Quercetin and Sesamin Protect Dopaminergic Cells from MPP<sup>+</sup>-Induced Neuroinflammation in a Microglial (N9)-Neuronal (PC12) Coculture System
Why this work is in the frame
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Bibliographic record
Abstract
A growing body of evidence indicates that the majority of Parkinson's disease (PD) cases are associated with microglia activation with resultant elevation of various inflammatory mediators and neuroinflammation. In this study, we investigated the effects of 2 natural molecules, quercetin and sesamin, on neuroinflammation induced by the Parkinsonian toxin 1-methyl-4-phenylpyridinium (MPP(+)) in a glial-neuronal system. We first established that quercetin and sesamin defend microglial cells against MPP(+)-induced increases in the mRNA or protein levels of 3 pro-inflammatory cytokines (interleukin-6, IL-1β and tumor necrosis factor-alpha), as revealed by real time-quantitative polymerase chain reaction and enzyme-linked immunoabsorbent assay, respectively. Quercetin and sesamin also decrease MPP(+)-induced oxidative stress in microglial cells by reducing inducible nitric oxide synthase protein expression as well as mitochondrial superoxide radicals. We then measured neuronal cell death and apoptosis after MPP(+) activation of microglia, in a microglial (N9)-neuronal (PC12) coculture system. Our results revealed that quercetin and sesamin rescued neuronal PC12 cells from apoptotic death induced by MPP(+) activation of microglial cells. Altogether, our data demonstrate that the phytoestrogen quercetin and the lignan sesamin diminish MPP(+)-evoked microglial activation and suggest that both these molecules may be regarded as potent, natural, anti-inflammatory compounds.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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