کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6123861 | 1219950 | 2013 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Application of nested PCR for diagnosis of histoplasmosis
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
ایمنی شناسی و میکروب شناسی
میکروبیولوژی و بیوتکنولوژی کاربردی
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چکیده انگلیسی
Histoplasmosis is a fungal infection that, although not endemic in Japan, has seen a rise in the number of Japanese cases since the mid-1980s. Diagnosis of the disease is not straightforward, and the main method of detection, fungal culture (which has biosafety-related issues), is of low sensitivity in general. Alternative methods that depend on antibody or antigen detection have had limited use. We have developed a histoplasmosis detection method based on PCR amplification of the Histoplasma capsulatum M antigen gene. We compared this method with fungal culture and serological diagnostic techniques. Among five cases that were finally diagnosed as histoplasmosis, the fungal culture method was only successful in identifying one such case. Although the presence of anti-H. capsulatum antibodies was confirmed in three cases, our PCR method identified four of five cases of histoplasmosis. The performance of our PCR method could not be compared with the antigen detection method, which is used in the United States but is not routinely used in Japan. However, the PCR method was shown to have high sensitivity and specificity for H. capsulatum. Although the number of histoplasmosis cases examined in this study was small, our data suggest that the molecular diagnosis technique has potential for increasing the reliability of histoplasmosis diagnosis when used in combination with established methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Infection and Chemotherapy - Volume 19, Issue 5, 2013, Pages 999-1003
Journal: Journal of Infection and Chemotherapy - Volume 19, Issue 5, 2013, Pages 999-1003
نویسندگان
Hideaki Ohno, Koichi Tanabe, Takashi Umeyama, Yukihiro Kaneko, Satoshi Yamagoe, Yoshitsugu Miyazaki, Hideaki Ohno, Koichi Tanabe, Takashi Umeyama, Satoshi Yamagoe,