Multiplex Identification of Post-Translational Modifications at Point-of-Care by Deep Learning-Assisted Hydrogel Sensors |
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Authors: | Dr Junjie Qin Dr Jia Guo Dr Guanghui Tang Prof?Dr Lin Li Prof?Dr Shao Q Yao |
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Institution: | 1. Department of Chemistry, National University of Singapore, Singapore, 117543 Singapore;2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, 639798 Singapore;3. The Institute of Flexible Electronics (IFE, Future Technologies), Xiamen University, Xiamen, 361005, Fujian China |
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Abstract: | Multiplex detection of protein post-translational modifications (PTMs), especially at point-of-care, is of great significance in cancer diagnosis. Herein, we report a machine learning-assisted photonic crystal hydrogel (PCH) sensor for multiplex detection of PTMs. With closely-related PCH sensors microfabricated on a single chip, our design achieved not only rapid screening of PTMs at specific protein sites by using only naked eyes/cellphone, but also the feasibility of real-time monitoring of phosphorylation reactions. By taking advantage of multiplex sensor chips and a neural network algorithm, accurate prediction of PTMs by both their types and concentrations was enabled. This approach was ultimately used to detect and differentiate up/down regulation of different phosphorylation sites within the same protein in live mammalian cells. Our developed method thus holds potential for POC identification of various PTMs in early-stage diagnosis of protein-related diseases. |
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Keywords: | Machine Learning Multiplex Detection Photonic Crystal Hydrogel Point-of-Care Post-Translational Modifications |
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