biostudies-literatureUnknown124(7)Shah I<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 responseEnvironmental health perspectives910-9https://www.ebi.ac.uk/biostudies/studies/S-EPMC4937847biostudies-literatureUsing ToxCast™ Data to Reconstruct Dynamic Cell State Trajectories and Estimate Toxicological Points of Departure.PMC4937847Kavlock RJLiu JJudson RSJack JCrofton KMKnudsen TBShah ISetzer RWHouck KAThomas RSMartin MTReif DMRichard AMDix DJfalseUsing ToxCast™ Data to Reconstruct Dynamic Cell State Trajectories and Estimate Toxicological Points of Departure.<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 response2016-01-01T00:00:00Z2016 Jul2025-04-19T21:53:15.172Z2019-03-27T02:17:51ZS-EPMC49378472647363110.1289/ehp.1409029