Oxygen and Glucose Levels in Cell Culture Media Determine Resveratrol’s Effects on Growth, Hydrogen Peroxide Production, and Mitochondrial Dynamics
Bibliographic record
Abstract
Resveratrol is a plant-derived polyphenol that has been widely studied for its putative health promoting effects. Many of those studies have been conducted in cell culture, in supra-physiological levels of oxygen and glucose. Resveratrol interacts with reactive oxygen species (ROS) as an antioxidant or pro-oxidant. Resveratrol affects the expression and activities of ROS-producing enzymes and organelles. It is therefore important to consider how cell culture conditions might determine the effects of resveratrol on cultured cells. We determined the effects of resveratrol on cell growth, hydrogen peroxide production, and mitochondrial network characteristics in C2C12 mouse myoblasts and PC3 human prostate cancer cells under conditions of physiological (5%) and supra-physiological (18%) oxygen, and normo- (5 mM) and hyper-glycemia (25 mM). Interestingly, most effects of resveratrol on the parameters measured here were dependent upon prevailing oxygen and glucose levels during the experiment. Many of the effects of resveratrol on cell growth, hydrogen peroxide production, and mitochondrial network characteristics that were seen in 25 mM glucose and/or 18% oxygen were absent under the physiologically relevant conditions of 5 mM glucose with 5% oxygen. These findings emphasize the importance of using physiologically meaningful starting conditions for cell-culture experiments with resveratrol and indeed any manipulation affecting ROS metabolism and mitochondria.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".