WHOLE SLIDE IMAGING SYSTEM FOR TRANSLATIONAL NEUROSCIENCE

描述（由申请人提供）：该提案要求提供资金，以在华盛顿大学建立一个全载玻片成像（WSI）设施，用于NIH资助的转化神经科学研究。全载玻片成像可快速将玻璃组织学载玻片的全部内容捕获到大型数字文件中，这些文件可以电子方式存档、分析和共享。拟议的系统包括一个商业扫描仪（奥林巴斯NanoZoomer）能够高通量，亚微米显微镜图像采集多达210个载玻片在明场或荧光模式，连同集成的硬件和软件的数据存储，图像分析和在线分配。该设施将直接支持代表7个部门的10个主要用户的工作，这些用户致力于研究阿尔茨海默氏症、多发性硬化症、缺血性中风、脑出血、中枢神经系统感染、脑肿瘤、神经创伤、朊病毒疾病和外周神经损伤等多种疾病的动物模型。研究人员由19个NIH赠款资助，包括P30中心赠款，两个计划项目赠款和几个培训赠款。如果得到资助，这将是华盛顿大学唯一的WSI研究设施。虽然80%的系统时间预计将采取的主要用户，剩余的资源将提供给其他研究人员在吴和其他地方，根据设施咨询委员会确定的优先事项。由于整个载玻片成像系统能够无人值守地采集某些类型的载玻片，我们预计每周的操作时间高达100小时。拟议中的系统将由神经疾病希望中心获得，该中心是神经病学系内的一个跨部门研究单位。希望中心将在第一年为装修、服务合同和人员提供财政支持，并将在此后为持续的设施费用提供支持。在现有的显微镜核心设施内进行安装将有助于用户培训、方案制定、时间安排、数据分析和传播。一名有经验的技术员将培训和协助用户，一个信息服务小组将提供数据管理支助。图像文件将自动传输到安全的存储阵列中，可从该阵列中访问这些文件，以进行定量分析、地图集形成或作为公开或受密码保护的内容进行网络导航。图像分析和在线图谱管理方面的强大专业知识将由共同研究者大卫货车埃森（解剖学和神经生物学系）和陶菊（计算机科学与工程系）提供。结合技术专长和WSI能力，将能够创建和开放共享新颖的高分辨率小鼠脑疾病模型图谱。与公共卫生的相关性：全载玻片成像（WSI）提供了整个显微镜载玻片的快速数字捕获。这将通过加速动物疾病模型中治疗效果的评估，协助研究合作，并允许科学家存档和共享结果来支持脑部疾病的研究。数据共享通过促进疾病模型之间的比较提供了巨大的红利，并允许在现有数据上进行新的研究发现，而无需进行额外的动物实验。

DESCRIPTION (provided by applicant): This proposal requests funds to establish a Whole Slide Imaging (WSI) facility for NIH-funded translational neuroscience research at Washington University. Whole slide imaging rapidly captures the entire content of glass histology slides into large digital files which can be archived, analyzed, and shared electronically. The proposed system includes a commercial scanner (Olympus NanoZoomer) capable of high-throughput, submicron microscopic image acquisition of up to 210 slides in brightfield or fluorescence modes, together with integrated hardware and software for data storage, image analysis, and on-line distribution. The facility will directly support the work of 10 major users representing 7 departments, working on animal models of disease as diverse as Alzheimer's, multiple sclerosis, ischemic stroke, intracerebral hemorrhage, CNS infections, brain tumors, neurotrauma, prion diseases, and peripheral nerve injury. The investigators are funded by 19 NIH grants including a P30 Center grant, two Program Projects grants, and several training grants. If funded, this will be the only WSI facility for research at Washington University. While 80% of system time is expected to be taken by major users, remaining resources will be made available to other researchers at WU and elsewhere, according to priorities established by a facility advisory committee. Since the whole slide imaging system is capable of unattended acquisition for certain slide types, we anticipate operation for as much as 100 hours per week. The proposed system will be acquired by the Hope Center for Neurological Disorders, an interdepartmental research unit administered within the Department of Neurology. The Hope Center will commit financial support for renovation, service contracts, and personnel in Year I and will provide support for ongoing facility expenses thereafter. Installation within an established microscopy core facility will assist in user training, protocol development, scheduling, data analysis and dissemination. An experienced technician will train and assist users, and data management support will be provided by an Information Services group. Image files will be automatically transferred to a secure storage array, from which they can be accessed for quantitative analysis, atlas formation, or web navigation as either public or password-protected content. Strong expertise in image analysis and online atlas management will be provided by co-investigators David Van Essen (Department of Anatomy and Neurobiology) and Tao Ju (Department of Computer Science and Engineering). The combined technical expertise and WSI capability will enable the creation and open sharing of novel high-resolution atlases of mouse brain disease models. Relevance to Public Health: Whole-slide imaging (WSI) provides rapid digital capture of entire microscope slides. This will support research in brain diseases by speeding assessment of therapeutic effects in animal disease models, assisting research collaboration, and allowing scientist to archive and share results. Data sharing provides great dividends by facilitating comparisons between disease models, and allowing new research findings on existing data without having to perform additional animal experiments.