Advancing SARS‐CoV‐2 Variant Detection with High Affinity Monoclonal Antibodies and Plasmonic Nanostructure
A nanoplasmonic biosensor for the precise detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) by leveraging advances in nanostructured sensing materials and highly selective monoclonal antibodies is presented. The sensor integrates plasmonic Au nanostructures optimized for surf...
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Veröffentlicht in: | Advanced functional materials 2024-11, Vol.34 (45), p.n/a |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | A nanoplasmonic biosensor for the precise detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) by leveraging advances in nanostructured sensing materials and highly selective monoclonal antibodies is presented. The sensor integrates plasmonic Au nanostructures optimized for surface‐enhanced Raman scattering (SERS), enhancing sensitivity through unique light interactions at the nanoscale. Coupled with exclusive antibodies that specifically target SARS‐CoV‐2 and its evolving variants, this sensor demonstrates remarkable selectivity and versatility. Validated with 270 clinical samples, it demonstrates a sensitivity of 98.9% and specificity of 100%. More importantly, the virus in nasopharyngeal swab samples collected over 3 years, marking the long‐term, large‐scale clinical validation of the nanoplasmonic biosensor for SARS‐CoV‐2 is been successfully detected. Furthermore, the integration of this sensor with face masks enables the detection of airborne SARS‐CoV‐2, highlighting its potential for routine management of coronavirus disease 2019 (COVID‐19).
Nanoplasmonic biosensor for accurate severe acute respriratory syndrome coronavirus 2 detection, utilizing plasmonic nanostructures and selective antibodies for enhanced sensitivity and specificity is reported. Validated with 270 clinical samples, it shows 98.9% sensitivity and 100% specificity, successfully detecting the virus across samples from 3 years. Its integration into face masks also allows for airborne virus detection, offering a promising tool for coronavirus disease 2019 management. |
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ISSN: | 1616-301X 1616-3028 |
DOI: | 10.1002/adfm.202405340 |