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This second edition volume expands on the previous edition by exploring the latest advancements in high throughput screening (HTS) in toxicity studies by using in vitro, ex vivo, and in vivo models. This volume also covers the application of artificial intelligence (AI) and data science to curate, manage, and use HTS data. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
Cutting-edge and thorough, High Throughput Screening Assays in Modern Toxicology, Second Edition is a valuable resource for scientists pursuing chemical toxicology research. This book will aid scientists and researchers in translating new HTS techniques into standardized chemical toxicology assessment tools that can refine, reduce, and replace animal testing.
List of contents
Cell-Based Assays to Identify ERR and ERR/PGC Modulators.- Mitochondrial Membrane Potential Assay.- Cell-Based hERG Inhibition Assay in a High-Throughput Format.- Identifying CAR Modulators Utilizing a Reporter Gene Assay.- Study Liver Cytochrome P450 3A4 Inhibition and Hepatotoxicity Using DMSO-Differentiated HuH-7 Cells.- Acetylcholinesterase Inhibition Assays for High-Throughput Screening.- Cell-Based Assays to Identify Modulators of Nrf2/ARE Pathway.- Cell-Based Imaging Assay for Detection of Phospholipdosis.- GFP-LC3 High-Content Assay for Screening Autophagy Modulators.- Generation of iPSC-Derived Brain Organoids for Drug Testing and Toxicological Evaluation.- Zebrafish Behavioral Assays in Toxicology.- High Throughput Screening Assay Profiling for Large Chemical Databases.- A Quantitative High Throughput Screening Data Analysis Pipeline for Activity Profiling.- CurveP Method for Rendering High Throughput Screening Dose-Response Data into Digital Fingerprints.- Accounting for Artifacts in High Throughput Toxicity Assays.- Automatic Quantitative Structure-Activity Relationship Modeling to Fill Data Gaps in High-Throughput Screening.- Use In Silico and In Vitro Methods to Screen Hepatotoxic Chemicals and CYP450 Enzyme Inhibitors.
