Amelioration of Neurosensory Structure and Function in Animal and Cellular Models of a Congenital Blindness
Bibliographic record
Abstract
Most genetically distinct inherited retinal degenerations are primary photoreceptor degenerations. We selected a severe early onset form of Leber congenital amaurosis (LCA), caused by mutations in the gene LCA5, in order to test the efficacy of gene augmentation therapy for a ciliopathy. The LCA5-encoded protein, Lebercilin, is essential for the trafficking of proteins and vesicles to the photoreceptor outer segment. Using the AAV serotype AAV7m8 to deliver a human LCA5 cDNA into an Lca5 null mouse model of LCA5, we show partial rescue of retinal structure and visual function. Specifically, we observed restoration of rod-and-cone-driven electroretinograms in about 25% of injected eyes, restoration of pupillary light responses in the majority of treated eyes, an ∼20-fold decrease in target luminance necessary for visually guided behavior, and improved retinal architecture following gene transfer. Using LCA5 patient-derived iPSC-RPEs, we show that delivery of the LCA5 cDNA restores lebercilin protein and rescues cilia quantity. The results presented in this study support a path forward aiming to develop safety and efficacy trials for gene augmentation therapy in human subjects with LCA5 mutations. They also provide the framework for measuring the effects of intervention in ciliopathies and other severe, early-onset blinding conditions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".