Genetic Aspects of Non-Alcoholic Fatty Liver Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Non-alcoholic fatty liver disease (NAFLD) is the most commonly diagnosed hepatopathy. There is an increase in the incidence of NAFLD in the structure of liver diseases in children and adolescents, which is directly related to the increasing prevalence of obesity. The spectrum of liver tissue changes in NAFLD ranges from benign hepatocellular steatosis to non-alcoholic steatohepatitis (NASH), fibrosis, cirrhosis of the liver, and hepatocellular carcinoma. With the increasing prevalence of NAFLD in children, we can expect an increase in the incidence of adverse outcomes among people of working age. The key problem for NAFLD is the prediction of disease outcomes. In epidemiological and genetic studies, the relationship between the morphological stage of NAFLD and hereditary factors is shown. Currently, there are three genes associated with NAFLD (PNPLA3, TM6SF2, and GCKR), which, together with the genes responsible for insulin resistance, lipid deposition, inflammation and fibrogenesis in hepatocytes, determine the phenotype of fatty liver disease. The article considers the modern understanding of the issues of genetics, development of liver steatosis and progression of NASH. It is expected that this knowledge can transform our risk stratification strategies in patients with NAFLD and help identify new therapeutic goals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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 it