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• W2891495520 abstract "Abstract Direct rapid energy dispersive X-ray fluorescence and scattering (EDXRFS) analysis of trace biometals in soft body tissues is important because it has an immense potential for biomedical applications. Unfortunately this is challenging because soft body tissues are characterized by dark matrix problems, weak analyte fluorescence, scattering, poor signal-to-noise ratio (SNR) of the analyte and spectral overlaps due to the properties of the detector and detection process. We report on hybridized utility of robust chemometrics approach for spectral preprocessing towards improving the quality of spectra towards quantitative analysis of trace biometals in soft body tissue. The study was based on (5–20 µm thick) paraffin wax model ‘standards’ spiked with biometals Fe, Cu, Mn, Zn, Co, Na and Mg. Wavelet transform (WT) and principal component analysis (PCA) were used conjointly for de-noising and mathematical enhancement of resolution. There was improved SNR of spectra by a factor of 3 compared to use of WT alone. The preprocessed spectra were used as input to artificial neural network (ANN) and partial least squares (PLS) models for developing multivariate calibration strategies for quantitative analysis. Both models predicted the concentrations of the biometals better than when raw spectra were utilized (R2 ~ 0.892–0.954 before, and ~ 0.990–0.998 after preprocessing for ANNs; and R2 ~ 0.876–0.931 before, and ~ 0.977–0.992 after preprocessing for PLS). There was also improvement in prediction of Na and Mg in model tissue when both fluorescence and scatter were utilized conjointly (EDXRFS) i.e. R2 = 0.970 for fluorescence alone and R2 = 0.998 for both fluorescence and scatter for Na; and R2 = 0.934 for fluorescence alone and R2 = 0.993 for both fluorescence and scatter for Mg for ANN model. The accuracy of the calibration model was tested using Oyster tissue (NIST 1566b). The results of all analyzed elements were in agreement with certified values to ≤ 6%. This shows proof-of-concept for use of hybridized robust chemometrics approaches for direct rapid determination of trace biometals in soft tissue utilizing EDXRFS spectrometry; an approach that has potential for biomedical applications of EDXRF." @default.
• W2891495520 created "2018-09-27" @default.
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• W2891495520 date "2018-12-01" @default.
• W2891495520 modified "2023-10-17" @default.
• W2891495520 title "Hybridized robust chemometrics approach for direct rapid determination of trace biometals in tissue utilizing energy dispersive X-ray fluorescence and scattering (EDXRFS) spectrometry" @default.
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• W2891495520 doi "https://doi.org/10.1016/j.radphyschem.2018.09.019" @default.
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