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

项目摘要 一个数据存储库捕获导致疾病状态下体重调节的输入是一个迫切需要的 生物医学界的资源。记录食物摄入量、代谢率和 体力活动太多了目前，研究人员没有存款或查找相关数据的地方。 这项建议寻求资金，以建立一个全面和方便用户的数据储存库， 研究人员可以存款他们的数据，以及很容易找到和重新使用，重新分析，并审查能量代谢 来自世界各地科学家的数据。 数据库将包括任何涉及啮齿动物间接热量测定的实验。数据可用 从改变行为（如饥饿、睡眠模式和锻炼）对体重影响的研究中， 以及各种疾病状态在体重调节中的作用的研究。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， 体重和能量代谢的改变通过为这些研究提供一个集中的数据库， 知识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 了解影响体重增加和减少的复杂因素。这项工作将作为一个模板， 未来用于间接量热法或其他模式生物的临床储存库。 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、体力活动和代谢率。我们组在 使用免费的在线工具CalR简化和标准化这些类型的数据。然而，在这方面， 目前不存在用于这些类型实验的数据储存库。在这种情况得到纠正之前，NIH资助的 研究人员无法遵守2023 NIH数据管理和共享政策。我们描述了 创建CalRepository，专门用于促进FAIR数据原则。大规模分析和 这些类型的数据的再利用将使对体重调节的复杂性的新的见解成为可能。 总之，创建一个专注于体重调节的数据库对于有效地 管理关于这一主题的快速增长的数据量，并促进新见解的发展 从而导致治疗干预。我们相信，该项目有可能大大推动我们的 了解体重调节，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.