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

基本信息

批准号：
10629905
负责人：
Yichen Ding
金额：
$ 38.39万
依托单位：
UNIVERSITY OF TEXAS DALLAS
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-04-15 至 2028-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10629905
关键词：
3-Dimensional Affect Amiodarone Anti-Arrhythmia Agents Antibiotics Antidepressive Agents Antiemetics Antifungal Agents Antineoplastic Agents Apical Arrhythmia Biological Models Bradycardia Calcium Calcium Signaling Cardiac Cardiac Myocytes Cell Nucleus Cells Clinical Collaborations Complication Computer Models Computing Methodologies Coupling Custom Developmental Biology Embryo Engineering Erythromycin Fertilization Fishes Fluoxetine Four-dimensional Functional disorder Genetic Genetic Models Goals Heart Heart Atrium Hour Human Image Individual Investigation Life Light Lighting Machine Learning Measures Mechanics Methodology Microscope Morphologic artifacts Motion Myocardial Myocardial Contraction Noise Patients Pattern Penetration Pentamidine Pharmaceutical Preparations Physicians Productivity Psychotropic Drugs Research Resolution Risk Factors Screening procedure Signal Transduction Sinus Structure TG gene Techniques Testing Time Transgenic Organisms Troponin T United States Variant Ventricular Work Zebrafish antimicrobial automated segmentation image processing imaging modality in vivo interest machine learning framework mutant prospective prototype response small molecule spatiotemporal success zebrafish development

项目摘要

PROJECT SUMMARY / ABSTRACT Volumetric imaging and computation to characterize cardiac electromechanical coupling Approximately 450,000 individuals in the United States die suddenly from cardiac arrhythmias every year. Many widely used medications such as antiarrhythmic agents, antimicrobials, anticancer drugs, and psychotropic drugs can cause or exacerbate a variety of arrhythmias. However, the fundamental mechanisms of most clinical arrhythmias remain poorly understood. The ability to prospectively identify potentially arrhythmogenic compounds would be clinically valuable. Recent advances demonstrate that zebrafish are a productive model system to screen small molecules that function as arrhythmic compounds in humans. However, much remains unknown about the involved excitation-contraction coupling abnormalities and mechanisms of arrhythmias associated with specific drugs. Despite the new zebrafish lines gained in past decades, technical difficulties including motion artifact, frame rate, penetration depth, and signal-to-noise ratio limits the in-depth investigation of aberrant calcium activities and contractile dysfunction. For this reason, we seek to integrate our 4-dimensional (4D, 3D spatial + 1D temporal) volumetric imaging with computational model to investigate whether a common mechanism of action underlies drug-induced excitation-contraction coupling abnormalities. In collaboration with Dr. Kelli Carroll (developmental biology), Dr. Catherine Makarewich (calcium signaling), and Dr. Jay Kuo (machine learning), we will test the hypothesis that small molecule-induced bradycardia activates distinct EC coupling abnormalities responsible for various arrhythmias. In Aim 1, we will reveal the 4D calcium activities across the intact heart with high spatiotemporal resolution via our custom-built structured-illumination light-field microscope. In Aim 2, we will elucidate the electromechanical interaction among neighboring cardiomyocytes during 5~10 cardiac cycles. In Aim 3, we will assess the excitation-contraction coupling abnormalities induced by small molecule compounds. In this context, success of this research will establish a new holistic strategy to in vivo investigate sophisticated electromechanical interaction, providing an entry point to further study the underlying mechanism of arrhythmias and prospectively identify arrhythmogenic compounds.

项目概要/摘要体积成像和计算来表征心脏机电耦合美国每年约有 45 万人死于心律失常。许多广泛使用的药物，如抗心律失常药、抗菌药、抗癌药和精神药物可引起或加剧多种心律失常。然而，大多数临床的基本机制心律失常仍然知之甚少。前瞻性识别潜在心律失常的能力化合物将具有临床价值。最近的进展表明斑马鱼是一种高效的模型筛选在人类中充当心律失常化合物的小分子的系统。然而，还有很多未知所涉及的兴奋-收缩耦合异常和心律失常的机制与特定药物有关。尽管在过去几十年中获得了新的斑马鱼品系，但技术困难包括运动伪影、帧速率、穿透深度和信噪比限制了深入研究异常的钙活性和收缩功能障碍。出于这个原因，我们寻求整合我们的 4 维（4D、3D 空间 + 1D 时间）体积成像与计算模型，以研究是否存在常见的作用机制是药物引起的兴奋-收缩耦合异常的基础。与合作 Kelli Carroll 博士（发育生物学）、Catherine Makarewich 博士（钙信号传导）和 Jay Kuo 博士（机器学习），我们将测试小分子诱导的心动过缓激活不同 EC 的假设耦合异常导致各种心律失常。在目标 1 中，我们将揭示 4D 钙活性通过我们定制的结构照明光场以高时空分辨率穿越完整的心脏显微镜。在目标 2 中，我们将阐明邻近心肌细胞之间的机电相互作用 5~10个心动周期。在目标 3 中，我们将评估诱发的兴奋-收缩耦合异常由小分子化合物组成。在此背景下，这项研究的成功将建立一个新的整体战略体内研究复杂的机电相互作用，为进一步研究提供了一个切入点心律失常的潜在机制并前瞻性地识别致心律失常的化合物。