Browsing by Author "Achar, Joan Beryl"

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    Characterization of urinary metabolites associated with malaria infection using infra‑red spectroscopy and liquid chromatography–mass spectrometry in South Western Uganda
    (2024-07) Birungi, Grace; Achar, Joan Beryl; Byamugisha, Denis
    Early malaria diagnosis improves outcomes during malaria treatment; routine diagnostic techniques rely on blood samples obtained invasively. Therefore, this study used infra-red (IR) spectroscopy coupled with Principle Component Analysis (PCA) to study the urinary profile of malaria patients and that of controls aimed at understanding metabolite perturbation during malaria infection so as to contribute towards development of non-invasive malaria diagnosis methods. Freeze dried human urine samples form malaria infected individuals (cases) and controls were screened in the IR region of 4000 cm−1 to 600 cm−1 and overall spectral differences were observed at wave numbers 1618 cm−1, 1679 cm−1 (amino acids). Peaks at 3030 cm−1 (NH4+) and 940 cm−1 (O–H of carboxylic acids) showed high absorbance in patients compared to controls. Liquid-chromatography–mass spectrometry (LC–MS/MS) was used to quantify amino acids in the urine samples and the results indicated a significant increase of amino acid cystine (P = 0.012). Lysine and tyrosine also increased in patients compared to controls. The use of IR-PCA differentiated clusters of urine samples from patients with malaria from control and the demonstrated amino acid perturbation is consistent with malaria infection. This data provides baseline information for application in development of a non-invasive diagnostic tests for malaria.Article HighlightsInfrared (IR) spectroscopy and Principle Component Analysis (PCA) were used to differentiate urine of malaria patients from controls.LC–MS/MS was used to determine creatinine, tyrosine, cystine, lysine and histidine in urine from malaria patients and controlsThe average concentration of cystine in patients and controls urine differed significantly. Publicly Available Content Database
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    Characterization of urinary metabolites associated with malaria infection using infra‑red spectroscopy and liquid chromatography–mass spectrometry in South Western Uganda
    (Springer Nature B.V, 2024-07) Birungi, Grace; Achar, Joan Beryl; Byamugisha, Denis
    Early malaria diagnosis improves outcomes during malaria treatment; routine diagnostic techniques rely on blood samples obtained invasively. Therefore, this study used infra-red (IR) spectroscopy coupled with Principle Component Analysis (PCA) to study the urinary profile of malaria patients and that of controls aimed at understanding metabolite perturbation during malaria infection so as to contribute towards development of non-invasive malaria diagnosis methods. Freeze dried human urine samples form malaria infected individuals (cases) and controls were screened in the IR region of 4000 cm−1 to 600 cm−1 and overall spectral differences were observed at wave numbers 1618 cm−1, 1679 cm−1 (amino acids). Peaks at 3030 cm−1 (NH4+) and 940 cm−1 (O–H of carboxylic acids) showed high absorbance in patients compared to controls. Liquid-chromatography–mass spectrometry (LC–MS/MS) was used to quantify amino acids in the urine samples and the results indicated a significant increase of amino acid cystine (P = 0.012). Lysine and tyrosine also increased in patients compared to controls. The use of IR-PCA differentiated clusters of urine samples from patients with malaria from control and the demonstrated amino acid perturbation is consistent with malaria infection. This data provides baseline information for application in development of a non-invasive diagnostic tests for malaria.Article HighlightsInfrared (IR) spectroscopy and Principle Component Analysis (PCA) were used to differentiate urine of malaria patients from controls.LC–MS/MS was used to determine creatinine, tyrosine, cystine, lysine and histidine in urine from malaria patients and controlsThe average concentration of cystine in patients and controls urine differed significantly. Publicly Available Content Database