Alcoholic liver disease and alcoholic pancreatitis: looking at the problem through the lens of the farnesoid X receptor
Bibliographic record
Abstract
Current statistical data show a sharp global increase in alcoholic liver disease (ALD), which is often associated with the onset of alcoholic pancreatitis. According to estimates, Ukraine has one of the highest rates of ALD mortality worldwide; it likely surpasses rates in Europe, the USA, Canada, Brazil, Australia, Indonesia, Africa, and Russia. The normal course of ALD is well-known and starts with liver steatosis and alcoholic hepatitis, progressing to liver cirrhosis and hepatocellular carcinoma. Alcohol’s toxic effects are not limited to the liver; it has a harmful impact on almost all organs and tissues, including the pancreas, brain, cardiovascular system, reproductive organs, bone tissue, hematopoietic organs, and the stimulation of carcinogenesis. The basic understanding of the pathophysiology of ALD has not changed: the damaging effects of acetaldehyde and other metabolic alterations, such as disturbances in the metabolism of bile acids (BA), including their enterohepatic circulation, are the core of this disorder. One of the most significant nuclear BA receptors, the farnesoid X-receptor (FXR), affects the metabolism of bile acidosis (BA) on two levels: it limits the synthesis of bile acid in the liver and decreases enterohepatic circulation activity while also restoring normal lipid metabolism. Systemic or extrahepatic effects are mediated by FXR, which is expressed not just in the liver but also in the pancreas and a number of other organs and systems. ALD therapy methods are regulated by several international guidelines, namely EASL (2018), AASLD (2019), and ALEH (2019). In addition to conventional therapy, innovative and promising ways to treat using S-adenosine methionine (SAM) are being explored. SAM is a promising medication for the treatment of alcoholic pancreatitis and ALD because of its antagonistic activity on FXR, BSEP, and NTCP, the main proteins and receptors involved in ALD pathophysiology. It also has anti-inflammatory, anti-cholestatic, antitumor, and antidepressant qualities.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".