Mesenchymal stem cells pretreated with melatonin ameliorate kidney functions in a rat model of diabetic nephropathy
Bibliographic record
Abstract
The aim of this study was to investigate the effect of a regenerative therapy comprising mesenchymal stem cells (MSCs) pretreated with melatonin (MT) as a new therapy for underlying diabetic nephropathy (DN) pathogenesis in a rat model, and its possible effect on autophagy protein Beclin-1. Forty adult male albino Wistar rats were distributed among 4 groups: (i) control, (ii) DN, (iii) MSC-treated, and (iv) treated with MSCs that were pre-incubated in-vitro with MT (5 μmol·L–1 for 24 h; MSCs + MT). MSCs treatment significantly improved the renal functions and ameliorated the measured underlying DN pathogenesis and elevation of Beclin-1 protein levels compared with the DN group. In-vitro pretreatment of MSCs with MT enhanced proliferation and efficiency, and thus improved the kidney functions by increasing superoxide dismutase (SOD-1) and Beclin-1, and decreasing transforming growth factor (TGF-β) markers in the kidney tissue, compared with the MSC group (P < 0.05). In conclusion: MSCs represent a promising target in DN management, and their effect can be intensified by pretreatment with MT. The elevated levels of Beclin-1 could be a mediator.
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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) | 0.001 | 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".