‘Classic’ Biomarkers of Liver Injury

Senior, John R.

doi:10.1016/b978-0-12-391496-5.00013-2

Cited by 5 publications

(3 citation statements)

References 43 publications

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“…The model is especially useful for testing substances with potential anti-inflammatory and anti-necrotic properties [14,15,16]. Protective effects were observed by using three criteria: plasma activities of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) enzymes, as well as liver necrosis score [11,12,17,18,19].…”

Section: Resultsmentioning

confidence: 99%

Hepatoprotective Effects of Met-enkephalin on Acetaminophen-Induced Liver Lesions in Male CBA Mice

et al. 2014

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Recent histopathological investigations in patients with hepatitis suggested possible involvement of Met-enkephalin and its receptors in the pathophysiology of hepatitis. Consequently, we evaluated the potential hepatoprotective effects of this endogenous opioid pentapeptide in the experimental model of acetaminophen induced hepatotoxicity in male CBA mice. Met-enkephalin exhibited strong hepatoprotective effects in a dose of 7.5 mg/kg, which corresponds to the protective dose reported for OPEN ACCESSMolecules 2014, 19 11834 several different animal disease models. In this group plasma alanine aminotransferase and aspartate aminotransferase enzyme activities, as well as liver necrosis score were significantly reduced in comparison to control animals treated with physiological saline (p > 0.01). The specificity of the peptide hepatoprotection was investigated from the standpoint of the receptor and peptide blockade. It was concluded that Met-enkephalin effects on the liver were mediated via δ and ζ opioid receptors. Genotoxic testing of Met-enkephalin confirmed the safety of the peptide.

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Section: Resultsmentioning

confidence: 99%

Hepatoprotective Effects of Met-enkephalin on Acetaminophen-Induced Liver Lesions in Male CBA Mice

et al. 2014

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“…The liver is a primary target region for drug-related toxicity as it is the main organ responsible for detoxifying and metabolizing endogenous and exogenous substances in our body. , The conventional indicators used in the diagnosis of liver damage are the activities of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), total bilirubin and albumin concentration in serum, and prothrombin time . These biomarkers have limited prognostic value for possible hepatic destruction, even though they indicate existing damage.…”

Section: Introductionmentioning

confidence: 99%

“…1,2 The conventional indicators used in the diagnosis of liver damage are the activities of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), total bilirubin and albumin concentration in serum, and prothrombin time. 3 These biomarkers have limited prognostic value for possible hepatic destruction, even though they indicate existing damage. On the other hand, increases in aminotransferase enzyme levels may not be specific to drug-induced hepatotoxicity; elevated AST and ALT levels are also observed as a result of myocardial injury, muscle damage, and intense exercise.…”

Section: ■ Introductionmentioning

confidence: 99%

Machine Learning-Based Prediction of Drug-Induced Hepatotoxicity: An OvA-QSTR Approach

Çeli̇k

Karaduman

2023

J. Chem. Inf. Model.

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Drug-induced hepatotoxicity, also known as drug-induced liver injury (DILI), is among the possible adverse effects of pharmacotherapy. This clinical condition is accepted as one of the factors leading to patient mortality and morbidity. The LiverTox database was built by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) to predict potential liver damage from medications and take appropriate precautions. The database has classified medicines into seven risk categories (A, B, C, D, E, E*, and X) to avoid medicine-induced liver toxicity. The hepatic damage risk decreases from group A to group E. This study did not include the E* and X classes because they contained unverified and unknown data groups. Our study aims to predict potential liver damage of new drug molecules without using experimental animals. We predict which of the LiverTox risk category drugs with unknown liver toxicity potential will fall into using our one-vs-all quantitative structure–toxicity relationship (OvA-QSTR) model. Our dataset, consisting of 678 organic drug molecules from different pharmacological classes, was collected from LiverTox. The OvA-QSTR models implemented by Bayesian Network (BayesNet) performed well based on the selected descriptors, with the precision–recall curve (PRC) areas ranging from 0.718 to 0.869. Our OvA-QSTR models provide a reliable premarketing risk evaluation of pharmaceutical-induced liver damage potential and offer predictions for different risk levels in DILI.

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Development and validation of an automatic machine learning model to predict abnormal increase of transaminase in valproic acid-treated epilepsy

Ma,

Huang,

et al. 2024

Arch Toxicol

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‘Classic’ Biomarkers of Liver Injury

Cited by 5 publications

References 43 publications

Hepatoprotective Effects of Met-enkephalin on Acetaminophen-Induced Liver Lesions in Male CBA Mice

Hepatoprotective Effects of Met-enkephalin on Acetaminophen-Induced Liver Lesions in Male CBA Mice

Machine Learning-Based Prediction of Drug-Induced Hepatotoxicity: An OvA-QSTR Approach

Development and validation of an automatic machine learning model to predict abnormal increase of transaminase in valproic acid-treated epilepsy

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