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dc.contributor.authorYi, Zhigao
dc.contributor.authorGao, Huxin
dc.contributor.authorJi, Xianglin
dc.contributor.authorYeo, Xin-Yi
dc.contributor.authorChong, Suet Yen
dc.contributor.authorMao, Yujie
dc.contributor.authorLuo, Baiwen
dc.contributor.authorShen, Chao
dc.contributor.authorHan, Sanyang
dc.contributor.authorWang, Jiong-Wei
dc.contributor.authorJung, Sangyong
dc.contributor.authorShi, Peng
dc.contributor.authorRen, Hongliang
dc.contributor.authorLiu, Xiaogang
dc.date.accessioned2021-09-02T06:19:36Z
dc.date.available2021-09-02T06:19:36Z
dc.date.issued2021-09-01
dc.identifier.citationYi, 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
dc.identifier.issn0002-7863
dc.identifier.issn1520-5126
dc.identifier.doi10.1021/jacs.1c07312
dc.identifier.urihttp://hdl.handle.net/10754/670900
dc.description.abstractChemotherapy 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.
dc.description.sponsorshipThis 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.
dc.publisherAmerican Chemical Society (ACS)
dc.relation.urlhttps://pubs.acs.org/doi/10.1021/jacs.1c07312
dc.rightsThis document is the Accepted Manuscript version of a Published Work that appeared in final form in Journal of the American Chemical Society, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/10.1021/jacs.1c07312.
dc.titleMapping Drug-Induced Neuropathy through In-Situ Motor Protein Tracking and Machine Learning
dc.typeArticle
dc.identifier.journalJournal of the American Chemical Society
dc.rights.embargodate2022-09-01
dc.eprint.versionPost-print
dc.contributor.institutionDepartment of Chemistry, National University of Singapore, Singapore 117543, Singapore
dc.contributor.institutionCenter for Functional Materials, National University of Singapore Suzhou Research Institute, Suzhou 215123, People’s Republic of China
dc.contributor.institutionDepartment of Biomedical Engineering, National University of Singapore, Singapore 117583, Singapore
dc.contributor.institutionDepartment of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong SAR 999077, People’s Republic of China
dc.contributor.institutionInstitute of Molecular and Cell Biology (IMCB), Agency for Science, Technology and Research (A*STAR), Singapore 138667, Singapore
dc.contributor.institutionDepartment of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117593, Singapore
dc.contributor.institutionDepartment of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore
dc.contributor.institutionCardiovascular Research Institute (CVRI), National University Heart Centre Singapore (NUHCS), Singapore 117599, Singapore
dc.contributor.institutionThe N1 Institute for Health, National University of Singapore, Singapore 117456, Singapore
dc.contributor.institutionCollege of Biology and Environmental Engineering, Zhejiang Shuren University, Hangzhou 310015, People’s Republic of China
dc.contributor.institutionThe Chinese University of Hong Kong (CUHK) Robotics Institute, Shatin, Hong Kong 999077, People’s Republic of China
dc.contributor.institutionJoint School of National University of Singapore and Tianjin University, International Campus of Tianjin University, Binhai New City, Fuzhou 350207, People’s Republic of China
kaust.grant.numberOSR-2018-CRG7-3736
kaust.acknowledged.supportUnitCRG
kaust.acknowledged.supportUnitOffice of Sponsored Research (OSR)
dc.date.published-online2021-09-01
dc.date.published-print2021-09-15


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