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    The influence of different liquid environments on the atomic force microscopy detection of living bEnd.3 cells

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    Authors
    Jin, Yan
    Sun, Baishun
    Xie, Chenchen
    Liu, Yan
    Song, Zhengxun
    Xu, Hongmei
    Wang, Zuobin
    Affiliation
    Changchun University of Science and Technology
    University of Bedfordshire
    Issue Date
    2021-05-10
    Subjects
    atomic force microscopy
    
    Metadata
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    Abstract
    Atomic force microscopy (AFM) is one of the most important tools in the field of biomedical science, and it can be used to perform the high-resolution three-dimensional imaging of samples in liquid environments to obtain their physical properties (such as surface potentials and mechanical properties). The influence of the liquid environment on the image quality of the sample and the detection results cannot be ignored. In this work, quantitative imaging (QI) mode AFM imaging and mechanical detection were performed on mouse brain microvascular endothelial (bEnd.3) cells in different liquid environments. The gray-level variance product (SMD2) function was used to evaluate the imaging quality of the cells in liquids with different physical properties, and the variations in cell mechanical properties were quantitatively analyzed. An AFM detection liquid containing less ions and organics compared with the traditional culture medium, which is beneficial for improving the imaging quality, is introduced, and it shows similar mechanical detection results within 3 h. This can greatly reduce the detection costs and could have positive significance in the field of AFM living-cell detection.
    Citation
    Yan J, Sun B, Xie C, Liu Y, Song Z, Xu H, Wang Z (2021) 'The influence of different liquid environments on the atomic force microscopy detection of living bEnd.3 cells', Analytical Methods, (13), pp.2384-2390.
    Publisher
    Royal Society of Chemistry
    Journal
    Analytical Methods
    URI
    http://hdl.handle.net/10547/624975
    DOI
    10.1039/d1ay00567g
    PubMed ID
    33970977
    Additional Links
    https://pubs.rsc.org/en/content/articlelanding/2021/AY/D1AY00567G#!divAbstract
    Type
    Article
    Language
    en
    ISSN
    1759-9660
    EISSN
    1759-9679
    ae974a485f413a2113503eed53cd6c53
    10.1039/d1ay00567g
    Scopus Count
    Collections
    Computing

    entitlement

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