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Journal of Spectroscopy publishes research into the theory and application of spectroscopy across all disciplines, including biology, chemistry, engineering, earth sciences, medicine, materials science, physics, and space science.
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Discrimination of Melanoma Using Laser-Induced Breakdown Spectroscopy Conducted on Human Tissue Samples
Discrimination and identification of melanoma (a kind of skin cancer) by using laser-induced breakdown spectroscopy (LIBS) combined with chemometrics methods are reported. The human melanoma and normal tissues are used in the form of formalin-fixed paraffin-embedded (FFPE) blocks as samples. The results demonstrated higher LIBS signal intensities of phosphorus (P), potassium (K), sodium (Na), magnesium (Mg), and calcium (Ca) in melanoma FFPE samples while lower signal intensities in normal FFPE tissue samples. Chemometric methods, artificial neural network (ANN), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and partial least square discriminant analysis (PLS-DA) are used to build the classification models. Different preprocessing methods, standard normal variate (SNV), mean-centering, normalization by total area, and autoscaling, were compared. A good performance of the model (sensitivity, specificity, and accuracy) for melanoma and normal FFPE tissues has been achieved by the ANN and PLS-DA models (all were 100%). The results revealed that LIBS combined with chemometric methods for detection and discrimination of human malignancies is a reliable, accurate, and precise technique.
The Vibrational Spectroscopy of the Valence Bonds of Cu-Doped TiO2 Using Electronegativity Principle Quantitative Calculations
The purpose of this study is to investigate the influence of Cu on TiO2 phase transformation and regioselectivity. TiO2 samples doped with different amounts of Cu2+ ions were synthesized by the sol-gel method. The phase and vibrational mode were characterized by X-ray diffraction (XRD), Fourier infrared spectroscopy (FTIR), and transmission electron microscope (TEM). The XRD phase analysis shows that the lattice parameters have not changed after Cu incorporation. In addition, the content of rutile increased obviously after Cu doping. This indicated that the addition of Cu obviously promoted the transformation from anatase phase to rutile phase. The vibration frequencies were calculated based on the principle of electronegativity. All types of bonds were qualitatively and quantitatively analyzed. The content of TiA-O, TiR-O, and H-O in the undoped TiO2 samples is 23.87%, 16.30%, and 7.41%, respectively. In the same way, the content of TiA-O, TiR-O, H-O, -O, and -O in the 2.5 mol%Cu-doped TiO2 samples is 21.23%, 18.56%, 7.34%, and 0.98%, respectively. For the 5 mol%Cu-doped TiO2 samples, the content of TiA-O, TiR-O, H-O, -O, -O, -O, and -O is 18.75%, 20.11%, 7.47%, 2.56%, 3.9%, 1.55%, and 2.35%, respectively. Cu was not present at substitutional sites in the 2.5 mol% doped sample, but Cu was present in the 2.5 mol% doped sample. It is indicated that Cu was more likely to exist in the form of interstitial position in the TiO2 lattice, with the number of Cu atoms in the interstitial position reaching saturation, and this forced Cu to replace Ti. The TEM shows that the stripes of different periods and orientations overlapped each other to form the Moiré patterns. In addition, the diffraction patterns of the Moiré image were slightly different from that of the matrix. The Cu replaced Ti position and the Cu atoms mixed into interstitial sites in the TiO2 lattice. The theoretical calculation was consistent with the experimental results.
Rapid and Nondestructive On-Site Classification Method for Consumer-Grade Plastics Based on Portable NIR Spectrometer and Machine Learning
The classification of plastic waste before recycling is of great significance to achieve effective recycling. In order to achieve rapid, nondestructive, and on-site detection, a portable near-infrared spectrometer was used in this study to obtain the diffuse reflectance spectrum for both standard and commercial plastics made by ABS, PC, PE, PET, PP, PS, and PVC. After applying a series of pretreatments, the principal component analysis (PCA) was used to analyze the cluster trend. K-nearest neighbor (KNN), support vector machine (SVM), and back propagation neural network (BPNN) classification models were developed and evaluated, respectively. The result showed that different plastics could be well separated in top three principal components space after pretreatment, and the classification models performed excellent classification results and high generalization capability. This study indicated that the portable NIR spectrometer, integrated with chemometrics, could achieve excellent performance and has great potential in the field of commercial plastic identification.
Simultaneous Determination of Caffeine and Taurine in Energy Drinks by FT-MIR Spectroscopy Coupled with Multivariate Analysis
Energy drinks have been studied due to their damaging side effects on the health of their consumers when consumed in excess or when combined with alcohol. Our objective was to develop chemometric models, based on Fourier-transform mid-infrared (FT-MIR) spectroscopy, to quantify the taurine and caffeine content in energy drinks rapidly and simultaneously. The taurine and caffeine content in the 50 samples ranged between 0 and 69.51 mg/100 mL and 14.92 and 1126.17 mg/100 mL, respectively. The best prediction model was obtained with the partial least squares (PLS1) algorithm; for taurine, the following values were obtained: determination coefficient of calibration (Rc2) = 0.9999, standard error of calibration (SEC) = 0.15, determination coefficient of validation (Rv2) = 0.9997, and standard error of prediction (SEP) = 0.16; for caffeine, Rc2 = 0.9999, SEC = 0.26, Rv2 = 0.9999, and SEP = 0.32. The model developed with PLS1 showed certainty in predictions during the validation stage and during application to external samples. FT-MIR coupled to chemometrics is a reliable and fast technique (compared to conventional techniques) to quantify taurine and caffeine in energy drinks simultaneously.
Characterization of Dielectric Relaxation Process by Impedance Spectroscopy for Polymers: Nitrile Butadiene Rubber and Ethylene Propylene Diene Monomer
We invented a dispersion analysis program that analyzes the relaxation processes from dielectric permittivity based on a combination of the Havriliak–Negami and conductivity contribution functions. By applying the created program to polymers such as nitrile butadiene rubber (NBR) and ethylene propylene diene monomer (EPDM), several relaxation processes were characterized: an α process due to segmental motions of the C-C bond, an α′ process attributed to fluctuations in the end-to-end dipole vector of the polymer chain, the conduction contribution by the filler observed above room temperature, and secondary relaxation processes β and γ of motion for the side group in NBR. In the EPDM specimen, the β process associated with the rotational motion of the side groups, the α process associated with the relaxation of local segmental motion, and the αβ process associated with the origin of the β process at high temperatures above 305 K were observed. The Maxwell–Wagner–Sillars effect and conduction contribution were also presented. The molecular chains responsible for the relaxation processes were assigned by building molecular models of the two polymers. The temperature dependence of the relaxation strength and the shape parameters that characterize the process were investigated. From the temperature-dependent relaxation analysis, the merged αβ process, activation energy, and glass transition temperature were determined and compared.
Chemometrics-Enabled Raman Spectrometric Qualitative Determination and Assessment of Biochemical Alterations during Early Prostate Cancer Proliferation in Model Tissue
The use of Raman spectroscopy combined with multivariate chemometrics for disease diagnosis has attracted great attention from researchers in recent years. This is because it is a noninvasive and nondestructive detection approach with enhanced sensitivity. However, a major challenge when analyzing spectra from biological samples has been the detection of subtle biochemical alterations buried in background and fluorescence noise. This work reports a qualitative chemometrics-assisted investigation of subtle biochemical alterations associated with prostate malignancy in model biological tissue (metastatic androgen insensitive (PC3) and immortalized normal (PNT1a) prostate cell lines). Raman spectra were acquired from PC3 and PNT1a cells at various stages of growth, and their biochemical alterations were determined from difference spectra between the two cell lines (for prominent alterations) and principal component analysis (PCA) (for subtle alterations). The Raman difference spectra were computed by subtracting the normalized mean spectral intensities of PNT1a cells from the normalized mean spectral intensities of PC3 cells. These difference spectra revealed prominent biochemical alterations associated with the malignant PC3 cells at 566 ± 0.70 cm−1, 630 cm−1, 1370 ± 0.86 cm−1, and 1618 ± 1.73 cm−1 bands. The band intensity ratios at 566 ± 0.70 cm−1 and 630 cm−1 suggested that prostate malignancy can be associated with an increase in relative amounts of nucleic acids and lipids, respectively, whereas those at 1370 ± 0.86 cm−1 and 1618 ± 1.73 cm−1 suggested that prostate malignancy can be associated with a decrease in relative amounts of saccharides and tryptophan, respectively. In the analysis using PCA, intermediate-order and high-order principal components (PCs) were used to extract the subtle biochemical fingerprints associated with the cell lines. This revealed subtle biochemical differences at 1076 cm−1, (1232, 1234 cm−1), (1276, 1278 cm−1), (1330, 1333 cm−1), (1434, 1442 cm−1), and (1471, 1479 cm−1). The band intensity ratios at 1076 cm−1 and 1232 cm−1 suggested that prostate malignancy can be associated with an increase in subtle amounts of nucleic acids and amide III components, respectively. The method reported here has demonstrated that subtle biochemical alterations can be extracted from Raman spectra of normal and malignant cell lines. The identified subtle bands could play an important role in quantitative monitoring of early biomarker alterations associated with prostate cancer proliferation.