Deep Learning-Enhanced Potentiometric Aptasensing with Magneto-Controlled Sensors

doi:10.1002/anie.202210513

CORC > 烟台海岸带研究所 > 中国科学院烟台海岸带研究所 > 中科院海岸带环境过程与生态修复重点实验室

	Deep Learning-Enhanced Potentiometric Aptasensing with Magneto-Controlled Sensors
	Mou, Junsong 1,4; Ding, Jiawang 2,3,4; Qin, Wei 2,3,4
刊名	ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
	2022-12-13
页码	10
关键词	Aptamer Biosensor Deep Learning Magnetic Fields Potentiometry
ISSN号	1433-7851
DOI	10.1002/anie.202210513
通讯作者	Ding, Jiawang(jwding@yic.ac.cn)
英文摘要	Bioelectronic sensors that report charge changes of a biomolecule upon target binding enable direct and sensitive analyte detection but remain a major challenge for potentiometric measurement, mainly due to Debye Length limitations and the need for molecular-level platforms. Here, we report on a magneto-controlled potentiometric method to directly and sensitively measure the target-binding induced charge change of DNA aptamers assembled on magnetic beads using a polymeric membrane potentiometric ion sensor. The potentiometric responses of the negatively charged aptamer, serving as a receptor and reporter, were dynamically controlled and modulated by applying a magnetic field. Based on a potentiometric array, this non-equilibrium measurement technique combined with deep learning algorithms allows for rapidly and reliably classifying and quantifying diverse small molecules using antibiotics as models. This potentiometric strategy opens new modalities for sensing applications.
WOS关键词	HEPARIN ; POLYION ; ELECTRODES
WOS研究方向	Chemistry
语种	英语
WOS记录号	WOS:000897857500001
资助机构	National Natural Science Foundation of China ; Taishan Scholar Program of Shandong Province ; Instrument Developing Project of the Chinese Academy of Sciences ; Key Development Project of Centre for Ocean Mega-Research of Science, Chinese Academy of Sciences
内容类型	期刊论文
源URL	[http://ir.yic.ac.cn/handle/133337/32438]
专题	烟台海岸带研究所_中科院海岸带环境过程与生态修复重点实验室
通讯作者	Ding, Jiawang
作者单位	1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao 266071, Shandong, Peoples R China 3.Pilot Natl Lab Marine Sci & Technol Qingdao, Lab Marine Biol & Biotechnol, Qingdao 266237, Shandong, Peoples R China 4.Chinese Acad Sci, Yantai Inst Coastal Zone Res YIC, CAS Key Lab Coastal Environm Proc & Ecol Remediat, Shandong Key Lab Coastal Environm Proc, Yantai 264003, Shandong, Peoples R China
推荐引用方式 GB/T 7714	Mou, Junsong,Ding, Jiawang,Qin, Wei. Deep Learning-Enhanced Potentiometric Aptasensing with Magneto-Controlled Sensors[J]. ANGEWANDTE CHEMIE-INTERNATIONAL EDITION,2022:10.
APA	Mou, Junsong,Ding, Jiawang,&Qin, Wei.(2022).Deep Learning-Enhanced Potentiometric Aptasensing with Magneto-Controlled Sensors.ANGEWANDTE CHEMIE-INTERNATIONAL EDITION,10.
MLA	Mou, Junsong,et al."Deep Learning-Enhanced Potentiometric Aptasensing with Magneto-Controlled Sensors".ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2022):10.