The beneficial effects of resveratrol on steatosis and mitochondrial oxidative stress in HepG2 cells
Bibliographic record
Abstract
Nonalcoholic fatty liver disease (NAFLD) is currently one of the most common chronic liver diseases, especially in developed countries. One group of substances with a potential use in the treatment of NAFLD are plant polyphenols, represented by resveratrol. The aim of this study was to evaluate the effect of resveratrol on steatosis and oxidative stress in HepG2 cells. The steatosis of cells was carried out using free fatty acids: oleic or palmitic acid and their mixtures. Steatosis was visualized using the intracellular lipid staining by Nile Red dye with a fluorescence microscope. This study also determined the viability of cells and mitochondrial membrane potential. The current study showed that fatty acids and their mixtures induced fat overloading in HepG2 cells. In the group of cells incubated with oleic acid (OA), observed changes were moderate with prevailing micro-vesicular steatosis. In case of cells incubated with palmitic acid (PA) and the mixtures of fatty acids, micro- and macro-vacuolar steatosis occurred in most of the cells. Resveratrol decreased steatosis in HepG2 cells induced by OA, PA, as well as their mixtures, and in most of experimental groups did not reduce cells viability. Resveratrol reduced the oxidative stress in HepG2 cells treated with fatty acids mixtures.
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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) | 0.001 | 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".