AIMC Topic: Adverse Outcome Pathways

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Mechanistic Insights into the Effects of Liquid Crystalline Monomers on Intestinal Stem Cell Differentiation Imbalance by Integrating Machine Learning and Adverse Outcome Pathway Framework Based on Organoids.

Environmental science & technology
The global annual output of liquid crystal monomers (LCMs) continues to increase, yet associated environmental and health risks remain poorly characterized. Assessing the toxic effects of the LCM mixture and individual components is critical for risk...

The Cost Outcome Pathway framework: Integrating socio-economic impacts to Adverse Outcome Pathways for supporting policy makers.

Toxicology
The Adverse Outcome Pathway (AOP) concept leverages existing data to formalize and disseminate knowledge and is a well-accepted concept in chemical risk assessment. However, it does not handle the socio-economic impact that environmentally-induced di...

In vitro test battery for testing molecular initiating events in chemical-induced cholestasis.

Toxicology
Cholestatic liver injury is a complex adversity leading to the toxic accumulation of.noxious bile salts in the liver and systemic circulation. Cholestasis can be instigated by a plethora of chemicals originating from several applicability domains. Cu...

Hepatic toxicity prediction of bisphenol analogs by machine learning strategy.

The Science of the total environment
Toxicological studies have demonstrated the hepatic toxicity of several bisphenol analogs (BPs), a prevalent type of endocrine disruptor. The development of Adverse Outcome Pathway (AOP) has substantially contributed to the rapid risk assessment for ...

Report of the First ONTOX Stakeholder Network Meeting: Digging Under the Surface of ONTOX Together With the Stakeholders.

Alternatives to laboratory animals : ATLA
The first Stakeholder Network Meeting of the EU Horizon 2020-funded ONTOX project was held on 13-14 March 2023, in Brussels, Belgium. The discussion centred around identifying specific challenges, barriers and drivers in relation to the implementatio...

Control list of high-priority chemicals based on 5-HT-RI functionality and the human health interference effects selective CNN-GRU deep learning model.

The Science of the total environment
The antidepressant drug known as 5-HT reuptake inhibitor (5-HT-RI) was commonly detected in biological tissues and result in significant adverse health effects. Homology modeling was used to characterize the functionalities (efficacy and resistance),...

Making the Case for Quantum Mechanics in Predictive Toxicology─Nearly 100 Years Too Late?

Chemical research in toxicology
The use of quantum mechanics (QM) has long been the norm to study covalent-binding phenomena in chemistry and biochemistry. The pharmaceutical industry leverages QM models explicitly in covalent drug discovery and implicitly to characterize short-ran...

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...

Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach.

Chemical research in toxicology
Exposure to certain chemicals such as disinfectants through inhalation is suspected to be involved in the development of pulmonary fibrosis, a lung disease in which lung tissue becomes damaged and scarred. Pulmonary fibrosis is known to be regulated ...

Machine Learning and Artificial Intelligence in Toxicological Sciences.

Toxicological sciences : an official journal of the Society of Toxicology
Machine learning and artificial intelligence approaches have revolutionized multiple disciplines, including toxicology. This review summarizes representative recent applications of machine learning and artificial intelligence approaches in different ...