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基于智能手机的基于流型分析的纸微流控芯片上的盐水漱口样本中 SARS-CoV-2 的灵敏检测。

Smartphone-based sensitive detection of SARS-CoV-2 from saline gargle samples via flow profile analysis on a paper microfluidic chip.

机构信息

Department of Biomedical Engineering, The University of Arizona, Tucson, AZ, 85721, United States.

Department of Biosystems Engineering, The University of Arizona, Tucson, AZ, 85721, United States.

出版信息

Biosens Bioelectron. 2022 Jul 1;207:114192. doi: 10.1016/j.bios.2022.114192. Epub 2022 Mar 17.

Abstract

Respiratory viruses, especially coronaviruses, have resulted in worldwide pandemics in the past couple of decades. Saliva-based paper microfluidic assays represent an opportunity for noninvasive and rapid screening, yet both the sample matrix and test method come with unique challenges. In this work, we demonstrated the rapid and sensitive detection of SARS-CoV-2 from saliva samples, which could be simpler and more comfortable for patients than existing methods. Furthermore, we systematically investigated the components of saliva samples that affected assay performance. Using only a smartphone, an antibody-conjugated particle suspension, and a paper microfluidic chip, we made the assay user-friendly with minimal processing. Unlike the previously established flow rate assays that depended solely on the flow rate or distance, this unique assay analyzes the flow profile to determine infection status. Particle-target immunoagglutination changed the surface tension and subsequently the capillary flow velocity profile. A smartphone camera automatically measured the flow profile using a Python script, which was not affected by ambient light variations. The limit of detection (LOD) was 1 fg/μL SARS-CoV-2 from 1% saliva samples and 10 fg/μL from simulated saline gargle samples (15% saliva and 0.9% saline). This method was highly specific as demonstrated using influenza A/H1N1. The sample-to-answer assay time was <15 min, including <1-min capillary flow time. The overall accuracy was 89% with relatively clean clinical saline gargle samples. Despite some limitations with turbid clinical samples, this method presents a potential solution for rapid mass testing techniques during any infectious disease outbreak as soon as the antibodies become available.

摘要

呼吸道病毒,尤其是冠状病毒,在过去几十年中引发了全球大流行。基于唾液的纸微流控分析代表了一种非侵入性和快速筛查的机会,但样本基质和测试方法都带来了独特的挑战。在这项工作中,我们展示了从唾液样本中快速灵敏地检测 SARS-CoV-2 的方法,与现有方法相比,这种方法对患者来说可能更简单、更舒适。此外,我们系统地研究了影响分析性能的唾液样本成分。仅使用智能手机、抗体偶联的粒子悬浮液和纸微流控芯片,我们通过最小的处理使分析变得用户友好。与之前仅依赖流速或距离的建立的流速分析方法不同,这种独特的分析方法通过分析流型来确定感染状态。粒子靶向免疫凝集改变了表面张力,进而改变了毛细管流动速度分布。智能手机相机使用 Python 脚本自动测量流动分布,不受环境光变化的影响。该方法的检测限(LOD)为 1%唾液样本中的 1 fg/μL SARS-CoV-2 和模拟盐水漱口样本中的 10 fg/μL(15%唾液和 0.9%盐水)。该方法具有高度特异性,如使用甲型流感病毒/ H1N1 所证明的那样。从样本到获得结果的分析时间<15 分钟,包括<1 分钟的毛细管流动时间。对于相对干净的临床盐水漱口样本,总体准确率为 89%。尽管临床混浊样本存在一些局限性,但一旦获得抗体,该方法就为任何传染病爆发期间的快速大规模测试技术提供了一种潜在的解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a7d/8926431/f4ed4b3e5c6b/gr1_lrg.jpg

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