Celecoxib modifies glomerular basement membrane, mesangium and podocytes in OVE26 mice, but ibuprofen is more detrimental
Bibliographic record
Abstract
The role of COXs/PGs (cyclo-oxygenases/prostaglandins) in diabetic kidneys remains unclear. NSAIDs (non-steroidal anti-inflammatory drugs) that inhibit COXs/PGs are known for their renal toxicity, and COX-2 inhibitors worsen cardiovascular outcomes in susceptible individuals. Given the renal controversies concerning COX-2 inhibitors, we compared the effect of chronic NSAIDs (non-selective, ibuprofen; COX-2-selective, celecoxib) on diabetic kidneys in OVE26 mice from 8 weeks of age. Systolic BPs (blood pressures) were increased by NSAIDs in diabetic mice at 20 weeks, but were unchanged at 32 weeks. Although NSAIDs further increased diabetic kidney/body weight ratios, they did not affect albuminuria. Mesangial matrix was increased 2-fold by celecoxib but not ibuprofen. Electron microscopy revealed that NSAIDs reduced GBM (glomerular basement membrane) thickness and slit pore diameters. Although diabetics had increased glomerular diameters and reduced foot process densities, these were unaltered by NSAIDs. Celecoxib does not exacerbate the diabetic state, but PG inhibition may contribute to disease progression by modifying the GBM, mesangial area and podocyte structure in OVE26 mice. Despite these findings, celecoxib remains safer than a similar dose of ibuprofen. The present study substantiates the need to more closely consider selective COX-2 inhibitors such as celecoxib as alternatives to non-selective NSAIDs for therapeutic management in a setting of chronic kidney disease.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".