Machine learning identifies phenotypic profile alterations of human dopaminergic neurons exposed to bisphenols and perfluoroalkyls.

ABSTRACT: Parkinson's disease (PD) is the second most common neurodegenerative disease and is characterized by the loss of midbrain dopaminergic neurons. Endocrine disrupting chemicals (EDCs) are active substances that interfere with hormonal signaling. Among EDCs, bisphenols (BPs) and perfluoroalkyls (PFs) are chemicals leached from plastics and other household products, and humans are unavoidably exposed to these xenobiotics. Data from animal studies suggest that EDCs exposure may play a role in PD, but data about the effect of BPs and PFs on human models of the nervous system are lacking. Previous studies demonstrated that machine learning (ML) applied to microscopy data can classify different cell phenotypes based on image features. In this study, the effect of BPs and PFs at different concentra

SUBMITTER: Di Credico A 

PROVIDER: S-EPMC10713827 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature