Dual function of TGFβ in lens epithelial cell fate: implications for secondary cataract
Bibliographic record
Abstract
The most common vision-disrupting complication of cataract surgery is posterior capsule opacification (PCO; secondary cataract). PCO is caused by residual lens cells undergoing one of two very different cell fates: either transdifferentiating into myofibroblasts or maturing into lens fiber cells. Although TGFβ has been strongly implicated in lens cell fibrosis, the factors responsible for the latter process have not been identified. We show here for the first time that TGFβ can induce purified primary lens epithelial cells within the same culture to undergo differentiation into either lens fiber cells or myofibroblasts. Marker analysis confirmed that the two cell phenotypes were mutually exclusive. Blocking the p38 kinase pathway, either with direct inhibitors of the p38 MAP kinase or a small-molecule therapeutic that also inhibits the activation of p38, prevented TGFβ from inducing epithelial-myofibroblast transition and cell migration but did not prevent fiber cell differentiation. Rapamycin had the converse effect, linking MTOR signaling to induction of fiber cell differentiation by TGFβ. In addition to providing novel potential therapeutic strategies for PCO, our findings extend the so-called TGFβ paradox, in which TGFβ can induce two disparate cell fates, to a new epithelial disease state.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".