Sphingosine-1-phosphate receptor 2 inhibition ameliorates familial exudative vitreoretinopathy models
Bibliographic record
Abstract
Familial exudative vitreoretinopathy (FEVR) is an inherited childhood blinding disorder with close to 85% of molecularly determined cases due to rare variants in gene encoding members of the frizzled 4 (FZD4) receptor complex.FEVR causes blindness due to complications arising from developmental peripheral non-perfusion of the retina.We sought to find a small molecule that could ameliorate FEVR models.In this study, we determine that the sphingosine1-phosphate receptor 2 (S1PR2) antagonist JTE-013 can ameliorate cellular and mouse models of FEVR.Using human primary retinal microvascular endothelial cells (hRMECs) we show that either knockdown of FZD4 expression using shRNA, or expression of a known FEVR causing dominant negative allele of FZD4, both decrease the ability of hRMECs to tubularize.The addition of JTE-013 to both hRMEC models of FEVR resulted in restoration of tubularization.In the well-established Fzd4 -/-mouse model of FEVR, dosing animals with JTE-013 ameliorated the retinal vascularization defects in these mice.The implications of these findings are (i) a major contributor to abnormal retinal angiogenesis in FEVR is likely through a decrease in vascular formation/integrity, and (ii) treatment with a well characterized S1PR2 inhibitor restores normal vascularization in cell and mouse models of FEVR.To our knowledge, this is the first study to implicate S1PR signaling in FEVR and to show that a small drug-like molecule can restore normal vascularization and prevent blinding complications. J o u r n a l P r e -p r o o f
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".