TGF-β1 promotes cell barrier function upon maturation of corneal endothelial cells
Bibliographic record
Abstract
Human corneal endothelial cells (HCECs) easily become fibroblastic-like when cultured, rendering them unsuitable for tissue engineering of the cornea. Transforming growth factor β (TGF-β) could be a key factor in this phenomenon; however, TGF-β is also known to maintain the endothelium in a quiescent state in vivo. This work aimed to compare the effects of TGF-β1 on the phenotype of HCECs during the proliferation and maturation phases. Our results show that addition of TGF-β1 during the active proliferation phase produced fibroblastic HCECs and loss of the cell junction markers ZO-1 and n-cadherin, independent from the presence of epidermal growth factor (EGF). By contrast, addition of TGF-β1 in maturation media containing few mitogens led to an endothelial phenotype and functional cell junctions as HCECs developed a high trans-endothelial resistance. Furthermore, addition of AG-1478, an epithelial growth factor receptor inhibitor, enhanced the gain of the endothelial phenotype and cell barrier function. Overall, these results show that TGF-β1 can be used to promote the formation of a typical leaky endothelial barrier during the maturation phase of cultured HCECs. A two-phase culture of HCECs using distinct proliferation and maturation media could also be key for developing ideal HCEC culture conditions.
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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 | 0.001 |
| 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".