Supplement to AMP-AD Brain Proteomic Network Enhancement, Validation and Translation into CSF Biomarkers

母公司AMP-AD项目的目标是从皮质组织中识别蛋白质组网络，并确定 与诊断、认知和神经病理学密切相关的蛋白质共表达模块。 这些研究取决于脑组织的准确神经病理诊断和分期。这些 评估通常涉及对组织的半定量评估，需要健壮、可靠、 和可扩展的更深的表型，为精确医学方法提供更坚实的基础。我们有 在埃默里开发了数字幻灯片档案(DSA)平台，该平台的资金来自U24和U01 该系统由NCI/NIH提供资金，主要针对癌症相关的图像分析工作流程进行了优化。在这 项目中，我们建议部署和定制一个基于Web的开源管理实例和 可视化平台，数字幻灯片档案馆(DSA)。最终，我们将实现协作团队科学 并将现有的DSA平台调整为神经病理学家的工作流程。这将直接提高 我们的蛋白质组学工作使我们能够更好地注释我们的大脑/蛋白质组样本。 在这项建议中，我们建议加强DSA的用户界面，以更好地适应 神经病理学家的工作流程，用于检查脑组织，并开发一个易于安装的神经路径插件 国土安全部。我们还将在本地的NP幻灯片侧面对我们的分析套件(历史记录TK)进行基准测试和优化 和基于云的计算资源，并准备教程，演示如何使用我们的工具 ADRD相关图像分析任务。这些目标与以下方面的互补和协同专业知识相匹配 我们的信息学、病理学和工程学将帮助开发健壮、可扩展、可靠和可共享的 平台为创新的变革性科学提供基础，以满足 神经退行性疾病研究。

The goal of the parent AMP-AD project is to identify proteomic networks from cortical tissue and identify protein co-expression modules that are strongly associated with diagnosis, cognition and neuropathology. These studies hinge on accurate neuropathologic diagnosis and staging of the brain tissue. These assessments typically involve semi-quantitative evaluation of tissues and there is a need for robust, reliable, and scalable deeper phenotyping to provide a firmer foundation for precision medicine approaches. We have developed the Digital Slide Archive (DSA) platform at Emory, which has been funded through a U24 and U01 grants from the NCI/NIH and has primarily been optimized for Cancer related image analysis workflows. In this project, we propose to deploy and customize a web-based instance of our open source management and visualization platform, the Digital Slide Archive (DSA). Ultimately, we will enable collaborative team science and adapt the existing DSA platform for a neuropathologist’s workflow. This will directly enhance the value of our proteomic work by allowing us to better annotate our brain/proteomic samples. In this proposal, we propose enhancing the user interface of the DSA to better accommodate a neuropathologist’s workflow for reviewing brain tissue, and develop an easily installable Neuropath plugin for the DSA. We will also benchmark and optimize our analysis suite (HistomicsTK) on NP slide sides on local and cloud-based computational resources, and prepare tutorials demonstrating how our tools can be used for ADRD related image analysis tasks. These aims paired with the complementary and synergistic expertise of our informatics, pathology, and engineering will aid in development of robust, scalable, reliable, and sharable platforms to provide a foundation for innovative transformative science addressing a critical unmet need in neurodegenerative disease research.