Neuroprotective abilities of resveratrol and other red wine constituents against nitric oxide‐related toxicity in cultured hippocampal neurons
Why this work is in the frame
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Bibliographic record
Abstract
Animal and epidemiological studies suggest that polyphenol constituents of red wine possess antioxidant activities that favour protection against cardiovascular disease - the so-called. 'French paradox' - and possibly, central nervous system disorders such as Alzheimer's disease (AD) and ischaemia. In the present study, the potential of three major red wine derived-polyphenols to protect against toxicity induced by the nitric oxide free radical donors sodium nitroprusside (SNP) and 3-morpholinosydnonimine (SIN-1) was examined in cultured rat hippocampal cells. Both co- and post-treatments with either the stilbene resveratrol (5 - 25 microM) or the flavonoids quercetin (5 - 25 microM) and (+)-catechin (1 - 10 microM) were capable of attenuating hippocampal cell death and intracellular reactive oxygen species accumulation produced by SNP (100 microM and 1 mM, respectively). However, among the phenolic compounds tested, only the flavonoids afforded significant protection against 5 mM SIN-1-induced toxicity. The effects of phenolic constituents were shared by Trolox (100 microM), a vitamin E analogue, but not by selective inhibitors of cyclo-oxygenases (COX) and lipoxygenases (LOX). Among the phenolic compounds tested, only quercetin (10 microM) inhibited 100 microM SNP-stimulated protein kinase C (PKC) activation, whereas none of them were able to attenuate nitrite accumulation caused by SNP (100 microM). Taken together, these data suggest that the neuroprotective abilities of quercetin, resveratrol, and (+)-catechin result from their antioxidant properties rather than their purported inhibitory effects on intracellular enzymes such as COX, LOX, or nitric oxide synthase. Quercetin, however, may also act via PKC to produce its protective effects.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 it