Health Benefits of Resveratrol in Kidney Disease: Evidence from In Vitro and In Vivo Studies
Bibliographic record
Abstract
Different diseases and disorders that affect the kidneys include, but are not limited to, glomerulonephritis, diabetic nephropathy, polycystic kidney disease, kidney stones, renal fibrosis, sepsis, and renal cell carcinoma. Kidney disease tends to develop over many years, making it difficult to identify until much later when kidney function is severely impaired and undergoing kidney failure. Although conservative care, symptom management, medication, dialysis, transplantation, and aggressive renal cancer therapy are some of the current strategies/approaches to kidney disease treatment, new preventative targeted therapies are needed. Epidemiological studies have suggested that a diet rich in fruits and vegetables is associated with health benefits including protection against kidney disease and renal cancer. Resveratrol, a polyphenol found in grapes and berries, has been reported to have antioxidant, anti-inflammatory, antidiabetic, hepatoprotective, neuroprotective, and anti-cancer properties. The current review summarizes the existing in vitro and in vivo animal and human studies examining the nephroprotective effects of resveratrol.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".