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    A massively multi-scale approach to characterizing tissue architecture by synchrotron micro-CT applied to the human placenta

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    Authors
    Tun, Win Min
    Poologasundarampillai, Gowsihan
    Bischof, H.
    Nye, Gareth
    King, Oliver N. F.
    Basham, Mark
    Tokudome, Y.
    Lewis, Rohan M.
    Johnstone, E. D.
    Brownbill, Paul
    Darrow, Michele
    Chernyavsky, Igor
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    Publication Date
    2021-06-02
    Submitted date
    2021-02-16
    
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    Abstract
    Multi-scale structural assessment of biological soft tissue is challenging but essential to gain insight into structure–function relationships of tissue/organ. Using the human placenta as an example, this study brings together sophisticated sample preparation protocols, advanced imaging and robust, validated machine-learning segmentation techniques to provide the first massively multi-scale and multi-domain information that enables detailed morphological and functional analyses of both maternal and fetal placental domains. Finally, we quantify the scale-dependent error in morphological metrics of heterogeneous placental tissue, estimating the minimal tissue scale needed in extracting meaningful biological data. The developed protocol is beneficial for high-throughput investigation of structure–function relationships in both normal and diseased placentas, allowing us to optimize therapeutic approaches for pathological pregnancies. In addition, the methodology presented is applicable in the characterization of tissue architecture and physiological behaviours of other complex organs with similarity to the placenta, where an exchange barrier possesses circulating vascular and avascular fluid spaces.
    Citation
    Tun W. M., Poologasundarampillai G., Bischof H., Nye G., King O. N. F., Basham M., Tokudome Y., Lewis R. M., Johnstone E. D., Brownbill P., Darrow M. and Chernyavsky I. L. (2021). A massively multi-scale approach to characterizing tissue architecture by synchrotron micro-CT applied to the human placentaJ. Journal of the Royal Society Interface, 18(179), 20210140 http://doi.org/10.1098/rsif.2021.0140
    Publisher
    The Royal Society
    URI
    http://hdl.handle.net/10034/624809
    DOI
    10.1098/rsif.2021.0140
    Type
    article
    Description
    From The Royal Society via Jisc Publications Router
    History: received 2021-02-16, accepted 2021-05-06, collection 2021-06, pub-electronic 2021-06-02
    Article version: VoR
    Publication status: Published
    Funder: Engineering and Physical Sciences Research Council; Id: http://dx.doi.org/10.13039/501100000266; Grant(s): EP/M023877/1, EP/T008725/1
    Funder: Medical Research Council; Id: http://dx.doi.org/10.13039/501100000265; Grant(s): MR/N011538/1
    Funder: Wellcome Trust; Id: http://dx.doi.org/10.13039/100004440; Grant(s): 212980/Z/18/Z
    Funder: Great Britain Sasakawa Foundation; Id: http://dx.doi.org/10.13039/501100000625
    ae974a485f413a2113503eed53cd6c53
    10.1098/rsif.2021.0140
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    Chester Medical School

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