3D RENDITION/QUANTITATIVE ANALYSIS GI2 DEFICIENT MICE

3D 呈现/定量分析 GI2 缺陷小鼠

• 批准号: 7358258
• 负责人: Lutz Birnbaumer
• 金额: $ 2.05万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-07-01 至 2007-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7358258
• 关键词: 3D; RENDITION; QUANTITATIVE; ANALYSIS; GI2

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Mice with a disrupted gene encoding (alpha subunit of Gi2 signaling protein) develop inflammatory bowel disease resembling human ulcerative colitis (UC; 1,2) and exhibit reduced number of intestinal Peyers patches. MRM imaging offers a unique opportunity to obtain relevant morphometric data. The changes are 100% penetrant, meaning they occur in all mutant animals, which makes the Gi2 mouse a good model for development and fine tuning of technical and computational refinements needed to make MRM an accessible tool to the scientific community. Problems preparing histological cuts from wild type mice in registry with those prepared from Gi2 mice make it very difficult to both qualitatively and quantitatively describe structural alterations in cerebellums of Gi2 mice. Insight is impossible to obtain using conventional serial histology without a major effort, innumerable manpower hours and manual recording of the data susceptible to errors associated with manual anno

该子项目是利用 NIH/NCRR 资助的中心拨款提供的资源的众多研究子项目之一。子项目和研究者 (PI) 可能已从另一个 NIH 来源获得主要资金，因此可以在其他 CRISP 条目中得到体现。列出的机构是中心的机构，不一定是研究者的机构。编码基因（Gi2 信号蛋白的 α 亚基）被破坏的小鼠会出现类似于人类溃疡性结肠炎 (UC; 1,2) 的炎症性肠病，并表现出肠道派氏斑数量减少。 MRM 成像提供了获取相关形态测量数据的独特机会。这些变化是 100% 渗透的，这意味着它们发生在所有突变动物中，这使得 Gi2 小鼠成为开发和微调技术和计算改进的良好模型，使 MRM 成为科学界可用的工具。 将野生型小鼠制备的组织学切片与Gi2小鼠制备的组织学切片进行登记时存在问题，使得定性和定量描述Gi2小鼠小脑的结构变化非常困难。如果不付出巨大的努力、无数的人力和手动记录容易出现与手动记录相关的错误的数据，使用传统的串行组织学就不可能获得洞察力。