Diet Induced Obesity Disrupts Hepatic Redox Homeostasis Leading to Oxidative Stress in Mice: Protective Effect of Natural Compounds
Bibliographic record
Abstract
Oxidative stress is associated with obesity, and while observed in several tissues, its occurrence in the liver during diet induced obesity (DIO) remains controversial. Therefore, our objectives were to investigate the effect of DIO on hepatic oxidative stress and to identify natural compounds capable of protecting against hepatic oxidative injury. Mice were fed either a control (10% kcals fat) or DIO (60% kcals fat) diet for 12 weeks. Compared with control mice, DIO mice weighed significantly more after the 12 week feeding period. In association with weight gain, DIO mice showed significant increases in serum malondialdehyde (MDA), a marker of lipid peroxidation, as well as a severe reduction in total serum antioxidants. Serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST), indices of liver injury, were markedly higher in DIO mice. Hepatic MDA levels were also significantly higher in these mice, indicating a disruption in redox balance in this organ. In accordance, hepatic NADPH oxidase‐mediated superoxide (O 2 − ) production was strikingly increased in DIO mice while the activity of the O 2 − detoxifying enzyme superoxide dismutase was impaired. Our preliminary results also indicate that certain natural compounds are hepatoprotective in DIO which may be mediated by their antioxidant effects in the liver. This study was supported by NSERC and MHRC.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".