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Updated: Jun 16, 2025

In Situ Detection and Single Cell Quantification of Metal Oxide Nanoparticles Using Nuclear Microprobe Analysis
Published on: February 3, 2018
Distinct Features of Proton-Induced X-ray Emission (PIXE) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS)
Kristina M Zierold1, Melissa J Smith2, Jason Xu3
1Department of Environmental Health Sciences, School of Public Health, University of Alabama at Birmingham, RPHB 534 C, 1720 2nd Ave S, Birmingham, AL, 35294-0022, USA. kzierold@uab.edu.
Abstract:
Biomarkers, such as toenails, are commonly used to investigate the health status of individuals. Nails samples are a useful marker of exposure, as they are easy to collect, store, and represent exposure from 6 to 12 months. There are multiple analytical methods that can be used to extract long-term exposure profiles from toenails including Proton-Induced X-Ray Emission(PIXE) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The overall goal of this research was to evaluate the level of agreement between the two analytical methods for assessment of different metals in nail samples. Children's nail samples were collected. Nail samples were first analyzed by PIXE and then analyzed by ICP-MS. To compute quantiles for the metal concentrations that had some fully observed and some left-censored concentrations, a reverse Kaplan-Meier estimator was used. Lin's concordance correlation coefficient (CCC) and the Pearson correlation coefficient were calculated to assess agreement between the two methods and to determine the strength of the linear association between the metal concentration measurements obtained under each analytical technique. PIXE and ICP-MS determined similar median concentrations for calcium, copper, potassium, and nickel. However, there were stark differences between other elements. Several elements, such as copper, potassium, and zinc represented strong concordance through use of the CCC. In many studies, scholars want to evaluate how well one measurement can reproduce another, and our paper used several elements to show the degree of reproducibility between the two analytical methods. This can be useful when scholars are determining methods to assess biomarkers in health-related studies.
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