Cloud-based High-throughput Acquisition and Analytics of Zebrafish Electrocardiogram for Cardiac Studies and Drug Development
Cloud-based High-throughput Acquisition and Analytics of Zebrafish Electrocardiogram for Cardiac Studies and Drug Development
批准号:
10248546
负责人:
Hung Cao
金额:
$76.94万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-08-15 至 2023-08-31
关键词:
AddressAdultAmiodaroneAnesthesia proceduresAnimal ModelAnimalsArrhythmiaAttentionBehavior assessmentBiologicalBiological ModelsBiomedical EngineeringCaliforniaCardiacCardiac Electrophysiologic TechniquesCardiac developmentCardiologyCardiomyopathiesCessation of lifeClientClinicClinical ResearchCollectionComplementCost SavingsDataData AnalysesData CollectionDetectionDevelopmentDevicesDiagnosticDiseaseDrug ScreeningEconomicsElectrocardiogramElectroencephalogramElectrophysiology (science)EmbryoEpilepsyExperimental ModelsFishesFundingGenerationsGenesGeneticGoalsGrantGuidelinesHeadHealthcareHeartHeart DiseasesHumanImmobilizationIndustryInstitutionInvestigationInvestigational DrugsLarvaLifeMachine LearningMaintenanceManualsMental disordersModelingMolecularMolecular BiologyMonitorNatural ProductsNatural regenerationNeurologicNeuropsychologyOpticsPainPatternPentylenetetrazolePharmaceutical PreparationsPharmacotherapyPhasePhenotypePhysiologicalPolymersProcessPsychological TransferResearchResearch InfrastructureSignal TransductionSmall Business Innovation Research GrantSmall Business Technology Transfer ResearchSocial BehaviorStreamSwimmingSystemSystems AnalysisSystems DevelopmentTechnologyTherapeuticTimeTractionTrainingTransgenic OrganismsUnited States National Institutes of HealthUniversitiesVariantVerapamilWireless TechnologyZebrafishaddictionautism spectrum disorderawakebasecloud basedcloud platformcommercializationcomputerized data processingcostcost effectivedata exchangedata managementdrug developmentevidence basegenetic approachgraphical user interfaceinnovationinterdisciplinary approachinterestlarge scale datamachine learning algorithmmortalitymutantnovelproduct developmentreal time monitoringresearch and developmentresearch studyscreeningtoolwireless communication
中文摘要
项目总结
英文摘要
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.
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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
影响因子:
--
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...
影响因子:
--
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
DOI:
10.3390/s22072788
发表时间:
2022-04-05
期刊:
Sensors (Basel, Switzerland)
影响因子:
--
作者:
[]
通讯作者:
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
共 7 条
Cloud-based High-throughput Acquisition and Analytics of Zebrafish Electrocardiogram for Cardiac Studies and Drug Development
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批准号:10080511
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项目类别:
-
资助金额:$76.94万
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财政年份:2018
-
负责人:Hung Cao
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依托单位:
海外基金