Mapping Drug-Induced Neuropathy through In-Situ Motor Protein Tracking and Machine Learning
Zhigao Yi, Huxin Gao, Xianglin Ji, Xin Yi Yeo, Suet Yen Chong, Yujie Mao, Baiwen Luo, Chao Shen, Sanyang Han, Jiong‐Wei Wang, Sangyong Jung, Peng Shi, Hongliang Ren, Xiaogang Liu
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.