Transient Overexpression of TGF-β1 Induces Epithelial Mesenchymal Transition in the Rodent Peritoneum
Bibliographic record
Abstract
Epithelial mesenchymal transition (EMT), a process involved in many growth and repair functions, has been identified in the peritoneal tissues of patients who undergo peritoneal dialysis. The sequence of changes in gene regulation and cellular events associated with EMT after TGF-beta1-induced peritoneal fibrosis is reported. Sprague-Dawley rats received an intraperitoneal injection of an adenovirus vector that transfers active TGF-beta1 (AdTGF-beta1) or control adenovirus, AdDL. Animals were killed 0 to 21 days after infection. Peritoneal effluent and tissue were analyzed for markers of EMT. In the animals that were treated with AdTGF-beta1, an increase in expression of genes associated with EMT and fibrosis, such as type I collagen A2, alpha-smooth muscle actin, and the zinc finger regulatory protein Snail, was identified. Transition of mesothelial cells 4 to 7 d after infection, with appearance of epithelial cells in the submesothelial zone 7 to 14 d after exposure to AdTGF-beta1, was demonstrated. This phase was associated with disruption of the basement membrane and increased expression of matrix metalloproteinase 2. By 14 to 21 d after infection, there was evidence of restoration of normal submesothelial architecture. These findings suggest that EMT occurs in vivo after TGF-beta1 overexpression in the peritoneum. Cellular changes and gene regulation associated with EMT are evident throughout the fibrogenic process and are not limited to early time points. This further supports the central role of TGF-beta1 in peritoneal fibrosis and provides an important model to study the sequence of events involved in TGF-beta1-induced EMT.
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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 | 0.001 | 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 | 0.001 |
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".