A Highly Specific Point-of-Care Rapid Real-time Sensing Device for COVID-19

摘要 自美国（美国）报告首例COVID-19病例以来，本集团已于二零二零年十二月三十一日（星期四）开始对COVID-19进行评估。2020年1月21日， 已确定影响> 90万例活动病例，死亡> 5万例。目前，COVID-19正在被诊断为 主要通过三种技术，即逆转录聚合酶链反应（RT-PCR）、基因工程（PCR）和基因工程（PCR）， 测序和胸部计算机断层扫描（CT）。然而，样本收集的局限性和 运输，以及工具包的性能与先进的仪器技术不足，往往 不能在最初出现时报告COVID-19，导致这种传染病传播到更广泛的地区， 社区此外，研究人员还发现了至少三种中心变异，它们可以通过氨基酸来区分。 在160个不同的完整的人类SARS-CoV-2基因组序列中，这限制了普遍性 目前可用的商业COVID-19试剂盒的适用性。在这个建议中，我们提出了一种新的方法， 用于使用电化学定量生物传感器筛查活动性COVID-19病例。这种独特的方法 用于选择性传感SARS-CoV-2消除了由于基因组 这种病毒的变体是目前COVID-19传感试剂盒最令人担忧的限制。我们 预期我们的传感器可以检测特定的靶核酸序列，而没有信号串扰， 检测极限为约50 fg/ml，响应时间为约2-3分钟。

ABSTRACT Since the first case of COVID-19 was reported in the United States (U.S.) on January 21st, 2020, it has already been ascertained to affect >900K active cases with >50K deaths. Currently, COVID-19 is being diagnosed primarily by three techniques, i.e. reverse-transcription polymerase chain reaction (RT-PCR), gene sequencing and chest computed tomography (CT). However, limitations of sample collection and transportation, as well as kit performance with inadequate access to advanced instrumental techniques, often cannot report COVID-19 at its initial presentation leading to the spread of this infectious disease to a wider community. Moreover, researchers found at least three central variants, distinguishable by amino acid changes, among 160 different complete human SARS-CoV-2 genome sequences. This limits the universal applicability of the currently available commercial COVID-19 kits. In this proposal we present a novel approach for screening of active COVID-19 cases with an electrochemical quantitative biosensor. This unique approach for selective sensing of SARS-CoV-2 eliminates the possibility of misinterpretation arisen due to the genomic variants of this virus which is the most concerning limitation of the current COVID-19 sensing kits. We anticipate that our sensor can detect the specific target nucleic acid sequences without signal cross talk with a detection limit to be around 50 fg/ml with time of response to be around 2-3 mins.