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

CalRepository：用于研究能量稳态的间接量热实验数据库

• 批准号: 10886264
• 负责人: ALEXANDER BANKS
• 金额: $ 27万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10886264
• 关键词: Administrative Supplement; Affect; Aging; Awareness; Basal metabolic rate; Behavior; Body Weight; Body Weight Changes; Body Weight decreased; Carbon Dioxide; Cardiovascular Diseases; Clinical; Communities; Complex; Computer software; Consensus; Data; Data Analyses; Data Set; Databases; Deposition; Development; Dimensions; Disease; Eating; Energy Intake; Energy Metabolism; Equation; Exercise; FAIR principles; Feedback; Frequencies; Functional disorder; Funding; Future; Gases; Goals; Hand; Health; Home; Homeostasis; Human; Hunger; Immunity; Impairment; Indirect Calorimetry; Individual; Information Retrieval; Infrastructure; Intervention; Laboratory Animals; Linear Regressions; Literature; Lung; Malignant Neoplasms; Measurement; Measures; Metabolic; Metabolism; Metadata; Methodology; Methods; Modeling; Modernization; Neurodegenerative Disorders; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Overweight; Pathologic; Pattern; Personal Satisfaction; Persons; Physical activity; Pilot Projects; Policies; Population; Process; Pulmonary Heart Disease; Recommendation; Regulation; Reproducibility; Reproductive Health; Research; Research Personnel; Resources; Rodent; Role; Sample Size; Scientist; Series; Speed; Standardization; Statistical Methods; System; Techniques; Testing; Texas; Therapeutic Intervention; Time; Time Series Analysis; United States National Institutes of Health; Visualization software; Weight; Weight Gain; cancer cachexia; central database; comorbidity; computerized data processing; computing resources; data management; data reduction; data repository; data sharing; data visualization; design; energy balance; experimental analysis; experimental study; flexibility; food surveillance; graphical user interface; improved; insight; instrument; large datasets; metabolic rate; model organism; novel therapeutic intervention; repository; response; sleep pattern; tool; usability; user-friendly; web-based tool

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.

项目概要 迫切需要一个数据存储库来捕获导致疾病状态下体重调节的输入 生物医学界的大量数据记录了食物摄入量、代谢率和 目前，研究人员没有地方存放或查找相关数据。 该提案寻求资金来创建一个全面且用户友好的数据存储库，该存储库将使 研究人员可以存储数据并轻松查找和重复使用、重新分析和审查能量代谢 来自世界各地科学家的数据。 数据存储库将包括任何涉及啮齿动物间接量热法的实验数据。 来自关于改变行为（例如饥饿、睡眠模式和运动）对体重影响的研究， 以及各种疾病状态在体重调节中的作用的研究还将包括实验。 探究病理状态，包括心肺疾病、衰老和癌症恶病质，这些状态会导致 通过为这些研究提供集中数据库，改变体重和能量代谢。 存储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。 用于间接量热法或其他模型生物体的未来临床存储库。 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。 使用免费在线工具 CalR 来简化和标准化这些类型的数据是最前沿的工作。 在这种情况得到纠正之前，目前尚不存在此类实验的数据存储库。 研究人员无法遵守 2023 年 NIH 数据管理和共享政策，我们对此进行了描述。 创建专门为促进公平数据原则而设计的 CalRepository。 重复使用这些类型的数据将为了解体重调节的复杂性提供新的见解。 总之，创建一个专注于体重调节的数据存储库对于有效地调节体重至关重要。 管理该主题快速增长的数据量并促进新见解的发展 我们相信该项目有可能显着推进我们的治疗干预。 了解体重调节并改善世界各地个人的健康和福祉。