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    Mapping Drug-Induced Neuropathy through In-Situ Motor Protein Tracking and Machine Learning

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    Type
    Article
    Authors
    Yi, Zhigao cc
    Gao, Huxin
    Ji, Xianglin
    Yeo, Xin-Yi
    Chong, Suet Yen
    Mao, Yujie
    Luo, Baiwen
    Shen, Chao
    Han, Sanyang
    Wang, Jiong-Wei
    Jung, Sangyong
    Shi, Peng cc
    Ren, Hongliang
    Liu, Xiaogang cc
    KAUST Grant Number
    OSR-2018-CRG7-3736
    Date
    2021-09-01
    Online Publication Date
    2021-09-01
    Print Publication Date
    2021-09-15
    Embargo End Date
    2022-09-01
    Permanent link to this record
    http://hdl.handle.net/10754/670900
    
    Metadata
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    Abstract
    Chemotherapy can induce toxicity in the central and peripheral nervous systems and result in chronic adverse reactions that impede continuous treatment and reduce patient quality of life. There is a current lack of research to predict, identify, and offset drug-induced neurotoxicity. Rapid and accurate assessment of potential neuropathy is crucial for cost-effective diagnosis and treatment. Here we report dynamic near-infrared upconversion imaging that allows intraneuronal transport to be traced in real time with millisecond resolution, but without photobleaching or blinking. Drug-induced neurotoxicity can be screened prior to phenotyping, on the basis of subtle abnormalities of kinetic characteristics in intraneuronal transport. Moreover, we demonstrate that combining the upconverting nanoplatform with machine learning offers a powerful tool for mapping chemotherapy-induced peripheral neuropathy and assessing drug-induced neurotoxicity.
    Citation
    Yi, Z., Gao, H., Ji, X., Yeo, X.-Y., Chong, S. Y., Mao, Y., … Liu, X. (2021). Mapping Drug-Induced Neuropathy through In-Situ Motor Protein Tracking and Machine Learning. Journal of the American Chemical Society. doi:10.1021/jacs.1c07312
    Sponsors
    This work was supported by the Agency for Science, Technology and Research (A*STAR) (A1983c0038), the National Research Foundation, Prime Minister’s Office, Singapore, under the NRF Investigatorship program (Award No. NRF-NRFI05-2019-0003), the King Abdullah University of Science and Technology (KAUST) Office of Sponsored Research (OSR) under Award No. OSR-2018-CRG7-3736, the NUS NANONASH Program (NUHSRO/2020/002/NanoNash/LOA; R143000B43114), the Singapore Ministry of Health’s National Medical Research Council (NMRC/OFYIRG/0081/2018), and the National Natural Science Foundation of China (21771135, 21871071). S.Y.C. would like to thank the generous support from the ESR/TENG GL PhD scholarship program. We thank Akihiro Yamanaka, Angelo All, John Jia En Chua, Yinghua Qu, Liangliang Liang, Yuxia Liu, Sirui Liu, and Di Fu for helpful discussions.
    Publisher
    American Chemical Society (ACS)
    Journal
    Journal of the American Chemical Society
    DOI
    10.1021/jacs.1c07312
    Additional Links
    https://pubs.acs.org/doi/10.1021/jacs.1c07312
    ae974a485f413a2113503eed53cd6c53
    10.1021/jacs.1c07312
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