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THE FAMILIAL CARDIOMYOPATHY REGISTRY

THE FAMILIAL CARDIOMYOPATHY REGISTRY
家族性心肌病登记处
批准号:
7604489
负责人:
Luisa Mestroni
金额:
$0.44万
依托单位国家:
美国
项目类别:
财政年份:
2007
资助国家:
美国
项目状态:
已结题
起止时间:
2007-07-01 至 2008-03-31

项目摘要

项目成果

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中文摘要
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英文摘要
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. The broad, long-term goal of this study is to study and understand the genetic (inherited) factors that can cause heart failure and sudden death. The specific human diseases studied are familial cardiomyopathies. We will analyze the clinical features, the evolution and gene defects causing familial cardiomyopathies (dilated, hypertrophic and right ventricular) to improve the clinical management, prevention and genetic counseling of this diseases.
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会议论文
Elucidating the Origin of Sudden Cardiac Death in Dilated Cardiomyopathy: from Phenotype Predictors to Therapeutic Targets
  • 批准号:
    10658201
  • 项目类别:
  • 资助金额:
    $72.73万
  • 财政年份:
    2023
  • 负责人:
    Luisa Mestroni
  • 依托单位:
Cardiomyocyte phenotype and mechanotransduction in Filamin C gene variants causing arrhythmogenic cardiomyopathy
  • 批准号:
    10542755
  • 项目类别:
  • 资助金额:
    $50.87万
  • 财政年份:
    2020
  • 负责人:
    Luisa Mestroni
  • 依托单位:
Cardiomyocyte phenotype and mechanotransduction in Filamin C gene variants causing arrhythmogenic cardiomyopathy
  • 批准号:
    9885476
  • 项目类别:
  • 资助金额:
    $52.42万
  • 财政年份:
    2020
  • 负责人:
    Luisa Mestroni
  • 依托单位:
Cardiomyocyte phenotype and mechanotransduction in Filamin C gene variants causing arrhythmogenic cardiomyopathy
  • 批准号:
    10333325
  • 项目类别:
  • 资助金额:
    $51.03万
  • 财政年份:
    2020
  • 负责人:
    Luisa Mestroni
  • 依托单位:
国内基金
海外基金
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data