Combining ursodeoxycholic acid or its NO-releasing derivative NCX-1000 with lipophilic antioxidants better protects mouse hepatocytes against amiodarone toxicity
Bibliographic record
Abstract
Nonalcoholic steatohepatitis (NASH) is a common and potentially severe form of liver disease. This study aimed to determine the effect of ursodeoxycholic acid and its NO-releasing derivative NCX-1000 alone or in combination with antioxidants on cultured mouse hepatocytes treated with amiodarone to mimic certain aspects of hepatocyte injury found in NASH. Isolated mouse hepatocytes were incubated with ursodeoxycholic acid or NCX-1000 (0-100 micromol/L) combined or not combined with the hydrophilic antioxidants butylated hydroxytoluene and ascorbic acid (0-100 micromol/L) or with the lipophilic antioxidant alpha-tocopherol (0-100 micromol/L) 15 min before adding amiodarone (50 micromol/L) to the culture medium. Twenty hours later, necrosis, apoptosis, superoxide anion production, and malondialdehyde levels were assessed in cultured cells. Amiodarone led to a dose-dependent decrease in cell viability with an LD50 of 50 micromol/L and increased production of superoxide anion and lipid peroxidation. NCX-1000 showed a better protective potential than ursodeoxycholic acid against the toxic effects of amiodarone. The hydrophilic antioxidants had no effect on the toxicity of amiodarone, whereas alpha-tocopherol at a concentration >100 micromol/L almost completely suppressed it. Ursodeoxycholic acid and NCX-1000 protection was additive only when they were combined with alpha-tocopherol, not with butylated hydroxytoluene or ascorbic acid. In addition, all the antioxidants tested reduced the superoxide anion detected, but only alpha-tocopherol prevented lipid peroxidation induced by amiodarone. The combination of lipophilic antioxidants with ursodeoxycholic acid or NCX-1000 enhances their protective potential and could represent an interesting therapeutic approach to explore for the treatment of NASH.
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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) | 0.001 | 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) | 0.001 | 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".