课题基金 / 基金详情

Cell Characterization and Imaging for Regenerative Therapies in Ischemic Diseases

Cell Characterization and Imaging for Regenerative Therapies in Ischemic Diseases
缺血性疾病再生疗法的细胞表征和成像
批准号:
8448630
负责人:
PHILLIP CHUNG-MING YANG
金额:
$48.73万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2012
资助国家:
美国
项目状态:
已结题
起止时间:
2012-03-23 至 2019-02-28

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中文摘要
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英文摘要
DESCRIPTION (provided by applicant): We are a collaborative and tightly knit group of investigators who wish to contribute to the CCTRN our expertise in 1) small molecules and stem cells in peripheral arterial disease (John Cooke); 2) clinical device development in stem cell delivery, coronary artery disease, and structural heart disease (William Fearon, Robert Robbins, and Alan Yeung); 3) multimodality cellular, molecular, and physiologic imaging of stem cells and ischemic cardiovascular diseases (Sanjiv Gambhir, Dwight Nishimura, Joseph Wu, and Phillip Yang); 4) bone marrow stem cell harvest and processing (Robert Negrin); and 5) stem cell characterization (Garry Nolan). We propose to contribute a novel multi-modality approach to assess stem cell engraftment employing manganese enhanced MRI (MEMRI) by Phillip Yang, and stem cell localization utilizing lndium-111 cell labeling by Joe Wu and Sam Gambhir. In addition, we will contribute innovative methodology to evaluate tissue perfusion and peri-infarct viability using magnetic resonance imaging (MRI) algorithms developed by Dwight Nishimura and Phillip Yang for peripheral and myocardial imaging, respectively. Finally, we will provide a comprehensive definition of the CD34+ mononuclear cells (MNCs) to be used in our human studies, using the paradigm-changing technology of single cell mass cytometry recently developed at Stanford (Bendall SC et al. Science 2011). This new technology provides a platform for massively multiplexed measurements of single-cell biological parameters that can finely delineate cellular subsets. We intend to correlate these subsets with clinical endpoints in our PAD and CAD research protocols, to determine what cell subsets may be most critical for any observed benefit.
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