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Development of a quantitative, portable, and automated fluorescent blue-ray device-based malaria diagnostic equipment with an on-disc SiO(2) nanofiber filter

There is an urgent need to develop an automated malaria diagnostic system that can easily and rapidly detect malaria parasites and determine the proportion of malaria-infected erythrocytes in the clinical blood samples. In this study, we developed a quantitative, mobile, and fully automated malaria...

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Detalles Bibliográficos
Autores principales: Yamamoto, Takeki, Hashimoto, Muneaki, Nagatomi, Kenji, Nogami, Takahiro, Sofue, Yasuyuki, Hayashi, Takuya, Ido, Yusuke, Yatsushiro, Shouki, Abe, Kaori, Kajimoto, Kazuaki, Tamari, Noriko, Awuor, Beatrice, Sonye, George, Kongere, James, Munga, Stephen, Ohashi, Jun, Oka, Hiroaki, Minakawa, Noboru, Kataoka, Masatoshi, Mita, Toshihiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7171072/
https://www.ncbi.nlm.nih.gov/pubmed/32313065
http://dx.doi.org/10.1038/s41598-020-63615-2
Descripción
Sumario:There is an urgent need to develop an automated malaria diagnostic system that can easily and rapidly detect malaria parasites and determine the proportion of malaria-infected erythrocytes in the clinical blood samples. In this study, we developed a quantitative, mobile, and fully automated malaria diagnostic system equipped with an on-disc SiO(2) nanofiber filter and blue-ray devices. The filter removes the leukocytes and platelets from the blood samples, which interfere with the accurate detection of malaria by the blue-ray devices. We confirmed that the filter, which can be operated automatically by centrifugal force due to the rotation of the disc, achieved a high removal rate of leukocytes (99.7%) and platelets (90.2%) in just 30 s. The automated system exhibited a higher sensitivity (100%) and specificity (92.8%) for detecting Plasmodium falciparum from the blood of 274 asymptomatic individuals in Kenya when compared to the common rapid diagnosis test (sensitivity = 98.1% and specificity = 54.8%). This indicated that this system can be a potential alternative to conventional methods used at local health facilities, which lack basic infrastructure.