Opposing effect of angiopoietin‐1 on VEGF‐mediated disruption of endothelial cell–cell interactions requires activation of PKCβ
Bibliographic record
Abstract
Angiopoietin-1 (Ang1) and vascular endothelial growth factor (VEGF) cooperate in migration and survival of endothelial cells by activation of phosphatidylinositol-3 (PI-3) kinase and mitogen activating protein (MAP) kinase pathways. However, Ang1 opposes the effect of VEGF on vascular permeability. We found that Ang1 also blocks VEGF-mediated diffusion of fluoresin isothiocyanate (FITC)-labeled albumin across an endothelial cell monolayer. VEGF-mediated vascular permeability has been attributed, in part, to activation of phospholipase A(2) and subsequent formation of platelet activating factor. However, Ang1 had no effect on VEGF-induced activation of phospholipase A(2) or the release of arachidonic acid. VEGF-mediated permeability was associated with disruption of endothelial cell junctional complexes, dissociation of beta-catenin from VE-cadherin, and accumulation of beta-catenin in the cytosol. In contrast, Ang1 enhanced the interaction of beta-catenin with VE-cadherin and impaired VEGF-mediated dissociation of this complex. Ang1 also blocked VEGF-induced translocation of protein kinase C (PKC) and beta2 to the membrane, but had no effect on activation of PKC alpha. In addition, staurosporine and a PKC beta inhibitor, LY379196, blocked VEGF-mediated dissociation of beta-catenin from VE-cadherin, diffusion of albumin across the endothelial cell monolayer, and translocation of PKC beta isoforms. These data indicate that VEGF-mediated disruption of endothelial cell-cell interactions requires activation of PKC beta isoforms and that this pathway is blocked by Ang1.
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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 | 0.001 |
| 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".