Fast and High-resolution Dynamic Mechanical Spectroscopy of Biological Cells

生物细胞的快速高分辨率动态机械光谱

• 批准号: 1435655
• 负责人: Igor Sokolov
• 金额: $ 40.81万
• 依托单位: Tufts University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2018-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1435655&HistoricalAwards=false
• 关键词: Fast; resolution; Dynamic; Mechanical; Spectroscopy

Dynamic mechanical spectroscopy allows measuring mechanical properties of materials at different speeds. It is a popular technique for studying soft material such as polymers. However, because of several intrinsic problems, this technique has not been extended to study the properties of biological cells as of yet. Besides fundamental interest, the study of cell mechanics makes a practical impact in understanding mechanical changes of cells in various diseases, like cancer, malaria, Alzheimer, and even aging. However, most cell studies were done for their static properties. While the changes in dynamic mechanical properties of cells are expected to be much richer, the existing attempts to measure cell dynamic properties have been very limited, and the results are controversial. This award supports fundamental research to provide knowledge needed for the development of a new quantitative technique to perform dynamic mechanical measurements of cells. The new method has the potential to revolutionize the study of cell mechanics. In general, it will also bring a new dimension to the study of the mechanics of biomaterials and nanocomposites at the nanoscale. It will expand the knowledge base to a scale of resolutions previously inaccessible. A translational part will include investigation of biomechanics of cancer cells. This application can build the foundation for nanomechanical applications in healthcare, which can benefit the U.S. society by saving billions of dollars through the early detection of cancer. The research will combine physics, biology, electronics, and nanotechnology. This multi-disciplinary approach will help broaden participation of underrepresented groups in research and positively impact mechanical and biomedical engineering education.Dynamic mechanical spectroscopy deals with the storage and loss moduli of materials which are the least model dependent quantities. While this method is standard for soft material, excessive time of measurements and low resolution preclude its use from obtaining reliable moduli on biological cells. In addition, cells are complex composite objects. This research will combine fast Fourier spectroscopy and atomic force microscopy to improve the speed and spatial resolution of dynamic mechanical spectroscopy. The improvement is expected to be more than 100x in speed and 100x in the resolution compared to the existing methods. The research team will apply this method to develop an appropriate viscoelastic cell model, in particular, taking into account pericellular brush, an important cellular organelle which dynamical mechanical properties are yet to be discovered. The obtained knowledge will be applied to study biomechanics of human cervical and breast cancer cells.

动态机械光谱允许以不同速度测量材料的机械性能。它是研究柔软材料（例如聚合物）的流行技术。但是，由于有几个固有的问题，该技术尚未扩展以研究生物细胞的特性。除了基本的兴趣外，对细胞力学的研究对理解各种疾病中细胞的力学变化（如癌症，疟疾，阿尔茨海默氏症甚至衰老）产生了实际影响。但是，大多数细胞研究都是针对其静态特性进行的。虽然预计细胞的动态机械性能的变化预计会更丰富，但现有的测量细胞动态特性的尝试非常有限，结果是有争议的。该奖项支持基础研究，以提供开发一种新的定量技术来执行细胞动态机械测量所需的知识。 新方法有可能彻底改变细胞力学的研究。通常，它还将为纳米级生物材料和纳米复合材料的力学带来新的维度。它将将知识库扩展到以前无法访问的一系列决议。翻译部分将包括研究癌细胞的生物力学。该应用程序可以为医疗保健中的纳米力学应用奠定基础，这可以通过通过早期发现癌症节省数十亿美元来使美国社会受益。该研究将结合物理，生物学，电子学和纳米技术。这种多学科的方法将有助于扩大代表性不足的群体参与研究中的参与，并积极影响机械和生物医学工程教育。基因动力学的机械光谱涉及材料的存储和损失模量，这是模型依赖性数量最小的材料。尽管该方法是软材料的标准配置，但测量时间过多，低分辨率排除了其在生物细胞上获得可靠模量的使用。另外，细胞是复杂的复合物体。这项研究将结合快速的傅立叶光谱和原子力显微镜，以提高动态机械光谱的速度和空间分辨率。与现有方法相比，该改进的速度将超过100倍，分辨率的改进将超过100倍。 研究团队将使用这种方法来开发适当的粘弹性细胞模型，特别是考虑到细胞细胞刷，这是一种重要的细胞细胞器，尚未发现动态机械性能。获得的知识将应用于研究人宫颈癌和乳腺癌细胞的生物力学。

项目成果

Can AFM be used to measure absolute values of Young's modulus of nanocomposite materials down to the nanoscale?

AFM 能否用于测量纳米复合材料杨氏模量的绝对值直至纳米尺度？

• DOI: 10.1039/d0nr02314k
• 发表时间: 2020-06-21
• 期刊: NANOSCALE
• 影响因子: 6.7
• 作者: Liu, Yuke;Sokolov, Igor;Peng, Ping'an
• 通讯作者: Peng, Ping'an