The General Electric Healthcare, InCell 6000 High Content Analysis (HCA) instrument is being requested to allow investigators from the University of Pittsburgh, the University of Pittsburgh Medical Center and Carnegie Mellon University to analyze complex cellular processes in both fixed and living cells, multicellular model systems and research organisms (Zebra Fish and C. elegans). This high instrument combines a high scan-rate confocal imaging device, an environmental chamber, 4-channel fluorescence, transmitted light and on-board fluid addition in a microplate-based system. The InCell 6000 permits automated, high throughput and high temporal and spatial resolution of subcelluar structures and biochemical reactions that are the basis of all cellular and tissue functions. The long-term objective is to extend our present capabilities in acquiring high temporal, spatial and spectral images from a small sample size to the acquisition of large data sets from populations of cells on a cell-by-cell basis, tissue models and experimental animals. This new capability will permit the application of computational and systems biology tools to understand the complexities of life processes based on statistical significance not possible before. The integration of the best biological experimental systems, fluorescence-based reagents and high throughput, automated imaging will enable large, combinatorial treatments of samples to allow the exploration of statistically relevant mechanisms of action in a variety of therapeutic areas. The NIH funded projects that will use this instrument include investigations on human adipocyte differentiation in cancer, the physiology of stem cell derived cardiomyocytes, the heterogeneity of drug responses in head and neck cancer models, the role of the immune response in cancer therapies, live, 3D breast cancer models with the analysis of pathways, cell migration in tumor models, modulation of Huntington's Disease progression in model systems, protein misfolding disease model of alpha 1- antitrypsin deficiency (ATD), and necrotizing enterocolitis (NEC) models in C. elgans. In addition, a kidney regeneration model in Zebra fish to identify small molecules that stimulate stem cell proliferation, as well as the application of a new generation of genetically encoded biosensors, standards for imaging and flow cytometry and the further application of active machine learning optimization of experimental strategies. The application of this platform to fundamental biomedical research and translational research programs will ultimately lead to better success in drug discovery and development, while helping to define the mechanisms of normal and disease processes.
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