Ontology highlight
ABSTRACT:
SUBMITTER: Fortino V
PROVIDER: S-EPMC9249793 | biostudies-literature | 2022 Jul
REPOSITORIES: biostudies-literature
Fortino Vittorio V Kinaret Pia Anneli Sofia PAS Fratello Michele M Serra Angela A Saarimäki Laura Aliisa LA Gallud Audrey A Gupta Govind G Vales Gerard G Correia Manuel M Rasool Omid O Ytterberg Jimmy J Monopoli Marco M Skoog Tiina T Ritchie Peter P Moya Sergio S Vázquez-Campos Socorro S Handy Richard R Grafström Roland R Tran Lang L Zubarev Roman R Lahesmaa Riitta R Dawson Kenneth K Loeschner Katrin K Larsen Erik Husfeldt EH Krombach Fritz F Norppa Hannu H Kere Juha J Savolainen Kai K Alenius Harri H Fadeel Bengt B Greco Dario D
Nature communications 20220701 1
There is an urgent need to apply effective, data-driven approaches to reliably predict engineered nanomaterial (ENM) toxicity. Here we introduce a predictive computational framework based on the molecular and phenotypic effects of a large panel of ENMs across multiple in vitro and in vivo models. Our methodology allows for the grouping of ENMs based on multi-omics approaches combined with robust toxicity tests. Importantly, we identify mRNA-based toxicity markers and extensively replicate them i ...[more]