InCell 6000 High Content Instrument for Cellular Systems Biology Program

产品说明：通用电气医疗保健公司的InCell 6000高含量分析（HCA）仪器被要求允许匹兹堡大学、匹兹堡大学医学中心和卡内基梅隆大学的研究人员分析固定细胞和活细胞、多细胞模型系统和研究生物体（斑马鱼和C. elegans）。这种高仪器结合了高扫描速率共聚焦成像设备，环境室，4通道荧光，透射光和板上流体添加在一个基于微孔板的系统。InCell 6000可实现亚细胞结构和生化反应的自动化、高通量和高时空分辨率，这些是所有细胞和组织功能的基础。长期目标是扩大我们目前的能力，从一个小的样本量获取高的时间，空间和光谱图像的大数据集从细胞群体的细胞，细胞的基础上，组织模型和实验动物的收购。这种新的能力将允许计算和系统生物学工具的应用，以了解基于统计意义的生命过程的复杂性，这在以前是不可能的。最好的生物实验系统，基于荧光的试剂和高通量，自动成像的集成将使大的，组合的样品处理，允许在各种治疗领域的统计相关的作用机制的探索。美国国立卫生研究院资助的项目将使用这种仪器，包括对人类脂肪细胞分化的研究， 癌症，干细胞衍生的心肌细胞的生理学，头颈癌模型中药物反应的异质性，免疫反应在癌症治疗中的作用，具有通路分析的活体3D乳腺癌模型，肿瘤模型中的细胞迁移，模型系统中亨廷顿病进展的调节，α 1-抗胰蛋白酶缺乏症（ATD）的蛋白质错误折叠疾病模型，和坏死性小肠结肠炎（NEC）模型。elgans。此外，斑马鱼的肾脏再生模型，以确定刺激干细胞增殖的小分子，以及新一代的应用， 基因编码的生物传感器、成像和流式细胞术的标准以及实验策略的主动机器学习优化的进一步应用。该平台在基础生物医学研究和转化研究项目中的应用将最终导致药物发现和开发的更大成功，同时有助于定义正常和疾病过程的机制。

DESCRIPTION: 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.