Preclinical evaluation of tolvaptan and salsalate combination therapy in a Pkd1-mouse model
Bibliographic record
Abstract
Background: Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic disorder and an important cause of end stage renal disease (ESRD). Tolvaptan (a V2R antagonist) is the first disease modifier drug for treatment of ADPKD, but also causes severe polyuria. AMPK activators have been shown to attenuate cystic kidney disease. Methods: In this study, we tested the efficacy of the combined administration of salsalate (a direct AMPK activator) and tolvaptan using clinically relevant doses in an adult-onset conditional Pkd1 knock-out (KO) mouse model. Results: Compared to untreated Pkd1 mutant mice, the therapeutic effects of salsalate were similar to that of tolvaptan. The combined treatment tended to be more effective than individual drugs used alone, and was associated with improved kidney survival ( p < 0.0001) and reduced kidney weight to body weight ratio ( p < 0.0001), cystic index ( p < 0.001) and blood urea levels ( p < 0.001) compared to untreated animals, although the difference between combination and single treatments was not statistically significant. Gene expression profiling and protein expression and phosphorylation analyses support the mild beneficial effects of co-treatment, and showed that tolvaptan and salsalate cooperatively attenuated kidney injury, cell proliferation, cell cycle progression, inflammation and fibrosis, and improving mitochondrial health, and cellular antioxidant response. Conclusion: These data suggest that salsalate-tolvaptan combination, if confirmed in clinical testing, might represent a promising therapeutic strategy in the treatment of ADPKD.
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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 | 0.001 | 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) | 0.000 | 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".