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Wearable Aiegens-Based Lateral Flow Test Strip for Rapid Detection of SARS-CoV-2 N Protein and BRD Protein (preprint)
ssrn; 2021.
Preprint in English | PREPRINT-SSRN | ID: ppzbmed-10.2139.ssrn.3956662
ABSTRACT
\Accurate and rapid detection of SARS-CoV-2 is significant for early tracing, isolating and treating the infected patients, which will efficiently prevent the virus large-scale spread from human to human. In this paper, two kinds of novel quantitative lateral flow test strip for N and RBD antigens of SARS-CoV-2 were established with high sensitivity, which utilize AIE luminogens (AIEgens) as reporter. Because of the high brightness and resistance of quenching property in aqueous of the AIEgens, the limit of detection of 7.2 ng/mL for N protein and 6.9 ng/mL for RBD protein could be achieved with the AIEgens-based lateral flow test strip. Furthermore, it was negative for other protein or antigen samples assay, which demonstrated the great specificity of the test strategy. A N95 mask equipped with the test strip was designed to employ as the antigen collector with excellent enrichment effect. Compared with the other two test strips based on the Au nanoparticle and FITC, the well-designed AIEgens-based lateral flow test strip presented high sensitivity and excellent anti-interference capacity in complex bio-samples. Furthermore, the AIEgens-based lateral flow test strip assay could be built as a promising platform for the emergency usage at pandemic.

Funding:

This work was supported by the NSFC (51961160730, 51873092, and 81921004), the National Key R&D Program of China (Intergovernmental Cooperation Project, 2017YFE0132200), the Fundamental Research Funds for the Central Universities, and the Tianjin Science Fund for Distinguished Young Scholars (19JCJQJC61200).Declaration of Interests The authors declare no competing interests.

Full text: Available Collection: Preprints Database: PREPRINT-SSRN Language: English Year: 2021 Document Type: Preprint

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Full text: Available Collection: Preprints Database: PREPRINT-SSRN Language: English Year: 2021 Document Type: Preprint