Vasohibin is up‐regulated by VEGF in the retina and suppresses VEGF receptor 2 and retinal neovascularization
Bibliographic record
Abstract
Vasohibin is a recently identified protein that is up-regulated in cultured vascular endothelial cells by vascular endothelial growth factor and fibroblast growth factor 2. It inhibits endothelial cell migration, proliferation, and tube formation, and suppresses angiogenesis in chick chorioallantoic membrane, after subcutaneous implantation of matrigel, and in a tumor xenograft model. This has led to the hypothesis that vasohibin functions as a negative feedback inhibitor of angiogenesis. In this study, we tested that hypothesis in a well-characterized model of retinal neovascularization. In ischemic retina, increased expression of VEGF was accompanied by elevation of vasohibin mRNA and blocking of the increase in vegf mRNA with vegf siRNA significantly attenuated the rise in vasohibin mRNA. In transgenic mice in which the rhodopsin promoter drives expression of VEGF in the retina, there was also a significant increase in vasohibin mRNA. In mice with ischemic retinopathy, there was increased expression of vasohibin in vascular endothelial cells, and vasohibin knockdown caused an increase in neovascularization. Conversely, intraocular injection of recombinant vasohibin or an adenoviral vector containing a vasohibin expression cassette strongly suppressed retinal neovascularization in mice with ischemic retinopathy. Knockdown of vasohibin mRNA in ischemic retina had no significant effect on vegf or vegf receptor 1 mRNA levels but caused a significant elevation in the level of vegf receptor 2 mRNA. These data support the hypothesis that vasohibin acts as a negative feedback regulator of neovascularization in the retina and suggest that suppression of VEGF receptor 2 may play some role in mediating its activity.
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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 | 0.000 | 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) | 0.000 | 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".