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dc.contributor.authorDryden, SD
dc.contributor.authorAnastasova, S
dc.contributor.authorSatta, G
dc.contributor.authorThompson, AJ
dc.contributor.authorLeff, DR
dc.contributor.authorDarzi, A
dc.date.accessioned2021-07-09T13:49:35Z
dc.date.available2021-07-09T13:49:35Z
dc.date.issued2021-04-22
dc.identifier.citationScientific reports, 2021, 11 (1), pp. 8802 - ?
dc.identifier.issn2045-2322
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/4677
dc.identifier.eissn2045-2322
dc.identifier.doi10.1038/s41598-021-88026-9
dc.description.abstractUrinary tract infection is one of the most common bacterial infections leading to increased morbidity, mortality and societal costs. Current diagnostics exacerbate this problem due to an inability to provide timely pathogen identification. Surface enhanced Raman spectroscopy (SERS) has the potential to overcome these issues by providing immediate bacterial classification. To date, achieving accurate classification has required technically complicated processes to capture pathogens, which has precluded the integration of SERS into rapid diagnostics. This work demonstrates that gold-coated membrane filters capture and aggregate bacteria, separating them from urine, while also providing Raman signal enhancement. An optimal gold coating thickness of 50 nm was demonstrated, and the diagnostic performance of the SERS-active filters was assessed using phantom urine infection samples at clinically relevant concentrations (10 5  CFU/ml). Infected and uninfected (control) samples were identified with an accuracy of 91.1%. Amongst infected samples only, classification of three bacteria (Escherichia coli, Enterococcus faecalis, Klebsiella pneumoniae) was achieved at a rate of 91.6%.
dc.formatElectronic
dc.format.extent8802 - ?
dc.languageeng
dc.language.isoeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.titleRapid uropathogen identification using surface enhanced Raman spectroscopy active filters.
dc.typeJournal Article
dcterms.dateAccepted2021-03-26
rioxxterms.versionVoR
rioxxterms.versionofrecord10.1038/s41598-021-88026-9
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2021-04-22
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfScientific reports
pubs.issue1
pubs.notesNot known
pubs.organisational-group/ICR
pubs.organisational-group/ICR
pubs.publication-statusPublished
pubs.volume11
pubs.embargo.termsNot known
dc.contributor.icrauthorDarzi, Ara


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Except where otherwise noted, this item's license is described as https://creativecommons.org/licenses/by/4.0