Platelet extracellular vesicles preserve lymphatic endothelial cell integrity and enhance lymphatic vessel function
Bibliographic record
Abstract
Lymphatic vessels are essential for preventing the accumulation of harmful components within peripheral tissues, including the artery wall. Various endogenous mechanisms maintain adequate lymphatic function throughout life, with platelets being essential for preserving lymphatic vessel integrity. However, since lymph lacks platelets, their impact on the lymphatic system has long been viewed as restricted to areas where lymphatics intersect with blood vessels. Nevertheless, platelets can also exert long range effects through the release of extracellular vesicles (EVs) upon activation. We observed that platelet EVs (PEVs) are present in lymph, a compartment to which they could transfer regulatory effects of platelets. Here, we report that PEVs in lymph exhibit a distinct signature enabling them to interact with lymphatic endothelial cells (LECs). In vitro experiments show that the internalization of PEVs by LECs maintains their functional integrity. Treatment with PEVs improves lymphatic contraction capacity in atherosclerosis-prone mice. We suggest that boosting lymphatic pumping with exogenous PEVs offers a novel therapeutic approach for chronic inflammatory diseases characterized by defective lymphatics.
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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 | 0.000 | 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) | 0.001 | 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".