CalRepository: A database of indirect calorimetry experiments for the study of energy homeostasis

项目摘要 在疾病状态下捕捉导致体重调节的输入的数据储存库是非常需要的 生物医学界的资源。记录食物摄入量、代谢率和 体力活动是压倒性的。目前，研究人员没有地方存放或定位相关数据。 这项提案寻求资金，以创建一个全面的、用户友好的数据存储库，以实现 研究人员存储他们的数据，并轻松地查找和重复使用、重新分析和审查能量代谢 来自世界各地科学家的数据。 该数据库将包括任何涉及啮齿动物间接热量测定的实验。数据将可用 根据对行为改变(如饥饿、睡眠模式和锻炼)对体重影响的研究， 以及研究各种疾病状态在体重调节中的作用。它还将包括实验 询问病理状态，包括心肺疾病、衰老和癌症恶病质，这些疾病导致 来改变体重和能量代谢。通过为这些研究提供一个中央数据库， 资料库将促进新的治疗干预措施的开发，并帮助研究人员更好地 了解影响体重增减的复杂因素。这一努力将作为一种模板 用于间接量热法或其他模型生物的未来临床储存库。 现代间接量热系统允许高频多维时间序列测量 影响能量平衡的因素--食物摄入量、体力活动和代谢率。我们的小组在 使用免费在线工具CALR简化和标准化这些类型数据的最前沿工作。然而， 目前还不存在这些类型的实验的数据库。在这种情况得到补救之前，美国国立卫生研究院资助 调查人员无法遵守2023年NIH数据管理和共享政策。我们描述了 创建CalRepository专门为促进公平数据原则而设计。大规模的分析和 这些类型的数据的重新使用将使人们能够对体重调节的复杂性有新的见解。 总而言之，创建一个专注于体重调节的数据存储库对于有效地 管理关于此主题的快速增长的数据量，并促进新见解的开发 导致了治疗性干预。我们相信这个项目有可能极大地推进我们的 了解体重调节并改善世界各地个人的健康和福祉。

Project Summary A data repository capturing the inputs leading to body weight regulation in disease states is a much-needed resource in the biomedical community. The sheer volume of data recording food intake, metabolic rate, and physical activity is overwhelming. Currently, there is no place for researchers to deposit or locate relevant data. This proposal seeks funding to create a comprehensive and user-friendly data repository that will enable researchers to deposit their data as well as easily find and re-use, reanalyze, and review energy metabolism data from scientists worldwide. The data repository will include any experiment involving indirect calorimetry in rodents. Data will be available from studies on the effects of altered behaviors (such as hunger, sleep patterns, and exercise) on body weight, and studies on the role of various disease states in body weight regulation. It will also include experiments interrogating pathological states including cardiopulmonary disorders, aging, and cancer cachexia, which lead to altered body weight and energy metabolism. By providing a centralized database for these studies, the repository will facilitate the development of new therapeutic interventions and help researchers to better understand the complex factors that influence weight gain and loss. This effort will serve as a template for a future clinical repository for indirect calorimetry or for additional model organisms. Modern indirect calorimetry systems allow for high-frequency multi-dimensional time-series measurements of the components affecting energy balance—food intake, physical activity, and metabolic rates. Our group is at the forefront of efforts to simplify and standardize these types of data using a free online tool, CalR. However, no data repository for these types of experiments currently exists. Until this situation is remedied, NIH-funded investigators are not able to comply with the 2023 NIH Data Management and Sharing Policy. We describe the creation of the CalRepository designed specifically to facilitate FAIR data principles. Large-scale analysis and re-use of these types of data will enable new insights into the complexities of body weight regulation. In summary, the creation of a data repository focused on body weight regulation is essential to effectively manage the rapidly growing volume of data on this topic and to facilitate the development of new insights leading to therapeutic interventions. We believe that this project has the potential to significantly advance our understanding of body weight regulation and improve the health and well-being of individuals around the world.