Your browser doesn't support javascript.
loading
Optimization of urinary sample preparation process for real-time PCR detection of BK virus / 第二军医大学学报
Academic Journal of Second Military Medical University ; (12): 438-441, 2010.
Article in Chinese | WPRIM | ID: wpr-840342
ABSTRACT

Objective:

To develop an effective preparation method to improve the sensitivity and accuracy of real-time PCR in detection of BK virus's (BKV's) load in urine samples.

Methods:

A total of 24 samples documented as positive probes in primary detection were enrolled in this study. The candidate samples were prepared by 4 different approaches unprocessed urine, BKV's DNA extracted from urine, 110 diluted urine, and 1100 diluted urine; and then they were subjected to real-time PCR examination to obtain the viral load. The data obtained were analyzed by SPSS 11.0.

Results:

The four different preparation processes for urinary specimens had significant impact on detection results of real-time PCR. Three samples were negative in the unprocessed urine group and 66.7% of its samples had the lowest viral loads compared with the other three groups. Two samples in the 1100 diluted urine group were negative and 79.2% of its samples had the highest viral loads, but its median load was similar to that of the 110 group. Viral gene was detected in all samples in the DNA extraction group and 110 diluted urine group, but the loss of the target gene was more severe in the DNA extraction group.

Conclusion:

The 110 diluted urine is better for real-time PCR detection of BKV's load, as it lose less viral gene and is more efficient, easy to perform and economical.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Diagnostic study Language: Chinese Journal: Academic Journal of Second Military Medical University Year: 2010 Type: Article

Similar

MEDLINE

...
LILACS

LIS

Full text: Available Index: WPRIM (Western Pacific) Type of study: Diagnostic study Language: Chinese Journal: Academic Journal of Second Military Medical University Year: 2010 Type: Article