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

Full article: Bringing together scientific disciplines for collaborative undertakings: a vision for advancing the adverse outcome pathway framework

PPARγ agonists inhibit TGF-β induced pulmonary myofibroblast differentiation and collagen production: implications for therapy of lung fibrosis

AOP-Wiki

Adverse outcome pathways as a tool for the design of testing strategies to support the safety assessment of emerging advanced materials at the nanoscale, Particle and Fibre Toxicology

The 2021 update of the EPA's adverse outcome pathway database

Full article: Collaborative efforts are needed among the scientific community to advance the adverse outcome pathway concept in areas of radiation risk assessment

Jaeseong JEONG, PostDoc Position, Doctor of Philosophy, University of Seoul, Seoul, School of Environmental Engineering

Adverse outcome pathways as a tool for the design of testing strategies to support the safety assessment of emerging advanced materials at the nanoscale, Particle and Fibre Toxicology

AOP-Wiki

AOP-Based Machine Learning for Toxicity Prediction

PDF) Identification of toxicity pathway of diesel particulate matter using AOP of PPARγ inactivation leading to pulmonary fibrosis

DDAC induces inflammation and fibroproliferation in the lungs. Mice