EP4 inhibition attenuates the development of diabetic and non-diabetic experimental kidney disease
Bibliographic record
Abstract
Abstract The therapeutic targeting of prostanoid subtype receptors may slow the development of chronic kidney disease (CKD) through mechanisms that are distinct from those of upstream COX inhibition. Here, employing multiple experimental models of CKD, we studied the effects of inhibition of the EP4 receptor, one of four receptor subtypes for the prostanoid prostaglandin E 2 . In streptozotocin-diabetic endothelial nitric oxide synthase knockout mice, EP4 inhibition attenuated the development of albuminuria, whereas the COX inhibitor indomethacin did not. In Type 2 diabetic db/db mice, EP4 inhibition lowered albuminuria to a level comparable with that of the ACE inhibitor captopril. However, unlike captopril, EP4 inhibition had no effect on blood pressure or hyperfiltration although it did attenuate mesangial matrix accumulation. Indicating a glucose-independent mechanism of action, EP4 inhibition also attenuated proteinuria development and glomerular scarring in non-diabetic rats subjected to surgical renal mass ablation. Finally, in vitro , EP4 inhibition prevented transforming growth factor-ß1 induced dedifferentiation of glomerular podocytes. In rodent models of diabetic and non-diabetic CKD, EP4 inhibition attenuated renal injury through mechanisms that were distinct from either broadspectrum COX inhibition or “standard of care” renin angiotensin system blockade. EP4 inhibition may represent a viable repurposing opportunity for the treatment of CKD.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".