Cell contact‐dependent regulation of epithelial‐mesenchymal transition in tubular cells
Bibliographic record
Abstract
Epithelial‐mesenchymal transition (EMT) of tubular cells into α‐smooth muscle actin (SMA)‐expressing myofibroblasts is a key pathologic feature of kidney fibrosis. Our recent studies have shown that an initial injury of intercellular contacts is a prerequisite for the transforming growth factor‐β (TGFβ)‐induced EMT in LLC‐PK1 proximal tubular cells. Here we analyzed the underlying mechanisms. Disruption of cadherin‐based contacts by Ca 2+ ‐removal induced Rho activation and Rho kinase (ROK)‐mediated myosin light chain (MLC) phosphorylation. Concomitantly, the SMA promoter was stimulated in a ROK‐dependent manner. Moreover, myosin‐based contractility per se played a causal role in the process since both the myosin ATPase inhibitor blebbistatin and a non‐phosphorylatable, dominant negative MLC mutant (DN‐MLC) abrogated SMA promoter activation triggered by Ca 2+ ‐removalin the absence or presence of TGFβ. To address the responsible mechanisms, we investigated the localization of the SMA‐inducing transcription factors, serum response factor (SRF) and myocardin‐related transcription factor (MRTF). Contact injury enhanced nuclear translocation of SRF and MRTF‐B. The latter process was prevented by inhibiting endogenous Rho with p190Rho‐GAP. Moreover, DN‐MLC suppressed the nuclear translocation of SRF and decreased the basal nuclear localization/retention of MRTF‐B. These studies define a new mechanism whereby cell contacts may regulate the SMA promoter via Rho‐ROK‐phospho‐MLC‐dependent nuclear translocation of MRTF and SRF. Support: Kidney Foundation of Canada, and Hungarian Science and Technology Foundation CN‐03‐04
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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 | 0.001 |
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".