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• W3202091773 endingPage "130825" @default.
• W3202091773 startingPage "130825" @default.
• W3202091773 abstract "Adequate assessment of the level of organic acids (OA) in human urine is significant for non-invasive diagnosis and monitoring of OA-related diseases. However, the common lock-and-key sampling method for specific OA analysis is dramatically perturbed by the complicated chemical components in urine. A comprehensive qualitative and quantitative analysis of OAs in urine samples remains a significant challenge. Herein, a cross-reactive fluorescent sensor array based on amino acid-functionalized carbon nanodots (CDs) was designed for simultaneous qualitative and quantitative analysis of seven kinds of OAs, including homovanillic acid (HVA), vanillylmandelic acid (VMA), 3-hydroxyisovaleric acid (3-HA), lactic acid (LA), pyruvic acid (PA), glutaric acid (GA), and methylmalonic acid (MMA). The array system can specifically recognize multiple OAs in urine samples over a wide concentrations range (0.1–1000 μM) with 100% accuracy. The wide concentration range and high accuracy of the CD array system for OA analysis depend on a distinct fluorescence response from the differential binding affinity of various OAs to the CDs. The excellent recognition ability and selectivity of the sensing system were further confirmed by the double-blind and interference experiments. The sensor array achieved satisfactory distinguishing effects of separate OAs and binary OA samples (HVA/VMA) in urine samples. In particular, the quantitative analysis of the one-OA system or two-OA system (HVA/VMA) can be realized by the array system. These results confirm that the sensor array based on the CDs is an efficient platform for OA analysis and a convenient tool for the non-invasive diagnosis of OA-related diseases." @default.
• W3202091773 created "2021-10-11" @default.
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• W3202091773 date "2022-01-01" @default.
• W3202091773 modified "2023-09-30" @default.
• W3202091773 title "Fluorescent sensor array constructed by functionalized carbon nanodots for qualitative and quantitative analysis of urinary organic acids biomarkers" @default.
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• W3202091773 doi "https://doi.org/10.1016/j.snb.2021.130825" @default.
• W3202091773 hasPublicationYear "2022" @default.
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