Double-Coffee Ring Nanoplasmonic Effects with Convolutional Neural Learning for Sars-Cov-2 Detection

Kamyar Behrouzi, Liwei Lin
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Abstract

We develop a sensing method based on the double-coffee ring phenomenon for the first time using localized surface plasmon resonance (LSPR) effect in gold nanoparticles (GNPs) to detect SARS-CoV-2 Nucleocapsid proteins with high sensitivity. Testing images are further analyzed via the convolutional neural learning for enhanced accuracy. The circular-shape hydrophilic PTFE porous membrane with a hydrophobic ring barrier is utilized as the sensing platform. When the virus proteins are interacting with antibody coated GNPs solution on the platform, a double-coffee ring image is observed and the convolutional neural network helps the differentiation for the first small protein-GNPs ring at the center and a second non-specific ring at the hydrophobic barrier. We use this double-coffee ring to detect viral infection and quantify the concentration of COVID-19 viruses in 5 ng/ml (LOD), similar to Abbott BinaxNOW® testing kit, to 1000 ng/ml. As such this detection scheme could open up a new class of biomolecular research in the field of micro/nano fluidics.
基于卷积神经学习的双咖啡环纳米等离子体效应检测Sars-Cov-2
本文首次利用金纳米粒子(GNPs)的局部表面等离子体共振(LSPR)效应,建立了一种基于双咖啡环现象的传感方法,以高灵敏度检测SARS-CoV-2核衣壳蛋白。通过卷积神经学习进一步分析测试图像,提高准确性。采用带疏水环屏障的圆形亲水性聚四氟乙烯多孔膜作为传感平台。当病毒蛋白与抗体包被的GNPs溶液在平台上相互作用时,观察到双咖啡环图像,卷积神经网络帮助区分中心的第一个小蛋白-GNPs环和疏水屏障处的第二个非特异性环。我们使用这种双咖啡环检测病毒感染,并将5 ng/ml (LOD)中COVID-19病毒的浓度(类似于雅培BinaxNOW®检测试剂盒)量化为1000 ng/ml。因此,该检测方案可以在微纳流体领域开辟一个新的生物分子研究类别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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