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  1. Article ; Online: Suppression of spectral interference in dual-elemental analysis of single particles using triple quadrupole ICP-MS.

    Chun, Ka-Him / Lum, Judy Tsz-Shan / Leung, Kelvin Sze-Yin

    Analytica chimica acta

    2022  Volume 1226, Page(s) 340258

    Abstract: Single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) was used in the analysis of single particles/cells. Although quadrupole mass analyzers are widely used, the long settling time restricts measurement to single elements in individual ...

    Abstract Single particle-inductively coupled plasma-mass spectrometry (SP-ICP-MS) was used in the analysis of single particles/cells. Although quadrupole mass analyzers are widely used, the long settling time restricts measurement to single elements in individual particles. Recently, dual-elemental analysis has successfully been developed with the assistance of oxygen gas in the collision cell. This simple approach greatly expands the capability of quadrupole-based ICP-MS. In this study, we adopted bandpass mode in the first quadrupole (Q1) to improve the limit of detection of single particles against spectral interference. A model was developed to explain the rationale behind the selection of quadrupole voltages. The quadrupole voltages were optimized systematically so that the mass bandwidth of Q1 allowed the transmission of two target analytes while the interference species were rejected. As a result, the signal from the polyatomic interference was reduced by 98% with no significant change in the analyte signal. The bandpass mode was further applied to accurately determine the isotope ratio of
    MeSH term(s) Isotopes ; Mass Spectrometry/methods ; Metal Nanoparticles ; Silver ; Spectrum Analysis
    Chemical Substances Isotopes ; Silver (3M4G523W1G)
    Language English
    Publishing date 2022-08-16
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1483436-4
    ISSN 1873-4324 ; 0003-2670
    ISSN (online) 1873-4324
    ISSN 0003-2670
    DOI 10.1016/j.aca.2022.340258
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Dual-elemental analysis of single particles using quadrupole-based inductively coupled plasma-mass spectrometry.

    Chun, Ka-Him / Lum, Judy Tsz-Shan / Leung, Kelvin Sze-Yin

    Analytica chimica acta

    2021  Volume 1192, Page(s) 339389

    Abstract: Single-particle inductively coupled plasma-mass spectrometry (SP-ICP-MS) is used for elemental analysis of single particles and biological cells. Time-of-flight (TOF) mass analyzers are widely used for multiple element analysis of individual particles. ... ...

    Abstract Single-particle inductively coupled plasma-mass spectrometry (SP-ICP-MS) is used for elemental analysis of single particles and biological cells. Time-of-flight (TOF) mass analyzers are widely used for multiple element analysis of individual particles. Owing to the sequential nature of the mass analyzer, quadrupole-based ICP-MS generally gives poor analytical performance when more than one element are being monitored. In this study, we present the first accurate and precise dual-mass measurement of individual particles using quadrupole-based ICP-MS, with the assistance of oxygen collision gas. Simultaneous measurement of the intensity of
    MeSH term(s) Isotopes ; Mass Spectrometry ; Metal Nanoparticles ; Silver ; Spectrum Analysis
    Chemical Substances Isotopes ; Silver (3M4G523W1G)
    Language English
    Publishing date 2021-12-21
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1483436-4
    ISSN 1873-4324 ; 0003-2670
    ISSN (online) 1873-4324
    ISSN 0003-2670
    DOI 10.1016/j.aca.2021.339389
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: A machine learning approach for early prediction of gestational diabetes mellitus using elemental contents in fingernails.

    Chan, Yun-Nam / Wang, Pengpeng / Chun, Ka-Him / Lum, Judy Tsz-Shan / Wang, Hang / Zhang, Yunhui / Leung, Kelvin Sze-Yin

    Scientific reports

    2023  Volume 13, Issue 1, Page(s) 4184

    Abstract: The aim of this pilot study was to predict the risk of gestational diabetes mellitus (GDM) by the elemental content in fingernails and urine with machine learning analysis. Sixty seven pregnant women (34 control and 33 GDM patient) were included. ... ...

    Abstract The aim of this pilot study was to predict the risk of gestational diabetes mellitus (GDM) by the elemental content in fingernails and urine with machine learning analysis. Sixty seven pregnant women (34 control and 33 GDM patient) were included. Fingernails and urine were collected in the first and second trimesters, respectively. The concentrations of elements were determined by inductively coupled plasma-mass spectrometry. Logistic regression model was applied to estimate the adjusted odd ratios and 95% confidence intervals. The predictive performances of multiple machine learning algorithms were evaluated, and an ensemble model was built to predict the risk for GDM based on the elemental contents in the fingernails. Beryllium, selenium, tin and copper were positively associated with the risk of GDM while nickel and mercury showed opposite result. The trained ensemble model showed larger area under curve (AUC) of receiver operating characteristic curve (0.81) using fingernail Ni, Cu and Se concentrations. The model was validated by external data set with AUC = 0.71. In summary, the results of the present study highlight the potential of fingernails, as an alternative sample, together with machine learning in human biomonitoring studies.
    MeSH term(s) Pregnancy ; Humans ; Female ; Diabetes, Gestational/diagnosis ; Nails ; Pilot Projects ; Copper ; Machine Learning
    Chemical Substances Copper (789U1901C5)
    Language English
    Publishing date 2023-03-14
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-31270-y
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Double-Viewing-Position Single-Particle Inductively Coupled Plasma-Atomic Emission Spectrometry for the Selection of ICP Sampling Position in SP-ICP Measurements.

    Chun, Ka-Him / Zhang, Hua / Chan, Wing-Tat

    Analytical sciences : the international journal of the Japan Society for Analytical Chemistry

    2018  Volume 34, Issue 6, Page(s) 711–717

    Abstract: Double-viewing-position single-particle inductively coupled plasma-atomic emission spectrometry (DVP-SP-ICP-AES) measures emission intensity at two ICP vertical positions simultaneously using a single photomultiplier tube. A particle travelling up the ... ...

    Abstract Double-viewing-position single-particle inductively coupled plasma-atomic emission spectrometry (DVP-SP-ICP-AES) measures emission intensity at two ICP vertical positions simultaneously using a single photomultiplier tube. A particle travelling up the ICP gives two consecutive temporal emission peaks. The Yb II 328.937-nm emission intensity of the two peaks for single Yb
    Language English
    Publishing date 2018
    Publishing country Japan
    Document type Journal Article
    ZDB-ID 1483376-1
    ISSN 1348-2246 ; 0910-6340
    ISSN (online) 1348-2246
    ISSN 0910-6340
    DOI 10.2116/analsci.18SBP11
    Database MEDical Literature Analysis and Retrieval System OnLINE

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