{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["124(7)"],"submitter":["Shah I"],"pubmed_abstract":["<h4>Background</h4>High-content imaging (HCI) allows simultaneous measurement of multiple cellular phenotypic changes and is an important tool for evaluating the biological activity of chemicals.<h4>Objectives</h4>Our goal was to analyze dynamic cellular changes using HCI to identify the \"tipping point\" at which the cells did not show recovery towards a normal phenotypic state.<h4>Methods</h4>HCI was used to evaluate the effects of 967 chemicals (in concentrations ranging from 0.4 to 200 μM) on HepG2 cells over a 72-hr exposure period. The HCI end points included p53, c-Jun, histone H2A.x, α-tubulin, histone H3, alpha tubulin, mitochondrial membrane potential, mitochondrial mass, cell cycle arrest, nuclear size, and cell number. A computational model was developed to interpret HCI response"],"journal":["Environmental health perspectives"],"pagination":["910-9"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC4937847"],"repository":["biostudies-literature"],"pubmed_title":["Using ToxCast™ Data to Reconstruct Dynamic Cell State Trajectories and Estimate Toxicological Points of Departure."],"pmcid":["PMC4937847"],"pubmed_authors":["Kavlock RJ","Liu J","Judson RS","Jack J","Crofton KM","Knudsen TB","Shah I","Setzer RW","Houck KA","Thomas RS","Martin MT","Reif DM","Richard AM","Dix DJ"],"additional_accession":[]},"is_claimable":false,"name":"Using ToxCast™ Data to Reconstruct Dynamic Cell State Trajectories and Estimate Toxicological Points of Departure.","description":"<h4>Background</h4>High-content imaging (HCI) allows simultaneous measurement of multiple cellular phenotypic changes and is an important tool for evaluating the biological activity of chemicals.<h4>Objectives</h4>Our goal was to analyze dynamic cellular changes using HCI to identify the \"tipping point\" at which the cells did not show recovery towards a normal phenotypic state.<h4>Methods</h4>HCI was used to evaluate the effects of 967 chemicals (in concentrations ranging from 0.4 to 200 μM) on HepG2 cells over a 72-hr exposure period. The HCI end points included p53, c-Jun, histone H2A.x, α-tubulin, histone H3, alpha tubulin, mitochondrial membrane potential, mitochondrial mass, cell cycle arrest, nuclear size, and cell number. A computational model was developed to interpret HCI response","dates":{"release":"2016-01-01T00:00:00Z","publication":"2016 Jul","modification":"2025-04-19T21:53:15.172Z","creation":"2019-03-27T02:17:51Z"},"accession":"S-EPMC4937847","cross_references":{"pubmed":["26473631"],"doi":["10.1289/ehp.1409029"]}}