Resveratrol Protects DAergic PC12 Cells from High Glucose-Induced Oxidative Stress and Apoptosis: Effect on p53 and GRP75 Localization
Bibliographic record
Abstract
Resveratrol (RESV), a polyphenolic natural compound, has long been acknowledged to have cardioprotective and antiinflammatory actions. Evidence suggests that RESV has antioxidant properties that reduce the formation of reactive oxygen species leading to oxidative stress and apoptotic death of dopaminergic (DAergic) neurons in Parkinson's disease (PD). Recent literature has recognized hyperglycemia as a cause of oxidative stress reported to be harmful for the nervous system. In this context, our study aimed (a) to evaluate the effect of RESV against high glucose (HG)-induced oxidative stress in DAergic neurons, (b) to study the antiapoptotic properties of RESV in HG condition, and c) to analyze RESV's ability to modulate p53 and GRP75, a p53 inactivator found to be under expressed in postmortem PD brains. Our results suggest that RESV protects DAergic neurons against HG-induced oxidative stress by diminishing cellular levels of superoxide anion. Moreover, RESV significantly reduces HG-induced apoptosis in DAergic cells by modulating DNA fragmentation and the expression of several genes implicated in the apoptotic cascade, such as Bax, Bcl-2, cleaved caspase-3, and cleaved PARP-1. RESV also prevents the pro-apoptotic increase of p53 in the nucleus induced by HG. Such data strengthens the correlation between hyperglycemia and neurodegeneration, while providing new insight on the high occurrence of PD in patients with diabetes. This study enlightens potent neuroprotective roles for RESV that should be considered as a nutritional recommendation for preventive and/or complementary therapies in controlling neurodegenerative complications in diabetes.
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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 | 0.001 |
| 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".