Transgenic Expression of <i>Cacna1f</i> Rescues Vision and Retinal Morphology in a Mouse Model of Congenital Stationary Night Blindness 2A (CSNB2A)
Bibliographic record
Abstract
Purpose: Congenital stationary night blindness 2A (CSNB2A) is a genetic retinal disorder characterized by poor visual acuity, nystagmus, strabismus, and other signs of retinal dysfunction resulting from mutations in Cacna1f—the gene coding for the pore-forming subunit of the calcium channel CaV1.4. Mouse models of CSNB2A have shown that mutations causing the disease deleteriously affect photoreceptors and their synapses with second-order neurons. This study was undertaken to evaluate whether transgenic expression of Cacna1f could rescue morphology and visual function in a Cacna1f-KO model of CSNB2A. Methods: Strategic creation, breeding and use of transgenic mouse lines allowed for Cre-driven retina-specific expression of Cacna1f in a CSNB2A model. Transgene expression and retinal morphology were investigated with immunohistochemistry in retinal wholemounts or cross-sections. Visual function was assessed by optokinetic response (OKR) analysis and electroretinography (ERG). Results: Mosaic, prenatal expression of Cacna1f in the otherwise Cacna1f-KO retina was sufficient to rescue some visual function. Immunohistochemical analyses demonstrated wild-type-like photoreceptor and synaptic morphology in sections with transgenic expression of Cacna1f. Conclusions: This report describes a novel system for Cre-inducible expression of Cacna1f in a Cacna1f-KO mouse model of CSNB2A and provides preclinical evidence for the potential use of gene therapy in the treatment of CSNB2A. Translational Relevance: These data have relevance in the treatment of CSNB2A and in understanding how photoreceptor integration might be achieved in retinas in which photoreceptors have been lost, such as retinitis pigmentosa, age-related macular degeneration, and other degenerative 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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".