Netrin-4 inhibits angiogenesis via binding to neogenin and recruitment of Unc5B
Bibliographic record
Abstract
Netrins are secreted molecules with roles in axon guidance and angiogenesis. We identified Netrin-4 as a gene specifically overexpressed in VEGF-stimulated endothelial cells (EC) in vitro as well as in vivo. Knockdown of Netrin-4 expression in EC increased their ability to form tubular structures on Matrigel. To identify which receptor is involved, we showed by quantitative RT-PCR that EC express three of the six Netrin-1 cognate receptors: neogenin, Unc5B, and Unc5C. In contrast to Netrin-1, Netrin-4 bound only to neogenin but not to Unc5B or Unc5C receptors. Neutralization of Netrin-4 binding to neogenin by blocking antibodies abolished the chemotactic effect of Netrin-4. Furthermore, the silencing of either neogenin or Unc5B abolished Netrin-4 inhibitory effect on EC migration, suggesting that both receptors are essential for its function in vitro. Coimmunoprecipitation experiments demonstrated that Netrin-4 increased the association between Unc5B and neogenin on VEGF- or FGF-2-stimulated EC. Finally, we showed that Netrin-4 significantly reduced pathological angiogenesis in Matrigel and laser-induced choroidal neovascularization models. Interestingly, Netrin-4, neogenin, and Unc5B receptor expression was up-regulated in choroidal neovessel EC after laser injury. Moreover, Netrin-4 overexpression delayed tumor angiogenesis in a model of s.c. xenograft. We propose that Netrin-4 acts as an antiangiogenic factor through binding to neogenin and recruitment of Unc5B.
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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".