Resveratrol Limits Lipogenesis and Enhance Mitochondrial Activity in HepG2 Cells
Bibliographic record
Abstract
PURPOSE: The aim of this study was to evaluate the effect of resveratrol on de novo lipogenesis in HepG2 cells caused by high glucose concentrations. Increased lipogenesis in the liver is the main reason for the development of nonalcoholic fatty liver disease (NAFLD) - currently one of the most common chronic liver diseases. In developed countries, this disease is mostly associated with nutritional disorders, resulting from the increasing consumption of monosaccharides. Resveratrol is a natural polyphenol with a promising potential for NAFLD treatment. METHODS: The steatosis of HepG2 cells was visualized using the intracellular lipid staining by Nile Red dye with a fluorescence microscope. This study also evaluated the effect of resveratrol on the mitochondrial activity (MitoTracker Green staining), dsDNA (Hoechst 33342 staining) and the viability of HepG2 cells treated with high glucose concentrations (25 and 33 mM). RESULTS: Current study showed that high glucose concentrations induced fat-overloading in HepG2 cells (microvacuolar steatosis occurred in most of the cells). Resveratrol (20 μM) limits the steatosis induction in HepG2 cells by glucose and increased the mitochondrial activity of cells. Resveratrol did not affect the viability of HepG2 cells. CONCLUSION: This beneficial effect could be helpful in the treatment of NAFLD.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".