Mapping Drug-Induced Neuropathy through In-Situ Motor Protein Tracking and Machine Learning
Chong, Suet Yen
KAUST Grant NumberOSR-2018-CRG7-3736
Online Publication Date2021-09-01
Print Publication Date2021-09-15
Embargo End Date2022-09-01
Permanent link to this recordhttp://hdl.handle.net/10754/670900
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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.
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
SponsorsThis 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.
PublisherAmerican Chemical Society (ACS)