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https://hdl.handle.net/10495/21416
Título : | A sensitive species-specific reverse transcription real-time PCR method for detection of Plasmodium falciparum and Plasmodium vivax |
Autor : | Gavina, Kenneth Arango Flórez, Eliana María Álvarez Larrotta, Catalina Maestre Buitrago, Amanda Elena Kim Yanow, Stephanie |
metadata.dc.subject.*: | Reacción en Cadena de la Polimerasa Polymerase Chain Reaction Malaria Plasmodium falciparum Plasmodium vivax Diagnóstico Diagnosis |
Fecha de publicación : | 2017 |
Editorial : | Elsevier |
Resumen : | ABSTRACT: As the global burden of malaria decreases and countries strive towards disease elimination, there is a greater demand for sensitive diagnostics to target the submicroscopic reservoir of infection. We describe here a sensitive species-specific RT-qPCR method to differentiate between Plasmodium falciparum and P. vivax infections at the submicroscopic level. With amplification of the 18S rRNA genes from total nucleic acids (both DNA and RNA), we discern P. falciparum and P. vivax with a limit of detection of 10 parasites/mL and 18 copies/μL, respectively. This assay was validated with 519 blood samples, negative by thick-smear, from febrile and asymptomatic cohorts from Colombia. These results were directly compared to a qPCR-based method (DNA only) as the gold standard. Of the samples from patients who presented with fever (n = 274), 34 infections were identified by RT-qPCR (16 P. falciparum, 15 P. vivax, and 3 mixed), of which only 10 infections were identified at the species level by qPCR. Within the asymptomatic cohort (n = 245), 13 infections were identified by RT-qPCR (3 P. falciparum, 3 P. vivax, and 7 mixed), whereas the species for only one infection was determined by qPCR. We conclude that this species-specific RT-qPCR method provides a more sensitive tool for species identification compared to DNA based qPCR methods. |
ISSN : | 2405-6731 |
metadata.dc.identifier.doi: | 10.1016/j.parepi.2017.04.001 |
Aparece en las colecciones: | Artículos de Revista en Ciencias Médicas |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
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ElianaArango_2017_SpeciesDetectionVivax.pdf | Artículo de investigación | 306.86 kB | Adobe PDF | Visualizar/Abrir |
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