Quercetin 3-Glucoside Protects Neuroblastoma (SH-SY5Y) Cells in Vitro against Oxidative Damage by Inducing Sterol Regulatory Element-binding Protein-2-mediated Cholesterol Biosynthesis
Bibliographic record
Abstract
The flavonoid quercetin 3-glucoside (Q3G) protected SH-SY5Y, HEK293, and MCF-7 cells against hydrogen peroxide-induced oxidative stress. cDNA microarray studies suggested that Q3G-pretreated cells subjected to oxidative stress up-regulate the expression of genes associated with lipid and cholesterol biosynthesis. Q3G pretreatment elevated both the expression and activation of sterol regulatory element-binding protein-2 (SREBP-2) only in SH-SY5Y cells subjected to oxidative stress. Inhibition of SREBP-2 expression by small interfering RNA or small molecule inhibitors of 2,3-oxidosqualene:lanosterol cyclase or HMG-CoA reductase blocked Q3G-mediated cytoprotection in SH-SY5Y cells. By contrast, Q3G did not protect either HEK293 or MCF-7 cells via this signaling pathway. Moreover, the addition of isopentenyl pyrophosphate rescued SH-SY5Y cells from the inhibitory effect of HMG-CoA reductase inhibition. Last, Q3G pretreatment enhanced the incorporation of [(14)C]acetate into [(14)C]cholesterol in SH-SY5Y cells under oxidative stress. Taken together, these studies suggest a novel mechanism for flavonoid-induced cytoprotection in SH-SY5Y cells involving SREBP-2-mediated sterol synthesis that decreases lipid peroxidation by maintaining membrane integrity in the presence of oxidative stress.
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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 | 0.000 |
| 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) | 0.001 | 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".