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Platform for high-throughput biomechanical measurements using metallic islands on boron nitride nanosheets

使用氮化硼纳米片上的金属岛进行高通量生物力学测量的平台

基本信息

批准号：
10158533
负责人：
Darren J Lipomi
金额：
$ 18.25万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-06-01 至 2023-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10158533
关键词：
Algorithms Animals Arrhythmia Award Benchmarking Biological Assay Biomechanics Biomedical Engineering Boron Cancer Patient Cardiac Myocytes Cardiomyopathies Cardiotoxicity Cardiovascular system Cells Cellular biology Cessation of life Classification Clinical Data Data Set Detection Development Devices Dilated Cardiomyopathy Disease Disease model Drug Compounding Drug Screening Electrical Resistance Engineering Evaluation Failure Functional disorder Health Heart Heart Diseases Heart failure Human Human Biology Hypertrophic Cardiomyopathy Individual Island Kinetics Maps Measurement Measures Mechanics Medicine Membrane Methods Modeling Mutation Myopathy Optics Outcome Patients Pharmaceutical Preparations Phenotype Play Process Proteins Relaxation Role Sarcomeres Signal Transduction Solid Testing Time Tissue Engineering Training United States National Institutes of Health Universities Ursidae Family analog base biomaterial compatibility cellular engineering chemotherapy design detection limit drug development drug discovery experience functional genomics high throughput analysis improved induced pluripotent stem cell innovation instrumentation machine learning algorithm mechanical force mechanical properties metallicity nano nanofabrication response sensor stem cells therapeutic target tool

项目摘要

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.

总结