Journal
RSC ADVANCES
Volume 11, Issue 55, Pages 34425-34431Publisher
ROYAL SOC CHEMISTRY
DOI: 10.1039/d1ra05778b
Keywords
-
Categories
Funding
- National Natural Science Foundation of China [81871734, 81471994]
- Natural Science Foundation of Anhui Province [1908085QB85]
- Postgraduate Research & Practice Innovation Program of Jiangsu Province [KYCX20_2472]
- Medical instrument supervise program of Hefei institute of physical science of CAS [YZJJ2021-J-YQ4]
Ask authors/readers for more resources
In this study, a label-free SERS method was developed for the accurate identification of methicillin-susceptible and methicillin-resistant Staphylococcus aureus using aptamer-guided AgNP enhancement and CNN classification. The method showed 100% identification accuracy for MSSA and MRSA, indicating its potential as a rapid detection tool for drug-sensitive and drug-resistant bacterial strains.
Here, we report a label-free surface-enhanced Raman scattering (SERS) method for the rapid and accurate identification of methicillin-susceptible Staphylococcus aureus (MSSA) and methicillin-resistant Staphylococcus aureus (MRSA) based on aptamer-guided AgNP enhancement and convolutional neural network (CNN) classification. Sixty clinical isolates of Staphylococcus aureus (S. aureus), comprising 30 strains of MSSA and 30 strains of MRSA were used to build the CNN classification model. The developed method exhibited 100% identification accuracy for MSSA and MRSA, and is thus a promising tool for the rapid detection of drug-sensitive and drug-resistant bacterial strains.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available