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A novel algorithm for second-order calibration of three-way data in fluorescence assays of multiple breast cancer-related DNAs
摘要： Fluorescent probes have been valuable tools for bioanalytical multiplex assays. However, as a common phenomenon in multiplex fluorescence assays, spectral overlap usually leads to difficulty in spectral analysis for multiple analytes. Although multiway calibrations have provided mathematic approaches for complex spectral analysis, it remains a grand challenge for these methods in practical applications because of the problems such as prior rank estimation. Herein, we report a novel second-order calibration algorithm of alternating residual trilinearization (ART) for the decomposition of complex spectra generated from multiplex fluorescence assays. By alternating iterative convergence to the spectral profiles of each component in convergence process, ART enables automatic rank estimation for second-order calibration, thus able to avoid the risk of chemical meaningless fitting of component spectra. Combined with fluorescence excitation-emission matrix (EEM) spectroscopy, the performance of ART has been demonstrated by a simulated example and an analytical experiment performed using molecular beacons (MBs) for the simultaneous assay of three breast cancer related DNA targets. The results revealed that the proposed algorithm is capable of automatic estimating the number of underlying components during its convergence process to produce acceptable performance in spectral profile resolution and concentration estimation. Compared with other existing iterative trilinear decomposition strategies such as parallel factor analysis (PARAFAC) requiring a prior rank estimation, the proposed ART therefore provides a robust second-order calibration strategy for complex spectral analysis in multiplex fluorescence assays.
关键词： Alternating residual trilinearization (ART),Molecular beacon,Fluorescence spectroscopy,Second-order calibration,Multiplex assay
更新于2025-09-10 09:29:36
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D-Optimal Design and PARAFAC as Useful Tools for the Optimisation of Signals from Fluorescence Spectroscopy Prior to the Characterisation of Green Tea Samples
摘要： A procedure based on a D-optimal design coupled with PARAFAC was proposed to optimise signals from molecular fluorescence spectroscopy to obtain the best experimental conditions for the achievement of the best fluorescence signal of green tea samples. Excitation-emission signals (EEMs) were used to analyse the liquid samples (tea infusions), whereas front-face fluorescence excitation-emission matrices (FFEEMs) were recorded for the solid samples (raw or powder tea leaves). The experimental effort was reduced considerably in both cases thanks to the D-optimal design. Once the optimal conditions have been found, the characterisation of green tea was carried out and the sensitivity and specificity were evaluated. The projection of the principal component analysis (PCA) scores enabled to differentiate among the types of liquid green tea (Chinese tea, Chinese tea with lemon and Indian tea with and without theine). The discrimination of solid green tea according to its geographical origin (Chinese, Indian and Japanese) was also carried out through PCA. In addition, the discrimination between the most expensive Japanese tea and the cheapest one was possible. The sensitivity of the models built with SIMCA was 100% and the specificity of the models for the Chinese tea with respect to the Japanese tea was also high.
关键词： Characterisation,Green tea,PCA,D-optimal design,Front-face fluorescence spectroscopy,PARAFAC
更新于2025-09-10 09:29:36
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Discrimination of several Indonesian specialty coffees using Fluorescence Spectroscopy combined with SIMCA method
摘要： Indonesia is one of the important producers of several specialty coffees, which have a particularly high economic value, including Civet coffee (‘kopi luwak’ in Indonesian language) and Peaberry coffee (‘kopi lanang’ in Indonesian language). The production of Civet and Peaberry coffee is very limited. In order to provide authentication of Civet and Peaberry coffee and protect consumers from adulteration, a robust and easy method for evaluating ground Civet and Peaberry coffee and detection of its adulteration is needed. In this study, we investigate the use of fluorescence spectroscopy combined with SIMCA (soft independent modelling of class analogies) method to discriminate three Indonesian specialty coffee: ground Peaberry, Civet and Pagar Alam coffee. Total 90 samples were used (30 samples for Civet, Peaberry and Pagar Alam coffee, respectively). All coffee samples were ground using a home-coffee- grinder. Since particle size in coffee powder has a significant influence on the spectra obtained, we sieved all coffee samples through a nest of U. S. standard sieves (mesh number of 40) on a Meinzer II sieve shaker for 10 minutes to obtain a particle size of 420 μm. The experiments were performed at room temperature (around 27-29°C). All samples were extracted with distilled water and then filtered. For each samples, 3 mL of extracted sample then was pipetted into 10 mm cuvettes for spectral data acquisition. The EEM (excitation-emission matrix) spectral data of coffee samples were acquired using JASCO FP-8300 Fluorescence Spectrometer. The principal component analysis (PCA) result shows that it is possible to discriminate types of coffee based on information from EEM (excitation-emission matrix) spectral data. Using SIMCA method, the discrimination model of Indonesian specialty coffee was successfully developed and resulted in high performance of discrimination with 100% of sensitivity and specificity for Peaberry, Civet and Pagar Alam coffee. This research has opened the possibility to develop a promising method to detect and evaluate authentication of Indonesian specialty coffees using fluorescence spectroscopy.
关键词： discrimination,Fluorescence Spectroscopy,authentication,Indonesian specialty coffee,SIMCA
更新于2025-09-10 09:29:36
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In vitro study of the demineralization induced in human enamel by an acidic beverage using X-ray fluorescence spectroscopy and Raman microscopy
摘要： This study was conducted with the purpose of evaluating the demineralization effect of a widely consumed acidic soft drink, Coca‐Cola?, in human enamel. This way, an in vitro model for the daily intake of this beverage was developed taking into account the intraoral environment. The evaluation of the enamel specimens was undertaken considering two approaches, the direct analysis of enamel surface and the study of specimens as cross sections. The depolarization ratio of the phosphate symmetric stretching band in Raman spectra was used to evaluate the loss of mineralization of the hydroxyapatite matrix, and the changes regarding the elemental content was performed using energy‐dispersive X‐ray fluorescence (EDXRF). For comparison, the Rayleigh‐to‐Compton ratio in EDXRF spectra of enamel samples was also determined in order to establish alterations in the average atomic number of the samples before and after erosive challenge. Considering the model applied and the timeframe of study, we determined evidences of demineralization after consumption of this drink. There was a significant increase of depolarization ratio in most of the analyzed specimens as well as a decrease of the concentration of major elements concomitant with apparent increase of the concentration of trace elements. Moreover, depths of demineralization of tens of micrometers were obtained with both spectroscopic techniques, showing consistency between the obtained results.
关键词： Raman microscopy,acidic beverage,demineralization,X‐ray fluorescence spectroscopy,human enamel
更新于2025-09-10 09:29:36
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Tea types classification with data fusion of UV–Vis, synchronous fluorescence and NIR spectroscopies and chemometric analysis
摘要： The potential of selected spectroscopic methods - UV-Vis, synchronous fluorescence and NIR as well a data fusion of the measurements by these methods - for the classification of tea samples with respect to the production process was examined. Four classification methods - Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Regularized Discriminant Analysis (RDA) and Support Vector Machine (SVM) - were used to analyze spectroscopic data. PCA analysis was applied prior to classification methods to reduce multidimensionality of the data. Classification error rates were used to evaluate the performance of these methods in the classification of tea samples. The results indicate that black, green, white, yellow, dark, and oolong teas, which are produced by different methods, are characterized by different UV-Vis, fluorescence, and NIR spectra. The lowest error rates in the calibration and validation data sets for individual spectroscopies and data fusion models were obtained with the use of the QDA and SVM methods, and did not exceed 3.3% and 0.0%, respectively. The lowest classification error rates in the validation data sets for individual spectroscopies were obtained with the use of RDA (12,8%), SVM (6,7%), and QDA (2,7%), for the UV-Vis, SF, and NIR spectroscopies, respectively. NIR spectroscopy combined with QDA outperformed other individual spectroscopic methods. Very low classification errors in the validation data sets - below 3% - were obtained for all the data fusion data sets (SF+UV-Vis, SF+NIR, NIR+UV-Vis combined with the SVM method). The results show that UV-Vis, fluorescence and near infrared spectroscopies may complement each other, giving lower errors for the classification of tea types.
关键词： Fluorescence spectroscopy,Food adulteration,NIR,Teas classification,Multivariate data analysis,Data fusion,UV-Vis
更新于2025-09-10 09:29:36
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Surface-enhanced Raman spectroscopy (SERS) in cotton fabrics analysis
摘要： This article presents some aspects of application the dispersive Micro-Raman Spectroscopy in textile fibers analysis. Research were dedicated to the methodology of surface enhancement Raman spectroscopy (SERS) studies on cotton fabric and possibility of its application in fibers characterization. Studies were carried out on dyed cotton fabrics modified by silver nanowires (AgNWs). Three reactive dyes (blue, yellow, red) and four color intensities (0.5%, 1%, 2% and 5%) were used. AgNWs colloid was deposited on undyed and dyed cotton fabrics by dipping and drying method. Dyed fabrics were examined by spectroscopic methods: FTIR ATR, Raman, UV-Vis Diffuse Reflectance Spectroscopy, Fluorescence Spectroscopy. Raman signal enhancement phenomena occurring on the silver nanoparticles increases the possibility of fiber and dye identification especially in the case of dyes used in cotton dyeing reveals fluorescence.
关键词： UV-Vis Diffuse Reflectance Spectroscopy,SERS,Fluorescence Spectroscopy,reactive dyes,FTIR ATR,Micro-Raman spectroscopy,Cotton fibers
更新于2025-09-09 09:28:46
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Spectral signatures of fluorescence and light absorption to identify crude oils found in the marine environment
摘要： To protect the natural marine ecosystem, it is necessary to continuously enhance knowledge of environmental contamination, including oil pollution. Therefore, to properly track the qualitative and quantitative changes in the natural components of seawater, a description of the essential spectral features describing petroleum products is necessary. This study characterises two optically-different types of crude oils (Petrobaltic and Romashkino) – substances belonging to multi-fluorophoric systems. To obtain the spectral features of crude oils, the excitation-emission spectroscopy technique was applied. The fluorescence and light absorption properties for various concentrations of oils at a stabilised temperature are described. Both excitation-emission spectra (EEMs) and absorption spectra of crude oils are discussed. Based on the EEM spectra, both excitation end emission peaks for the wavelength-independent fluorescence maximum (Exmax/Emmax) – characteristic points for each type of oil – were identified and compared with the literature data concerning typical marine chemical structures.
关键词： seawater,Excitation-emission spectra,fluorescence spectroscopy,oil pollution,absorption spectra
更新于2025-09-09 09:28:46