首页|Zhejiang University Reports Findings in Machine Learning (Machine Learning-Based Toxicological Modeling for Screening Environmental Obesogens)
Zhejiang University Reports Findings in Machine Learning (Machine Learning-Based Toxicological Modeling for Screening Environmental Obesogens)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning is th e subject of a report. According to news reporting out of Hangzhou, People’s Rep ublic of China, by NewsRx editors, research stated, “The emerging presence of en vironmental obesogens, chemicals that disrupt energy balance and contribute to a dipogenesis and obesity, has become a major public health challenge. Molecular i nitiating events (MIEs) describe biological outcomes resulting from chemical int eractions with biomolecules.” Our news journalists obtained a quote from the research from Zhejiang University , “Machine learning models based on MIEs can predict complex toxic end points du e to chemical exposure and improve the interpretability of models. In this study , a system was constructed that integrated six MIEs associated with adipogenesis and obesity. This system showed high accuracy in external validation, with an a rea under the receiver operating characteristic curve of 0.78. Molecular hydroph obicity (SlogP_VSA) and direct electrostatic interactions (PEOE_ VSA) were identified as the two most critical molecular descriptors representing the obesogenic potential of chemicals. This system was further used to predict the obesogenic effects of chemicals on the candidate list of substances of very high concern (SVHCs). Results from 3T3-L1 adipogenesis assays verified that the system correctly predicted obesogenic or nonobesogenic effects of 10 of the 12 S VHCs tested, and identified four novel potential obesogens, including 2-benzotri azol-2-yl-4,6-dibutylphenol (UV-320), 4-(1,1,5-trimethylhexyl)phenol (p262-NP), 2-[4-(1,1,3,3-tetramethylbutyl)phenoxy] et hanol (OP1EO) and endosulfan.”
HangzhouPeople’s Republic of ChinaAs iaAdipogenesisChemicalsCyborgsEmerging TechnologiesHealth and MedicineMachine Learning
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