Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min
Population-wide surveillance of COVID-19 requires tests to be quick and accurate to minimize community transmissions. The detection of breath volatile organic compounds presents a promising option for COVID-19 surveillance but is currently limited by bulky instrumentation and inflexible analysis pro...
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| Veröffentlicht in: | ACS nano 2022-02, Vol.16 (2), p.2629-2639 |
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| creator | Leong, Shi Xuan Leong, Yong Xiang Tan, Emily Xi Sim, Howard Yi Fan Koh, Charlynn Sher Lin Lee, Yih Hong Chong, Carice Ng, Li Shiuan Chen, Jaslyn Ru Ting Pang, Desmond Wei Cheng Nguyen, Lam Bang Thanh Boong, Siew Kheng Han, Xuemei Kao, Ya-Chuan Chua, Yi Heng Phan-Quang, Gia Chuong Phang, In Yee Lee, Hiang Kwee Abdad, Mohammad Yazid Tan, Nguan Soon Ling, Xing Yi |
| description | Population-wide surveillance of COVID-19 requires tests to be quick and accurate to minimize community transmissions. The detection of breath volatile organic compounds presents a promising option for COVID-19 surveillance but is currently limited by bulky instrumentation and inflexible analysis protocol. Here, we design a hand-held surface-enhanced Raman scattering-based breathalyzer to identify COVID-19 infected individuals in under 5 min, achieving >95% sensitivity and specificity across 501 participants regardless of their displayed symptoms. Our SERS-based breathalyzer harnesses key variations in vibrational fingerprints arising from interactions between breath metabolites and multiple molecular receptors to establish a robust partial least-squares discriminant analysis model for high throughput classifications. Crucially, spectral regions influencing classification show strong corroboration with reported potential COVID-19 breath biomarkers, both through experiment and in silico. Our strategy strives to spur the development of next-generation, noninvasive human breath diagnostic toolkits tailored for mass screening purposes. |
| doi_str_mv | 10.1021/acsnano.1c09371 |
| format | Article |
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The detection of breath volatile organic compounds presents a promising option for COVID-19 surveillance but is currently limited by bulky instrumentation and inflexible analysis protocol. Here, we design a hand-held surface-enhanced Raman scattering-based breathalyzer to identify COVID-19 infected individuals in under 5 min, achieving >95% sensitivity and specificity across 501 participants regardless of their displayed symptoms. Our SERS-based breathalyzer harnesses key variations in vibrational fingerprints arising from interactions between breath metabolites and multiple molecular receptors to establish a robust partial least-squares discriminant analysis model for high throughput classifications. Crucially, spectral regions influencing classification show strong corroboration with reported potential COVID-19 breath biomarkers, both through experiment and in silico. 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The detection of breath volatile organic compounds presents a promising option for COVID-19 surveillance but is currently limited by bulky instrumentation and inflexible analysis protocol. Here, we design a hand-held surface-enhanced Raman scattering-based breathalyzer to identify COVID-19 infected individuals in under 5 min, achieving >95% sensitivity and specificity across 501 participants regardless of their displayed symptoms. Our SERS-based breathalyzer harnesses key variations in vibrational fingerprints arising from interactions between breath metabolites and multiple molecular receptors to establish a robust partial least-squares discriminant analysis model for high throughput classifications. Crucially, spectral regions influencing classification show strong corroboration with reported potential COVID-19 breath biomarkers, both through experiment and in silico. Our strategy strives to spur the development of next-generation, noninvasive human breath diagnostic toolkits tailored for mass screening purposes.</description><subject>COVID-19</subject><subject>Humans</subject><subject>Mass Screening</subject><subject>Point-of-Care Systems</subject><subject>SARS-CoV-2</subject><subject>Spectrum Analysis, Raman - methods</subject><issn>1936-0851</issn><issn>1936-086X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kU9v1DAQxSMEoqVw5oZ83AqltfPXviDRdIFKhaIuIG7WxB53XSV2sZOVypfhq-JqlxUcOM1I83tvRvOy7CWjJ4wW7BRUdOD8CVNUlC17lB0yUTY55c33x_u-ZgfZsxhvKa1b3jZPs4OyphUtWXWY_frknXUbiHaDBJwmn711U-5N3kFAspqDAYX50q3BKdTkGkZwZKVgmjBYd0MWq-X16jg_g5imZwFhWsNw_xMDMT6QjxBjogOie4C9IZ0P3sHGhjmScxsx6UhBmSCL7urbxXnOxDGZnU76mozWPc-eGBgivtjVo-zru-WX7kN-efX-ont7mUMl6invQfNKNNgKoQwvlNK84EKAMBqqXgtRcNXUFW9MhUy0htKyVKXuddFXytRQHmVvtr53cz-iVuimAIO8C3aEcC89WPnvxNm1vPEbyVvBaNkkg8XOIPgfM8ZJjjYqHAZw6Ocoi6ZglPG6KRJ6ukVV8DEGNPs1jMqHWOUuVrmLNSle_X3dnv-TYwJeb4GklLd-Di496792vwGtOa81</recordid><startdate>20220222</startdate><enddate>20220222</enddate><creator>Leong, Shi Xuan</creator><creator>Leong, Yong Xiang</creator><creator>Tan, Emily Xi</creator><creator>Sim, Howard Yi Fan</creator><creator>Koh, Charlynn Sher Lin</creator><creator>Lee, Yih Hong</creator><creator>Chong, Carice</creator><creator>Ng, Li Shiuan</creator><creator>Chen, Jaslyn Ru Ting</creator><creator>Pang, Desmond Wei Cheng</creator><creator>Nguyen, Lam Bang Thanh</creator><creator>Boong, Siew Kheng</creator><creator>Han, Xuemei</creator><creator>Kao, Ya-Chuan</creator><creator>Chua, Yi Heng</creator><creator>Phan-Quang, Gia Chuong</creator><creator>Phang, In Yee</creator><creator>Lee, Hiang Kwee</creator><creator>Abdad, Mohammad Yazid</creator><creator>Tan, Nguan Soon</creator><creator>Ling, Xing Yi</creator><general>American Chemical Society</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0003-0823-4111</orcidid><orcidid>https://orcid.org/0000-0001-5495-6428</orcidid></search><sort><creationdate>20220222</creationdate><title>Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min</title><author>Leong, Shi Xuan ; Leong, Yong Xiang ; Tan, Emily Xi ; Sim, Howard Yi Fan ; Koh, Charlynn Sher Lin ; Lee, Yih Hong ; Chong, Carice ; Ng, Li Shiuan ; Chen, Jaslyn Ru Ting ; Pang, Desmond Wei Cheng ; Nguyen, Lam Bang Thanh ; Boong, Siew Kheng ; Han, Xuemei ; Kao, Ya-Chuan ; Chua, Yi Heng ; Phan-Quang, Gia Chuong ; Phang, In Yee ; Lee, Hiang Kwee ; Abdad, Mohammad Yazid ; Tan, Nguan Soon ; Ling, Xing Yi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a495t-bad8496e799cf82ccd82899a9fda4bd9928c65486f4e197f0033c3dbd2b4cf5a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>COVID-19</topic><topic>Humans</topic><topic>Mass Screening</topic><topic>Point-of-Care Systems</topic><topic>SARS-CoV-2</topic><topic>Spectrum Analysis, Raman - methods</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Leong, Shi Xuan</creatorcontrib><creatorcontrib>Leong, Yong Xiang</creatorcontrib><creatorcontrib>Tan, Emily Xi</creatorcontrib><creatorcontrib>Sim, Howard Yi Fan</creatorcontrib><creatorcontrib>Koh, Charlynn Sher Lin</creatorcontrib><creatorcontrib>Lee, Yih Hong</creatorcontrib><creatorcontrib>Chong, Carice</creatorcontrib><creatorcontrib>Ng, Li Shiuan</creatorcontrib><creatorcontrib>Chen, Jaslyn Ru Ting</creatorcontrib><creatorcontrib>Pang, Desmond Wei Cheng</creatorcontrib><creatorcontrib>Nguyen, Lam Bang Thanh</creatorcontrib><creatorcontrib>Boong, Siew Kheng</creatorcontrib><creatorcontrib>Han, Xuemei</creatorcontrib><creatorcontrib>Kao, Ya-Chuan</creatorcontrib><creatorcontrib>Chua, Yi Heng</creatorcontrib><creatorcontrib>Phan-Quang, Gia Chuong</creatorcontrib><creatorcontrib>Phang, In Yee</creatorcontrib><creatorcontrib>Lee, Hiang Kwee</creatorcontrib><creatorcontrib>Abdad, Mohammad Yazid</creatorcontrib><creatorcontrib>Tan, Nguan Soon</creatorcontrib><creatorcontrib>Ling, Xing Yi</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>ACS nano</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Leong, Shi Xuan</au><au>Leong, Yong Xiang</au><au>Tan, Emily Xi</au><au>Sim, Howard Yi Fan</au><au>Koh, Charlynn Sher Lin</au><au>Lee, Yih Hong</au><au>Chong, Carice</au><au>Ng, Li Shiuan</au><au>Chen, Jaslyn Ru Ting</au><au>Pang, Desmond Wei Cheng</au><au>Nguyen, Lam Bang Thanh</au><au>Boong, Siew Kheng</au><au>Han, Xuemei</au><au>Kao, Ya-Chuan</au><au>Chua, Yi Heng</au><au>Phan-Quang, Gia Chuong</au><au>Phang, In Yee</au><au>Lee, Hiang Kwee</au><au>Abdad, Mohammad Yazid</au><au>Tan, Nguan Soon</au><au>Ling, Xing Yi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min</atitle><jtitle>ACS nano</jtitle><addtitle>ACS Nano</addtitle><date>2022-02-22</date><risdate>2022</risdate><volume>16</volume><issue>2</issue><spage>2629</spage><epage>2639</epage><pages>2629-2639</pages><issn>1936-0851</issn><eissn>1936-086X</eissn><abstract>Population-wide surveillance of COVID-19 requires tests to be quick and accurate to minimize community transmissions. The detection of breath volatile organic compounds presents a promising option for COVID-19 surveillance but is currently limited by bulky instrumentation and inflexible analysis protocol. Here, we design a hand-held surface-enhanced Raman scattering-based breathalyzer to identify COVID-19 infected individuals in under 5 min, achieving >95% sensitivity and specificity across 501 participants regardless of their displayed symptoms. Our SERS-based breathalyzer harnesses key variations in vibrational fingerprints arising from interactions between breath metabolites and multiple molecular receptors to establish a robust partial least-squares discriminant analysis model for high throughput classifications. Crucially, spectral regions influencing classification show strong corroboration with reported potential COVID-19 breath biomarkers, both through experiment and in silico. Our strategy strives to spur the development of next-generation, noninvasive human breath diagnostic toolkits tailored for mass screening purposes.</abstract><cop>United States</cop><pub>American Chemical Society</pub><pmid>35040314</pmid><doi>10.1021/acsnano.1c09371</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0003-0823-4111</orcidid><orcidid>https://orcid.org/0000-0001-5495-6428</orcidid><oa>free_for_read</oa></addata></record> |
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| source | ACS Publications; MEDLINE |
| subjects | COVID-19 Humans Mass Screening Point-of-Care Systems SARS-CoV-2 Spectrum Analysis, Raman - methods |
| title | Noninvasive and Point-of-Care Surface-Enhanced Raman Scattering (SERS)-Based Breathalyzer for Mass Screening of Coronavirus Disease 2019 (COVID-19) under 5 min |
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