The Role of Nutrients in the Development, Progression, and Treatment of Nonalcoholic Fatty Liver Disease
Bibliographic record
Abstract
Nonalcoholic fatty liver disease (NAFLD) is the most common cause of liver disease in adults and children and is currently the third most common indication for liver transplantation in North America. Its pathogenesis is thought to be secondary to multiple "hits" derived from the dietary components, adipose tissue, immune system, and intestinal microbiota. Lack of physical activity may contribute as well. Nutrients may exert their effect directly or through alteration of the intestinal microbiota. Research focusing on specific dietary components predisposing to NAFLD has shown conflicting results. Total energy intake, and macronutrients, has been linked to the development of NAFLD. Fructose not only contributes to hepatic steatosis but may trigger inflammatory signals as well. Polyunsaturated fatty acids are thought to exert anti-inflammatory effects. The role of vitamins as well as minerals in this field is actively being investigated. In this review, we discuss the evidence-linking macronutrients (such as carbohydrates and fat in general and fructose, fiber, short chain fatty acids, polyunsaturated fatty, and choline specifically) and micronutrients (such as vitamin E and C and minerals) with the development and treatment of NAFLD. We also discuss the literature on physical activity and 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".