Search

The green-light driven photocatalytic N-deethylation reaction of Rhodamine B (RhB) on a TiO 2 film was investigated by UV-vis absorption and fluorescence emission spectroscopies, in addition to HPLC and HR-MS, to ascertain the nature of the reaction products. The evolution of the photocatalytic reaction was chemometrically analyzed using Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) of the spectroscopic data to obtain the kinetic and spectral decomposition of the RhB derivatives involved in the reaction. This was then compared with the results obtained by standard HPLC analysis. The MCR-ALS analysis yielded satisfactory spectral and kinetic profiles for RhB and the fully deethylated product, Rhodamine 110. However, the spectral profiles for the N-triethyl (3EtRh) and the mixture of the two isomeric N-diethyl (2EtRh) derivatives exhibited some spectral distortions due to significant spectral overlap between these compounds. In contrast to the HPLC analysis, the MCR-ALS could not resolve the N-ethylrhodamine (EtRh) derivative. The deethylation reactions occurred via independent zero-order steps at the surface of TiO 2 , indicating that the RhB degradation reaction is governed by the adsorption-desorption equilibrium of the dye and derivatives on the photocatalyst surface, thereby enhancing the diffusion of compounds on the surface., (© 2024 American Society for Photobiology.)

Background: Recent interest has been focused on the application of multivariate curve resolution-alternating least-squares (MCR-ALS) to systems involving the measurement of first-order and non-bilinear second-order data. The latter pose important challenges to bilinear decomposition models, due to the phenomenon of rotational ambiguity in the solutions, even under the application of the full set of chemical constraints that is usually employed in MCR-ALS calibration., Results: After the analysis of several simulated and experimental datasets, important conclusions regarding the role of the selectivity patterns in the constituent spectra have been drawn concerning the achievement of the second-order advantage. Theoretical considerations based on the calculation of the areas of feasible solutions helped to support the observations regarding the predictive ability of MCR- ALS in the various datasets., Significance: The understanding of the impact of rotational ambiguity in obtaining the second-order advantage with both first-order and non-bilinear second-order data is of paramount importance in the future development of analytical protocols of complex samples., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Across numerous investigations delved into second- and higher-order data, an undoubted finding emerges: models based on such data can effectively exploit the second-order advantage. However, whether further benefits can be achieved by modeling data of higher dimensions remains a subject of inquiry. In this regard, a prevailing question emerges in third-order data-based applications regarding the fundamental need to increase the data dimension and, hence, the data analysis complexity. This study aims to provide meaningful evidence to support the advantages inherent in employing third-order calibration methods despite the associated efforts, such as instrumentation and data analysis complexity., Results: This study compares the analytical performance achieved using a third-order calibration method with those obtained from most of the possible second-order calibration approaches derived from the same dataset. This work delves into the structural properties of the data, modeling limitations, and analytical characteristics associated with each model. Additionally, it includes a comprehensive statistical comparison of the models based on their recovery performance. First, the outcomes demonstrate the importance of capitalizing on all available chemical information and harnessing the full potential of data to maximize its benefits. Moreover, the results provide evidence that asserts the fact that third-order calibration methods bring the opportunity to increase the number of analytes that can be simultaneously determined, notwithstanding the need for more tedious experimental protocols, specialized instrumentation (sometimes), and quite complex data analysis., Significance: this research marks the first extensive comparison of third-order data calibration models with possible second-order calibration methods. Moreover, this work pioneers the incorporation of highly challenging non-multilinear data. The advancements detailed in this study emphasize the advantages of third-order data acquisition, notwithstanding the need for more tedious experimental protocols, specialized instrumentation (sometimes), and quite complex data analysis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The application of agrochemicals in citrus fruits is widely used to improve the quality of crops, increase production yields, and prolong post-harvest life. However, these substances are potentially toxic for humans and the ecosystem due to their widespread use, high stability, and bioaccumulation. Conventional techniques for determining pesticide residues in citrus fruits are chromatographic methods coupled with different detectors. However, in recent years, the need for analytical strategies that are less polluting for the environment has encouraged the appearance of new alternatives, such as sensors and biosensors, which allow selective and sensitive detection of pesticide residues in real time. A comprehensive overview of the analytical platforms used to determine pesticide residues in citrus fruits and citrus-derived products is presented herein. The review focuses on the evolution of these methods since 2015, their limitations, and possible future perspectives for improving pesticide residue determination and reducing environmental contamination., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

The aim of this study was to investigate uterine lesions, uterine endocrine status and expression of genes involved in uterine differentiation in a rat model of polycystic ovary syndrome (PCOS). The possible involvement of the androgen receptor (AR) was also investigated. PCOS rats showed an increased incidence of uterine epithelial and glandular lesions and elevated serum testosterone level, which was not detected in uterine tissue. Uterine 17β-estradiol, estrone and progesterone were detected in 100%, 75% and 50% of the animals, respectively. This was associated with a decrease in Star and an increase in Hsd17b2, Srd5a1 and Cyp19a1, suggesting that uterine steroids are not synthesized de novo in PCOS and that alterations in these enzymes may explain the absence of testosterone and low progesterone. In addition, ESR2 decreased and AR increased, suggesting possible steroid receptor crosstalk. Genes associated with uterine differentiation, PTEN and WNT5a, also showed reduced expression. PCOS rats treated with flutamide, an AR antagonist, were similar to PCOS rats in terms of uterine lesions, serum steroid levels, ESR2, PTEN and WNT5a expression. However, testosterone, AR and aromatase levels were similar to control rats, with decreased expression of ESR1 and HOXA10, suggesting that these expressions are AR dependent. Our results suggest that the primary cause of the observed uterine lesions in the PCOS rat model is the altered endocrine status and consequently changes in genes related to uterine differentiation., Competing Interests: Declaration of competing interest The authors declare that there are no conflicts of interest that could be perceived as prejudicing the impartiality of the research reported., (Copyright © 2024. Published by Elsevier B.V.)

Organic UV filters (UVFS) are used to mitigate the dermal effects associated with health risks from UV radiation, making them essential in personal care products. UVFS are frequently identified in environmental samples due to their high lipophilicity and persistence, underscoring the urgency of comprehensive assessments and regulatory measures aimed at safeguarding ecosystems and human health. The present study reports a multiclass analytical method for determining 16 UV sunscreens and metabolites in breast milk based on an ultrasound-assisted-dispersive liquid-liquid micro-extraction (UA-DLLME) with further chromatographic and chemometric resolution. The experimental conditions of the UA-DLLME were optimized through the implementation of the Design of Experiment tools. To model the responses, least-squares and artificial neural network methodologies were implemented. The optimal conditions were found by employing the desirability function. The samples were analyzed through reverse-phase liquid chromatographic separation, UV diode array, and fast-scanning fluorescence detection. The chromatographic analysis enabled the resolution of 16 analytes in a total time of 13.0 min. Multivariate curve resolution-alternating least-square (MCR-ALS) modelling was implemented to resolve analytes that were not fully resolved and to determine analytes that coeluted with endogenous components of the breast milk samples. An enrichment factor of 5-fold concentration was obtained with this methodology, reaching recoveries between 65 % and 105 % for 13 multiclass UV sunscreens and metabolites in breast milk samples with RSD % and REP % lower than 12 %., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

In this work, a four-way multivariate calibration method for the simultaneous determination of four pesticides - carbendazim (CBZ), thiabendazole (TBZ), pirimiphos-methyl (PMM), and clothianidin (CLT) - in lemon juice is presented. Third-order data were acquired by registering the photoinduced fluorescence of the analytes as excitation-emission matrices at different times of UV-light irradiation, in the presence of organized media (direct micelles) as fluorescence enhancers. The optimal experimental conditions (pH 11.5 and 32 mmol L -1 hexadecyltrimethylammonium chloride surfactant) were determined through a central composite design using the response surface methodology. The analytes were individually calibrated, except for TBZ and CBZ due to the inner filter effect of TBZ on CBZ. Test samples containing all analytes and imidacloprid (as potential interference) were analysed. PARAFAC was utilized to evaluate both the trilinearity and quadrilinearity of the third-order data and four-way arrays, respectively. PMM was successfully determined with quadrilinear PARAFAC decomposition, whereas CLT, TBZ, and CBZ were satisfactorily modelled using U-PLS/RTL due to the loss of quadrilinearity caused by different phenomena. The profitable applicability of the analytical method in the CBZ, TBZ, PMM, and CLT determination in lemon juice samples was demonstrated, achieving limits of detection below the maximum residue levels reported by the European Commission, and mean recoveries at 90 ± 5%., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

This study aimed to assess whether perinatal exposure to propiconazole (PRO), glyphosate (GLY) or their mixture (PROGLY) alters key endocrine pathways and the development of the male rat mammary gland. To this end, pregnant rats were orally exposed to vehicle, PRO, GLY, or a mixture of PRO and GLY from gestation day 9 until weaning. Male offspring were euthanized on postnatal day (PND) 21 and PND60. On PND21, GLY-exposed rats showed reduced mammary epithelial cell proliferation, whereas PRO-exposed ones showed increased ductal p-Erk1/2 expression without histomorphological alterations. On PND60, GLY-exposed rats showed reduced mammary gland area and estrogen receptor alpha expression and increased aromatase expression, whereas PRO-exposed ones showed enhanced lobuloalveolar development and increased lobular hyperplasia. However, PROGLY did not modify any of the endpoints evaluated. In summary, PRO and GLY modified the expression of key molecules and the development of the male mammary gland individually but not together., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

An external-cavity quantum cascade laser (EC-QCL)-based flow-through mid-infrared (IR) spectrometer was placed in line with a preparative size exclusion chromatography system to demonstrate real-time analysis of protein elutions with strongly overlapping chromatographic peaks. Two different case studies involving three and four model proteins were performed under typical lab-scale purification conditions. The large optical path length (25 μm), high signal-to-noise ratios, and wide spectral coverage (1350 to 1750 cm -1 ) of the QCL-IR spectrometer allow for robust spectra acquisition across both the amide I and II bands. Chemometric analysis by self-modeling mixture analysis and multivariate curve resolution enabled accurate quantitation and structural fingerprinting across the protein elution transient. The acquired concentration profiles were found to be in excellent agreement with the off-line high-performance liquid chromatography reference analytics performed on the collected effluent fractions. These results demonstrate that QCL-IR detectors can be used effectively for in-line, real-time analysis of protein elutions, providing critical quality attribute data that are typically only accessible through time-consuming and resource-intensive off-line methods.

In this review, recent advances and applications using multi-way calibration protocols based on the processing of multi-dimensional chromatographic data are discussed. We first describe the various modes in which multi-way chromatographic data sets can be generated, including some important characteristics that should be taken into account for the selection of an adequate data processing model. We then discuss the different manners in which the collected instrumental data can be arranged, and the most usually applied models and algorithms for the decomposition of the data arrays. The latter activity leads to the estimation of surrogate variables (scores), useful for analyte quantitation in the presence of uncalibrated interferences, achieving the second-order advantage. Recent experimental reports based on multi-way liquid and gas chromatographic data are then reviewed. Finally, analytical figures of merit that should always accompany quantitative calibration reports are described.

In this investigation, the fermentation step of a standard mammalian cell-based industrial bioprocess for the production of a therapeutic protein was studied, with particular emphasis on the evolution of cell viability. This parameter constitutes one of the critical variables for bioprocess monitoring since it can affect downstream operations and the quality of the final product. In addition, when the cells experiment an unpredictable drop in viability, the assessment of this variable through classic off-line methods may not provide information sufficiently in advance to take corrective actions. In this context, Process Analytical Technology (PAT) framework aims to develop novel strategies for more efficient monitoring of critical variables, in order to improve the bioprocess performance. Thus, in this work, a set of chemometric tools were integrated to establish a PAT strategy to monitor cell viability, based on fluorescence multiway data obtained from fermentation samples of a particular bioprocess, in two different scales of operation. The spectral information, together with data regarding process variables, was integrated through chemometric exploratory tools to characterize the bioprocess and stablish novel criteria for the monitoring of cell viability. These findings motivated the development of a multivariate classification model, aiming to obtain predictive tools for the monitoring of future lots of the same bioprocess. The model could be satisfactorily fitted, showing the non-error rate of prediction of 100%., (© 2021 American Institute of Chemical Engineers.)

Second-order based calibration methods have been widely investigated capitalizing on the inherent benefits of the data structure and the decomposition models, demonstrating that second-order advantage is a property that conspires to a high likelihood success in the resolution of systems of varying complexity. This work aims to demonstrate the applicability of a combined chemometric strategy to solve non-linear multivariate calibration systems in the presence of non-multilinear multi-way data. The determination of histamine by differential pulse voltammetry at different pH is presented as case study. The experimental system has the outstanding difficulty arisen from the large displacement along the potential axis by the pH, which was successfully overcome by implementation of the presented combined strategy. For data modeling, MCR-ALS, U-PLS/RBL and U-PCA/RBL-RBF were used. MCR-ALS allowed unraveling the non-linear behavior between the signal and the concentration, and extracting the underlying profiles of the constituent. Quantitative analysis was performed through the three models, and a comparative evaluation of the predictive performance was done. The best results were achieved with U-PCA/RBL-RBF (mean recovery = 101%) whereas, MCR-ALS yield the lowest mean recovery for all samples (70%)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

A novel external cavity-quantum cascade laser (EC-QCL)-based setup for mid-IR transmission spectroscopy in the amide I and amide II region was employed for monitoring pH-induced changes of protein secondary structure. pH titration of β-lactoglobulin revealed unfolding of the native β-sheet secondary structure occurring at basic pH. Chemometric analysis of the dynamic IR spectra was performed by multivariate curve resolution-alternating least squares (MCR-ALS). Using this approach, spectral and abundance distribution profiles of the conformational transition were obtained. A proper post-processing procedure was implemented allowing to extract information about pure protein spectra and spurious signals that may interfere in the interpretation of the system. This work demonstrates the potential and versatility of the EC-QCL-based IR transmission setup for flow-through applications, benefitting from the high available optical path length., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Multivariate curve resolution has been applied to both simulated and experimental data sets where high or even complete overlapping occurs between component profiles in one data mode. It is shown that rotational ambiguity exists in the bilinear decomposition of the augmented data matrices built with second-order data for pure analyte standards and test samples containing uncalibrated interferents. However, even in the presence of rotational ambiguity, initialization based on the so-called purest variables in one of the data modes may allow one to develop analytical protocols with reasonable statistical indicators for the prediction of the analyte of interest. In one of the explored experimental systems, the analyte ciprofloxacin was determined in the presence of the interferent salicylate, measuring time decay-luminescence matrix data. The average prediction error was 0.02 mg L -1 in the test set, corresponding to a relative error of ca. 8%. In the second system, capillary electrophoresis with UV detection was employed to determine ciprofloxacin in aqueous samples in the presence of other fluoroquinolones, achieving analyte recoveries in the range 101-113%. Although further theoretical work may still be needed, the present analysis of the feasible component profiles after bilinear decomposition provides some clues to interpret the phenomenon., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The latest advances in both theory and experimental procedures on third-order/four-way and fourth-order/five-way calibration methods are discussed. This report is focused on excitation-emission (fluorescence and phosphorescence) matrices generation, employing different variables as the third data mode (time retention in chromatography, pH gradient, fluorescence/phosphorescence lifetime, kinetics, or other chemical treatments). Fully capitalizing on the second-order advantage, it has been possible to develop appealing analytical applications in spite of the complexity of the data. Extraction of the significant chemical information about the system under study as well as the individual abundance of the contributing constituents after proper higher-order data decomposition has allowed to analytical researchers performing quantitative analysis of complex samples. The experimental works reported up to the present are introduced and discussed in order to illustrate concepts. Throughout this work, the analytical benefits achieved by modeling third- and fourth-order data are exposed, attempting to contribute to the ongoing debate in the chemometric community regarding the existence and the true nature of the third-order advantage., (Copyright © 2019 Elsevier B.V. All rights reserved.)

In this work, aiming at exploiting the essential particularities of modulation excitation spectroscopy (MES) coupled to phase sensitive detection (PSD) and chemometrics, a data analysis procedure was implemented to analyze phase-resolved infrared (IR) data. The fundamental principle of the proceedings is the application of successive multivariate curve resolution-alternating least squares (MCR-ALS) resolutions to MES-PSD IR data. The applicability of the strategy was evaluated in several cases of simulated data considering the effect of spectral band overlapping and presence of noise. Outcomes related to data-processing are depicted in detail. As a proof of concept, the data resolution approach was validated by resolving an experimental real system related to the adsorption-desorption dynamic of oxalic acid on titanium dioxide by in situ IR spectroscopy in attenuated total reflection (ATR) mode. After data resolution, different oxalate species were assigned to each spectral band and information about the kinetics in terms of phase lag was obtained. In the light of the obtained results, this approach is rather appealing in other research fields, very helpful for the non-chemometric community and foresees manifold applications, specially, in catalytic system investigations., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In this work, a direct in-flow methodology for the acquisition of excitation-emission fluorescence matrices is presented. The system is particularly suited for measurements in the order of tens of milliseconds. A light source operated in continuous mode is dispersed through a grating and focused onto a square-section capillary. Under the spatially resolved excitation, the emission is collected, dispersed through a second grating and further focused onto a CCD array sensor. To allow the wavelength accuracy, a spectral calibration was performed registering the scattering signal of a dispersive element using interference filters ranging from 340 nm to 740 nm. The theoretical performance of the method was analyzed and second-order data obtained for different analyte mixtures are presented and discussed. PARAFAC was applied to evaluate the trilinearity of the obtained data. Mathematical evaluation by means of the criterion of similarity corroborates the agreement between experimental pure spectra and spectral profiles retrieved from PARAFAC. Moreover, the feasibility of the spectrometer to obtain second-order data for analyses with quantitative aims was demonstrated. Finally, fast data acquisition was proved by monitoring a chromatographic analysis of dye mixtures for the generation of third-order LC-EEM data. Here, an improvement in the resolution of the different instrumental modes was demonstrated., (Copyright © 2018 Elsevier B.V. All rights reserved.)

The present study reports a sensitive chromatographic method for the analysis of seven fluoroquinolones (FQs) in environmental water samples, by coupling yttrium-analyte complex and three-way chromatographic data modeling. This method based on the use of HPLC-FSFD does not require complex or tedious sample treatments or enrichment processes before the analysis, due to the significant fluorescence increments of the analytes reached by the presence of Y(3+). Enhancement achieved for the FQs signals obtained after Y(3+) addition reaches 103- to 1743-fold. Prediction results corresponding to the application of MCR-ALS to the validation set showed relative error of prediction (REP%) values below 10% in all cases. A recovery study that includes the simultaneous determination of the seven FQs in three different environmental aqueous matrices was conducted. The recovery studies assert the efficiency and the accuracy of the proposed method. The LOD values calculated are in the order of part per trillion (below 0.5 ng mL(-1) for all the FQs, except for enoxacin). It is noteworthy to mention that the method herein proposed, which does not include pre-concentration steps, allows reaching LOD values in the same order of magnitude than those achieved by more sophisticated methods based on SPE and UHPLC-MS/MS., (Copyright © 2015 Elsevier B.V. All rights reserved.)

This paper reports the modeling of excitation-emission matrices for classification of Argentinean white wines according to the grape variety employing chemometric tools for pattern recognition. The discriminative power of the data was first investigated using Principal Component Analysis (PCA) and Parallel Factor Analysis (PARAFAC). The score plots showed strong overlapping between classes. A forty-one samples set was partitioned into training and test sets by the Kennard-Stone algorithm. The algorithms evaluated were SIMCA, N- and U-PLS-DA and SPA-LDA. The fit of the implemented models was assessed by mean of accuracy, sensitivity and specificity. These models were then used to assign the type of grape of the wines corresponding to the twenty samples test set. The best results were obtained for U-PLS-DA and SPA-LDA with 76% and 80% accuracy., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

In this work the Successive Projection Algorithm is presented for intervals selection in N-PLS for three-way data modeling. The proposed algorithm combines noise-reduction properties of PLS with the possibility of discarding uninformative variables in SPA. In addition, second-order advantage can be achieved by the residual bilinearization (RBL) procedure when an unexpected constituent is present in a test sample. For this purpose, SPA was modified in order to select intervals for use in trilinear PLS. The ability of the proposed algorithm, namely iSPA-N-PLS, was evaluated on one simulated and two experimental data sets, comparing the results to those obtained by N-PLS. In the simulated system, two analytes were quantitated in two test sets, with and without unexpected constituent. In the first experimental system, the determination of the four fluorophores (l-phenylalanine; l-3,4-dihydroxyphenylalanine; 1,4-dihydroxybenzene and l-tryptophan) was conducted with excitation-emission data matrices. In the second experimental system, quantitation of ofloxacin was performed in water samples containing two other uncalibrated quinolones (ciprofloxacin and danofloxacin) by high performance liquid chromatography with UV-vis diode array detector. For comparison purpose, a GA algorithm coupled with N-PLS/RBL was also used in this work. In most of the studied cases iSPA-N-PLS proved to be a promising tool for selection of variables in second-order calibration, generating models with smaller RMSEP, when compared to both the global model using all of the sensors in two dimensions and GA-NPLS/RBL., (Copyright © 2013 Elsevier B.V. All rights reserved.)