Cyclooxygenase 2 inhibition slows disease progression and improves the altered renal lipid mediator profile in the Pkd2WS25/− mouse model of autosomal dominant polycystic kidney disease
Bibliographic record
Abstract
BACKGROUND: mouse model of autosomal dominant polycystic kidney disease (ADPKD). METHODS: Weanling normal and diseased male Pkd2 mice were provided diets that provided 0 or 50 mg celecoxib/kg body weight/day, for 13 weeks. Renal disease and function were assessed by histomorphometric analysis of renal cysts and measurement of serum creatinine and urea nitrogen (SUN) levels. Targeted lipidomic analysis of renal oxylipins was performed by HPLC-MS/MS. RESULTS: Diseased mice had significant cyst involvement and reduced renal function as indicated by elevated serum creatinine and SUN. Celecoxib reduced cyst area by 48%, cyst volume by 70%, and serum creatinine and SUN by 20% and 16%, respectively. Consistent with our previous studies, 8 of the 11 COX derived oxylipins were higher in diseased kidneys. In addition, 24 of 33 lipoxygenase (LOX) derived oxylipins and 7 of 16 cytochrome P450 (CYP) derived oxylipins were lower in diseased kidneys. Celecoxib reduced total and five of the eight individual elevated COX oxylipins and increased 5 of 24 LOX and 5 of 7 CYP oxylipins that were reduced by disease. CONCLUSIONS: COX2 inhibition ameliorates disease progression, improves renal function and improves the altered oxylipins in Pkd2 mice. This represents a potential new approach for treatment of ADPKD, a disorder for which no effective treatment currently exists.
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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) | 0.002 | 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".