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) | 0.000 | 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 | 0.000 |
| 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".