UAB-UCSD O'Brien Center for Acute Kidney Injury Research

总体-项目摘要 一般的肾脏疾病和特别是急性肾损伤（阿基）造成相当大的发病率和死亡率。 尽管近几十年来为降低这两种死亡率作出了协调一致的努力，但这两种死亡率仍然有增无减。整个使命 UAB-UCSD奥布莱恩阿基研究中心的目标是通过促进研究来改善患者的健康 专门针对阿基及其并发症的预防和治疗。为了完成这个使命， 我们的两个机构为基础的中心跨越机构边界和研究领域，利用 在我们每个机构和全国范围内正在进行的临床前和临床研究的势头和独创性。 在这个申请成为国家资源中心（NRC）在奥布莱恩肾脏联盟，我们的主题- 基于中心建议共享和联合收割机资源，方法，创新和其他专业知识， 在指导委员会、国家协调中心和NIDDK的指导下， 吸引新的科学专门知识进入该领域，协调和优先考虑资源开发， 创新的服务，是最重要的财团。提出了以下目标：（1）整合 我们的奥布莱恩中心加入联盟，通过支持AKI相关研究的步伐， 共享核心设施和专业知识，同时确保质量保证/质量控制、严格性和可重复性 （2）促进联盟中研究人员之间有意义的互动;（3）通过 NCC和联盟共享中心的智力资源和基础设施，以扩大 AKI相关研究的研究者多样性，重点是早期研究者;（4）利用 我们的资源发展核心，以回应不断变化的需求，通过促进调查人员， AKI相关研究的创新研究路线;（5）通过我们的研究， 暑期学生培训计划;以及（6）利用我们的实质性机构承诺，推动 在联盟内开展AKI相关研究。拟议的生物医学研究核心（a 临床核心和临床前核心）和资源开发核心将整合现有的知识和 技术资源，为联合体提供一套创新研究的服务/资源， AKI相关研究我们的临床核心将独特地建立在建立网络和基础设施， 临床阿基研究，包括大量生物标本收集，并通过使用协作数字 工作空间，加强这些资源，使它们随时可供联盟使用。同时， 我们的临床前核心将独特地提供广泛的专业知识、实验工具和资源，以帮助 研究人员克服了利用相关啮齿动物模型的障碍， 阿基的病理生理学为了推进这两个领域，我们的资源开发核心将提供一个动态的 平台开发，测试和完善创新，包括代谢组学的新分析方法， 功能性体内成像和使用大型电子健康记录数据进行联合机器学习的工具。

Overall - Project Summary Kidney diseases in general and acute kidney injury (AKI) in particular impose substantial morbidity and mortality that remain unabated despite concerted efforts in recent decades to reduce both. The overall mission of the UAB-UCSD O’Brien Center for AKI Research is to improve the health of patients by fostering research specifically targeted to the prevention and treatment of AKI and its complications. To achieve this mission, our two institution-based Center crosses institutional boundaries and research fields, harnessing the momentum and ingenuity of ongoing pre-clinical and clinical research in each of our institutions and nationally. In this application to become a National Resource Center (NRC) in the O’Brien Kidney Consortium, our theme- based Center proposes to share and combine resources, methods, innovations, and other expertise with the other NRCs, under the guidance of the Steering Committee, National Coordinating Center, and NIDDK, to attract new scientific expertise into the field and coordinate and prioritize resource development and innovative services that are most essential to the Consortium. The following aims are proposed: (1) Integrate our O’Brien Center into the Consortium to accelerate the pace of AKI-related research through the support of shared Core facilities and expertise while ensuring quality assurance/quality control, rigor, and reproducibility for the Core services; (2) Foster meaningful interactions among investigators in the Consortium; (3) Through the NCC and the Consortium, share the Center’s intellectual resources and infrastructure to expand the diversity of investigators in AKI-related research, with an emphasis on early-stage investigators; (4) Utilize our Resource Development Core to respond to the evolving needs of investigators through promotion of innovative lines of investigation in AKI-related research; (5) Develop tomorrow’s thought leaders through our Summer Student Training Program; and (6) Leverage our substantial institutional commitments to propel the development of AKI-related research within the Consortium. The proposed Biomedical Research Cores (a Clinical Core and a Pre-clinical Core) and Resource Development Core will integrate existing intellectual and technological resources to provide the Consortium a set of services/resources for innovative investigation in AKI-related research. Our Clinical Core will uniquely build upon established networks and infrastructure in clinical AKI research, including a large biospecimen collection, and through the use of a collaborative digital workspace, enhance these resources and make them readily available to the Consortium. Simultaneously, our Pre-Clinical Core will uniquely provide the breadth of expertise, experimental tools, and resources to help investigators overcome barriers to the utilization of relevant rodent models and advance understanding of the pathophysiology of AKI. To advance both realms, our Resource Development Core will provide a dynamic platform to develop, test, and refine innovations, including new analytical approaches in metabolomics and functional in vivo imaging and tools for federated machine learning using big electronic health record data.