کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8737165 | 1591324 | 2018 | 24 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Use of matrix-assisted laser desorption ionization-time of flight mass spectrometry to identify MLST clade 4 Clostridium difficile isolates
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
ایمنی شناسی و میکروب شناسی
میکروبیولوژی و بیوتکنولوژی کاربردی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Use of matrix-assisted laser desorption ionization-time of flight mass spectrometry to identify MLST clade 4 Clostridium difficile isolates Use of matrix-assisted laser desorption ionization-time of flight mass spectrometry to identify MLST clade 4 Clostridium difficile isolates](/preview/png/8737165.png)
چکیده انگلیسی
Clostridium difficile is the leading cause of health care-associated infections. Previous studies suggest that C. difficile MLST clade 4 strains with higher drug resistance rates constitute the major clone spreading in China. Thus development of a rapid and accurate typing method for these strains is needed to monitor the epidemiology of this clone and to guide clinical treatment. A total of 160 non-duplicate C. difficile isolates recovered from three large teaching hospitals in Beijing were studied. All the 41 clade 4 C. difficile isolates clustered together on the PCA dendrogram. Spectra peak statistics revealed that five markers (2691.43Da, 2704.91Da, 2711.93Da, 3247.27Da and 3290.76Da) can easily and reliably distinguish between clade 4 and non-clade 4 isolates, with area under the curve (AUC) values of 0.991, 0.997, 0.973, 1 and 1, respectively. In conclusion, MALDI-TOF MS is a very simple and accurate method for identifying C. difficile MLST clade 4 strains.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Diagnostic Microbiology and Infectious Disease - Volume 92, Issue 1, September 2018, Pages 19-24
Journal: Diagnostic Microbiology and Infectious Disease - Volume 92, Issue 1, September 2018, Pages 19-24
نویسندگان
Jing-Wei Cheng, Chang Liu, Timothy Kudinha, Meng Xiao, Shu-Ying Yu, Chun-Xia Yang, Ming Wei, Guo-Wei Liang, Dong-Hua Shao, Fanrong Kong, Zhao-Hui Tong, Ying-Chun Xu,