Ophthalmic Nonsteroidal Anti-Inflammatory Drugs as a Therapy for Corneal Dystrophies Caused by SLC4A11 Mutation
Bibliographic record
Abstract
Purpose: SLC4A11 is a plasma membrane protein of corneal endothelial cells. Some mutations of the SLC4A11 gene result in SLC4A11 protein misfolding and failure to mature to the plasma membrane. This gives rise to some cases of Fuchs' endothelial corneal dystrophy (FECD) and congenital hereditary endothelial dystrophy (CHED). We screened ophthalmic nonsteroidal anti-inflammatory drugs (NSAIDs) for their ability to correct SLC4A11 folding defects. Methods: Five ophthalmic NSAIDs were tested for their therapeutic potential in some genetic corneal dystrophy patients. HEK293 cells expressing CHED and FECD-causing SLC4A11 mutants were grown on 96-well dishes in the absence or presence of NSAIDs. Ability of NSAIDs to correct mutant SLC4A11 cell-surface trafficking was assessed with a bioluminescence resonance energy transfer (BRET) assay and by confocal microscopy. The ability of mutant SLC4A11-expressing cells to mediate water flux (SLC4A11 mediates water flux across the corneal endothelial cell basolateral membrane as part of the endothelial water pump) was measured upon treatment with ophthalmic NSAIDs. Results: BRET-assays revealed significant rescue of SLC4A11 mutants to the cell surface by 4 of 5 NSAIDs tested. The NSAIDs, diclofenac and nepafenac, were effective in moving endoplasmic reticulum-retained missense mutant SLC4A11 to the cell surface, as measured by confocal immunofluorescence. Among intracellular-retained SLC4A11 mutants, 20 of 30 had significant restoration of cell surface abundance upon treatment with diclofenac. Diclofenac restored mutant SLC4A11 water flux activity to the level of wild-type SLC4A11 in some cases. Conclusions: These results encourage testing diclofenac eye drops as a treatment for corneal dystrophy in patients whose disease is caused by some SLC4A11 missense mutations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".