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
• 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
• 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

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.

项目总结/摘要 表征心脏机电耦合的体积成像和计算 美国每年约有45万人死于心律失常。许多 广泛使用的药物，如抗肿瘤药、抗微生物药、抗癌药和精神药物 会导致或加重多种心律失常。然而，大多数临床疾病的基本机制 心律失常仍然知之甚少。前瞻性识别潜在致瘤性的能力 这些化合物将具有临床价值。最近的进展表明，斑马鱼是一种生产模式， 该系统用于筛选在人体中起药物作用的小分子。然而， 涉及的兴奋-收缩偶联异常和心律失常机制未知 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， 包括运动伪影、帧速率、穿透深度和信噪比限制了深入研究 钙离子活动异常和收缩功能障碍因此，我们寻求整合我们的四维 (4D 3D空间+ 1D时间）体积成像，以研究是否存在常见的 作用机制是药物诱导的兴奋-收缩偶联异常的基础。协同 博士Kelli卡罗尔（发育生物学）、Catherine Makarewich博士（钙信号）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， 显微镜在目标2中，我们将阐明相邻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，我们将评估由神经元诱发的兴奋-收缩偶联异常。 小分子化合物。在这种情况下，这项研究的成功将建立一个新的整体战略， 在体内研究复杂的机电相互作用，提供了一个切入点，以进一步研究 心律失常的潜在机制，并前瞻性地识别致心律失常化合物。