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相关概念视频

Glucose Transporters01:27

Glucose Transporters

Glucose transporters facilitate the transport of glucose across the cell membrane. In addition to glucose, some glucose transporters can also aid the movement of other hexoses such as fructose, mannose, and galactose.
Facilitated diffusion-glucose transporters (GLUTs) are encoded by the solute-linked carrier (SLC) family 2, subfamily A gene family, or SLC2A. The 14 GLUT protein members are distributed into three classes:
Bioavailability Study Design: Healthy Subjects Versus Patients01:15

Bioavailability Study Design: Healthy Subjects Versus Patients

Bioavailability studies are essential for evaluating a drug's therapeutic efficacy and understanding its absorption patterns under various physiological conditions. Conducting such studies on target patient populations provides more relevant data by simulating real-world disease states. However, practical challenges often necessitate the use of young, healthy adult volunteers as study subjects.Patients may exhibit altered drug absorption patterns due to the effects of the disease itself,...

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Isolation of Human Islets from Partially Pancreatectomized Patients
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在德国糖尿病研究中实施FAIRification工作流程的经验教训

Esther Thea Inau1, Angela Dedié2, Ivona Anastasova2

  • 1Medical Informatics Laboratory, University Medicine Greifswald, Greifswald, Germany.

PLOS digital health
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对糖尿病研究的两个FAIR数据工作流进行比较,发现域特定的调整提高了效率,但不一定是核心数据集的FAIR度得分. 早期规划FAIR数据策略至关重要.

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科学领域:

  • 医疗信息学 医疗信息学
  • 数据科学数据科学数据科学
  • 研究数据管理研究数据管理

背景情况:

  • 公平原则 (可查找,可访问,可互操作,可重复使用) 对于最大限度地提高科学数据价值至关重要.
  • 研究社区开发特定领域的工作流程,以获得FAIR数据.
  • 实施FAIR数据工作流需要仔细考虑标准和实践.

研究的目的:

  • 为了比较通用与特定领域的FAIRification工作流程的实现.
  • 通过德国的糖尿病研究数据,评估这些工作流对公平度评分的影响.
  • 确定有效实施FAIR数据核心数据集的要求.

主要方法:

  • 应用了两个外部开发的结构化FAIRification工作流程:一个通用,一个域特定.
  • 利用了德国糖尿病研究的元数据.
  • 采用了来自研究数据联盟 (RDA) 的FAIR数据成熟度模型.

主要成果:

  • 通用和特定领域的工作流程都需要类似的资源来实现.
  • 这两种工作流都为核心数据集提供了相当的公平度评级.
  • 对健康研究数据的调整提高了工作流程的效率,但并没有提高核心数据集的公平性得分.

结论:

  • 针对健康数据的特定领域的工作流适应提高了效率,但并没有本质上提高核心数据集的 FAIRness 评分.
  • 确定了核心数据集的 FAIRification 的通用要求清单.
  • 早期的战略规划和基础设施开发对于成功实施FAIR数据至关重要.