Therapeutic effect of liposomal-N-acetylcysteine against acetaminophen-induced hepatotoxicity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Acetaminophen (APAP) is an antipyretic analgesic drug that when taken in overdose causes depletion of glutathione (GSH) and hepatotoxicity. N-acetylcysteine (NAC) is the antidote of choice for the treatment of APAP toxicity; however, due to its short-half-life repeated dosing of NAC is required. PURPOSE: To determine whether a NAC-loaded liposomal formulation (Lipo-NAC) is more effective than the conventional NAC in protecting against acute APAP-induced hepatotoxicity. METHODS: Male Sprague-Dawley rats were challenged with an intragastric dose of APAP (850 mg/kg b.wt.); 4 h later, animals were administered saline, NAC, Lipo-NAC or empty liposomes and sacrificed 24 h post-APAP treatment. RESULTS: APAP administration resulted in hepatic injury as evidenced by increases in plasma bilirubin, alanine (AST) and aspartate (ALT) aminotransferase levels and tissue levels of lipid peroxidation and myeloperoxidase as well as decreases in hepatic levels of reduced GSH, GSH peroxidase and GSH reductase. Treatment of animals with Lipo-NAC was significantly more effective than free NAC in reducing APAP-induced hepatotoxicity. Histological evaluation showed that APAP caused periacinar hepatocellular apoptosis and/or necrosis of hepatocytes around the terminal hepatic venules which was reduced by NAC treatment, the degree of reduction being greater for Lipo-NAC. CONCLUSION: These data suggest that administration of Lipo-NAC ameliorated the APAP-induced hepatotoxicity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it