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AuthorHassan, Manal
AuthorZhao, Yiping
AuthorZughaier, Susu M.
Available date2024-12-08T09:12:30Z
Publication Date2024-08-01
Publication NameBiosensors
Identifierhttp://dx.doi.org/10.3390/bios14080375
CitationHassan, M., Zhao, Y., & Zughaier, S. M. (2024). Recent Advances in Bacterial Detection Using Surface-Enhanced Raman Scattering. Biosensors, 14(8), 375.
URIhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85202348109&origin=inward
URIhttp://hdl.handle.net/10576/61710
AbstractRapid identification of microorganisms with a high sensitivity and selectivity is of great interest in many fields, primarily in clinical diagnosis, environmental monitoring, and the food industry. For over the past decades, a surface-enhanced Raman scattering (SERS)-based detection platform has been extensively used for bacterial detection, and the effort has been extended to clinical, environmental, and food samples. In contrast to other approaches, such as enzyme-linked immunosorbent assays and polymerase chain reaction, SERS exhibits outstanding advantages of rapid detection, being culture-free, low cost, high sensitivity, and lack of water interference. This review aims to cover the development of SERS-based methods for bacterial detection with an emphasis on the source of the signal, techniques used to improve the limit of detection and specificity, and the application of SERS in high-throughput settings and complex samples. The challenges and advancements with the implementation of artificial intelligence (AI) are also discussed.
SponsorThis research was funded by Qatar National Research Fund (QNRF) (grant number: NPRP12S-0224-190144). The APC is funded by Qatar University student grant number QUST-1-CMED-2024-1727.
Languageen
PublisherMultidisciplinary Digital Publishing Institute (MDPI)
Subjectartificial intelligence
high sensitivity
pathogenic bacteria
surface-enhanced Raman scattering
TitleRecent Advances in Bacterial Detection Using Surface-Enhanced Raman Scattering
TypeArticle
Issue Number8
Volume Number14
ESSN2079-6374
dc.accessType Open Access


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