An Integrated, Portable, and Automatic Digital Detection System for Hepatitis B Virus Using Hybrid Magnetic System.

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL
Xiaoying Han, Juxin Yin, Yu Wang, Jianjian Zhuang, Kai Hu, Yehong Gui, Haohua Mei, Jizhi Tong, Ying Mu
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引用次数: 0

Abstract

The rapid, precise, and automated diagnosis of infectious diseases is crucial for effective disease management and control. Herein, the integrated portable and automatic digital detection system (IPADS), a novel diagnostic platform for nucleic acid detection is introduced. The device employs the hybrid magnetic system (HMS), which uses an electromagnet and a movable permanent magnet to modulate the magnetic field and control bead movement, increasing nucleic acid extraction efficiency to over 80%, while simplifying the traditional labor-intensive process and enabling quick, low-risk sample processing. Additionally, a disposable cartridge is designed for integrated HMS based preprocessing, with detection performed using digital RPA-Cas12a, enabling rapid, enclosed, and automation-friendly detection across a dynamic range spanning five orders of magnitude, with a sensitivity as low as 100 copies mL-1 in serum samples. An automated platform further optimizes workflow. As a proof of concept, IPADS is applied to detect hepatitis B virus (HBV) DNA in 20 clinical serum samples, demonstrating high concordance with gold-standard quantitative PCR (qPCR) methods. These results validate the potential of IPADS as a reliable point-of-care testing solution.

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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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