Notch1 induces endothelial plasticity to mediate hyaloid vessel involution
Bibliographic record
Abstract
Abstract Hyaloid vascular regression is a critical developmental process essential for vitreous transparency and normal vision, yet the molecular cues orchestrating its involution remain incompletely defined. Here, we identify Notch1 as a pivotal regulator of hyaloid vessel clearance, acting independently of apoptosis to coordinate endothelial detachment, transient plasticity, and migration. Using an endothelial-specific Notch1 knockout mouse model, we demonstrate that loss of Notch1 results in persistent hyaloid vasculature characterized by excessive proliferation and stabilization of the vascular network. Mechanistically, Notch1 activation during the regression window induces endothelial-to-mesenchymal transition (EndoMT) marked by Snail1 and Slug upregulation. This transcriptional signature is accompanied by detachment of endothelial cells from the vascular tubes. In contrast, Notch1-deficient hyaloid vessels retain endothelial cells stably adherent to the vessel wall. Further analysis reveals that Wnt receptors FZD4, LRP5 and LRP6 previously implicated in hyaloid involution are transcriptionally downregulated in Notch1-deficient hyaloids, suggesting that the collaboration between these processes may occur through crosstalk between the Notch and Wnt pathways. Collectively, our findings uncover a Notch1-driven multicellular regression program that governs developmental vessel regression, redefining the molecular principles of vascular pruning. These results have broad implications for understanding vascular remodeling in both physiological and pathological contexts and may guide therapeutic strategies to modulate vascular regression in ocular disorders. One-Sentence Summary Notch1 drives hyaloid regression through a multicellular program that defines an apoptosis-non-exclusive paradigm of vessel pruning.
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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) | 0.004 | 0.001 |
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".