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Three-dimensional spectrochromatographic determination of chlorogenic acid in Melampyrum stenophyllum Boiss. extracts by parallel factor analysis

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PHYTOCHEMICAL analysis 2025年第1期36卷 279-288页

作者： Ertekin, Zehra Ceren Koroglu, Aysegul Dinc, Erdal Ankara Univ Fac Pharm Dept Analyt Chem TR-06560 Yenimahalle Ankara Turkiye Hacettepe Univ Fac Pharm Dept Pharmaceut Bot Yenimahalle Turkiye

Introduction:Co-elution is a common challenge in phytochemical chromatography. Full chromatographic separation often requires extensive optimization, long analysis times, and excessive solvent use. A viable alternative could be mathematical elution of analytes using three-dimensional decomposition. Objectives:This study aimed to develop a method to determine chlorogenic acid in Melampyrum stenophyllum Boiss. extracts without complete chromatographic separation, to validate the method, and to cross-validate assay results against a classical ultra-performance liquid chromatography (UPLC) method. Methodology:Ultra-performance liquid chromatography-photodiode array (UPLC-PDA) spectrochromatograms were arranged into a three-way data cube with dimensions of time, wavelength, and sample and then decomposed using parallel factor analysis to reveal chromatographic, spectral, and concentration profiles. The chromatographic and spectral profiles were used to identify chlorogenic acid in overlapping signals. The relative concentration profile was used to quantify it in the plant extract. The assay results were statistically compared with those from an in-house classical UPLC method. Results:Chlorogenic acid was co-eluted at 1.45 min and quantified as 16.11 mg per gram dry weight of Melampyrum stenophyllum extracts (SD = 0.28), despite significant interference in a 4-min runtime. The analytical validity was confirmed by recovery calculations from standard solutions and standard addition samples (RSD < 2%), and the t-test resulted in a p-value of 0.09 (alpha = 0.05), indicating no significant difference between the results obtained from mathematical elution and chromatographic separation. Conclusion:Chlorogenic acid was quantified from plant material accurately despite the co-elution. Validation and cross-validation results support the method's applicability.

关键词： chemometrics chlorogenic acid co-elution natural products parallel factor analysis UPLC

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parallel factor analysis of fluorescence EEM spectra to identify THM precursors in lake waters

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2010年第1-4期161卷 71-81页

作者： Hua, Bin Veum, Kristen Yang, John Jones, John Deng, Baolin Lincoln Univ Missouri Ctr Environm Sci Jefferson City MO 65102 USA Univ Missouri Dept Fisheries & Wildlife Sci Columbia MO 65211 USA Univ Missouri Dept Civil & Environm Engn Columbia MO 65211 USA

Dissolved organic matter (DOM) can react with chlorine and yield undesirable disinfection byproducts (DBPs), e.g., trihalomethanes (THMs). Numerous studies have demonstrated that various DOM constituents have DBP formation potentials. We explored in this study the use of fluorescence excitation-emission (EEM) spectroscopy to identify THM precursors in 55 lakes in Missouri, USA. EEMs of the lake waters were decomposed into five factors of different origins through parallel factor analysis. The correlations between the component scores of the factors and THM formation potentials reveal that factors 1 and 2 are likely THM precursors and provided better surrogates than SUVA (dissolved organic carbon-normalized UV254) for predicting DBP formation potential. Thus, monitoring the component scores of the DOM-origin factors would provide a practical tool to identify THM precursors and facilitate utilities to choose appropriate techniques for DBP mitigation and optimize the degree of water treatment.

关键词： Fluorescence Excitation-emission matrix parallel factor analysis Disinfection byproduct Water quality assessment

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parallel factor analysis and trilinear partial least squares applied to the UPLC-PDA data array for the quantification of brimonidine tartrate and timolol maleate in an eye drop formulation

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JOURNAL OF LIQUID CHROMATOGRAPHY & RELATED TECHNOLOGIES 2016年第7期39卷 374-383页

作者： Dinc, Erdal Buker, Eda Ankara Univ Fac Pharm Dept Analyt Chem TR-06100 Ankara Turkey

Simultaneous quantification of brimonidine tartrate (BRI) and timolol maleate (TIM) in an eye drop formulation was performed by applying parallel factor analysis (PARAFAC) and trilinear (three way) partial least squares to the ultra performance liquid chromatography-photodiode array (UPLC-PDA) data array. In PARAFAC and 3 W-PLS1 applications, the co-elution of the related compounds in their chromatograms obtained in the presence of ornidazole as an internal standard (IS) was resolved, and then analyses were performed. On the other hand, a new conventional ultra performance liquid chromatography (UPLC) method was developed after long and tedious studies to get desirable elution of BRI and TIM in a chromatogram using different column and mobile phase system than that of chromatographic conditions of PARAFAC and 3 W-PLS1 applications. The performance and validity of all the proposed methods were confirmed by analyzing independent validation samples consisting of synthetic mixture, intraday and interday samples, and standard addition samples. analysis results of BRI and TIM in eye drop samples by chemometric PARAFAC and 3 W-PLS1, and conventional UPLC were statistically compared to each other. It was concluded that PARAFAC and 3 W-PLS1 have shortest analysis time and lower cost than the developed conventional UPLC method for the analysis of the related compounds in commercial eye drop preparation with adequate selectivity and sensitivity.

关键词： Brimonidine tartrate eye drop formulation parallel factor analysis trilinear partial least squares timolol maleate ultra-performance liquid chromatography

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parallel factor analysis for monitoring data from a grape harvest in Qualified Designation of Origin Rioja including spatial and temporal variability

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2015年 146卷 347-353页

作者： Melendez, E. Sarabia, L. A. Ortiz, M. C. Estn Enol Haro Haro 26200 La Rioja Spain Univ Burgos Fac Ciencias Dept Quim Burgos 9001 Spain Univ Burgos Fac Ciencias Dept Matemat & Computac Burgos 9001 Spain

The proper ripening of grapes is the key to obtain a high-quality wine. Ripening is a temporal process that is influenced, in addition to uncontrollable climate factors, by the spatial distribution of the vineyard and planted variety. It is a complex process that cannot be characterized by a single parameter;rather, it is a modification of the profile of the compounds of the grape. This paper analyzes the joint evolution of twelve physicochemical parameters determined in red grapes from four different varieties, in sixteen representative (in both geographical and edaphic point of view) plots belonging to the Qualified Designation of Origin (DOC) Rioja. Samples were collected in September 2009 during four consecutive weeks prior to harvest. The data are naturally structured in a three-dimensional cube of data (named tensor) with these profiles: sample (plot/variety), physicochemical, and temporal. For the first time, studies are made for jointly analyzing the effect of the spatial and temporal distribution on the physicochemical profile of the grape. A PARAFAC model shows an internal data structure that accurately reproduces the ripening process with its distinctive features according to plot/variety, evolution of the physicochemical parameter of grapes, and ripening time. PARAFAC analysis reveals the different grape maturity depending on the vineyard's situation (zone and altitude) and the grape variety (garnacha, tempranillo, graciano, mazuelo). The obtained information allows evaluating the attainable quality in the grape related to the potential of the zone and its variety. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Three-way data parallel factor analysis Grape quality Maturation Qualified Designation of Origin Rioja Variability among vineyards

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parallel factor analysis and multivariate curve resolution as data fusion tools to supervise a stream

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2014年 137卷 120-127页

作者： Garcia-Reiriz, Alejandro G. Univ Nacl Rosario Fac Ciencias Bioquim & Farmaceut Dept Quim Analit Inst Quim Rosario IQUIR CONICET Suipacha 531S2002LRK RA-2000 Rosario Santa Fe Argentina

In this work, a new method is proposed to monitor the distribution, evolution and correlation of dissolved organic matter on the superficial water of a stream with respect to physicochemical variables that characterize the basin and season sampling of each campaign. The method is based on measuring fluorescence emission-excitation matrices and some physicochemical parameters of water samples through both time and space. In a first phase, parallel factor analysis (PARAFAC) or multivariate curve resolution with alternating least-squares (MCR-ALS) were applied to extract the information on the relative proportions of each fluorophore on each sample. Then, MCR-ALS was applied again to the entire database, in order to study the spatial and time distribution. This methodology was used to study the behavior of a basin stream that is significantly modified by anthropic activities. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Chemometrics Multivariate curve resolution parallel factor analysis Environmental monitoring

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parallel factor analysis for multidimensional decomposition of functional near-infrared spectroscopy data

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NEUROPHOTONICS 2022年第4期9卷 45004页

作者： Husser, Alejandra Caron-Desrochers, Laura Tremblay, Julie Vannasing, Phetsamone Martinez-Montes, Eduardo Gallagher, Anne St Justine Univ Hosp Neurodev Opt Imaging Lab LIONlab Res Ctr Montreal PQ Canada Univ Montreal Dept Psychol Montreal PQ Canada Cuban Neurosci Ctr CNEURO Havana Cuba

Significance: Current techniques for data analysis in functional near-infrared spectroscopy (fNIRS), such as artifact correction, do not allow to integrate the information originating from both wavelengths, considering only temporal and spatial dimensions of the signal's structure. parallel factor analysis (PARAFAC) has previously been validated as a multidimensional decomposition technique in other neuroimaging fields. Aim: We aimed to introduce and validate the use of PARAFAC for the analysis of fNIRS data, which is inherently multidimensional (time, space, and wavelength). Approach: We used data acquired in 17 healthy adults during a verbal fluency task to compare the efficacy of PARAFAC for motion artifact correction to traditional two-dimensional decomposition techniques, i.e., target principal (tPCA) and independent component analysis (ICA). Correction performance was further evaluated under controlled conditions with simulated artifacts and hemodynamic response functions. Results: PARAFAC achieved significantly higher improvement in data quality as compared to tPCA and ICA. Correction in several simulated signals further validated its use and promoted it as a robust method independent of the artifact's characteristics. Conclusions: This study describes the first implementation of PARAFAC in fNIRS and provides validation for its use to correct artifacts. PARAFAC is a promising data-driven alternative for multidimensional data analyses in fNIRS and this study paves the way for further applications. (c) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 International License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

关键词： near-infrared spectroscopy multidimensional decomposition parallel factor analysis canonical decomposition artifact correction language paradigm

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"parallel factor analysis of multi-excitation ultraviolet resonance Raman spectra for protein secondary structure determination"

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ANALYTICA CHIMICA ACTA 2015年 892卷 59-68页

作者： Oshokoya, Olayinka O. Jiji, Renee D. Univ Missouri Dept Chem Columbia MO 65211 USA

Protein secondary structural analysis is important for understanding the relationship between protein structure and function, or more importantly how changes in structure relate to loss of function. The structurally sensitive protein vibrational modes (amide I, II, III and S) in deep-ultraviolet resonance Raman (DUVRR) spectra resulting from the backbone C-O and N-H vibrations make DUVRR a potentially powerful tool for studying secondary structure changes. Experimental studies reveal that the position and intensity of the four amide modes in DUVRR spectra of proteins are largely correlated with the varying fractions of alpha-helix, beta-sheet and disordered structural content of proteins. Employing multivariate calibration methods and DUVRR spectra of globular proteins with varying structural compositions, the secondary structure of a protein with unknown structure can be predicted. A disadvantage of multivariate calibration methods is the requirement of known concentration or spectral profiles. Second-order curve resolution methods, such as parallel factor analysis (PARAFAC), do not have such a requirement due to the "second-order advantage." An exceptional feature of DUVRR spectroscopy is that DUVRR spectra are linearly dependent on both excitation wavelength and secondary structure composition. Thus, higher order data can be created by combining protein DUVRR spectra of several proteins collected at multiple excitation wavelengths to give multi-excitation ultraviolet resonance Raman data (ME-UVRR). PARAFAC has been used to analyze ME-UVRR data of nine proteins to resolve the pure spectral, excitation and compositional profiles. A three factor model with non-negativity constraints produced three unique factors that were correlated with the relative abundance of helical, beta-sheet and poly-proline II dihedral angles. This is the first empirical evidence that the typically resolved "disordered" spectrum represents the better defined poly-proline II type structure.

关键词： parallel factor analysis Ultraviolet resonance Raman Protein secondary structure Multiway Trilinear

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parallel factor analysis of gait waveform data: A multimode extension of Principal Component analysis

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HUMAN MOVEMENT SCIENCE 2012年第3期31卷 630-648页

作者： Helwig, Nathaniel E. Hong, Sungjin Polk, John D. Univ Illinois Dept Psychol Champaign IL 61820 USA Univ Illinois Dept Stat Champaign IL 61820 USA Univ Illinois Dept Anthropol Urbana IL 61801 USA Univ Illinois Dept Surg Urbana IL 61801 USA

Gait data are typically collected in multivariate form, so some multivariate analysis is often used to understand interrelationships between observed data. Principal Component analysis (PCA), a data reduction technique for correlated multivariate data, has been widely applied by gait analysts to investigate patterns of association in gait waveform data (e.g., interrelationships between joint angle waveforms from different subjects and/or joints). Despite its widespread use in gait analysis, PCA is for two-mode data, whereas gait data are often collected in higher-mode form. In this paper, we present the benefits of analyzing gait data via parallel factor analysis (Parafac), which is a component analysis model designed for three- or higher-mode data. Using three-mode joint angle waveform data (subjects x time x joints), we demonstrate Parafac's ability to (a) determine interpretable components revealing the primary interrelationships between lower-limb joints in healthy gait and (b) identify interpretable components revealing the fundamental differences between normal and perturbed subjects' gait patterns across multiple joints. Our results offer evidence of the complex interconnections that exist between lower-limb joints and limb segments in both normal and abnormal gaits, confirming the need for the simultaneous analysis of multi-joint gait waveform data (especially when studying perturbed gait patterns). (C) 2011 Elsevier B.V. All rights reserved.

关键词： Walking Locomotion Multivariate analysis Principal Component analysis parallel factor analysis

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parallel factor analysis of spider fluorophores

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JOURNAL OF PHOTOCHEMISTRY AND PHOTOBIOLOGY B-BIOLOGY 2008年第3期93卷 149-154页

作者： Reed, Scott M. Do, My-Trinh Masta, Susan E. Portland State Univ Dept Chem Portland OR 97207 USA Portland State Univ Dept Biol Portland OR 97207 USA

Fluorophores from the hemolymph of yellow sac spiders (Cheiracanthium mildei) have been characterized using excitation emission matrix (EEM) fluorescence spectroscopy. This approach provides characterization of fluorophores present in the organism without having to isolate pure samples. Minimal variation occurs between individual samples and each EEM has two distinct peaks, suggesting two fluorophores may be present in the hemolymph. parallel factor analysis reveals that three fluorophores (with excitation and emission maxima at 270/319, 330/389, and 350/465 nm) best explains the sample to sample variation. By comparing the spectra of the three individual components to fluorophores found in scorpions it is shown that these spiders possess different fluorophores than scorpions. Furthermore, the fluorescence observed is not consistent with beta-carboline or 4-methyl-7-hydroxycoumarin, two compounds previously described in scorpions. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Fluorescence Chemometric Biological fluorophore Spider Trilinear data analysis parallel factor analysis

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parallel factor analysis in the Study of Event-Related Potentials

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Human Physiology 2019年第3期45卷 233-241页

作者： Ponomarev, V.A. Pronina, M.V. Kropotov, Yu. D. Bechtereva Institute of the Human Brain Russian Academy of Sciences St. Petersburg Russian Federation

Abstract: The study evaluated whether a parallel factor analysis model is adequate and efficient in describing the event-related potentials (ERPs). ERPs evoked in a visual Go/NoGo task were recorded in 351 healthy subjects aged 18–55 years. The parallel factor analysis made it possible to separate the ERP components that differed in topography and waveform;the latter components proved to depend on the type of a subject’s response. The magnitudes of the components were individual, varied among subjects, and were mutually uncorrelated. Based on our results, the parallel factor analysis was concluded to provide an adequate approach for describing common characteristics and individual features of ERPs. © 2019, Pleiades Publishing, Inc.

关键词： event-related potentials Go/NoGo task parallel factor analysis

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