Cloud-based High-throughput Acquisition and Analytics of Zebrafish Electrocardiogram for Cardiac Studies and Drug Development

基于云的斑马鱼心电图高通量采集和分析，用于心脏研究和药物开发

• 批准号: 10248546
• 负责人: Hung Cao
• 金额: $ 76.94万
• 依托单位: SENSORIIS, INC.
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10248546
• 关键词: Address; Adult; Amiodarone; Anesthesia procedures; Animal Model; Animals; Arrhythmia; Attention; Behavior assessment; Biological; Biological Models; Biomedical Engineering; California; Cardiac; Cardiac Electrophysiologic Techniques; Cardiac development; Cardiology; Cardiomyopathies; Cessation of life; Client; Clinic; Clinical Research; Collection; Complement; Cost Savings; Data; Data Analyses; Data Collection; Detection; Development; Devices; Diagnostic; Disease; Drug Screening; Economics; Electrocardiogram; Electroencephalogram; Electrophysiology (science); Embryo; Epilepsy; Experimental Models; Fishes; Funding; Generations; Genes; Genetic; Goals; Grant; Guidelines; Head; Healthcare; Heart; Heart Diseases; Human; Immobilization; Industry; Institution; Investigation; Investigational Drugs; Larva; Life; Machine Learning; Maintenance; Manuals; Mental disorders; Modeling; Molecular; Molecular Biology; Monitor; Natural Products; Natural regeneration; Neurologic; Neuropsychology; Optics; Pain; Pattern; Pentylenetetrazole; Pharmaceutical Preparations; Pharmacotherapy; Phase; Phenotype; Physiological; Polymers; Process; Psychological Transfer; Research; Research Infrastructure; Signal Transduction; Small Business Innovation Research Grant; Small Business Technology Transfer Research; Social Behavior; Stream; Swimming; System; Systems Analysis; Systems Development; Technology; Therapeutic; Time; Traction; Training; Transgenic Organisms; United States National Institutes of Health; Universities; Variant; Verapamil; Wireless Technology; Zebrafish; addiction; autism spectrum disorder; awake; base; cloud based; cloud platform; commercialization; computerized data processing; cost; cost effective; data exchange; data management; drug development; evidence base; genetic approach; graphical user interface; innovation; interdisciplinary approach; interest; large scale data; machine learning algorithm; mortality; mutant; novel; product development; real time monitoring; research and development; research study; screening; tool; wireless communication

Project Summary Sensoriis, Inc is a company that, develops evidence-based sensing solutions to support biological investigations and address health care problems. The goal of this NIH SBIR Phase II grant with University of California Irvine is to provide novel systems to assess cardiac electrophysiology in zebrafish models, supporting heart disease studies and drug screening. Heart disease plagues the world as the leading cause of mortality. Cardiac arrhythmic diseases alone contributed about 350,000 deaths annually in the U.S. Although causative genes for some of them have been partially discovered, genetic basis for the majority remains poorly understood. The zebrafish (Dario rerio) model system is an important vertebrate experimental model owing to its small size, low-cost for maintenance, short generation time, amenable and conserved genetics, and optical transparency. Zebrafish have long been used as model system for understanding human cardiac development, disease, and regeneration. Further, zebrafish model enables a forward genetic approach to reveal the genetic basis and underlying molecular mechanisms of numerous heart diseases. Owing to the physiological similarities to humans’, zebrafish have also proven to be an ideal model system for drug screening. The conventional setup for cardiac phenotype acquisition in zebrafish (i.e. electrocardiogram – ECG) involves anesthesia causing variation in functionality. To date, there is no system which can offer cardiac phenotype monitoring in freely-swimming zebrafish, not to mention for multiple fish simultaneously. Further, data processing and analysis have been done manually, making it impossible to conduct large-scale studies. In this context, we propose to establish a long-term roadmap using multidisciplinary approaches to enable i) novel devices and systems to provide reliable ECG data of multiple fish (both adult fish and larvae) over a long period of time; ii) cloud-based systems to effectively process and interpret as well as study large-scale data; and iii) a host of cardiac studies as well as drug investigations using the zebrafish models and our novel tools.

项目摘要 Sensoriis，Inc是一家开发基于证据的传感解决方案的公司， 调查和解决保健问题。这项NIH SBIR第二阶段拨款的目标是与美国大学合作， 加州尔湾分校将提供新的系统来评估斑马鱼模型的心脏电生理学， 支持心脏病研究和药物筛选。 心脏病作为死亡的主要原因困扰着世界。仅心血管疾病 在美国，每年约有35万人死亡，尽管其中一些人的致病基因已经被发现， 部分发现，大多数的遗传基础仍然知之甚少。斑马鱼（Dario Rerio） 模型系统是一种重要的脊椎动物实验模型，具有体积小、维护成本低、 短世代时间，顺从和保守的遗传，和光学透明。长期以来， 用作了解人类心脏发育、疾病和再生的模型系统。此外，本发明的目的是， 斑马鱼模型使正向遗传学方法能够揭示遗传基础和潜在的分子生物学特征。 许多心脏病的机制。由于与人类的生理相似性，斑马鱼 也被证明是药物筛选的理想模型系统。 斑马鱼心脏表型采集（即心电图- ECG）的常规设置包括： 导致功能变化的麻醉。到目前为止，还没有一个系统可以提供心脏表型 监测自由游动的斑马鱼，更不用说同时监测多条鱼了。此外，数据 处理和分析都是手工进行的，因此无法进行大规模研究。 在这种情况下，我们建议使用多学科方法建立长期路线图，以实现i） 提供多条鱼（成鱼和幼鱼）长时间的可靠ECG数据的新设备和系统 ii）基于云的系统，以有效地处理和解释以及研究大规模数据; 以及iii）使用斑马鱼模型和我们的新工具进行的大量心脏研究以及药物研究。

项目成果

Deep learning-based framework for cardiac function assessment in embryonic zebrafish from heart beating videos.

• DOI: 10.1016/j.compbiomed.2021.104565
• 发表时间: 2021-08
• 期刊: Computers in biology and medicine
• 影响因子: 7.7
• 作者: Naderi AM;Bu H;Su J;Huang MH;Vo K;Trigo Torres RS;Chiao JC;Lee J;Lau MPH;Xu X;Cao H
• 通讯作者: Cao H

Investigation of Machine Learning and Deep Learning Approaches for Detection of Mild Traumatic Brain Injury from Human Sleep Electroencephalogram.

从人类睡眠脑电图中检测轻度创伤性脑损伤的机器学习和深度学习方法的研究。

• DOI: 10.1109/embc46164.2021.9630423
• 发表时间: 2021
• 期刊: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
• 作者: Vishwanath,Manoj;Jafarlou,Salar;Shin,Ikhwan;Dutt,Nikil;Rahmani,AmirM;Jones,CarolynE;Lim,MirandaM;Cao,Hung
• 通讯作者: Cao,Hung

Home-based mobile fetal/maternal electrocardiogram acquisition and extraction with cloud assistance.

• DOI: 10.1109/imbioc.2019.8777741
• 发表时间: 2019-05
• 期刊: The IEEE MTT-S 2019 International Microwave Biomedical Conference (IMBioC 2019) : proceedings : May 06-08, 2019, International Conference Hotel of Nanjing, Nanjing, China. IEEE MTT-S International Microwave Bio Conference (2019 : Nanjin...
• 作者: Le T;Fortunato J;Maritato N;Cho Y;Nguyen QD;Ghirmai T;Lau MPH;Han HD;Nguyen CK;Nguyen VC;Cao H
• 通讯作者: Cao H

Fetal Electrocardiogram Extraction from the Mother's Abdominal Signal Using the Ensemble Kalman Filter.

• DOI: 10.3390/s22072788
• 发表时间: 2022-04-05
• 期刊: Sensors (Basel, Switzerland)

A novel wireless ECG system for prolonged monitoring of multiple zebrafish for heart disease and drug screening studies.

• DOI: 10.1016/j.bios.2021.113808
• 发表时间: 2022-02-01
• 期刊: Biosensors & bioelectronics
• 影响因子: 12.6
• 作者: Le T;Zhang J;Nguyen AH;Trigo Torres RS;Vo K;Dutt N;Lee J;Ding Y;Xu X;Lau MPH;Cao H
• 通讯作者: Cao H