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基于编程 M13 噬菌体的仿生选择性电子鼻的神经机制。

Neural mechanism mimetic selective electronic nose based on programmed M13 bacteriophage.

机构信息

Bio-IT Fusion Technology Research Institute, Pusan National University, Busan, 46241, South Korea; School of Nano Convergence Technology, Hallym University, Chuncheon, Gangwon-do, 24252, South Korea.

Bio-IT Fusion Technology Research Institute, Pusan National University, Busan, 46241, South Korea.

出版信息

Biosens Bioelectron. 2022 Jan 15;196:113693. doi: 10.1016/j.bios.2021.113693. Epub 2021 Oct 6.

DOI:10.1016/j.bios.2021.113693
PMID:34700263
Abstract

The electronic nose is a reliable practical sensor device that mimics olfactory organs. Although numerous studies have demonstrated excellence in detecting various target substances with the help of ideal models, biomimetic approaches still suffer in practical realization because of the inability to mimic the signal processing performed by olfactory neural systems. Herein, we propose an electronic nose based on the programable surface chemistry of M13 bacteriophage, inspired by the neural mechanism of the mammalian olfactory system. The neural pattern separation (NPS) was devised to apply the pattern separation that operates in the memory and learning process of the brain to the electronic nose. We demonstrate an electronic nose in a portable device form, distinguishing polycyclic aromatic compounds (harmful in living environment) in an atomic-level resolution (97.5% selectivity rate) for the first time. Our results provide practical methodology and inspiration for the second-generation electronic nose development toward the performance of detection dogs (K9).

摘要

电子鼻是一种可靠的实用传感器设备,模拟嗅觉器官。尽管许多研究已经证明了在理想模型的帮助下检测各种目标物质的卓越性能,但仿生方法在实际实现中仍然存在困难,因为无法模拟嗅觉神经系统执行的信号处理。在这里,我们提出了一种基于 M13 噬菌体可编程表面化学的电子鼻,灵感来自于哺乳动物嗅觉系统的神经机制。神经模式分离(NPS)被设计用来将在大脑的记忆和学习过程中起作用的模式分离应用于电子鼻。我们首次以便携式设备的形式展示了一种电子鼻,能够以原子级分辨率(97.5%的选择性率)区分多环芳烃(生活环境中的有害物质)。我们的结果为第二代电子鼻的发展提供了实用的方法和灵感,以实现检测犬(K9)的性能。

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