Insights into new therapies for aniridia associated keratopathy in a novel mouse model
Bibliographic record
Abstract
Aniridia is a rare genetic disorder that disrupts normal eye development. Heterozygous mutations of PAX6 are the main cause of the disease. Importantly, aniridia patients are susceptible to complete visual loss from a progressive aniridia‐associated keratopathy (AAK). The complete degeneration or disappearance of Vogt's limbal palisades is related to the more advanced stages of AAK, and therefore a limbal stem cell deficit or dysfunction (LSCD) is expected to have an important role in the development of AAK. In LSCD and aniridia, a neurotrophic deficit occurs leading to inflammation, neovascularization (CNV) consisting of blood and lymphatic vessels, and a chronic wound healing response. To establish new therapeutic options, essential knowledge is needed concerning the factors which maintain the limbal niche and how these relate to PAX6. Mouse models with aniridia often have a very aggressive phenotype, with advanced AAK observable shortly after birth, upon eye opening, despite the known delayed development of AAK in humans, occurring during the second to third decades of life. In this study, we intended to investigate more accurately the role of LSCD in progression of AAK in a new mouse model of aniridia with delayed onset of AAK using Single‐cell RNA sequencing (scRNA‐Seq) technology. This novel mouse model consists of the Pax6Sey mouse on a 129S1/SvImJ background was first developed and reported by the Simpson group in Vancouver and yields a transparent cornea at birth, and delayed development of AAK. The efficacy of new pharmacologic therapy to decrease the advancement of AAK or perhaps even stop its development can be assessed by comprehending the temporal dynamics of AAK development in this model. (scRNA‐Seq) technology is a potent tool for acquisition of essential knowledge about the characteristics and functions of LSCs, including the identification of new and highly specific expression markers and additional niche‐regulated elements that can either promote or inhibit the proliferation and differentiation of LSCs. Despite the other traditional techniques that were able to detect the average expression of genes in multiple cells, single‐cell sequencing may make it possible to detect differential signals between individual limbal stem cells. To this aim, we will compare the single cell RNA profile between Pax6 +/− haploinsufficient 129S1/SvImJ cornea vs healthy cornea from wild type mice of the same background at two different time points (at 1 month and 4 months of age). We will specifically focus on LSCs contribution to CNV pathophysiology in order to find novel therapeutic targets. The results of this study may lead to improved prevention and treatment methods for treating blindness and enhancing the clinical prognosis of people with LSCD and other LSC‐related disorders.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".