The Effect of Liver Cirrhosis on the Regulation and Expression of Drug Metabolizing Enzymes
Bibliographic record
Abstract
Cirrhosis is the end stage of many forms of liver pathologies including hepatitis. The liver is known for its vital role in the processing of xenobiotics, including drugs and toxic compounds. Cirrhosis causes changes in the architecture of the liver leading to changes in blood flow, protein binding, and drug metabolizing enzymes. Drug metabolizing enzymes are primarily decreased due to loss of liver tissue. However, not all enzyme activities are reduced and some are only altered in specific cases. There is a great deal of discrepancy between various reports on cytochrome p450 alterations in liver cirrhosis, likely due to differences in disease severity and other underlying conditions. In general, however, CYP1A and CYP3A levels and related enzyme activities are usually reduced and CYP2C, CYP2A, and CYP2B are mostly unaltered. Both alcohol dehyrogenases and aldehyde dehydrogenases are altered in liver cirrhosis, although the etiology of the disease may determine the expression of alcohol dehydrogenases. Glucuronidation is mainly preserved, but there are a number of factors that determine whether glucuronidation is affected in patients with liver cirrhosis. Low sulphation rates are usually found in patients with liver disease but a decrease in sulfatase activity compensates for the decrease in sulphation rates. In all cases, a reduction in drug metabolizing enzyme activities in liver cirrhosis contributes to decreased clearance of drugs seen in patients with liver abnormalities. The reduction in drug metabolizing enzyme activity must be taken into consideration when adjusting doses, especially in patients with severe liver disease.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
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".