Blood flow diverts extracellular vesicles from endothelial degradative compartments to promote angiogenesis
Bibliographic record
Abstract
Extracellular vesicles released by tumors (tEVs) disseminate via circulatory networks and promote microenvironmental changes in distant organs favoring metastatic seeding. Despite their abundance in the bloodstream, how hemodynamics affect the function of circulating tEVs remains unsolved. We demonstrated that efficient uptake of tEVs occurs in venous endothelial cells that are subjected to hemodynamics. Low flow regimes observed in veins partially reroute internalized tEVs toward non-acidic and non-degradative Rab14-positive endosomes, at the expense of lysosomes, suggesting that endothelial mechanosensing diverts tEVs from degradation. Subsequently, tEVs promote the expression of pro-angiogenic transcription factors in low flow-stimulated endothelial cells and favor vessel sprouting in zebrafish. Altogether, we demonstrate that low flow regimes potentiate the pro-tumoral function of circulating tEVs by promoting their uptake and rerouting their trafficking. We propose that tEVs contribute to pre-metastatic niche formation by exploiting endothelial mechanosensing in specific vascular regions with permissive hemodynamics.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".