From Non-Alcoholic Fatty Liver Disease to Liver Cancer: Microbiota and Inflammation as Key Players
Bibliographic record
Abstract
It is estimated that 25% of the world's population has non-alcoholic fatty liver disease. This disease can advance to a more severe form, non-alcoholic steatohepatitis (NASH), a disease with a greater probability of progression to cirrhosis and hepatocellular carcinoma (HCC). NASH could be characterized as a necro-inflammatory complication of chronic hepatic steatosis. The combination of factors that lead to NASH and its progression to HCC in the setting of inflammation is not clearly understood. The portal vein is the main route of communication between the intestine and the liver. This allows the transfer of products derived from the intestine to the liver and the hepatic response pathway of bile and antibody secretion to the intestine. The intestinal microbiota performs a fundamental role in the regulation of immune function, but it can undergo changes that alter its functionality. These changes can also contribute to cancer by disrupting the immune system and causing chronic inflammation and immune dysfunction, both of which are implicated in cancer development. In this article, we address the link between inflammation, microbiota and HCC. We also review the different in vitro models, as well as recent clinical trials addressing liver cancer and microbiota.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".