PPARα-dependent increase of mouse urine output by gemfibrozil and fenofibrate
Bibliographic record
Abstract
While gemfibrozil and fenofibrate are prescribed for anti-dyslipidemia treatment, a rational basis for the use of these drugs for treatment of dyslipidemia with concurrent metabolic syndrome has not been established. In this study, wild-type and Pparα-null mice were fed gemfibrozil- or fenofibrate-containing diets for 14 days. Urine output (24 h) was monitored, and urine, serum, and liver and kidney tissues were subjected to toxicity assessment. A 2-month challenge followed by a 2-week wash-out was performed for gemfibrozil to determine urine output and the potential toxicity. A therapeutically equivalent dose of gemfibrozil was more effective than fenofibrate in increasing urine output. This regulatory effect was not observed in Pparα-null mice. In contrast, hepatomegaly induced by fenofibrate was more pronounced than that of gemfibrozil. No significant toxicity was observed in liver or kidney in the 2-month treatment with gemfibrozil. These data demonstrated PPARα mediates the increased urine output by fibrates. Considering the relative action on hepatomegaly and the regulatory effect on urine output, gemfibrozil may be the preferable drug to increase urine output. These results revealed a new pharmacodynamic effect of clinically prescribed PPARα agonists and suggested the potential value of gemfibrozil in modification of blood pressure.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".