Delta-like 4 inhibits choroidal neovascularization despite opposing effects on vascular endothelium and macrophages
Bibliographic record
Abstract
Inflammatory neovascularization, such as choroidal neovascularization (CNV), occur in the presence of Notch expressing macrophages. DLL4s anti-angiogenic effect on endothelial cells (EC) has been widely recognized, but its influence on Notch signaling on macrophages and its overall effect in inflammatory neovascularization is not well understood. We identified macrophages and ECs as the main Notch 1 and Notch 4 expressing cells in CNV. A soluble fraction spanning Ser28-Pro525 of the murine extracellular DLL4 domain (sDLL4/28-525) activated the Notch pathway, as it induces Notch target genes in macrophages and ECs and inhibited EC proliferation and vascular sprouting in aortic rings. In contrast, sDLL4/28-525 increased pro-angiogenic VEGF, and IL-1β expression in macrophages responsible for increased vascular sprouting observed in aortic rings incubated in conditioned media from sDLL4/28-525 stimulated macrophages. In vivo, Dll4(+/-) mice developed significantly more CNV and sDLL4/28-525 injections inhibited CNV in Dll4(+/-) CD1 mice. Similarly, sDLL4/28-525 inhibited CNV in C57Bl6 and its effect was reversed by a γ-secretase inhibitor that blocks Notch signaling. The inhibition occurred despite increased VEGF, IL-1β expression in infiltrating inflammatory macrophages in sDLL4/28-525 treated mice and might be due to direct inhibition of EC proliferation in laser-induced CNV as demonstrated by EdU labelling in vivo. In conclusion, Notch activation on macrophages and ECs leads to opposing effects in inflammatory neovascularization in situations such as CNV.
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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".