@article{(Open Science Index):https://publications.waset.org/pdf/10006262,
	  title     = {The Use of SD Bioline TB AgMPT64® Detection Assay for Rapid Characterization of Mycobacteria in Nigeria},
	  author    = {S. Ibrahim and  U. B. Abubakar and  S. Danbirni and  A. Usman and  F. M. Ballah and  C. A. Kudi and  L. Lawson and  G. H. Abdulrazak and  I. A. Abdulkadir},
	  country	= {},
	  institution	= {},
	  abstract     = {Performing culture and characterization of mycobacteria in low resource settings like Nigeria is a very difficult task to undertake because of the very few and limited laboratories carrying out such an experiment; this is a largely due to stringent and laborious nature of the tests. Hence, a rapid, simple and accurate test for characterization is needed. The “SD BIOLINE TB Ag MPT 64 Rapid ®” is a simple and rapid immunochromatographic test used in differentiating Mycobacteria into Mycobacterium tuberculosis (NTM). The 100 sputa were obtained from patients suspected to be infected with tuberculosis and presented themselves to hospitals for check-up and treatment were involved in the study. The samples were cultured in a class III Biosafety cabinet and level III biosafety practices were followed. Forty isolates were obtained from the cultured sputa, and there were identified as Acid-fast bacilli (AFB) using Zeihl-Neelsen acid-fast stain. All the isolates (AFB positive) were then subjected to the SD BIOLINE Analyses. A total of 31 (77.5%) were characterized as MTBC, while nine (22.5%) were NTM. The total turnaround time for the rapid assay was just 30 minutes as compared to a few days of phenotypic and genotypic method. It was simple, rapid and reliable test to differentiate MTBC from NTM.
},
	    journal   = {International Journal of Animal and Veterinary Sciences},
	  volume    = {11},
	  number    = {2},
	  year      = {2017},
	  pages     = {97 - 100},
	  ee        = {https://publications.waset.org/pdf/10006262},
	  url   	= {https://publications.waset.org/vol/122},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 122, 2017},
	}