Establishing Preclinical Quantitative Parameters for Future Assessment of Corneal and Retinal Therapeutics for Aniridia
Bibliographic record
Abstract
Purpose: Aniridia is a rare congenital-blinding disorder caused by pathogenic variants in PAX6 for which there is no vision-saving treatment. Here we aim to deliver quantitative mouse data sufficient to provide preclinical testing of therapeutic approaches to aniridia with reliable power calculations. Methods: We histologically quantify the peripheral thickness of the cornea, retina, and their sublayers in the B6129F1-Sey mouse model of aniridia, using the largest cohort of Wt and Sey mice to date (67 mice, 134 eyes). Results: We show a highly significant thinning of the total cornea and the corneal epithelium. However, the corneal stromal-endothelial layer thickness was unaffected by Sey. Nevertheless, the epithelium and stromal-endothelial layer thickness were highly significantly correlated in Sey mice only. We also show a highly significant thinning of the total retina, and a very-to-highly, significant thinning of the ganglion cell layer (GCL), inner nuclear layer (INL), and outer nuclear layer (ONL) sublayers. In the retina, we found that the GCL layer thickness was very significantly correlated with the ONL and INL thickness, in Sey mice only. Using the data generated here, we calculated the number of mice needed to demonstrate a full or partial correction of the Sey aniridic phenotype. For example, at 80% power a 50% effect will require: for the epithelium, 21 Wt and 21 Sey mice; total cornea, 58 Wt and 58 Sey mice; and total retina, 28 Wt and 28 Sey mice. Conclusions: We deliver quantitative mouse data, which provides preclinical research testing of therapeutic approaches with the information needed to make reliable power calculations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".