The Pathogenesis of Nonalcoholic Steatohepatitis and Other Fatty Liver Diseases: A Four-Step Model including the Role of Lipid Release and Hepatic Venular Obstruction in the Progression to Cirrhosis
Bibliographic record
Abstract
Fatty liver disease involves the accumulation of triglycerides in hepatocytes, necrosis of hepatocytes, inflammation, and often fibrosis with progression to cirrhosis. The two-hit model summarizes the important early metabolic events leading to hepatocellular necrosis in nonalcoholic steatohepatitis (NASH). In this article, we provide evidence of lipid release from hepatocytes in posttransplant fat necrosis and in NASH and quantify vascular obliteration in a series of biopsies with NASH. Obliteration of small hepatic veins (<30 microm) in small numbers is compensated by collateral flow. Obliteration of larger hepatic veins (>30 microm) is associated with fibrotic collapse lesions that are not easily resorbed. Based on these observations, we propose a new four-step model that includes the later events that lead to cirrhosis after necrosis has occurred. This model is applicable to nonalcoholic fatty liver disease (NAFLD), alcoholic disease, postjejunoileal bypass disease, and posttransplant fat necrosis. The first step is steatosis facilitated by insulin, and the second is necrosis induced by intracellular lipid toxicity or lipid peroxidation, or both, modified by alcohol, drugs, and ischemia. The third step is release of bulk lipid from hepatocytes into the interstitium leading to direct and inflammatory injury to hepatic veins. The fourth step is venous obstruction with secondary collapse and ultimately fibrous septation and cirrhosis.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".