TGF-β Promotes Endothelial-to-Mesenchymal Transition and Alters Corneal Endothelial Cell Migration in Fuchs Endothelial Corneal Dystrophy
Bibliographic record
Abstract
Fuchs endothelial corneal dystrophy (FECD) is a progressive corneal disease characterized by corneal endothelial cell (CEC) loss and guttae formation. Elevated levels of Transforming Growth Factor-Beta 1 and 2 (TGF-β1/-β2) have been reported in the aqueous humor (AH) of FECD patients and have been implicated with abnormal extracellular matrix (ECM) production, endothelial-to-mesenchymal transition (EndoMT), the unfolded protein response, and cell death. However, how TGF-β signaling affects cell migration in FECD remains to be elucidated. In this study, we found that TGF-β2 levels were significantly elevated in the AH of FECD patients compared to controls. We performed bulk RNA sequencing on FECD CECs treated with TGF-β1 or TGF-β2 and identified the epithelial-to-mesenchymal (EMT) pathway as one of the top dysregulated pathways. We found that TGF-β1 and TGF-β2 increased EMT markers, filamentous-actin (F-actin) expression and produced more EMT-like phenotype in FECD and control CECs. We also observed that TGF-β1 and TGF-β2 significantly increased FECD CEC migration speed as detected by scratch assay and individual cell tracking and promoted individual cellular migration behavior. This study provides novel insight into FECD pathogenesis and how increased TGF-β signaling promotes EndoMT and alters cellular migration in FECD CECs.
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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".