PPAR-γ agonist ameliorates kidney and liver disease in an orthologous rat model of human autosomal recessive polycystic kidney disease
Bibliographic record
Abstract
In autosomal recessive polycystic kidney disease (ARPKD), progressive enlargement of fluid-filled cysts is due to aberrant proliferation of tubule epithelial cells and transepithelial fluid secretion leading to extensive nephron loss and interstitial fibrosis. Congenital hepatic fibrosis associated with biliary cysts/dilatations is the most common extrarenal manifestation in ARPKD and can lead to massive liver enlargement. Peroxisome proliferator-activated receptor γ (PPAR-γ), a member of the ligand-dependent nuclear receptor superfamily, is expressed in a variety of tissues, including the kidneys and liver, and plays important roles in cell proliferation, fibrosis, and inflammation. In the current study, we determined that pioglitazone (PIO), a PPAR-γ agonist, decreases polycystic kidney and liver disease progression in the polycystic kidney rat, an orthologous model of human ARPKD. Daily treatment with 10 mg/kg PIO for 16 wk decreased kidney weight (% of body weight), renal cystic area, serum urea nitrogen, and the number of Ki67-, pERK1/2-, and pS6-positive cells in the kidney. There was also a decrease in liver weight (% of body weight), liver cystic area, fibrotic index, and the number of Ki67-, pERK1/2-, pERK5-, and TGF-β-positive cells in the liver. Taken together, these data suggest that PIO inhibits the progression of polycystic kidney and liver disease in a model of human ARPKD by inhibiting cell proliferation and fibrosis. These findings suggest that PPAR-γ agonists may have therapeutic value in the treatment of the renal and hepatic manifestations of ARPKD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".