The Role of the TGF/Smad Signaling Pathway in Peritoneal Fibrosis Induced by Peritoneal Dialysis Solutions
Bibliographic record
Abstract
BACKGROUND: Peritoneal dialysis (PD) solutions contribute to peritoneal membrane damage. We investigated how conventional and biocompatible PD solutions with different glucose concentrations affect morphological and functional signs of peritoneal fibrosis as well as the TGF-beta1/Smad signaling pathway in a chronic PD rat model. METHODS: Non-uremic male Wistar rats (n = 28) were dialyzed thrice daily for 28 days with 20 ml of a conventional solution (Dianeal 1.36%, D1, or 3.86%, D3) or a biocompatible solution (Physioneal 1.36%, P1, or 3.86%, P3). A peritoneal equilibration test was performed. Six rats without dialysis served as controls. RESULTS: The use of conventional solutions, particularly D3, resulted in expansion of the submesothelial compact zone, loss of mesothelial cell layer integrity, hypercellularity, accumulation of collagen I, increased vessel numbers and increased TGF-beta1/Smad expression, but this did not significantly change fluid and solute peritoneal transport characteristics. In comparison with D1 and D3, the use of P1 and P3 was associated with less TGF-beta1/Smad expression and less expansion of the submesothelial cell layer. CONCLUSIONS: Our findings indicate that biocompatible solutions with less glucose may decrease the rate of peritoneal fibrosis. The TGF-beta1/Smad pathway is stimulated by PD solutions, representing a plausible pathophysiological mechanism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
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".