Protective effect of C-peptide on experimentally induced diabetic nephropathy and the possible link between C-peptide and nitric oxide
Bibliographic record
Abstract
Diabetic nephropathy one of the major microvascular diabetic complications. Besides hyperglycemia, other factors contribute to the development of diabetic complications as the proinsulin connecting peptide, C-peptide. We described the role of C-peptide replacement therapy on experimentally induced diabetic nephropathy, and its potential mechanisms of action by studying the role of nitric oxide (NO) as a mediator of C-peptide effects by in vivo modulating its production by NG-nitro-l-arginine methyl ester (L-NAME). Renal injury markers measured were serum urea, creatinine, tumor necrosis factor alpha, and angiotensin II, and malondialdehyde, total antioxidant, Bcl-2, and NO in renal tissue. In conclusion, diabetic induction resulted in islet degenerations and decreased insulin secretion with its metabolic consequences and subsequent renal complications. C-Peptide deficiencies in diabetes might have contributed to the metabolic and renal error, since C-peptide treatment to the diabetic rats completely corrected these errors. The beneficial effects of C-peptide are partially antagonized by L-NAME coadministration, indicating that NO partially mediates C-peptide effects.
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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) | 0.000 | 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 | 0.001 |
| 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".