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Detection and differentiation of Entamoeba histolytica and Entamoeba dispar in clinical samples through PCR-denaturing gradient gel electrophoresis

Overview of attention for article published in Brazilian Journal of Medical and Biological Research, January 2017
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Title
Detection and differentiation of Entamoeba histolytica and Entamoeba dispar in clinical samples through PCR-denaturing gradient gel electrophoresis
Published in
Brazilian Journal of Medical and Biological Research, January 2017
DOI 10.1590/1414-431x20175997
Pubmed ID
Authors

P. López-López, M.C. Martínez-López, X.M. Boldo-León, Y. Hernández-Díaz, T.B. González-Castro, C.A. Tovilla-Zárate, J.P. Luna-Arias

Abstract

Amebiasis is one of the twenty major causes of disease in Mexico; however, the diagnosis is difficult due to limitations of conventional microscopy-based techniques. In this study, we analyzed stool samples using polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) to differentiate between Entamoeba histolytica (pathogenic) and E. dispar (non-pathogenic). The target for the PCR amplification was a small region (228 bp) of the adh112 gene selected to increase the sensitivity of the test. The study involved 62 stool samples that were collected from individuals with complaints of gastrointestinal discomfort. Of the 62 samples, 10 (16.1%) were positive for E. histolytica while 52 (83.9%) were negative. No sample was positive for E. dispar. These results were validated by nested PCR-RFLP (restriction fragment length polymorphism) and suggest that PCR-DGGE is a promising tool to differentiate among Entamoeba infections, contributing to determine the specific treatment for patients infected with E. histolytica, and therefore, avoiding unnecessary treatment of patients infected with the non-pathogenic E. dispar.

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 29 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 17%
Student > Bachelor 4 14%
Researcher 3 10%
Lecturer 2 7%
Other 2 7%
Other 7 24%
Unknown 6 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 21%
Immunology and Microbiology 5 17%
Medicine and Dentistry 3 10%
Agricultural and Biological Sciences 3 10%
Nursing and Health Professions 2 7%
Other 4 14%
Unknown 6 21%