Transcription factor 4 promotes increased corneal endothelial cellular migration by altering microtubules in Fuchs endothelial corneal dystrophy
Bibliographic record
Abstract
Fuchs endothelial corneal dystrophy (FECD) is a complex corneal disease characterized by the progressive decline and morphological changes of corneal endothelial cells (CECs) that leads to corneal edema and vision loss. The most common mutation in FECD is an intronic CTG repeat expansion in transcription factor 4 (TCF4) that leads to its altered expression. Corneal endothelial wound healing occurs primarily through cell enlargement and migration, and FECD CECs have been shown to display increased migration speeds. In this study, we aim to determine whether TCF4 can promote cellular migration in FECD CECs. We generated stable CEC lines derived from FECD patients that overexpressed different TCF4 isoforms and investigated epithelial-to-mesenchymal (EMT) expression, morphological analysis and cellular migration speeds. We found that full length TCF4-B isoform overexpression promotes cellular migration in FECD CECs in an EMT-independent manner. RNA-sequencing identified several pathways including the negative regulation of microtubules, with TUBB4A (tubulin beta 4A class IVa) as the top upregulated gene. TUBB4A expression was increased in FECD ex vivo specimens, and there was altered expression of cytoskeleton proteins, tubulin and actin, compared to normal healthy donor ex vivo specimens. Additionally, there was increased acetylation and detyrosination of microtubules in FECD supporting that microtubule stability is altered in FECD and could promote cellular migration. Future studies could be aimed at investigating if targeting the cytoskeleton and microtubules would have therapeutic potential for FECD by promoting cellular migration and regeneration.
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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".