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Relative frequency of malaria pigment-carrying monocytes of nonimmune and semi-immune patients from flow cytometric depolarized side scatter

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Abstract

BACKGROUND: Recently, it was observed that malaria can be detected by performing automated complete blood count analysis including depolarization measurement of scattered laser light. To explain large discrepancies in sensitivity and specificity observed in semi-immune and nonimmune malaria patients, we determined the relative frequencies of malaria pigment-carrying monocytes (PCM) by flow cytometric measurements combined with rare event analysis. METHODS: An experimental cell-sorting unit utilizing argon, krypton, and helium-neon lasers measured the relative frequencies of leukocytes of malaria patients. Single white blood cells showing high intensity in their depolarized side scatter were sorted for subsequent microscopic analysis. RESULTS: From microscopic inspection of sorted cells, we identified malaria PCM as a distinct cluster in scatter diagrams that is well separated from normal leukocytes. For nonimmune patients, the average relative frequency of PCM is 1.5 x 10(-4) (median), for semi-immune patients 8.8 x 10(-4), and for malaria-negative persons 4.4 x 10(-6). Results derived from depolarized side scatter at 488, 633, or 647 nm agree well. Furthermore, malaria pigment-carrying neutrophilic granulocytes were identified microscopically after sorting. We discuss briefly how pigment-carrying neutrophils might be differentiated from normal leukocytes and PCM by using flow cytometry and measuring depolarized side scatter at two wavelengths. CONCLUSION: Our results confirm the feasibility of malaria detection by flow cytometry for semi-immune patients and extend malaria detection to nonimmune patients with low frequencies of PCM. High sensitivity and specificity for malaria detection were obtained
Original languageEnglish
Pages (from-to)133-140
JournalCytometry
Volume45
Issue number2
DOIs
Publication statusPublished - 2001

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This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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