Search

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.

The textile industry is an important potential source of environmental pollution due to the use of chemical products. Dyes, hydrolyzed dyes, and surfactants, among others, are chemical compounds present in wastewater of textile plant. Moreover, the anionic surfactants have toxic effects for various aquatic organisms even in low concentrations. The methodologies investigated to quantify surfactants, in general, consume a lot of analysis time and frequently use toxic or environmentally objectionable reagents. For these reasons, the objective of this work was to develop a quick and simple method to quantify surfactants without the use of expensive reagents and equipment, avoiding extraction and preconcentration stages. The proposed method is based on fluorescent spectroscopy measurements for the acquisition of second-order data in excitation-emission matrices and multivariate calibration techniques applied to the data. The unfolded partial least squares combined to residual bilinearization (U-PLS/RBL) algorithm was better than parallel factor analysis (PARAFAC). U-PLS/RBL accurately quantified alkylnonylphenolethoxylated (APEO), dodecylbenzenesulfonic acid (ADBS), and 2-phenoxy-ethoxylated fatty alcohol (AGFE) surfactants. The chemometric model obtained good analytical figures of merit: REP% between 5 and 13 and LOQ between 0.45 and 2.77 μg mL-1. This methodology had no significant difference compared with results obtained by a HPLC-FD reference technique, in addition with a considerable reduction in analysis time, reagent consumption, and therefore lower cost. For environmental applications, APEO, ADBS, and AGFE were quantify in textile wastewater treatment and in the receiving water body. The concentrations varied from 8.73 to 73.94 μg mL-1 in the textile wastewater and were not detected in the receiving water body.

Multi-way calibration based on second-order data constitutes a revolutionary milestone for analytical applications. However, most classical chemometric models assume that these data fulfil the property of low rank bilinearity, which cannot be accomplished by all instrumental methods. Indeed, various techniques are able to generate non-bilinear data, which are all potentially useful for the development of novel second-order calibration methodologies. However, the achievement of the second-order advantage in these cases may be severely limited, since methods for comprehensive modelling of non-bilinear second-order data remain only partially explored. In this research, the analytical performance of three well-known second-order models, namely non-bilinear rank annihilation (NBRA), unfolded partial least-squares with residual bilinearization (U-PLS-RBL) and multivariate curve resolution - alternating least-squares (MCR-ALS) is systematically assessed through sets of simulated and experimental non-bilinear second-order data, involving one analyte and one interferent. Although it is not possible to establish a single strategy to model any type of non-bilinear second-order data with the studied methods, each approach may lead to successful predictions under certain circumstances. It is shown that the prediction capacity is severely affected by data properties such as the level of instrumental noise, the rank of the response matrices and the signal selectivity pattern of the analyte.

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.

This work presents the development of a strategy for the quantitation of 2-hydroxy-4-methoxybenzophenone (BP-3) in mice serum and human plasma. The instrumental determination only lasts 2 min and is based on ultra-high-performance liquid chromatography (UHPLC) coupled to second-order data modeling with multivariate curve resolution-alternating least-squares (MCR-ALS). Coelution of BP-3 with the matrix components was resolved by exploiting the second-order advantage of multi-way calibration. The validation study led to the following results: linear range from 0.002 to 1.509 μg mL−1; in the case of mice serum samples: recoveries from 95 to 98%, with intra and inter day precision of 2.7 and 5.7, respectively; and in the case of human plasma samples: recoveries from 94 to 99% with intra and inter day precision of 2.3 and 4.6%, respectively. Special emphasis was put on the determination of the LOD and LOQ by utilizing several approaches for their calculation and making focus on the experimental verification of the figures provided by the multivariate methodology. Following the mentioned approach, the LOD and LOQ of the method were estimated as 0.66 and 2.00 ng mL−1, respectively. Eventually, the method was successfully applied to the determination of BP-3 in mice serum. Fil: Teglia, Carla Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral; Argentina Fil: Santamaría, Clarisa Guillermina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Rodriguez, Horacio Adolfo. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Culzoni, Maria Julia. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

In the present study, we have developed a novel electroanalytical method based on coupling of four-way multivariate calibration (MVC) models with third-order differential pulse voltammetric (DPV) data for simultaneous determination of amaranth (AM), tartrazine (TT) and quinoline yellow (QY) in the presence of sunset yellow (SY) as uncalibrated interference at a glassy carbon electrode (GCE). The third-order DPV data were recorded by changing pulse height and pulse time as instrumental parameters. After performing some preprocessing actions such as baseline correction by asymmetric least squares spline regression (AsLSSR) and potential shift correction by correlation optimized warping (COW) on the raw data, two well-known third-order algorithms including unfolded partial least squares/residual trilinearization (U-PLS/RTL) and multidimensional partial least squares/RTL (N-PLS/RTL) were used to build four-way calibration models and their performance was checked by predicting the concentrations of the validation and test sets as synthetic samples. The results confirmed more superiority of N-PLS/RTL than U-PLS/RTL in synthetic samples which encouraged us to apply the N-PLS/RTL to the analysis of real samples. The results of the analysis of real samples showed that the N-PLS/RTL had an acceptable potential for predicting concentrations of AM, TT and QY in real matrices. Fil: Ghanbari, Kazhal. Kermanshah University Of Medical Sciences; Irán Fil: Roushani, Mahmoud. Kermanshah University Of Medical Sciences; Irán Fil: Farzadfar, Farshad. Kermanshah University Of Medical Sciences; Irán Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral; Argentina Fil: Jalalvand, Ali R.. Kermanshah University Of Medical Sciences; Irán

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. Fil: Alcaraz, Mirta Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Aguirre, Alejo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química. Departamento de Ingeniería de Los Fotorreactores | Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico Para la Industria Química. Departamento de Ingeniería de Los Fotorreactores; Argentina Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Culzoni, Maria Julia. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Collins, Sebastián Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico Para la Industria Química. Departamento de Ingeniería de Los Fotorreactores | Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico Para la Industria Química. Departamento de Ingeniería de Los Fotorreactores; Argentina

This article reports results of one of our projects related to the investigation of interactions of miglitol (MIG) with normal human serum albumin (HSA) and glycated HSA (GHSA) with the help of recording spectroscopic and electrochemical data. The experimental data were analyzed by conventional and chemometric methods to extract useful information for comprehensive justifications of the interactions of the MIG with HSA and GHSA. Hard- and soft-modeling chemometric methods were used to extract quantitative and qualitative information. Then, molecular docking techniques were used to further investigation of the binding of the MIG with HSA and GHSA and the extracted results were compatible with those obtained by experimental methods. Finally, according to the binding of the BV with HSA and GHSA, second-order differential pulse voltammetric data were recorded and calibrated with three-way calibration methods for exploiting second-order advantage for determination of the GHSA in the presence of the HSA to develop a novel chemometrics assisted-electroanalytical method for diagnostic and monitoring of diabetic.

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%.

A novel analytical method using voltammetric second-order modeling based on multivariate curve resolution-alternating least-square (MCR-ALS) is presented for the first time for the quantitation of carvacrol (CAR) in oregano essential oils (OEO). The second-order cyclic voltammetry data were generated on the basis that CAR shows a diffusional system. Thus, the scan rate (v) was used as a second instrumental mode and cyclic voltammograms at different v were acquired for a single sample, generating the second-order data. CAR determination was performed in presence of thymol, included as a potential interferent. Results demonstrated that MCR-ALS successfully exploited the second-order advantage and the recoveries were not statistically different than 100%. The limits of detection and quantitation were estimated using the MCR-ALS which were 6.27 × 10−5°mol°L−1°and 1.90 × 10−4°mol L−1, respectively. Finally, the developed methodology was implemented to quantify of CAR in OEO samples.

The present tutorial aims to review the most frequently reported criteria for the calculation of the limits of detection (LOD) and quantification (LOQ) in univariate calibration, summarizing their fundamentals, advantages, and limitations. The current criteria for estimating LOD and LOQ are based on diverse theoretical and/or empirical assumptions and require different amounts of experimental data, making the calculation rather complex in some cases. Moreover, alternative forms for calculating LOD/LOQ frequently lead to dissimilar results. This scenario might worsen in the case of complex analytical systems. Throughout this tutorial, different forms of calculating LOD/LOQ are illustrated using previously reported experimental datasets in the environmental chemistry field as examples. The influence of the sample matrix during the estimation of LOD/LOQ parameters is investigated through one calibration approache. The discrepancies in the obtained results with different criteria for the calculation of LOD/LOQ are highlighted. Finally, general guidelines and recommendations regarding experimental and data processing issues are proposed, aiming to promote fair criteria for the comparison of different analytical methodologies in terms of prediction ability and detection capability.

This work reports for the first time the analytical performance of glassy carbon electrodes (GCE) modified with a dispersion of multi-wall carboxylated carbon nanotubes (MWCNTs-COOH) using a mixture of a natural deep eutectic solvent (NADES - LGH/lactic acid-glucose-water), ethylene glycol (EG) and water (GCE/MWCNT-LGH-EG) for the determination and N-(4-hydroxyphenyl) acetamide (paracetamol) (APAP) in urine samples. The optimization of both dispersion and measurement conditions was carried out using experimental design. The modified electrode exhibited enhanced current responses, demonstrating excellent electrochemical response towards APAP oxidation compared to MWCNTs-LGH, MWCNTs-EG, MWCNTs-H

Six veterinary active ingredients (imidacloprid, albendazole, fenbendazole, praziquantel, fipronil and permethrin) were extracted and quantified by liquid chromatography with diode array detection in water samples from a wetland system used for the treatment of waste from a dog breeding plant. Response surface methodology, based on least-squares and artificial neural networks modelling, was applied for the optimization of a dispersive liquid-liquid microextraction (DLLME) procedure. Firstly, two experimental designs were built for screening and optimization, respectively. Then, the desirability function was implemented for the simultaneous optimization of the six recoveries (chromatographic areas of the six compounds). The optimum conditions were: 600 μL of acetone (dispersive solvent), 670 μL of dichloromethane (extractant solvent) and 0.6 min of vortex mixing. The preconcentration factor was 37.5. Then, in order to identify and quantify the six drugs, second-order calibration with MCR-ALS modeling of HPLC-DAD data was implemented attaining successful results. The limits of quantification were 4 ng mL−1 for imidaclopril, albendazole and fenbendazole; 8 ng mL−1 for praziquantel and fipronil; and 26 ng mL−1 for permethrin. The developed method allowed the quantitation of the target analytes, even in the presence of unexpected compounds from dirty water samples. The following maximum levels of veterinary drugs were found (in ng mL−1): imidaclopril, 7; albendazole, 46; fenbendazole, 21; praziquantel, 29; fipronil, 29 and permethrin, 217.

The use of machine learning for multivariate spectroscopic data analysis in applications related to process monitoring has become very popular since non-linearities in the relationship between signal and predicted variables are commonly observed. In this regard, the use of artificial neural networks (ANN) to develop calibration models has demonstrated to be more appropriate and flexible than classical multivariate linear methods. The most frequently reported type of ANN is the so-called multilayer perceptron (MLP). Nevertheless, the latter models still lack a complete statistical characterization in terms of prediction uncertainty, which is an advantage of the parametric counterparts. In the field of analytical calibration, developments regarding the estimation of prediction errors would derive in the calculation of other analytical figures of merit (AFOMs), such as sensitivity, analytical sensitivity, and limits of detection and quantitation. In this work, equations to estimate the sensitivity in MLP-based calibrations were deduced and are here reported for the first time. The reliability of the derived sensitivity parameter was assessed through a set of simulated and experimental data. The results were also applied to a previously reported MLP fluorescence calibration methodology for the biopharmaceutical industry, yielding a value of sensitivity ca. 30 times larger than for the univariate reference method.

In this work, for the first time, we have developed a novel and very interesting electroanalytical methodology assisted by first-order multivariate calibration (MVC) for simultaneous determination of doxorubicin (DX), daunorubicin (DN) and idarubicin (ID) as three chemotherapeutic drugs at simulated physiological conditions. A sever overlapping was observed among signals of the three drugs which hindered us for simultaneous determination of them by conventional electroanalytical techniques. Therefore, we had to assist our method by chemometric approaches to develop a novel method for simultaneous determination of DX, DN and ID. Among the existing electroanalytical methods, electrochemical impedance spectroscopy (EIS) due to its high sensitivity was chosen. After individual calibration of the three drugs with the EIS data, a set of calibration samples was designed which was used to develop several first-order MVC models by partial least squares (PLS), continuum power regression (CPR), radial basis function-partial least squares (RBF-PLS), RBF-artificial neural network (RBF-ANN) and least squares-support vector machines (LS-SVM) as linear and non-linear chemometric algorithms. Then, performance of the developed MVC models in predicting concentrations of DX, DN and ID in synthetic samples was compared to choose the best model for the analysis of real samples. Our records confirmed more superiority of RBF-PLS algorithm than the other developed models which motivated us to choose it for the analysis of real samples. Fortunately, the results of the RBF-PLS in the analysis of real samples towards simultaneous determination DX, DN and ID was acceptable.

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%)

The aim of this study was to develop a fluorescence-detection based analytical methodology consisting in the photolysis of abacavir induced by UV irradiation to determine the concentration of the analyte in complex samples. Initially, with the goal of maximizing the fluorescence signal, the optimal experimental conditions were determined by means of design of experiments using the response surface methodology. Once these conditions were established, two types of data were generated: excitation-emission fluorescence matrices acquired after UV irradiation of the analyte (second-order data), and excitation-emission fluorescence matrices recorded at different irradiation times (third-order data), which were processed using both multivariate curve resolution by alternating least squares (MCR-ALS) and parallel factor analysis (PARAFAC) algorithms. These strategies were carried out with the objective of assessing the chemometric advantages in terms of predictive ability by increasing the order of the data, and improvement in figures of merit, such as sensitivity and limits of detection and quantitation. Finally, test samples, containing the analyte and potential interferences, and water samples were evaluated. This study allowed the development of a simple and sensitive methodology for the determination of abacavir in water samples, and showed similar predictive ability between both algorithms. The analytical figures of merit displayed limits of detection and quantitation of 3-5 µg L?1 and 11-14 µg L?1, respectively. The main advantages of third-order data with respect to second-order data were associated with improvements in selectivity and precision. Fil: Paradina Fernández, Lesly Anniled. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Brasca, Romina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral; Argentina Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral; Argentina Fil: Culzoni, Maria Julia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral; Argentina

Capillary electrophoresis with diode array detection (CE-DAD) and multidimensional fluorescence spectroscopy (EEM) second-order data were fused and chemometrically processed for geographical and grape variety classification of wines. Multi-levels data fusion strategies on three-way data were evaluated and compared revealing their advantages/disadvantages in the classification context. Straightforward approaches based on a series of data preprocessing and feature extraction steps were developed for each studied level. Partial least square discriminant analysis (PLS-DA) and its multi-way extension (NPLS-DA) were applied to CE-DAD, EEM and fused data matrices structured as two-way and three-way arrays, respectively. Classification results achieved on each model were evaluated through global indices such as average sensitivity non-error rate and average precision. Different degrees of improvement were observed comparing the fused matrix results with those obtained using a single one, clear benefits have been demonstrated when level of data fusion increases, achieving with the high-level strategy the best classification results. Fil: Ríos Reina, Rocío. Universidad de Sevilla; España Fil: Azcarate, Silvana Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina Fil: Camiña, José Manuel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina

This review presents applications of response surface methodology (RSM) when mixture experiments are involved for the optimization in the field of analytical methods development. Several critical issues such as sort of designs, modeling with least squares or artificial neural networks, and multiple response optimization are discussed. The results of a literature survey of the works reported up to 2019 are presented. Finally, an illustrative example providing the necessary information to carry out this kind of work is discussed. A list of the most popular software available to apply RSM is also presented. Fil: Azcarate, Silvana Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Ciencias de la Tierra y Ambientales de La Pampa. Universidad Nacional de La Pampa. Facultad de Ciencias Exactas y Naturales. Instituto de Ciencias de la Tierra y Ambientales de La Pampa; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Pinto, Licarion. Universidade Federal de Pernambuco; Brasil Fil: Goicoechea, Héctor C.. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina

A novel, simple, easy and cheap sample treatment strategy based on salting-out assisted liquid-liquid extraction for ochratoxin A (OTA) ultra-trace analysis in beer samples using ultra-high-performance liquid chromatography-tandem mass spectrometry determination was developed. The factors involved in the efficiency of pre-treatment were studied employing factorial design in the screening phase and the optimal conditions of the significant variables on the analytical response were evaluated using a central composite face-centred design. Consequently, the amount of salt ((NH4)2SO4), together with the volumes of sample, hydrophilic (acetone) and nonpolar (toluene) solvents, and times of vortexing and centrifugation were optimised. Under optimised conditions, the limits of detection and quantification were 0.02 µg l−1 and 0.08 µg l−1 respectively. OTA extraction recovery by SALLE was approximately 90% (0.2 µg l−1). Furthermore, the methodology was in agreement with EU Directive requirements and was successfully applied for analysis of beer samples. Fil: Marino Repizo, Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Investigaciones en Tecnología Química. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Investigaciones en Tecnología Química; Argentina Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina Fil: Raba, Julio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Investigaciones en Tecnología Química. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Investigaciones en Tecnología Química; Argentina Fil: Cerutti, Estela Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Investigaciones en Tecnología Química. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Investigaciones en Tecnología Química; Argentina

This paper proposes a new variable selection method for nonlinear multivariate calibration, combining the Successive Projections Algorithm for interval selection (iSPA) with the Kernel Partial Least Squares (Kernel-PLS) modelling technique. The proposed iSPA-Kernel-PLS algorithm is employed in a case study involving a Vis-NIR spectrometric dataset with complex nonlinear features. The analytical problem consists of determining Brix and sucrose content in samples from a sugar production system, on the basis of transflectance spectra. As compared to full-spectrum Kernel-PLS, the iSPA-Kernel-PLS models involve a smaller number of variables and display statistically significant superiority in terms of accuracy and/or bias in the predictions. Fil: de Almeida, Valber Elias. Universidade Federal da Paraíba; Brasil Fil: de Araújo Gomes, Adriano. Universidade Federal do Sul e Sudoeste do Pará; Brasil Fil: de Sousa Fernandes, David Douglas. Universidade Federal da Paraíba; Brasil Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina Fil: Galvão, Roberto Kawakami Harrop. Instituto Tecnológico de Aeronáutica; Brasil Fil: Araújo, Mario Cesar Ugulino. Universidade Federal da Paraíba; Brasil

This paper proposes a multiway calibration strategy implementing the modeling with MCR-ALS and U-PLS/RBL of second-order chromatographic data for quantitation of six analytes: gliclazide, glibenclamide, glimepiride, atenolol, enalapril and amlodipine in serum samples, in an analysis time of 3 min. The performance of both algorithms was compared in terms of predictive ability, showing relative error of prediction values below 10% in all cases. LOD values calculated are below 30 ng mL−1 for all the studied drugs, which allow detection in human serum in patients under treatment. U-PLS/RBL has higher sensitivity and better detection and quantification limits for all the studied analytes; however results obtained by MCR-ALS enable its usage as well. Both methods provide comparable results for glibenclamide, glimepiride and gliclazide. With this multiway calibration strategy, the presence of enalapril, amlodipine and atenolol could be quantitated with high accuracy. Run time was reduced by 50% considering previous reports, as well as reduction of solvents, in accordance with green chemistry principles. Fil: Monzón, Celina María. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina Fil: Teglia, Carla Mariela. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina Fil: Delfino, Mario Raul. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Química Básica y Aplicada del Nordeste Argentino. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Química Básica y Aplicada del Nordeste Argentino; Argentina Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina

2 Tablas.-- 6 Figuras, The use of data fusion methodologies has increased at the same rhythm as the capability of modern analytical laboratories of measuring sample from multiple sources. Almost all data fusion strategies can be grouped into three levels, they fuse the data differently with the sole aim of obtaining a better response (qualitative or quantitative) than that obtained by the instruments individually. One of the major key points for the data fusion methodologies to succeed is the understanding of the data structure obtained from a particular instrument. This point is not exhaustively commented in the literature focused on data fusion, sometimes paying too much attention to the algorithms instead. This manuscript explains data fusion from the structure of the different data obtained by different analytical platforms. Special attention will be given to the nature of the data and the relationships between the samples and the variables, as well as within the variables., The authors are grateful to Univ. Nacional de La Pampa, and CONICET (Consejo Nacional de Investigaciones Científicas y Técnicas, (Project PIP-2015 Nº 0111) and ANPCyT (Agencia Nacional de Promoción Científica y Tecnológica, (Projects PICT 2017-0340 and PICT-2018-04496) for financial support.

In this paper, we have collected useful information about interactions of dapagliflozin (DPA) with normal human serum albumin (HSA) and glycated HSA (GHSA) by using spectroscopic and electrochemical methods. Instrumental data were analyzed by graphical and conventional methods and then, the data were mathematically modeled and simultaneously analyzed by multivariate curve resolution-alternating least squares (MCR-ALS). Hard-modeling algorithm of the data helped us to obtain qualitative and quantitative information to cast a deep look at the interactions of the DPA with HSA and GHSA. The results of MCR-BANDS showed that the MCR-ALS gave us unambiguous and reliable results. Afterwards, molecular docking techniques were used to investigate binding of the DPA with HSA and GHSA to obtain new information and to complete the previous findings. The DPA was bound with HSA and GHSA with different binding strengths. Fortunately, the results were compatible and confirmed each other. Finally, according to the results of interaction and binding of the DPA with HSA and GHSA, a second-order calibration model was developed with aim of exploiting second-order advantage for determination of the GHSA in the presence of HSA as uncalibrated interference. The developed method had a good performance for determination of the GHSA in both of synthetic and real samples.

In this paper, we are going to report results of one of our projects in which we have investigated binding and inhibition of myeloperoxidase (MO) by bivalirudin (BV) with the help of electrochemical and spectroscopic techniques assisted by chemometric methods. Different electrochemical and spectroscopic data were combined or individually used to justify binding and inhibition of the MO by BV. Hard and soft modeling chemometric methods were used to the analysis of experimental data to extract concentration profiles, pure instrumental signal profiles and binding constant value (Kb). Results of conventional and chemometric analyses confirmed a relatively strong binding of BV with MO which inhibited it. Concentration and pure instrumental signal profiles revealed interaction and binding of BV with MO and formation of one complex species. Inhibition of the MO by BV helped us to exploit a quantitative concept for electrochemical determination of the MO based on its binding with BV. Determination of the MO was performed by electrochemical impedance spectroscopy (EIS) and differential pulse voltammetry (DPV) and the results of the EIS were better than DPV which can be suggested for the analysis of serum samples with the aim of evaluation of patients with acute coronary syndrome.

Temperature-induced conformational transitions of poly-L-lysine were monitored with Fourier-transform infrared (FT-IR) spectroscopy between 10 °C and 70 °C. Chemometric analysis of dynamic IR spectra was performed by multivariate curve analysis–alternating least squares (MCR-ALS) of the amide I′ and amide II′ spectral region. With this approach, the pure spectral and concentration profiles of the conformational transition were obtained. Beside the initial α-helical, the intermediate random coil/extended helices and the final β-sheet structure, an additional intermediate PLL conformation was identified and attributed to a transient β-sheet structure. Fil: Alcaraz, Mirta Raquel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina. Vienna University of Technology; Austria Fil: Schwaighofer, Andreas. Vienna University of Technology; Austria Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas; Argentina Fil: Lendl, Bernhard. Vienna University of Technology; Austria

Electrochemistry studies the relationship between electricity and identifiable chemical change, with either electricity considered an outcome of a particular chemical change or vice-versa. Chemometrics is the chemical discipline that uses mathematical and statistical methods to design or select optimal procedures and experiments, and to provide maximum chemical information by analyzing chemical data. Multivariate curve resolution-alternating least squares (MCR-ALS) has become a popular chemometric method used for data analysis in many different application fields. This article intends to propose a comprehensive review on different applications of MCR-ALS in electrochemistry such as complexation studies, small molecule-biomacromolecule interactions, minimization of electrodic adsorption, separation of the faradic current contribution from total current to enhance the sensitivity of the electroanalytical techniques, quantification and spectroelectrochemistry. This review was written from both electrochemical and chemometrical points of view with the aim of providing useful information for the electrochemists and to promote the use of MCR-ALS in electrochemistry. Fil: Jalalvand, Ali R.. Kermanshah University of Technology; Iraq Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral; Argentina

An application of four-way multivariate calibration for the quantitation of azinphos-methyl (AZM) in fruits is presented. The known photochemically induced degradation of AZM into a highly fluorescent product was exploited for the generation of third-order data with quantitative purpose. The data generation consisted in the measurement of excitation-emission fluorescence matrices at different times after UV-light irradiation. For this purpose, a reactor was built connecting an external UV-light source through an optical fiber to the sample holder. The data were modelled with two algorithms, PARAFAC and U-PLS/RTL. The second-order advantage was exploited in the analysis of samples containing un-modelled components and an improvement in the analytical figures of merit was observed as long as the data dimensions were increased. The method was successfully applied to the quantitation of AZM in apple, pear and peach juice samples with and without spiked analyte. The limits of detection were of 3.6 ug L −1 in aqueous solution and 21?66 ug L−1 in fruit juice samples. Fil: Montemurro, Milagros. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina Fil: Siano, Gabriel German. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina Fil: Culzoni, Maria Julia. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Departamento de Química. Cátedra de Química Analítica; Argentina

In the last years, regulatory agencies in biopharmaceutical industry have promoted the design and implementation of Process Analytical Technology (PAT), which aims to develop rapid and high-throughput strategies for real-time monitoring of bioprocesses key variables, in order to improve their quality control lines. In this context, spectroscopic techniques for data generation in combination with chemometrics represent alternative analytical methods for on-line critical process variables prediction. In this work, a novel multivariate calibration strategy for the at-line prediction of etanercept, a recombinant protein produced in a mammalian cells-based perfusion process, is presented. For data generation, samples from etanercept processes were daily obtained, from which fluorescence excitation-emission matrices were generated in the spectral ranges of 225.0 and 495.0 nm and 250.0 and 599.5 nm for excitation and emission modes, respectively. These data were correlated with etanercept concentration in supernatant (measured by an off-line HPLC-based reference univariate technique) by implementing different chemometric strategies, in order to build predictive models. Partial least squares (PLS) regression evidenced a non-linear relation between signal and concentration when observing actual vs. predicted concentrations. Hence, a non-parametric approach was implemented, based on a multilayer perceptron artificial neural network (MLP). The MLP topology was optimized by means of the response surface methodology. The prediction performance of MLP model was superior to PLS, since the first is able to cope with non-linearity in calibration models, reaching percentage mean relative error in predictions of about 7.0% (against 12.6% for PLS). This strategy represents a fast and inexpensive approach for etanercept monitoring, which conforms the principles of PAT. Fil: Chiappini, Fabricio Alejandro. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Teglia, Carla Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral; Argentina Fil: Forno, Ángela G.. Zelltek S.a.; Argentina Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

This paper reports results of a valuable study on investigation of inhibitory effects of the sulfonamide derivative of quercetin (QD) on human carbonic anhydrase II (CA-II) by electrochemical and chemometrical approaches. To achieve this goal, a glassy carbon electrode (GCE) was chosen as the sensing platform and different electrochemical techniques such as cyclic voltammetry (CV), differential pulse voltammetry (DPV), linear sweep voltammetry (LSV) and electrochemical impedance spectroscopy (EIS) were used to investigate and comparing inhibitory effects of quercetin (Q) and QD on CA-II. By the use of EQUISPEC, SPECFIT, SQUAD and REACTLAB as efficient hard-modeling algorithms, bindings of Q and QD with CA-II were investigated and the results confirmed that the QD inhibited the CA-II stronger than Q suggesting a highly relevant role of QD's-SO2NH2 group in inhibiting activity and also was confirmed by docking studies. Finally, a novel EIS technique based on interaction of Q and CA-II was developed for sensitive electroanalytical determination of CA-II and in this section of our study, the sensitivity of the developed electroanalytical methodology was improved by the modification of the GCE was with multi-walled carbon nanotubes-ionic liquid. Fil: Khodarahmi, Reza. Kermanshah University of Medical Sciences; Irán Fil: Khateri, Shaya. Kermanshah University of Medical Sciences; Irán Fil: Adibi, Hadi. Kermanshah University of Medical Sciences; Irán Fil: Nasirian, Vahid. State University of Louisiana; Estados Unidos Fil: Hedayati, Mehdi. Kermanshah University of Medical Sciences; Irán Fil: Faramarzi, Elahe. Kermanshah University of Medical Sciences; Irán Fil: Soleimani, Shokoufeh. Kermanshah University of Medical Sciences; Irán Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; Argentina Fil: Jalalvand, Ali Reza. Kermanshah University Of Medical Sciences; Irán

This work reports the results of an interesting study related to the investigation of interactions of bromocriptine (BCP) with human serum albumin (HSA) by mathematicall modelling of voltammetric and spectroscopic data into an augmented data matrix and its resolution by multivariate curve resolution-alternating least squares (MCR-ALS). The quality of the results obtained by MCR-ALS was examined by MCR-BANDS and its outputs confirmed the absence of rotational ambiguities in the MCR-ALS results. BCP-HSA interactions were also modeled by molecular docking methods to verify the results obtained from experimental sections and fortunately, they were compatible. Hard modeling of the experimental data by EQUISPEC helped us to calculate the binding constant of the complex formed from BCP-HSA interactions which was in a good agreement with that of calculated from direct analysis of the experimental data. Finally, with the help of two different amperometric measurements based on BCP-HSA interactions a novel electroanalytical method was developed for biosensing of HSA in serum samples. Fil: Jalalvand, Ali R.. Kermanshah University of Medical Sciences; Irán Fil: Ghobadi, Sirous. Kermanshah University of Medical Sciences; Irán Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina Fil: Faramarzi, Elahe. Kermanshah University of Medical Sciences; Irán Fil: Mahmoudi, Majid. Kermanshah University of Medical Sciences; Irán

In this work, the use of design of experiments and posterior data modelling by artificial neural network (ANN) and least squares (LS) is presented as a suitable analytical tool for the performance optimization of a tandem mass spectrometric detector coupled to ultra-high performance liquid chromatography for the analysis of seventeen veterinary drugs. Firstly, a central composite design was built considering as factors the cone, capillary, extractor and radio frequency voltages of the mass spectrometer in order to obtain a proper combination to improve the sensitivity of the method. Secondly, a one factor design considering the collision voltage was built to define the adequate voltage for each daughter ion. The response surface methodology (RSM) was then applied, and the prediction capability of ANN and LS were compared. As conclusion, the ANN modelling provided better results than LS, both in terms of the ANOVA and predicted areas results. The accuracy of the model prediction was between 85 and 125%, confirming that the estimates of the model were correct, and endorsing the optimization procedure as a suitable way to gather excellent results. The suitability of the new approach and its implications on the simultaneous analysis of seventeen veterinary drugs by ultra-high liquid chromatography coupled to tandem mass spectrometry detection are discussed. Fil: Teglia, Carla Mariela. Universidad Nacional del Litoral. Facultad de Bioquimica y Ciencias Biologicas. Laboratorio de Desarrollo Analitico y Quimioterapia.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Química de San Luis. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Química de San Luis; Argentina Fil: Guiñez, María Evangelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Química de San Luis. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Química de San Luis; Argentina Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Bioquimica y Ciencias Biologicas. Laboratorio de Desarrollo Analitico y Quimioterapia.; Argentina Fil: Culzoni, Maria Julia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral. Facultad de Bioquimica y Ciencias Biologicas. Laboratorio de Desarrollo Analitico y Quimioterapia.; Argentina Fil: Cerutti, Estela Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - San Luis. Instituto de Química de San Luis. Universidad Nacional de San Luis. Facultad de Química, Bioquímica y Farmacia. Instituto de Química de San Luis; Argentina

In this work, a novel electrochemical biosensor has been fabricated based on step-by-step modification of aglassy carbon electrode (GCE) with methylene blue (MB)-DNA/multiwalled carbon nanotubes (MWCNTs)-chitosan (CS)/palladium nanoparticles (Pd NPs)/fullerene C60 (C60) for voltammetric and impedimetric detection of DNA damage induced by bisphenol A (BPA). Modifications applied to the GCE were characterized bycyclic voltammetry (CV), differential pulse voltammetry (DPV), electrochemical impedance spectroscopy (EIS)and scanning electron microscopy. The EIS and DPV responses of the biosensor were increased and decreased,respectively, by the DNA damage induced by BPA which led us to develop novel systems for detection of DNAdamage. Our records confirmed that the biosensor was able to rapid and sensitive detection of DNA damageinduced by BPA. Finally, according to the developed systems for detection of DNA damage, we have developedvoltammetric and impedimetric methods for determination of BPA Fil: Jalalvand, Ali R.. Kermanshah University Of Medical Sciences; Irán Fil: Haseli, Ali. Kermanshah University Of Medical Sciences; Irán Fil: Farzadfar, Farshad. Kermanshah University Of Medical Sciences; Irán Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

A novel method for the determination of pirimiphos-methyl (PMM) in maize grains by fluorescence spectroscopy and three-way calibration was developed. The formation of supramolecular complexes and their effect on the luminescence properties of PMM were studied. A solvent extraction step followed by solid phase extraction for sample clean-up was optimized. A chemometric approach consisting in PARAFAC as second-order data processing tool and piecewise direct standardization (PDS) for reducing the complexity of the calibration process was developed to overcome the matrix effect. This strategy allowed dealing with the matrix effect while reducing the number of samples to be processed and, consequently, the solvent consumption and the total analysis time. Finally, three-way calibration was applied to predict the PMM concentration in unknown samples. The mean recovery was 115% and the limits of detection and quantitation were in the order of the parts per trillion, i.e. 6 and 20 ng g−1, respectively. Fil: Montemurro, Milagros. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Brasca, Romina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Culzoni, Maria Julia. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral; Argentina Fil: Goicoechea, Hector Casimiro. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina

The use of fluoroquinolones for the treatment of infections in humans and animals has increased in Argentina, and they can be found in large amounts in water bodies. The present study investigated the occurrence and associated ecological risk of 5 fluoroquinolones in rivers and farm wastewaters of San Luis, Santa Fe, Córdoba, Entre Ríos, and Buenos Aires provinces of Argentina by high-performance liquid chromatography coupled to fast-scanning fluorescence detection and ultra–high-performance liquid chromatography coupled to triple quadrupole mass spectrometry detection. The maximum concentrations of ciprofloxacin, enrofloxacin, ofloxacin, enoxacin, and difloxacin found in wastewater were 1.14, 11.9, 1.78, 22.1, and 14.2 μg L–1, respectively. In the case of river samples, only enrofloxacin was found, at a concentration of 0.97 μg L–1. The individual risk of aquatic organisms associated with water pollution due to fluoroquinolones was higher in bacteria, cyanobacteria, algae, plants, and anurans than in crustaceae and fish, with, in some cases, risk quotients >1. The proportion of samples classified as high risk was 87.5% for ofloxacin, 63.5% for enrofloxacin, 57.1% for ciprofloxacin, and 25% for enoxacin. Our results suggest that the prevalence of fluoroquinolones in water could be potentially risky for the aquatic ecosystem, and harmful to biodiversity. Fil: Teglia, Carla Mariela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina Fil: Perez, Florencia Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina Fil: Michlig, Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Programa de Investigación y Análisis de Residuos y Contaminantes Químicos; Argentina Fil: Repetti, María Rosa. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Programa de Investigación y Análisis de Residuos y Contaminantes Químicos; Argentina Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina Fil: Culzoni, Maria Julia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; Argentina

Fluorescence excitation-emission matrix spectroscopy coupled to multi-way analysis has proved to be a powerful tool for the study of complex systems with analytical purposes. However, scattering phenomena that are usually present in fluorescence landscapes can significantly affect the performance of the chemometric modelling or lead to misinterpretations of the spectral information. In this work, an improved algorithm that collects the strengths of the reported approaches and enhances their performances was developed. The proposed algorithm, which is based on the signal-conservative principle, enables the fluorescence landscapes correction by preserving the inherent particularities of the original. Moreover, corrected second-order data were subjected to trilinear decomposition analysis to assess the performance of the scatter correction in terms of trilinearity and prediction ability. In light of the obtained results, this new strategy showed to be adequate for scattering correction in several experimental situations. Fil: Chiappini, Fabricio Alejandro. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Alcaraz, Mirta Raquel. Universidad Nacional del Litoral; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral; Argentina

According to the recently rumors about abusing of sodium dithionite (SDT) in baking bread bysome bakers, we motivated to plan a study to fabricate an electrochemical SDT sensor. Thiswork reports our results on fabricating a novel and high performance electrochemical sensorbased on AuPd nanoparticles (AuPd NPs)/chitin-ionic liquid (Ch-IL)/ferrocene dicarboxylicacid-carbon black-ionic liquid (FDCA-CB-IL)/glassy carbon electrode (GCE) to ultrasensitivedetermination of SDT in bread samples. The modifications steps were characterized with thehelp of cyclic voltammetry, electrochemical impedance spectroscopy and scanning electronmicroscopy. After characterization of the modifications, the sensor was electroanalyticallycharacterized by chronoamperometry and the sensor was able to detect SDT in two linear rangesof 0.001-6 and 6-200 μM with a limit of detection of 0.1 nM and a sensitivity of 21.76 μA μM-1.After confirming the capability of the sensor for SDT determination in synthetic samples, it wasapplied to determination of SDT in three Iranian traditional bread samples and fortunately, therewasn?t any SDT in the tested bread samples and to further investigation of the ability of the Fil: Jalalvand, Ali R.. Kermanshah University Of Medical Sciences; Irán Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral; Argentina Fil: Gu, Hui-Wen. College Of Chemistry And Environmental Engineering; China

The possibility of building an interference-free calibration with first-order instrumental data with multivariate curve resolution-alternating least-squares (MCR-ALS) has been a recent topic of interest. When the protocols were successful, MCR-ALS proved to be suitable for the extraction of chemically meaningful information from first-order calibration datasets, even in the presence of unexpected species, i.e., constituents present in the test samples but absent in the calibration set. This may represent an interesting advantage over classical first-order models, e.g. partial least-squares regression (PLS). However, the predictive capacity of MCR-ALS models can be severely affected by rotational ambiguity (RA), which is usually present in first-order datasets when interferents occur, and has not been always characterized in the published analytical protocols. The aim of this report is to discuss important issues regarding MCR-ALS modelling of first-order data for a calibration scenario with a single analyte and one interferent through simulated and experimental data. Specifically, the question of when and why MCR-ALS allows one to build interference-free calibration models with first-order data is studied in terms of signal overlapping, extent of RA, and especially the role of ALS initialization procedures in prediction performance. The aim is to alert analytical chemists that interference-free MCR-ALS with first-order data may not always be successful.