Article
Environmental Sciences
Pietro Cozzini, Francesca Cavaliere, Giulia Spaggiari, Gianluca Morelli, Marco Riani
Summary: According to Eurostat, the production of hazardous chemicals in the EU reached 211 million tonnes in 2019, which has attracted considerable attention from the scientific community. Due to the large number of chemical compounds, it is impossible to identify all possible toxic interactions using traditional in vitro/in vivo tests. Therefore, this study uses computational approaches to screen the interactions of food contact chemicals with the nuclear receptor family, providing a cost and time-effective solution.
Article
Environmental Sciences
Xiaoqing Wang, Li Wang, Fei Li, Yuefa Teng, Chenglong Ji, Huifeng Wu
Summary: Endocrine-disrupting chemicals, such as organophosphorus ester (OPEs) flame retardants, can impact lipid metabolism and induce chronic health issues. Triphenyl phosphate (TPP) in OPEs is particularly concerning for causing lipid metabolism abnormalities by damaging cell membrane structures and activating the G protein-coupled estrogen receptor 1 (GPER) pathway.
Article
Toxicology
Piaopiao Zhao, Yayuan Peng, Xuan Xu, Zhiyuan Wang, Zengrui Wu, Weihua Li, Yun Tang, Guixia Liu
Summary: The article discusses the importance of mitochondria in human cells and the potential impact of drugs and chemicals on them, focusing on the development of models that can accurately predict mitochondrial toxicity.
JOURNAL OF APPLIED TOXICOLOGY
(2021)
Article
Environmental Sciences
Celeste K. Carberry, Toby Turla, Lauren E. Koval, Hadley Hartwell, Rebecca C. Fry, Julia E. Rager
Summary: This study used in silico methods to identify common chemicals co-occurring in household environments that may have joint effects on PPAR gamma. Testing five commonly co-occurring chemicals in human liver cells showed that mixtures had a more significant impact on PPAR gamma and INSR expression. Future studies will further quantify these joint effects at various doses to prioritize chemical combinations.
Article
Toxicology
Maciej Noga, Agata Michalska, Kamil Jurowski
Summary: This study used in silico methods to predict the acute toxicity of V-series nerve agents. The results show that VX and VM are the most deadly, while V-sub x and Substance 100A are the least toxic. In silico methods are crucial for filling data gaps and preparing for the use of nerve agents.
ARCHIVES OF TOXICOLOGY
(2023)
Article
Engineering, Environmental
Faith N. Lambert, Sandy Raimondo, Mace G. Barron
Summary: New approach methods are being developed to address the challenges of reducing animal testing and assessing risks to the diversity of species in aquatic environments. The toxicity-normalized species sensitivity distribution (SSDn) approach is a novel method for developing compound-specific hazard concentrations. This method shows promise for developing statistically robust hazard concentrations when adequate taxonomic representation is not available for a single chemical.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2022)
Article
Multidisciplinary Sciences
Jongwoon Kim, Myungwon Seo, Jiwon Choi, Minju Na
Summary: The paradigm of chemical risk assessment is changing from substance-based to product/mixture-based and from animal testing to alternative testing. This study introduces the development and application of the Mixture Risk Assessment Toolbox, a web-based platform that supports mixture risk assessment through various prediction models and public databases. The toolbox provides assessors with new functionalities to easily assess and compare the toxicity of mixture products using different computational techniques and find strategic solutions to minimize mixture toxicity in product development.
SCIENTIFIC REPORTS
(2022)
Article
Environmental Sciences
Warangkana Arpornchayanon, Subhawat Subhawa, Kanjana Jaijoy, Nirush Lertprasertsuk, Noppamas Soonthornchareonnon, Seewaboon Sireeratawong
Summary: This study investigated the acute and chronic toxicities of the Triphala formula in a rat model. The results showed that long-term use of Triphala in rats is safe, with no toxic effects observed.
Article
Environmental Sciences
Simon Hansul, Andreas Fettweis, Erik Smolders, Karel De Schamphelaere
Summary: The study tested the prediction of Cu-Ni-Zn mixture toxicity to Daphnia magna populations using the DEB-IBM model, finding that mixture effects were concentration and endpoint dependent. The DEB-IBM accurately predicted effects on 6-week density, including antagonistic effects at high concentrations, while initial population growth rate effects were more challenging to predict.
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY
(2021)
Article
Environmental Sciences
Sally A. Mayasich, Michael R. Goldsmith, Kali Z. Mattingly, Carlie A. LaLone
Summary: New approach methodologies (NAMs) are being developed to reduce and replace vertebrate animal testing in the field of ecotoxicology and risk assessment. In this study, the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was used to assess the conservation of a specific enzyme's amino acid sequence across different species, demonstrating the application of NAMs in understanding chemical interactions with protein targets. Variants of the enzyme were created through mutagenesis and tested for chemical inhibition in vitro, revealing significant differences in inhibitory concentrations. Molecular modeling and virtual docking were also performed to analyze the protein's structure and potential binding sites. The development of NAMs for evaluating chemical susceptibility across species requires consideration of various factors such as chemical characteristics, substituted amino acids, and complexity of the protein target.
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY
(2023)
Article
Toxicology
Maciej Noga, Agata Michalska, Kamil Jurowski
Summary: Novichoks, the fourth generation chemical warfare agents produced by the Soviet Union during the Cold War, have paralytic and convulsive effects. The public debate about their true nature highlights the importance of examining their properties, especially the toxicological aspects.
ARCHIVES OF TOXICOLOGY
(2023)
Article
Environmental Sciences
Justin Scott, Ryan Grewe, Matteo Minghetti
Summary: This study compared the sensitivity of the Fathead minnow fish embryo acute toxicity (FET) test, the fish gill cells (RTgill-W1) in vitro assay, and the fish larvae acute toxicity test for evaluating whole-effluent toxicity (WET) testing. The results showed a significant correlation between FET and fish larvae tests, while no correlation was found between RTgill-W1 cells and FET. The in vitro alternative models demonstrated good predictability of toxicity in fish for WET chemicals.
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY
(2022)
Article
Toxicology
Hung-Lin Kan, Chun-Wei Tung, Shao-En Chang, Ying-Chi Lin
Summary: Exposure to neurotoxicants has been associated with Parkinson's disease, but the identification of these neurotoxicants relies on animal models due to the clinical variation and slow progression of the disease. In this study, an innovative in silico model was proposed for predicting parkinsonian neurotoxicants. The model showed high specificity in ruling out non-neurotoxic chemicals and successfully predicted several chemicals related to parkinsonian motor deficits, providing a potential tool for prioritizing chemicals for further evaluations on Parkinson's disease potential.
ARCHIVES OF TOXICOLOGY
(2022)
Review
Toxicology
Francesca Caloni, Isabella De Angelis, Thomas Hartung
Summary: Alternative methods to animal use in toxicology are evolving, offering relevant and valid tests for drugs and chemicals. Integrated Approaches for Testing and Assessment (IATA) is a new strategy for solving complex toxicological endpoints, which requires the integration of diverse evidence streams.
ARCHIVES OF TOXICOLOGY
(2022)
Article
Environmental Sciences
Julia E. Rager, Jeliyah Clark, Lauren A. Eaves, Vennela Avula, Nicole M. Niehoff, Yong Ho Kim, Ilona Jaspers, M. Ian Gilmour
Summary: This study utilized computational approaches to identify chemical groups induced by variable biomass burn conditions associated with biological responses in the mouse lung, showing potential protective effects of certain chemical compounds.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Medicine, Research & Experimental
Heather L. Ciallella, Daniel P. Russo, Lauren M. Aleksunes, Fabian A. Grimm, Hao Zhu
Summary: Computational modeling has emerged as a promising and cost-effective alternative method for screening and prioritizing potentially endocrine-active compounds. This study applies classic machine learning algorithms and deep learning approaches to a panel of over 7500 compounds tested against 18 Toxicity Forecaster assays related to nuclear estrogen receptor activity.
LABORATORY INVESTIGATION
(2021)
Article
Engineering, Environmental
Heather L. Ciallella, Daniel P. Russo, Swati Sharma, Yafan Li, Eddie Sloter, Len Sweet, Heng Huang, Hao Zhu
Summary: This study developed a predictive and explainable computational model for evaluating the developmental toxicity potential of chemicals. The model was constructed by combining data from public repositories and literature sources, and successfully predicted developmental toxicity in external validation.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2022)
Article
Chemistry, Physical
Ali Abou Taka, Shao-Yu Lu, Duncan Gowland, Tim J. Zuehlsdorff, Hector H. Corzo, Aurora Pribram-Jones, Liang Shi, Hrant P. Hratchian, Christine M. Isborn
Summary: The simulation of optical spectra is essential but traditional methods may lead to state mixings and inaccurate description. In this study, an alternative method using self-consistent field and maximum overlap model is proposed, which produces spectra more aligned with vertical gradient and molecular dynamics. The study warns against using excited-state adiabatic Hessian in simulation and showcases three alternatives.
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2022)
Article
Pharmacology & Pharmacy
Emily Marques, Marisa Pfohl, Wei Wei, Giuseppe Tarantola, Lucie Ford, Ogochukwu Amaeze, Jessica Alesio, Sangwoo Ryu, Xuelian Jia, Hao Zhu, Geoffrey D. Bothun, Angela Slitt
Summary: It has been found that certain per- and polyfluoroalkyl substances (PFAS) are associated with hepatic steatosis. Shorter chain PFAS and alternative PFAS are more potent gene inducers and should be evaluated for their potential health effects in humans.
TOXICOLOGY AND APPLIED PHARMACOLOGY
(2022)
Article
Engineering, Environmental
Xuelian Jia, Xia Wen, Daniel P. Russo, Lauren M. Aleksunes, Hao Zhu
Summary: This study developed an adverse outcome pathway (AOP) to predict hepatotoxicity using computational modeling and in vitro assays. The mechanistic hepatotoxicity model showed good predictability for compounds tested, and the strategy can be expanded to develop predictive models for other complex toxicities.
JOURNAL OF HAZARDOUS MATERIALS
(2022)
Article
Chemistry, Physical
Tong Wang, Dimitrios Bitounis, Philip Demokritou, Xuelian Jia, Heng Huang, Hao Zhu
Summary: Modern nanotechnology provides efficient and cost-effective nanomaterials, but concerns about nanotoxicity in humans are rising. Traditional animal testing for nanotoxicity is expensive and time-consuming. Modeling studies using machine learning approaches offer a promising alternative, but the complex structures of nanomaterials make them difficult to annotate and quantify. This study addresses this issue by constructing a virtual graphene library using nanostructure annotation techniques and demonstrates good predictivity in toxicity-related endpoints.
Article
Chemistry, Medicinal
Emily Golden, Daniel C. Ukaegbu, Peter Ranslow, Robert H. Brown, Thomas Hartung, Alexandra Maertens
Summary: In our previous work, we demonstrated 70-80% accuracies for various skin sensitization computational tools using human data. In this study, we expanded the data set using the NICEATM human skin sensitization database, resulting in a final data set of 1355 chemicals. We evaluated the performance of different computational tools and found lower accuracies compared to previous estimates, with Toxtree and OECD QSAR Toolbox achieving balanced accuracies of 63% and 65%, respectively.
CHEMICAL RESEARCH IN TOXICOLOGY
(2023)
Review
Chemistry, Multidisciplinary
Xiliang Yan, Tongtao Yue, David A. A. Winkler, Yongguang Yin, Hao Zhu, Guibin Jiang, Bing Yan
Summary: Decades of nanotoxicology research have generated extensive and diverse data sets. However, data is not equal to information. This review discusses the role of artificial intelligence (AI) and molecular simulation in transforming nanotoxicity data into critical information, by constructing quantitative nanostructure-toxicity relationships and elucidating toxicity-related molecular mechanisms. Several obstacles must be overcome for AI and molecular simulation to have their full impact, including the lack of high-quality nanomaterials, standardized nanotoxicity data, model-friendly databases, specific and universal nanodescriptors, and realistic simulation of nanomaterials. The review also provides a comprehensive summary of current capability gaps and tools required to fill these gaps, as well as a perspective on future trends and challenges.
Article
Engineering, Environmental
Elena Chung, Daniel P. Russo, Heather L. Ciallella, Yu-Tang Wang, Min Wu, Lauren M. Aleksunes, Hao Zhu
Summary: Traditional methodologies for assessing chemical toxicity are expensive and time-consuming, but computational modeling approaches, particularly QSAR models, provide a low-cost alternative. However, conventional QSAR models have limited training data and poor predictivity for new compounds. This study developed data-driven models for carcinogenicity and successfully identified potential new human carcinogens.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Review
Engineering, Environmental
Xuelian Jia, Tong Wang, Hao Zhu
Summary: Chemical toxicity evaluations have critical impact on human health. Computational toxicology utilizing machine learning and deep learning techniques is a promising alternative approach. However, many toxicity models are difficult to interpret, which hampers their use in chemical risk assessments.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Article
Engineering, Environmental
Daniel P. Russo, Lauren M. Aleksunes, Katy Goyak, Hua Qian, Hao Zhu
Summary: Animal models are not effective in predicting hepatotoxicity in humans, leading to the development of biological pathway-based alternatives such as in vitro assays. Public screening programs have tested thousands of chemicals using high-throughput screening assays. Developing pathway-based models for complex toxicities like hepatotoxicity remains challenging. This study aimed to develop a computational strategy for developing pathway-based models for complex toxicities.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
