Indexed by:
Abstract:
Gram-negative bacteria had been regarded as several important sources of lethal infection. Rapid identification of pathogenic bacteria is extremely important for the diagnosis and clinical treatment of diseases. In current study, three gram-negative bacteria, including Klebsiella aerogenes, Enterobacter cloacae and Escherichia coli, were used to access the feasibility of characterizing Gram-negative bacteria by surface-enhanced Raman Spectroscopy (SERS). Bacterial samples were from Escherichia coli isolates (n=1000), Klebsiella aerogenes isolates (n=1000) and Enterobacter cloacaeand isolates (n=1000). The differences of three Gram-negative bacteria were characterized by SERS spectra. Furthermore, four multivariate statistical algorithms based on the combination of principal component analysis (or partial least squares) and linear discriminant analysis (or support vector machine) were used to discriminate the spectra of three gram-negative bacteria. © 2023 IOS Press. All rights reserved.
Keyword:
Reprint 's Address:
Email:
Source :
ISSN: 0926-9630
Year: 2023
Volume: 308
Page: 253-260
Language: English
Cited Count:
SCOPUS Cited Count:
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 1
Affiliated Colleges: