Lymphocytic microparticles inhibit angiogenesis by stimulating oxidative stress and negatively regulating VEGF-induced pathways
Bibliographic record
Abstract
Recent studies have demonstrated that lymphocyte-derived microparticles (LMPs) impair endothelial cell function. However, no data currently exist regarding the contribution of LMPs in the regulation of angiogenesis. In the present study, we investigated the effects of LMPs on angiogenesis in vivo and in vitro and demonstrated that LMPs strongly suppressed aortic ring microvessel sprouting and in vivo corneal neovascularization. In vitro, LMPs considerably diminished human umbilical vein endothelial cell survival and proliferation in a concentration-dependent manner. Mechanistically, the antioxidants U-74389G and U-83836E were partially protective against the antiproliferative effects of LMPs, whereas the NADPH oxidase (NOX) inhibitors apocynin and diphenyleneiodonium significantly abrogated these effects. Moreover, LMPs increased not only the expression of the NOX subunits gp91(phox), p22(phox), and p47(phox), but also the production of ROS and NOX-derived superoxide (O(2)(-)). Importantly, LMPs caused a pronounced augmentation in the protein expression of the CD36 antiangiogenic receptor while significantly downregulating the protein levels of VEGF receptor type 2 and its downstream signaling mediator, phosphorylated ERK1/2. In summary, LMPs potently suppress neovascularization in vivo and in vitro by augmenting ROS generation via NOX and interfering with the VEGF signaling pathway.
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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".