Weight loss enhances hepatic antioxidant status in a NAFLD model induced by high-fat diet
Bibliographic record
Abstract
Nonalcoholic fatty liver disease (NAFLD) is a benign condition that can progress to more severe liver damage in a process mediated, in part, by disturbances in redox balance. Additionally, some argue that it is set to become the main cause of end-stage liver disease in the near future. Here, we investigated whether diet-induced weight loss is able to reverse hepatic lipid accumulation and reduce oxidative stress in liver from C57BL/6 mice fed a high-fat (HF) diet. Male C57BL/6 mice were divided into 4 groups: standard chow (SC; 10% energy from fat, 16 weeks); HF (50% energy from fat, 16 weeks); SC-HF (SC for 8 weeks followed by HF for 8 weeks); and HF-SC (HF for 8 weeks followed by SC for 8 weeks). The HF diet during 8 (SC-HF) and 16 weeks (HF) downregulated messenger RNA levels and protein expression of Nrf2 and endogenous antioxidant enzymes (superoxide dismutase, catalase, glutathione peroxidase, and glutathione reductase) in the liver; caused liver steatosis; affected liver function markers; increased intra-abdominal and subcutaneous adipose tissue; and induced glucose intolerance and hypercholesterolemia compared with controls (SC). Diet-induced weight loss significantly reduced the intrahepatic lipid accumulation, improved glucose tolerance, and restored both gene and protein expression of the antioxidant enzymes. Our findings suggest that a dietary intervention aimed to induce weight loss may exert protective effects in NAFLD as it can reduce hepatic oxidative stress and intrahepatic lipid accumulation, which can hinder the progression of this condition to more severe states.
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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 | 0.000 | 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".