Human pluripotent stem cell-derived neural constructs for predicting neural toxicity

dc.contributor.author Schwartz,MP en
dc.contributor.author Hou,ZG en
dc.contributor.author Propson,NE en
dc.contributor.author Zhang,J en
dc.contributor.author Engstrom,CJ en
dc.contributor.author Vítor Santos Costa en
dc.contributor.author Jiang,P en
dc.contributor.author Nguyen,BK en
dc.contributor.author Bolin,JM en
dc.contributor.author Daly,W en
dc.contributor.author Wang,Y en
dc.contributor.author Stewart,R en
dc.contributor.author Page,CD en
dc.contributor.author Murphy,WL en
dc.contributor.author Thomson,JA en
dc.date.accessioned 2018-01-19T01:31:27Z
dc.date.available 2018-01-19T01:31:27Z
dc.date.issued 2015 en
dc.description.abstract Human pluripotent stem cell-based in vitro models that reflect human physiology have the potential to reduce the number of drug failures in clinical trials and offer a cost-effective approach for assessing chemical safety. Here, human embryonic stem (ES) cell-derived neural progenitor cells, endothelial cells, mesenchymal stem cells, and microglia/macrophage precursors were combined on chemically defined polyethylene glycol hydrogels and cultured in serum-free medium to model cellular interactions within the developing brain. The precursors self-assembled into 3D neural constructs with diverse neuronal and glial populations, interconnected vascular networks, and ramified microglia. Replicate constructs were reproducible by RNA sequencing (RNA-Seq) and expressed neurogenesis, vasculature development, and microglia genes. Linear support vector machines were used to construct a predictive model from RNA-Seq data for 240 neural constructs treated with 34 toxic and 26 nontoxic chemicals. The predictive model was evaluated using two standard hold-out testing methods: a nearly unbiased leave-one-out cross-validation for the 60 training compounds and an unbiased blinded trial using a single hold-out set of 10 additional chemicals. The linear support vector produced an estimate for future data of 0.91 in the cross-validation experiment and correctly classified 9 of 10 chemicals in the blinded trial. en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/7023
dc.identifier.uri http://dx.doi.org/10.1073/pnas.1516645112 en
dc.language eng en
dc.relation 5129 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Human pluripotent stem cell-derived neural constructs for predicting neural toxicity en
dc.type article en
dc.type Publication en
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