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Molecular Characterization of Echinococcus granulosus through Amplification of 12S rRNA Gene and Cox1 Gene Fragments from Cattle in Chittagong, Bangladesh

Year: 2017 Volume: 11 Issue: 4 301 - 305 Pages

Abstract: The dog tapeworms Echinococcus granulosus develop hydatid cysts in various organs in human and domestic animals worldwide including Bangladesh. The aim of this study was to identify and characterize the genotype of E. granulosus isolated from cattle using 12S rRNA and Cytochrome oxidase 1 (COX 1) genes. A total of 43 hydatid cyst samples were collected from 390 examined cattle samples derived from slaughterhouses. Among them, three cysts were fertile. Genomic DNA was extracted from germinal membrane and/or protoscoleces followed by PCR amplification of mitochondrial 12S rRNA and Cytochrome oxidase 1 gene fragments. The sequence data revealed existence of G1 (64.28%) and possible G3 (21.43%) genotypes for the first time in Bangladesh. The study indicates that common sheep strain G1 is the dominant subtype of E. granulosus in Chittagong region of Bangladesh. This will increase our understanding of the epidemiology of hydatidosis in the southern part of the country and will be useful to plan suitable control measures in the long run.

Implementing a Database from a Requirement Specification

Year: 2015 Volume: 9 Issue: 1 33 - 41 Pages

Abstract: Creating a database scheme is essentially a manual process. From a requirement specification the information contained within has to be analyzed and reduced into a set of tables, attributes and relationships. This is a time consuming process that has to go through several stages before an acceptable database schema is achieved. The purpose of this paper is to implement a Natural Language Processing (NLP) based tool to produce a relational database from a requirement specification. The Stanford CoreNLP version 3.3.1 and the Java programming were used to implement the proposed model. The outcome of this study indicates that a first draft of a relational database schema can be extracted from a requirement specification by using NLP tools and techniques with minimum user intervention. Therefore this method is a step forward in finding a solution that requires little or no user intervention.