Gurvir S. Virdi

1 INTRODUCTION In conventional microscopy, the overlapping fluorescence from molecules separated by distances shorter than the diffraction limit of light, ~250 nm, prevents them from being distinguished (Abbe 1873; Lelek et al. 2021). To overcome this limitation, super-resolution (SR) microscopy has been developed to study proteins at the nanometer length scale in various biological systems, achieving resolutions as high as 5 nm (Löschberger et al. 2014).

Abstract Neuronal insulin resistance is linked to the pathogenesis of Parkinsons disease through unclear, but potentially targetable, mechanisms. We delineated neuronal and glial mechanisms of insulin resistance and glucagon-like 1 peptide (GLP-1) receptor agonism in human iPSC models of synucleinopathy, and corroborated our findings in patient samples from a Phase 2 trial of a GLP-1R agonist in Parkinsons (NCT01971242).

Abstract Parkinson’s disease is a common, incurable neurodegenerative disorder that is clinically heterogeneous: it is likely that different cellular mechanisms drive the pathology in different individuals. So far it has not been possible to define the cellular mechanism underlying the neurodegenerative disease in life. We generated a machine learning-based model that can simultaneously predict the presence of disease and its primary mechanistic subtype in human neurons.