Specialized endothelial tip cells guide neuroretina vascularization and blood-retina-barrier formation
Bibliographic record
Abstract
Endothelial tip cells guiding tissue vascularization are primary targets for angiogenic therapies. Whether tip cells require differential signals to develop their complex branching patterns remained unknown. Here, we show that diving tip cells invading the mouse neuroretina (D-tip cells) are distinct from tip cells guiding the superficial retinal vascular plexus (S-tip cells). D-tip cells have a unique transcriptional signature, including high TGF-β signaling, and they begin to acquire blood-retina barrier properties. Endothelial deletion of TGF-β receptor I (Alk5) inhibits D-tip cell identity acquisition and deep vascular plexus formation. Loss of endothelial ALK5, but not of the canonical SMAD effectors, leads to aberrant contractile pericyte differentiation and hemorrhagic vascular malformations. Oxygen-induced retinopathy vasculature exhibits S-like tip cells, and Alk5 deletion impedes retina revascularization. Our data reveal stage-specific tip cell heterogeneity as a requirement for retinal vascular development and suggest that non-canonical-TGF-β signaling could improve retinal revascularization and neural function in ischemic retinopathy.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".