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血小板驱动的界面肽纳米网络生物传感器的形成,实现了一种非侵入性的早期阿尔茨海默病检测方法。

Platelet-driven formation of interface peptide nano-network biosensor enabling a non-invasive means for early detection of Alzheimer's disease.

机构信息

Key Laboratory of Nuclear Medicine, Ministry of Health, Jiangsu Key Laboratory of Molecular Nuclear Medicine, Jiangsu Institute of Nuclear Medicine, Wuxi, Jiangsu, 214063, China.

Department of Biochemistry and Molecular Biology, Nanjing Medical University, Nanjing, 211166, Jiangsu, China.

出版信息

Biosens Bioelectron. 2019 Dec 1;145:111701. doi: 10.1016/j.bios.2019.111701. Epub 2019 Sep 13.

DOI:10.1016/j.bios.2019.111701
PMID:31541786
Abstract

Soft material fabricated with DNA origami or peptide cross-linking technique may be promising theranostic platforms in the future; however, their naturally occurring counterparts, such as the peptide aggregates in the neurodegenerative diseases, constitute an increasingly burdensome issue of public health. Thus, a design of artificial peptide nano-network biosensor is conceived, in an attempt to combat the natural pathological peptides, by mimicking their pathogenesis process. Specifically, periphery platelet can secrete A-beta and induce its cross-linking & aggregation to form a surface peptide nano-network, resulting in large numbers of poly-tyrosine strands being covalently trapped in the network to serve as an efficient signal amplifier, through the electrochemical oxidation of tyrosine. This method is sensitive and quantitative in the range of normal and pathological periphery platelet distribution and can effectively discriminate Alzheimer's disease (AD) patients based on the detected potential neurodegenerative activity of platelet. These results may point to some future perspective of this method in the early screening of AD.

摘要

采用 DNA 折纸或肽交联技术制造的软材料可能是未来有前途的治疗诊断平台;然而,它们的天然对应物,如神经退行性疾病中的肽聚集物,构成了日益严重的公共卫生问题。因此,设计了一种人工肽纳米网络生物传感器,试图通过模拟其发病过程来对抗天然病理肽。具体来说,血小板可以分泌 A-β并诱导其交联和聚集形成表面肽纳米网络,导致大量聚酪氨酸链通过酪氨酸的电化学氧化被共价捕获在网络中作为有效的信号放大器。该方法在正常和病理血小板分布范围内具有灵敏和定量的检测能力,并能根据血小板检测到的潜在神经退行性活性有效区分阿尔茨海默病 (AD) 患者。这些结果可能为该方法在 AD 的早期筛查中提供了一些未来的前景。

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