AIMC Topic: Chemical and Drug Induced Liver Injury

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Metabonomic and transcriptomic analyses of glycosides tablet-induced hepatotoxicity in rats.

Drug and chemical toxicology
We aimed to explore novel biomarkers involved in alterations of metabolism and gene expression related to the hepatotoxic effects of glycosides tablet (TGT) in rats. Rats were randomly divided into groups based on oral administration of TGTs for 6 w...

Thyroid endocrine disruption and hepatotoxicity induced by bisphenol AF: Integrated zebrafish embryotoxicity test and deep learning.

The Science of the total environment
Bisphenol AF (BPAF) is an emerging contaminant prevalent in the environment as one of main substitutes of bisphenol A (BPA). It was found that BPAF exhibited estrogenic effects in zebrafish larvae in our previous study, while little is known about it...

Predictive Model for Drug-Induced Liver Injury Using Deep Neural Networks Based on Substructure Space.

Molecules (Basel, Switzerland)
Drug-induced liver injury (DILI) is a major concern for drug developers, regulators, and clinicians. However, there is no adequate model system to assess drug-associated DILI risk in humans. In the big data era, computational models are expected to p...

Prediction of Drug-Induced Liver Toxicity Using SVM and Optimal Descriptor Sets.

International journal of molecular sciences
Drug-induced liver toxicity is one of the significant safety challenges for the patient's health and the pharmaceutical industry. It causes termination of drug candidates in clinical trials and also the retractions of approved drugs from the market. ...

Derivation, characterisation and analysis of an adverse outcome pathway network for human hepatotoxicity.

Toxicology
Adverse outcome pathways (AOPs) and their networks are important tools for the development of mechanistically based non-animal testing approaches, such as in vitro and/or in silico assays, to assess toxicity induced by chemicals. In the present study...

Machine Learning Approaches to Predict Hepatotoxicity Risk in Patients Receiving Nilotinib.

Molecules (Basel, Switzerland)
Although nilotinib hepatotoxicity can cause severe clinical conditions and may alter treatment plans, risk factors affecting nilotinib-induced hepatotoxicity have not been investigated. This study aimed to elucidate the factors affecting nilotinib-i...

An artificial intelligence algorithm for analyzing acetaminophen-associated toxic hepatitis.

Human & experimental toxicology
INTRODUCTION: Very little artificial intelligence (AI) work has been performed to investigate acetaminophen-associated hepatotoxicity. The objective of this study was to develop an AI algorithm for analyzing weighted features for toxic hepatitis afte...

Application of Supervised SOM Algorithms in Predicting the Hepatotoxic Potential of Drugs.

International journal of molecular sciences
The hepatotoxic potential of drugs is one of the main reasons why a number of drugs never reach the market or have to be withdrawn from the market. Therefore, the evaluation of the hepatotoxic potential of drugs is an important part of the drug devel...

Drug properties and host factors contribute to biochemical presentation of drug-induced liver injury: a prediction model from a machine learning approach.

Archives of toxicology
Drug-induced liver injury (DILI) presentation varies biochemically and histologically. Certain drugs present quite consistent injury patterns, i.e., DILI signatures. In contrast, others are manifested as broader types of liver injury. The variety of ...