Transforming growth factor β-induced peritoneal fibrosis is mouse strain dependent*
Bibliographic record
Abstract
BACKGROUND: Encapsulating peritoneal sclerosis (EPS) is a rare but devastating complication of peritoneal dialysis. The etiology is unclear, but genetic predisposition may be a contributing factor. We used adenovirus-mediated gene transfer of transforming growth factor (TGF) β1 to the peritoneum in four genetically distinct laboratory mouse strains to assess differences in fibrogenic response. METHODS: Mice from four genetic backgrounds (C57BL/6J, DBA/2J, C3H/HeJ and SJL/J) received an intraperitoneal injection of an adenovirus expressing TGFβ1 (AdTGFβ1) or control adenovirus (AdDL) and were assessed 4 and 10 days after infection. Submesothelial thickening, angiogenesis and gene expression were quantified from peritoneal tissue. Protein was extracted from omental tissue and assessed for collagen, E-cadherin and TGFβ signaling pathway proteins. RESULTS: There was a graded response among the mouse strains to the peritoneal overexpression of TGFβ1. TGFβ1 induced a significant fibrogenic response in the C57BL/6J mice, whereas the SJL/J mice were resistant. The DBA/2J and the C3H/HeJ mice had intermediate responses. A similar graded response was seen in collagen protein levels in the omental tissue and in fibrosis-associated gene expression. TGFβ type 1 receptor and SMAD signaling pathways appeared to be intact in all the mouse strains. CONCLUSIONS: There were significant differences in mouse strain susceptibility to peritoneal fibrosis, suggesting that genetic factors may play a role in the development of peritoneal fibrosis and possibly EPS. As early TGFβ1 signaling mechanisms appear to be intact, we hypothesize that fibrosis resistance in the SJL/J mice lies further down the wound-healing cascade or in an alternate, non-SMAD pathway.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".