Challenging Safety and Efficacy of Retinal Gene Therapies by Retinogenesis
Bibliographic record
Abstract
Gene-expression programs modulated by transcription factors (TFs) mediate key developmental events. Here, we show that the synthetic transcriptional repressor (TR; ZF6-DB), designed to treat Rhodopsin-mediated autosomal dominant retinitis pigmentosa (RHO-adRP), does not perturb murine retinal development, while maintaining its ability to block Rho expression transcriptionally. To express ZF6-DB into the developing retina, we pursued two approaches, (i) the retinal delivery (somatic expression) of ZF6-DB by Adeno-associated virus (AAV) vector (AAV-ZF6-DB) gene transfer during retinogenesis and (ii) the generation of a transgenic mouse (germ-line transmission, TR-ZF6-DB). Somatic and transgenic expression of ZF6-DB during retinogenesis does not affect retinal function of wild-type mice. The P347S mouse model of RHO-adRP, subretinally injected with AAV-ZF6-DB, or crossed with TR-ZF6-DB or shows retinal morphological and functional recovery. We propose the use of developmental transitions as an effective mode to challenge the safety of retinal gene therapies operating at genome, transcriptional, and transcript levels.
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 | 0.002 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".