Author: Yeo, Seon-Ju; Kang, Homan; Dao, Tung Duy; Cuc, Bui Thi; Nguyen, Anh Thi Viet; Tien, Trinh Thi Thuy; Hang, Nguyen Le Khanh; Phuong, Hoang Vu Mai; Thanh, Le Thi; Mai, Le Quynh; Rah, Yoonhyuk; Yu, Kyoungsik; Shin, Ho-Joon; Chong, Chom-Kyu; Choi, Hak Soo; Park, Hyun
Title: Development of a smartphone-based rapid dual fluorescent diagnostic system for the simultaneous detection of influenza A and H5 subtype in avian influenza A-infected patients Cord-id: nzfq5a86 Document date: 2018_11_29
ID: nzfq5a86
Snippet: Accurate and rapid diagnosis of highly pathogenic avian influenza A H5N1 is of critical importance for the effective clinical management of patients. Here, we developed a rapid and simultaneous detection toolkit for influenza A H5 subtype viruses in human samples based on a bioconjugate of quantum dots (QDs) assembly and a smartphone-based rapid dual fluorescent diagnostic system (SRDFDS). Methods: Two types of QDs were assembled on a latex bead to enhance the detection sensitivity and specifici
Document: Accurate and rapid diagnosis of highly pathogenic avian influenza A H5N1 is of critical importance for the effective clinical management of patients. Here, we developed a rapid and simultaneous detection toolkit for influenza A H5 subtype viruses in human samples based on a bioconjugate of quantum dots (QDs) assembly and a smartphone-based rapid dual fluorescent diagnostic system (SRDFDS). Methods: Two types of QDs were assembled on a latex bead to enhance the detection sensitivity and specificity of influenza A infection (QD580) and H5 subtype (QD650). The dual signals of influenza A and H5 subtype of H5N1-infected patients were detected simultaneously and quantified separately by SRDFDS equipped with two emission filters. Results: Our results showed a high sensitivity of 92.86% (13/14) and 78.57% (11/14), and a specificity of 100% (38/38, P < 0.0001) and 97.37% (37/38) for influenza A and H5 subtype detection, respectively. Conclusion: Therefore, our multiplex QD bioconjugates and SRDFDS-based influenza virus detection toolkit potentially provide accurate and meaningful diagnosis information with improved detection accuracies and sensitivities for H5N1 patients.
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