Platform for high-throughput biomechanical measurements using metallic islands on boron nitride nanosheets
Platform for high-throughput biomechanical measurements using metallic islands on boron nitride nanosheets
批准号:
10158533
负责人:
Darren J Lipomi
金额:
$18.25万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-06-01 至 2023-05-31
关键词:
AlgorithmsAnimalsArrhythmiaAwardBenchmarkingBiological AssayBiomechanicsBiomedical EngineeringBoronCancer PatientCardiac MyocytesCardiomyopathiesCardiotoxicityCardiovascular systemCellsCellular biologyCessation of lifeClassificationClinicalDataData SetDetectionDevelopmentDevicesDilated CardiomyopathyDiseaseDisease modelDrug CompoundingDrug ScreeningElectrical ResistanceEngineeringEvaluationFailureFunctional disorderHealthHeartHeart DiseasesHeart failureHumanHuman BiologyHypertrophic CardiomyopathyIndividualIslandKineticsMapsMeasurementMeasuresMechanicsMedicineMembraneMethodsModelingMutationMyopathyOpticsOutcomePatientsPharmaceutical PreparationsPhenotypePlayProcessProteinsRelaxationRoleSarcomeresSignal TransductionSolidTestingTimeTissue EngineeringTrainingUnited States National Institutes of HealthUniversitiesUrsidae Familyanalogbasebiomaterial compatibilitycellular engineeringchemotherapydesigndetection limitdrug developmentdrug discoveryexperiencefunctional genomicshigh throughput analysisimprovedinduced pluripotent stem cellinnovationinstrumentationmachine learning algorithmmechanical forcemechanical propertiesmetallicitynanonanofabricationresponsesensorstem cellstherapeutic targettool
中文摘要
总结
该提案描述了一种新的平台,用于高通量测量细胞中的机械现象。
该平台基于一种应变传感器,其包括由六方硼支撑的金属纳米岛
氮化物机械变形会引起电阻和光学散射的变化
这些传感器。这些过程允许检测≤1 ppm(≤0.0001%应变)的变形。这
前所未有的灵敏度允许测量细胞产生的微小力,
使用现有方法测量,并且可以使用机器学习快速分析电信号
算法虽然这种传感器在细胞生物学中具有广泛的潜在应用,但我们将其应用于
在心血管医学和药物发现中普遍存在的挑战。特别是,
心肌细胞的损伤与一系列难以治疗的心肌病有关。在药物发现中,心脏毒性
(肌病、心律失常或两者兼有)是药物在开发和售后市场失败的主要原因
发射对于某些类别的药物-特别是那些用于化疗-高达30%的患者的经验
与治疗有关的心脏病。事实上,心力衰竭是第二个最常见的死亡原因,
癌症患者。目前还没有既能预测心脏毒性又能充分预测
在药物开发早期实现的生产量(即,当更安全的药物先导可以选择,
类似物)。我们建议使用具有诱导性多能干细胞来源的心肌细胞(iPSC-CM),
各种疾病相关的突变作为我们的纳米生物力学传感器的测试案例。特别是,
我们将构建一个基于“96孔”板格式的阵列,并结合高通量分析,
专门设计的机器学习算法,以测量收缩力和动力学,
细胞这样的平台将能够大规模评估疾病机制,并加速治疗。
通过允许高通量、无偏倚的测试来发现目标。这个应用程序提供了令人兴奋的可能性
将人类心脏生物学的各个方面引入发现管道的早期。更广泛地说,平台
我们描述了提供了回答关于细胞中机械现象的深层问题的潜力-“
“机械组”-在人类健康中发挥关键作用。
英文摘要
SUMMARY
This proposal describes a new platform for high-throughput measurement of mechanical phenomena in cells.
The platform is based on a type of strain sensor comprising metallic nanoislands supported by hexagonal boron
nitride. Mechanical deformation produces a change in both the electrical resistance and the optical scattering of
these sensors. These processes allow the detection of deformations ≤1 ppm (≤0.0001% strain). This
unprecedented level of sensitivity permits the measurement of minute forces produced by cells that cannot be
measured using existing methods, and the electrical signals can be analyzed rapidly using machine-learning
algorithms. While this sensor has a broad range of potential applications in cell biology, we apply it here to a
ubiquitous challenge in cardiovascular medicine and drug discovery. In particular, contractile dysfunction in
cardiomyocytes is associated with a range of difficult-to-treat cardiomyopathies. In drug discovery, cardiotoxicity
(myopathy, arrhythmia, or both) is a leading reason for the failure of drugs during development and aftermarket
launch. For some classes of drugs—especially those used in chemotherapy—up to 30% of patients experience
heart disease related to their treatment. Indeed, heart failure is the second most common reason for death of
cancer patients. There are currently no assays that are both predictive of cardiotoxicity and are of sufficient
throughput to implement early in drug development (i.e., when safer drug leads can be selected among
analogues). We propose the use of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) bearing
various disease-associated mutations as a test case of our nano-enabled biomechanical sensor. In particular,
we will construct an array based on a “96-well” plate format combined with high-throughput analysis using a
purpose-designed machine learning algorithm in order to measure the forces and kinetics of contractility of the
cells. Such a platform would enable large-scale evaluation of disease mechanisms and accelerate therapeutic
target discovery by permitting high-throughput, unbiased testing. This application offers the exciting possibility
of introducing aspects of the biology of the human heart early in the discovery pipeline. More broadly, the platform
we describe offers the potential of answering deep questions about mechanical phenomena in cells—“the
mechanome”—which play critical roles in human health.
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会议论文
Stretchable, Biodegradable, and Self-Healing Semiconductors for Wearable and Implantable Sensors
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批准号:8954687
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项目类别:
-
资助金额:$219.33万
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财政年份:2015
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负责人:Darren J Lipomi
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依托单位:
Stretchable, Biodegradable, and Self-Healing Semiconductors for Wearable and Implantable Sensors
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批准号:9980002
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项目类别:
-
资助金额:$47.25万
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财政年份:2015
-
负责人:Darren J Lipomi
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依托单位:
海外基金