Results 21 to 30 of about 1,723,253 (280)

Estimating provisional margins of exposure for data-poor chemicals using high-throughput computational methods

Frontiers in Pharmacology, 2022
Current computational technologies hold promise for prioritizing the testing of the thousands of chemicals in commerce. Here, a case study is presented demonstrating comparative risk-prioritization approaches based on the ratio of surrogate hazard and ...
Chantel I. Nicolas, Matthew W. Linakis, Melyssa S. Minto, Kamel Mansouri, Rebecca A. Clewell, Miyoung Yoon, John F. Wambaugh, Grace Patlewicz, Patrick D. McMullen, Melvin E. Andersen, Harvey J. Clewell III   +10 more
doaj   +1 more source

High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures

npj Systems Biology and Applications, 2021
The ToxCast in vitro screening program has provided concentration-response bioactivity data across more than a thousand assay endpoints for thousands of chemicals found in our environment and commerce.
Jill A. Franzosa, Jessica A. Bonzo, John Jack, Nancy C. Baker, Parth Kothiya, Rafal P. Witek, Patrick Hurban, Stephen Siferd, Susan Hester, Imran Shah, Stephen S. Ferguson, Keith A. Houck, John F. Wambaugh   +12 more
doaj   +1 more source

Antidiabetic activity of avocado seeds (Persea americana Mill.) in diabetic rats via activation of PI3K/AKT signaling pathway

Scientific Reports, 2022
The treatment of diabetes involves the use of herbal plants, attracting interest in their cost-effectiveness and efficacy. An aqueous extract of Persea americana seeds (AEPAS) was explored in this study as a possible therapeutic agent in rats with ...
Oluwafemi Adeleke Ojo, Jennifer Chidubem Amanze, Abosede Itunuoluwa Oni, Susan Grant, Matthew Iyobhebhe, Tobiloba Christiana Elebiyo, Damilare Rotimi, Nnaemeka Tobechukwu Asogwa, Babatunji Emmanuel Oyinloye, Basiru Olaitan Ajiboye, Adebola Busola Ojo   +10 more
doaj   +1 more source

Artificial intelligence as the new frontier in chemical risk assessment

Frontiers in Artificial Intelligence, 2023
The rapid progress of AI impacts various areas of life, including toxicology, and promises a major role for AI in future risk assessments. Toxicology has shifted from a purely empirical science focused on observing chemical exposure outcomes to a data ...
Thomas Hartung, Thomas Hartung
doaj   +1 more source

An introduction to systems toxicology

, 2020
The science of toxicology is the science of the system. Toxicologists aim to understand and predict the adverse effects of chemicals on biological systems.
Plant, NJ
core   +2 more sources

In silico toxicology: computational methods for the prediction of chemical toxicity [PDF]

, 2016
Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design.
Arwa B. Raies, Raies, Arwa B., Bajic, Vladimir B., Vladimir B. Bajic   +3 more
core   +1 more source

A Combined In Vitro/In Silico Approach to Identifying Off-Target Receptor Toxicity

iScience, 2018
Summary: Many xenobiotics can bind to off-target receptors and cause toxicity via the dysregulation of downstream transcription factors. Identification of subsequent off-target toxicity in these chemicals has often required extensive chemical testing in ...
Joseph Leedale, Kieran J. Sharkey, Helen E. Colley, Áine M. Norton, David Peeney, Chantelle L. Mason, Jean G. Sathish, Craig Murdoch, Parveen Sharma, Steven D. Webb   +9 more
doaj   +1 more source

High-throughput AR dimerization assay identifies androgen disrupting chemicals and metabolites

Frontiers in Toxicology, 2023
Introduction: Analysis of streamlined computational models used to predict androgen disrupting chemicals revealed that assays measuring androgen receptor (AR) cofactor recruitment/dimerization were particularly indispensable to high predictivity ...
Evan C. Brown, Evan C. Brown, Daniel R. Hallinger, Steven O. Simmons   +3 more
doaj   +1 more source

The CompTox Chemistry Dashboard: a community data resource for environmental chemistry

Journal of Cheminformatics, 2017
Despite an abundance of online databases providing access to chemical data, there is increasing demand for high-quality, structure-curated, open data to meet the various needs of the environmental sciences and computational toxicology communities.
Antony J. Williams, Christopher M. Grulke, Jeff Edwards, Andrew D. McEachran, Kamel Mansouri, Nancy C. Baker, Grace Patlewicz, Imran Shah, John F. Wambaugh, Richard S. Judson, Ann M. Richard   +10 more
doaj   +1 more source

Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxicology [PDF]

, 2012
Non-negative matrix factorization is a useful tool for reducing the dimension of large datasets. This work considers simultaneous non-negative matrix factorization of multiple sources of data.
Clare M. Lee, Vass J. Keith, D R Haggart, Lee Clare M., Mudaliar, MAV, Higham, Desmond, Vass, D.J., Manikhandan A V Mudaliar, Gino Miele, Mudaliar, Manikhandan A.V., Haggart, D. R., Mudaliar, M.A.V., Higham, Desmond J., Haggart D. R., Crowther, Daniel, D. R. Haggart, Lee, C.M., Lee, Clare M., Mudaliar Manikhandan A. V., J Keith Vass, Higham Desmond J., Wolf, C.R., Higham, D.J., Wolf C. Roland, Miele Gino, Mudaliar, Manikhandan A. V., Miele, Geno, Desmond J Higham, Clare M Lee, C. Roland Wolf, Miele, G., Manikhandan A. V. Mudaliar, C Roland Wolf, Crowther Daniel, Vass, J.K., Miele, Gino, J. Keith Vass, Crowther, D., Crowther, Daniel; id_orcid, Daniel Crowther, Vass, J. Keith, Desmond J. Higham, Haggart, D.R., Wolf, C. Roland, Lee, Clare   +44 more
core   +1 more source