Researchers report distinct profiles of volatile emissions from human skin between malaria-infected and uninfected individuals, and between symptomatic and asymptomatic infected individuals, based on analysis of skin odors from more than 400 children, ages 12 and under, in Western Kenya; machine learning models identified asymptomatic infections based on skin volatile profiles, including in individuals with parasite loads that were too low to be detected by microscopy.
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Article #18-01512: "Volatile biomarkers of symptomatic and asymptomatic malaria infection in humans," by Consuelo M. De Moraes et al.
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Proceedings of the National Academy of Sciences