Wireless, battery-free, multifunctional integrated bioelectronics for respiratory pathogens monitoring and severity evaluation
The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, r...
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| Veröffentlicht in: | Nature communications Jg. 14; H. 1; S. 7539 - 13 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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London
Nature Publishing Group UK
20.11.2023
Nature Publishing Group Nature Portfolio |
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| ISSN: | 2041-1723, 2041-1723 |
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| Abstract | The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections.
The SARS-CoV-2 pandemic highlighted our need for methods that allow rapid viral surveillance. Here, authors report a wireless, battery-free and wearable self-diagnosis platform that can continuously capture viral particles, diagnose infection status and evaluate symptom severity via breath and blow. |
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| AbstractList | Abstract The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections. The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections. The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections. The SARS-CoV-2 pandemic highlighted our need for methods that allow rapid viral surveillance. Here, authors report a wireless, battery-free and wearable self-diagnosis platform that can continuously capture viral particles, diagnose infection status and evaluate symptom severity via breath and blow. The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections.The SARS-CoV-2 pandemic highlighted our need for methods that allow rapid viral surveillance. Here, authors report a wireless, battery-free and wearable self-diagnosis platform that can continuously capture viral particles, diagnose infection status and evaluate symptom severity via breath and blow. The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections.The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional pathogenic infection diagnosis system (PIDS) for diagnosing SARS-CoV-2 infection and symptom severity by blow and breath within 110 s and 350 s, respectively. The accuracies reach to 100% and 92% for evaluating the infection and symptom severity of 42 participants, respectively. PIDS realizes simultaneous gaseous sample collection, biomarker identification, abnormal physical signs recording and machine learning analysis. We transform PIDS into other miniaturized wearable or portable electronic platforms that may widen the diagnostic modes at home, outdoors and public places. Collectively, we demonstrate a general-purpose technology for rapidly diagnosing respiratory pathogenic infection by breath and blow, alleviating the technical bottleneck of saliva and nasopharyngeal secretions. PIDS may serve as a complementary diagnostic tool for other point-of-care techniques and guide the symptomatic treatment of viral infections. |
| ArticleNumber | 7539 |
| Author | Yu, Xinge Yiu, Chun Ki Hu, Wenchuang Hu, Jie Gao, Zhan Wong, Tsz Hung Su, Jingyou Chen, Zhenlin Chang, Lingqian Dou, Ying Li, Dengfeng Zhang, Binbin Liu, Yiming Xu, Guoqiang Zhou, Jingkun PARK, Wooyoung Huang, Jiandong Lin, Long Gong, Huarui Wu, Mengge Li, Jian Wu, Han Gao, Yuyu Chang, Tianrui Bai, Hao Shi, Rui Li, Ji Yu Wang, Yuqiong Li, Hu Huang, Ya Xu, Chenjie Jia, Huiling Jia, Shengxin Huang, Xingcan Chu, Hongwei |
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Cerebro-Cardiovascular Health Engineering – sequence: 5 givenname: Yuqiong surname: Wang fullname: Wang, Yuqiong organization: Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University – sequence: 6 givenname: Long surname: Lin fullname: Lin, Long organization: College of Engineering, Peking University – sequence: 7 givenname: Ying surname: Dou fullname: Dou, Ying organization: School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong – sequence: 8 givenname: Huiling orcidid: 0000-0001-7918-0945 surname: Jia fullname: Jia, Huiling organization: Department of Biomedical Engineering, City University of Hong Kong, Hong Kong Centre for Cerebro-Cardiovascular Health Engineering – sequence: 9 givenname: Xingcan orcidid: 0000-0003-4210-2470 surname: Huang fullname: Huang, Xingcan organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 10 givenname: Zhan surname: Gao fullname: Gao, Zhan organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 11 givenname: Rui surname: Shi fullname: Shi, Rui organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 12 givenname: Ya orcidid: 0000-0002-0965-8226 surname: Huang fullname: Huang, Ya organization: Department of Biomedical Engineering, City University of Hong Kong, Hong Kong Centre for Cerebro-Cardiovascular Health Engineering – sequence: 13 givenname: Zhenlin surname: Chen fullname: Chen, Zhenlin organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 14 givenname: Wooyoung orcidid: 0000-0003-2250-3613 surname: PARK fullname: PARK, Wooyoung organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 15 givenname: Ji Yu surname: Li fullname: Li, Ji Yu organization: Department of Biomedical Engineering, City University of Hong Kong, Hong Kong Centre for Cerebro-Cardiovascular Health Engineering – sequence: 16 givenname: Hongwei surname: Chu fullname: Chu, Hongwei organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 17 givenname: Shengxin orcidid: 0000-0002-6998-3872 surname: Jia fullname: Jia, Shengxin organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 18 givenname: Han surname: Wu fullname: Wu, Han organization: Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University – sequence: 19 givenname: Mengge orcidid: 0000-0002-8116-5717 surname: Wu fullname: Wu, Mengge organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 20 givenname: Yiming orcidid: 0000-0003-0134-1934 surname: Liu fullname: Liu, Yiming organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 21 givenname: Dengfeng orcidid: 0000-0002-8875-6974 surname: Li fullname: Li, Dengfeng organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 22 givenname: Jian orcidid: 0000-0002-9768-0932 surname: Li fullname: Li, Jian organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 23 givenname: Guoqiang surname: Xu fullname: Xu, Guoqiang organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 24 givenname: Tianrui surname: Chang fullname: Chang, Tianrui organization: Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University – sequence: 25 givenname: Binbin surname: Zhang fullname: Zhang, Binbin organization: Department of Biomedical Engineering, City University of Hong Kong, Hong Kong Centre for Cerebro-Cardiovascular Health Engineering – sequence: 26 givenname: Yuyu surname: Gao fullname: Gao, Yuyu organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 27 givenname: Jingyou surname: Su fullname: Su, Jingyou organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 28 givenname: Hao surname: Bai fullname: Bai, Hao organization: Department of Laboratory Medicine, Med+X Center for Manufacturing, West China Precision Medicine Industrial Technology Institute, Department of Liver Surgery, Department of Pathology, West China Hospital, Sichuan University – sequence: 29 givenname: Jie surname: Hu fullname: Hu, Jie organization: Department of Laboratory Medicine, Med+X Center for Manufacturing, West China Precision Medicine Industrial Technology Institute, Department of Liver Surgery, Department of Pathology, West China Hospital, Sichuan University – sequence: 30 givenname: Chun Ki surname: Yiu fullname: Yiu, Chun Ki organization: Department of Biomedical Engineering, City University of Hong Kong, Hong Kong Centre for Cerebro-Cardiovascular Health Engineering – sequence: 31 givenname: Chenjie orcidid: 0000-0002-8278-3912 surname: Xu fullname: Xu, Chenjie organization: Department of Biomedical Engineering, City University of Hong Kong – sequence: 32 givenname: Wenchuang orcidid: 0000-0002-6748-1916 surname: Hu fullname: Hu, Wenchuang email: huwenchuang@wchscu.cn organization: Department of Laboratory Medicine, Med+X Center for Manufacturing, West China Precision Medicine Industrial Technology Institute, Department of Liver Surgery, Department of Pathology, West China Hospital, Sichuan University – sequence: 33 givenname: Jiandong orcidid: 0000-0001-7531-2816 surname: Huang fullname: Huang, Jiandong email: jdhuang@hku.hk organization: Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, University of Hong Kong, Clinical Oncology Center, Shenzhen Key Laboratory for cancer metastasis and personalized therapy, The University of Hong Kong-Shenzhen Hospital, Guangdong-Hong Kong Joint Laboratory for RNA Medicine, Sun Yat-Sen University – sequence: 34 givenname: Lingqian surname: Chang fullname: Chang, Lingqian email: lingqianchang@buaa.edu.cn organization: Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, School of Biomedical Engineering, Research and Engineering Center of Biomedical Materials, Anhui Medical University – sequence: 35 givenname: Xinge orcidid: 0000-0003-0522-1171 surname: Yu fullname: Yu, Xinge email: xingeyu@cityu.edu.hk organization: Department of Biomedical Engineering, City University of Hong Kong, Hong Kong Centre for Cerebro-Cardiovascular Health Engineering |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37985765$$D View this record in MEDLINE/PubMed |
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| Snippet | The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free, multifunctional... Abstract The rapid diagnosis of respiratory virus infection through breath and blow remains challenging. Here we develop a wireless, battery-free,... |
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| SubjectTerms | 631/154/140 639/166/985 692/53/2421 692/699/255/2514 9/10 Biomarkers Body Fluids COVID-19 - diagnosis Diagnosis Humanities and Social Sciences Humans Infections Machine learning multidisciplinary Pandemics Respiratory diseases Saliva SARS-CoV-2 Science Science (multidisciplinary) Secretions Severe acute respiratory syndrome coronavirus 2 Specimen Handling Viral diseases Viral infections Wearable technology |
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| Title | Wireless, battery-free, multifunctional integrated bioelectronics for respiratory pathogens monitoring and severity evaluation |
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| Volume | 14 |
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