Preclinical Models for Studying Fuchs Endothelial Corneal Dystrophy
Bibliographic record
Abstract
Fuchs Endothelial Corneal Dystrophy (FECD) is a corneal endothelial disease that causes microenvironment alterations and endothelial cell loss, which leads to vision impairment. It has a high global prevalence, especially in elderly populations. FECD is also one of the leading indications of corneal transplantation globally. Currently, there is no clearly defined canonical pathway for this disease, and it has been proposed that the combinatorial effects of genetic mutations and exogenous factors cause FECD. Clinical studies and observations have provided valuable knowledge and understanding of FECD, while preclinical studies are essential for gaining insights into disease progression and mechanisms for the development and testing of regenerative medicine therapies. In this review, we first introduce the proposed genetic and molecular pathologies of FECD. Notably, we discuss the impact of abnormal extracellular matrix deposition (guttata), endothelial-to-mesenchymal transition, cell senescence, and oxidative stress on the pathology and etiology of FECD. We review and summarize the in vitro cell models, ex vivo tissues, and in vivo animal models used to study FECD. The benefits and challenges of each model are also discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".