Integrating imaging and computation to characterize neural crest cells in the myocardial development and regeneration
整合成像和计算来表征心肌发育和再生中的神经嵴细胞
基本信息
- 批准号:10203220
- 负责人:
- 金额:$ 24.66万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-09-04 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:3-DimensionalAblationAnimal GeneticsAnimal ModelArchitectureBiologyBlood VesselsBranchial arch structureCardiacCardiac MyocytesCellsCollaborationsConsultDefectDevelopmentDevelopmental BiologyDiastoleDiphtheria ToxinDominant-Negative MutationDoxorubicinEmbryoFishesFluorescence MicroscopyGenetic EngineeringGenetic ModelsGoalsHealth SciencesHeartHeart AbnormalitiesHeart InjuriesHeterogeneityImageJointsKnowledgeLightLiteratureMagnetic Resonance ImagingMechanicsMediatingMedical centerMentorshipMessenger RNAModelingMusMyocardialMyocardiumNatural regenerationNeonatalNeural CrestNeural Crest CellNeural tubeNotch Signaling PathwayOregonPeriodicalsPhasePhenotypePhysiologicalPopulationRecovery of FunctionRegulationResolutionRoleSignal TransductionStructureSystoleTechniquesTestingTracerTransgenic AnimalsTransgenic ModelTransgenic OrganismsUniversitiesVentricularVentricular RemodelingZebrafishbasecongenital heart disorderfluorescence microscopeheart dimension/sizeimage processingimprovedinsightmechanotransductionmigrationmouse modelmutantneural networknotch proteinoverexpressionprofessorrepairedrestorationseptal defectspatiotemporalstem cellsvirtual reality
项目摘要
Project Summary / Abstract
Integrating imaging and computation to characterize neural crest cells in the myocardial development
and regeneration
Cardiac neural crest cells are a population of highly migratory cells emerging from the neural tube, migrating
through the pharyngeal arches and integrating into the developing heart. Recent advances demonstrate that a
new sub-population of neural crest cells has the capacity to integrate into the cardiac chamber and differentiate
into cardiomyocytes in both zebrafish and mice. Notch signaling regulates cardiomyocyte proliferation and
differentiation during ventricular chamber development. Despite the knowledge gained in the past decades, the
contribution of neural crest-derived cardiomyocytes to contractile function and the role of these cardiomyocytes
in Notch signaling-mediated ventricular remodeling remain elusive. The small heart size in zebrafish embryos
and neonatal mice also hinders precise cardiac structural and functional assessment. For these reasons, I seek
to integrate our advanced imaging (sub-voxel resolution light-sheet fluorescence microscopy, SV-LSFM) with
computation (displacement analysis of myocardial mechanical deformation, DIAMOND) to characterize the
structural and functional contributions of the neural crest-derived cardiomyocytes to the myocardial development
and regeneration with high spatiotemporal resolution. Under the joint mentorship from Professor Tzung Hsiai
(Mechanotransduction, UCLA), Professor Jau-Nian Chen (Developmental biology, UCLA) and Professor Debiao
Li (MR imaging, Cedars-Sinai Medical Center), I will continue to collaborate with Professor Atsushi Nakano
(Developmental biology, UCLA) and Dr. Adam Langenbacher (Developmental biology, UCLA), and consult with
Professor Joseph Wu (Cardiac stem cells, Stanford), Professor Sandra Rugonyi (Oregon Health & Science
University), Professor Linda Demer (Vascular biology, UCLA) to test our hypothesis. We hypothesize that neural
crest cells contribute to the ventricular myocardium and neural crest-derived cardiomyocytes are essential for
the contractile function and ventricular repair. To test this hypothesis, we will have three aims. In Aim 1, we will
elucidate the 4-D migration path of cardiac neural crest cell via SV-LSFM. In Aim 2, we will demonstrate 4-D
structure and function following cardiac neural crest cell contribution to the ventricular myocardium via DIAMOND.
In Aim 3, I will independently quantify the ventricular repair following the ablation of neural crest-derived
cardiomyocytes in zebrafish and mouse models with my collaborators. In this context, we believe that the
integration of genetic models with advanced imaging and computation will provide new mechanical and
developmental insights into the contribution of neural crest cells to contractile function and ventricular repair
under the regulation of Notch signaling pathway.
项目摘要 /摘要
整合成像和计算以表征心肌发育中的神经rest细胞
和再生
心脏神经rest细胞是从神经管中出现的高度迁移细胞的群体,迁移
通过咽弓并整合到发育中的心脏中。最近的进步表明
神经rest细胞的新亚种群具有整合到心脏腔中并分化的能力
进入斑马鱼和小鼠的心肌细胞。 Notch信号传导调节心肌细胞的增殖和
心室发育过程中的分化。尽管过去几十年中获得了知识,但
神经rest衍生的心肌细胞对收缩功能的贡献以及这些心肌细胞的作用
在Notch信号传导介导的心室重塑中仍然难以捉摸。斑马鱼胚胎中的小心脏大小
新生儿小鼠还阻碍了精确的心脏结构和功能评估。由于这些原因,我寻求
为了整合我们的高级成像(亚素分辨率灯页荧光显微镜,SV-LSFM)
计算(心肌机械变形的位移分析,钻石)以表征
神经衍生的心肌细胞对心肌发育的结构和功能贡献
并具有高时空分辨率的再生。在Tzung Hsiai教授的联合指导下
(加州大学洛杉矶分校的机械转移),Jau-Nian Chen教授(加州大学洛杉矶分校的发展生物学)和Debiao教授
李(雪松锡奈医学中心的成像先生),我将继续与nakano教授合作
(发育生物学,加州大学洛杉矶分校)和亚当·兰肯巴赫(Adam Langenbacher)博士(加州大学洛杉矶分校的发展生物学),并咨询
Joseph Wu教授(Stanford心脏干细胞),Sandra Rugonyi教授(俄勒冈州健康与科学
大学),琳达·德默(Linda Demer)教授(UCLA血管生物学),以检验我们的假设。我们假设该神经
波峰细胞有助于心室心肌和神经rest衍生的心肌细胞对
收缩功能和心室修复。为了检验这一假设,我们将有三个目标。在AIM 1中,我们将
通过SV-LSFM阐明心脏神经rest细胞的4-D迁移路径。在AIM 2中,我们将展示4-D
通过钻石对心室心肌的心脏神经rest细胞贡献后的结构和功能。
在AIM 3中,我将在消融神经rest衍生后独立量化心室修复
斑马鱼和小鼠模型中的心肌细胞与我的合作者。在这种情况下,我们相信
遗传模型与高级成像和计算的整合将提供新的机械和
对神经rest细胞对收缩功能和心室修复的贡献的发展见解
在Notch信号通路的调节下。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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{{ truncateString('Yichen Ding', 18)}}的其他基金
Volumetric imaging and computation to characterize cardiac electromechanical coupling
体积成像和计算来表征心脏机电耦合
- 批准号:
10629905 - 财政年份:2023
- 资助金额:
$ 24.66万 - 项目类别:
Integrating imaging and computation to characterize neural crest cells in the myocardial development and regeneration
整合成像和计算来表征心肌发育和再生中的神经嵴细胞
- 批准号:
10252944 - 财政年份:2020
- 资助金额:
$ 24.66万 - 项目类别:
Integrating imaging and computation to characterize neural crest cells in the myocardial development and regeneration
整合成像和计算来表征心肌发育和再生中的神经嵴细胞
- 批准号:
10471282 - 财政年份:2020
- 资助金额:
$ 24.66万 - 项目类别:
Integrating imaging and computation to characterize neural crest cells in the myocardial development and regeneration
整合成像和计算来表征心肌发育和再生中的神经嵴细胞
- 批准号:
9806864 - 财政年份:2019
- 资助金额:
$ 24.66万 - 项目类别:
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