| Extending High Content Analysis to Animal Models of Injury |
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Presentation: P03044 Session: Robotic Screening & Automation Technologies - Poster SessionMegan Cuda, Jason Callio (University of Pittsburgh School of Medicine) and Charleen Chu (University of Pittsburgh School of Medicine), Lisa Reuter, Everett Ramer and Jeffrey R. Haskins, Cellomics, Inc. Presenting Author: Megan Cuda, Cellomics Inc. - USA Parkinson's disease is a neurodegenerative disease characterized by a progressive loss of the dopaminergic neurons in the substantia nigra pars compacta, and their associated terminals in the striatum. Loss of these neurons is accompanied by decreases in the dopaminergic-associated enzyme, tyrosine hydroxylase (TH). Astrocyte hypertrophy (known as gliosis), often accompanies this neuronal loss and has been associated with increases in glial fibrillary acidic protein (GFAP). In this study we show how High Content Analysis (ArrayScan® HCS Reader with Slideport™ slide insert) can be utilized to automatically analyze tissue sections obtained from mice treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydro-pyridine (MPTP), an oxidative injury model that mimics Parkinson’s. Quantitative differences in TH and GFAP levels were detected between control and treated animals. This study shows how HCA can be leveraged to analyze samples that previously could only be examined using traditional microscopy, including cells grown on cover slips, TMAs, and tissues sections, among others. |