Resolving interactions of miglitol with normal and glycated human serum albumin by multivariate methods.

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.

Chemometric modeling of the electrochemical data to investigate proline cis/trans isomeration effect on aggregation of Tau protein.

Tau protein (Tau) is a proline-rich protein and in this work, we have developed a very interesting strategy based on combination of electrochemistry with chemometric methods to investigate proline cis/trans isomeration effect on the Tau aggregation. To achieve this goal, the proline residues at RTPPK motif have been replaced by alanine to generate RTPAK, RTAPK and RTAAK mutants of the Tau. Then, cyclic voltammetric (CV) responses of the Tau and RTPAK, RTAPK and RTAAK as its mutants in the presence of heparin (HEP) as an anionic inducing agent which could trigger aggregation of the Tau were recorded at physiological conditions every hour during 12 h. Therefore, 48 data sets of titrations were obtained which were handled by chemometric methods to extract useful information about aggregation of the Tau. The data were hard-modeled by EQUISPEC, SQUAD, REACTLAB and SPECFIT to extract useful quantitative information. Our results confirmed that the strength of the binding of the HEP with proteins was obeyed from Tau > RTPAK ~ RTAPK > RTAAK which confirmed that the aggregation of the proteins was obeyed from this order as well. Therefore, aggregation of the Tau is decreased by transforming Cis isomer to Trans even in the presence of an anionic inducing agent such as HEP which may have value for the treatment of Alzheimer's disease.

Chromatographic Applications in the Multi-Way Calibration Field.

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.

Sensitivity for Multivariate Calibration Based on Multilayer Perceptron Artificial Neural Networks.

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.

Open-Source Assisted Laboratory Automation through Graphical User Interfaces and 3D Printers: Application to Equipment Hyphenation for Higher-Order Data Generation.

Higher-order data generation implies some automation challenges, which are mainly related to the hidden programming languages and electronic details of the equipment. When techniques and/or equipment hyphenation are the key to obtaining higher-order data, the required simultaneous control of them demands funds for new hardware, software, and licenses, in addition to very skilled operators. In this work, we present Design of Inputs-Outputs with Sikuli (DIOS), a free and open-source code program that provides a general framework for the design of automated experimental procedures without prior knowledge of programming or electronics. Basically, instruments and devices are considered as nodes in a network, and every node is associated both with physical and virtual inputs and outputs. Virtual components, such as graphical user interfaces (GUIs) of equipment, are handled by means of image recognition tools provided by Sikuli scripting language, while handling of their physical counterparts is achieved using an adapted open-source three-dimensional (3D) printer. Two previously reported experiments of our research group, related to fluorescence matrices derived from kinetics and high-performance liquid chromatography, were adapted to be carried out in a more automated fashion. Satisfactory results, in terms of analytical performance, were obtained. Similarly, advantages derived from open-source tools assistance could be appreciated, mainly in terms of lesser intervention of operators and cost savings.

Nondestructive Total Excitation-Emission Fluorescence Microscopy Combined with Multi-Way Chemometric Analysis for Visually Indistinguishable Single Fiber Discrimination.

The potential of total excitation-emission fluorescence microscopy combined with multiway chemometric analysis was investigated for the nondestructive forensic analysis of textile fibers. The four pairs of visually indistinguishable fibers consisted of nylon 361 dyed with acid yellow 17 and acid yellow 23, acetate satin 105B dyed with disperse blue 3 and disperse blue 14, polyester 777 dyed with disperse red 1 and disperse red 19, and acrylic 864 dyed with basic green 1 and basic green 4. Excitation emission matrices were recorded with the aid of an inverted microscope and a commercial spectrofluorimeter. The full information content of excitation-emission matrices was processed with the aid of unsupervised parallel factor analysis (PARAFAC), PARAFAC supervised by linear discriminant analysis (LDA), and discriminant unfolded partial least-squares (DU-PLS). The ability of the latter algorithm to classify the four pairs of fibers demonstrates the advantage of using the multidimensionality of fluorescence data formats for the nondestructive analysis of forensic fiber evidence.

Second-order capillary electrophoresis diode array detector data modeled with the Tucker3 algorithm: A novel strategy for Argentinean white wine discrimination respect to grape variety.

Data obtained by capillary electrophoresis with diode array detection (CE-DAD) were modeled with the purpose to discriminate Argentinean white wines samples produced from three grape varieties (Torrontés, Chardonnay, and Sauvignon blanc). Thirty-eight samples of commercial white wine from four wine-producing provinces of Argentina (Mendoza, San Juan, Salta, and Rio Negro) were analyzed. CE-DAD matrices with dimensions of 421 elution times (from 1.17 to 7.39 minutes) × 71 wavelengths (from 227 to 367 nm) were joined in a three way data array and decomposed by Tucker3 method under non-negativity constraint, employing 18, 18 and six factors in the modes 1, 2 and 3, respectively. Using the scores of Tucker model, it was possible to discriminate samples of Argentinean white wine by linear discriminant analysis and Kernel linear discriminant analysis. Core element analysis of the Tucker3 model allows identifying the loading profiles in spectral mode related to Argentinean white wine samples.

Highly Selective and Ultrasensitive Turn-on Luminescence Chemosensor for Mercury (II) Determination Based on the Rhodamine 6G Derivative FC1 and Au Nanoparticles.

A method for the detection and quantitation of Hg2+ in aqueous samples by fluorescence spectroscopy is presented. It consists of a turn-on sensor developed by coupling Gold nanoparticles (AuNPs) with the rhodamine 6G derivative FC1, in which the response is generated by a mercury-induced ring-opening reaction. The AuNPs were included in order to improve the sensitivity of the method towards the analyte, maintaining its high selectivity. The method was validated in terms of linearity, precision and accuracy, and applied to the quantitation of Hg2+ in Milli-Q and tap water with and without spiked analyte. The limit of detection and quantitation were 0.15 µg·L-1 and 0.43 µg·L-1, respectively, constituting a substantial improvement of sensitivity in comparison with the previously reported detection of Hg2+ with free FC1.

Parallel Factor Analysis of 4.2 K Excitation-Emission Matrices for the Direct Determination of Dibenzopyrene Isomers in Coal-Tar Samples with a Cryogenic Fiber-Optic Probe Coupled to a Commercial Spectrofluorimeter.

Several studies have shown high concentrations of polycyclic aromatic hydrocarbons (PAHs) in living spaces and soil adjacent to parking lots sealed with coal-tar-based products. Recent attention has been paid to the presence of seven PAHs in coal-tar samples, namely, benz[a]anthracene, benzo[k]-fluoranthene, benzo[b]fluoranthene, benzo[a]pyrene, chrysene, dibenz[a,h]anthracene, and indeno[1,2,3-cd]pyrene, and their association to significant increases in estimated excess lifetime cancer risk for nearby residents. Herein, we present an analytical approach to screen the presence of five highly toxic, high-molecular weight PAHs (HMW-PAHs) in coal-tar samples. These include dibenzo[a,l]pyrene, dibenzo[a,i]pyrene, dibenzo[a,e]pyrene, dibenzo[a,h]pyrene, and naphtho[2,3-a]pyrene. Their direct analysis, without chromatographic separation, in a reference coal-tar sample is made possible with the combination of excitation-emission matrices (EEMs) and parallel factor analysis (PARAFAC). EEMs are recorded at 4.2 K with the aid of a cryogenic fiber-optic probe and a commercial spectrofluorimeter. The simplicity of the experimental procedure and the excellent analytical figures of merit demonstrate the screening potential of this environmentally friendly approach for the routine analysis of numerous coal-tar samples.

A new modeling strategy for third-order fast high-performance liquid chromatographic data with fluorescence detection. Quantitation of fluoroquinolones in water samples.

Matrix augmentation is regularly employed in extended multivariate curve resolution-alternating least-squares (MCR-ALS), as applied to analytical calibration based on second- and third-order data. However, this highly useful concept has almost no correspondence in parallel factor analysis (PARAFAC) of third-order data. In the present work, we propose a strategy to process third-order chromatographic data with matrix fluorescence detection, based on an Augmented PARAFAC model. The latter involves decomposition of a three-way data array augmented along the elution time mode with data for the calibration samples and for each of the test samples. A set of excitation-emission fluorescence matrices, measured at different chromatographic elution times for drinking water samples, containing three fluoroquinolones and uncalibrated interferences, were evaluated using this approach. Augmented PARAFAC exploits the second-order advantage, even in the presence of significant changes in chromatographic profiles from run to run. The obtained relative errors of prediction were ca. 10 % for ofloxacin, ciprofloxacin, and danofloxacin, with a significant enhancement in analytical figures of merit in comparison with previous reports. The results are compared with those furnished by MCR-ALS.

Unfolded partial least squares/residual bilinearization combined with the Successive Projections Algorithm for interval selection: enhanced excitation-emission fluorescence data modeling in the presence of the inner filter effect.

The use of the successive projections algorithm (SPA) for elimination of uninformative variables in interval selection, and unfold partial least squares regression (U-PLS) modeling of excitation-emission matrices (EEM), when under the inner filter effect (IFE) is reported for first time. Post-calibration residual bilinearization (RBL) was employed against events of unknown components in the test samples. The inner filter effect can originate changes in both the shape and intensity of analyte spectra, leading to trilinearity losses in both modes, and thus invalidating most multiway calibration methods. The algorithm presented in this paper was named iSPA-U-PLS/RBL. Both simulated and experimental data sets were used to compare the prediction capability during: (1) simulated EEM; and (2) quantitation of phenylephrine (PHE) in the presence of paracetamol (PAR) (or acetaminophen) in water samples. Test sets containing unexpected components were built in both systems [a single interference was taken into account in the simulated data set, while water samples were added with varying amounts of ibuprofen (IBU), and acetyl salicylic acid (ASA)]. The prediction results and figures of merit obtained with the new algorithm were compared with those obtained with U-PLS/RBL (without intervals selection), and with the well-known parallel factors analysis (PARAFAC). In all cases, U-PLS/RBL displayed better EEM handling capability in the presence of the inner filter effect compared with PARAFAC. In addition, iSPA-U-PLS/RBL improved the results obtained with the full U-PLS/RBL model, in this case demonstrating the potential of variable selection.

Rapid determination of retinoic acid and its main isomers in plasma by second-order high-performance liquid chromatography data modeling.

This paper reports the development of a method based on high-performance liquid chromatography (HPLC) coupled to second-order data modeling with multivariate curve resolution-alternating least-squares (MCR-ALS) for quantification of retinoic acid and its main isomers in plasma in only 5.5 min. The compounds retinoic acid (RA), 13-cis-retinoic acid, 9-cis-retinoic acid, and 9,13-di-cis-retinoic acid were partially separated by use of a Poroshell 120 EC-C18 (3.0 mm × 30 mm, 2.7 µm particle size) column. Overlapping not only among the target analytes but also with the plasma interferents was resolved by exploiting the second-order advantage of the multi-way calibration. A validation study led to the following results: trueness with recoveries of 98.5-105.9 % for RA, 95.7-110.1 % for 13-cis-RA, 97.1-110.8 % for 9-cis-RA, and 99.5-110.9 % for 9,13-di-cis-RA; repeatability with RSD of 3.5-3.1 % for RA, 3.5-1.5 % for 13-cis-RA, 4.6-2.7 % for 9-cis-RA, and 5.2-2.7 % for 9,13-di-cis-RA (low and high levels); and intermediate precision (inter-day precision) with RSD of 3.8-3.0 % for RA, 2.9-2.4 % for 13-cis-RA, 3.6-3.2 % for 9,13-di-cis-RA, and 3.2-2.9 % for 9-cis-RA (low and high levels). In addition, a robustness study revealed the method was suitable for monitoring patients with dermatological diseases treated with pharmaceutical products containing RA and 13-cis-RA.

Ultrafast quantitation of six quinolones in water samples by second-order capillary electrophoresis data modeling with multivariate curve resolution-alternating least squares.

This paper presents the development of a capillary electrophoresis method with diode array detector coupled to multivariate curve resolution-alternating least squares (MCR-ALS) to conduct the resolution and quantitation of a mixture of six quinolones in the presence of several unexpected components. Overlapping of time profiles between analytes and water matrix interferences were mathematically solved by data modeling with the well-known MCR-ALS algorithm. With the aim of overcoming the drawback originated by two compounds with similar spectra, a special strategy was implemented to model the complete electropherogram instead of dividing the data in the region as usually performed in previous works. The method was first applied to quantitate analytes in standard mixtures which were randomly prepared in ultrapure water. Then, tap water samples spiked with several interferences were analyzed. Recoveries between 76.7 and 125 % and limits of detection between 5 and 18 µg L(-1) were achieved.

Differentiating Nylon Samples with Visually Indistinguishable Fluorescence Using Principal Component Analysis and Common Dimension Partial Least Squares Linear Discriminant Analysis with Synchronous Fluorescence Spectroscopy.

Fluorescence spectroscopy is an attractive candidate for analyzing samples of nylon. Impurities within the polymers formed during the synthesis and processing of nylons give rise to the observed fluorescence, allowing for nylons to be analyzed based on their impurities. Nylons from the same source are expected to display similar fluorescence profiles, and nylons with different fluorescence are expected to be from different sources. This paper investigates an important case where different nylons displayed similar fluorescence, preventing easy discrimination. Samples of Nylon 6 and Nylon 6/12 had visually indistinguishable excitation-emission matrices (EEM), excitation spectra, fluorescence spectra, and synchronous fluorescence spectra at larger Δλ. By collecting synchronous fluorescence spectra at smaller Δλ, additional features in the fluorescence profiles were identified that allowed for some discrimination between the two nylons. Combining the EEM and synchronous fluorescence data with chemometric algorithms provided a clearer differentiation between the two nylons. parallel factor analysis, principal component analysis, and common dimension partial least squares (ComDim-PLS) showed two distinct clusters in the data, with ComDim-PLS providing the greatest distinction between the clusters. The loadings revealed the variables of interest to the ComDim-PLS were the 400 nm and 335 nm bands for all synchronous fluorescence spectra, the 460 nm and 310 nm bands for the Δλ = 20 nm and Δλ = 30 nm synchronous fluorescence spectra, and the 440 nm band for the Δλ = 20 nm synchronous fluorescence spectra. The linear discriminant analysis performed with the PLS data yielded a classification accuracy of 95% with the EEM data and 100% with the synchronous fluorescence data, displaying the power of this technique to differentiate two different nylons with visually indistinguishable fluorescence spectra.

Multivariate curve resolution-alternating least-squares and second-order advantage in first-order calibration. A systematic characterisation for three-component analytical systems.

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.

A novel strategy for the quantify of emerging isomeric pollutants belonging to the dihydroxybenzene family for environmental sample monitoring by amperometric detection.

This study introduces an innovative approach for quantifying isomeric pollutants utilizing an amperometric sensor. The determination of the isomers hydroquinone and catechol is based on the use of a glassy carbon electrode modified with Cu@PtPd/C nanoparticles (Cu@PtPd/C/GCE) in core-shell form, showing significant electrocatalytic activity in the oxidation of the later compounds. The determination was carried out at two different potentials: one at which where only hydroquinone is oxidized, and another in which where both hydroquinone and catechol are oxidized. Using these potentials, two calibration curves were built, one for the quantification of hydroquinone and the other for both isomers. Subsequently, the quantification of catechol was performed using a strategy based on the calculation of a difference using the information collected in the first step. The experiments using hydrogen peroxide as a redox probe demonstrate a clear synergistic effect in the catalytic reduction of hydrogen peroxide at -0.100 V, when Pt, Pd and Cu are incorporated into the core-shell nanostructure. The best performance was achieved with Cu@PtPd/C/GCE 1.00 mg mL-1. For the selected sensor, the analytical parameters are very competitive compared to similar devices reported in recent years for hydroquinone and catechol, with comparable linearity ranges of 0.010-0.200 mmol L-1 (hydroquinone) and 0.005-0.500 mmol L-1 (catechol), low limits of detection (LODs) of 14.0 nmol L-1 (S/N = 3.3) and 1.75 nmol L-1 (S/N = 3.3) for hydroquinone and catechol. The resulting sensor platform has been successfully applied for the quantification of hydroquinone and catechol in river and tap water and could be a promising candidate for environmental monitoring and drinking water safety.

The advantages behind the efforts of performing higher-order calibration methods - A case study.

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.

Removal of enrofloxacin using Eichhornia crassipes in microcosm wetlands.

The global consumption of antibiotics leads to their possible occurrence in the environment. In this context, nature-based solutions (NBS) can be used to sustainably manage and restore natural and modified ecosystems. In this work, we studied the efficiency of the NBS free-water surface wetlands (FWSWs) using Eichhornia crassipes in microcosm for enrofloxacin removal. We also explored the behavior of enrofloxacin in the system, its accumulation and distribution in plant tissues, the detoxification mechanisms, and the possible effects on plant growth. Enrofloxacin was initially taken up by E. crassipes (first 100 h). Notably, it accumulated in the sediment at the end of the experimental time. Removal rates above 94% were obtained in systems with sediment and sediment + E. crassipes. In addition, enrofloxacin was found in leaves, petioles, and roots (8.8-23.6 µg, 11-78.3 µg, and 10.2-70.7 µg, respectively). Furthermore, enrofloxacin, the main degradation product (ciprofloxacin), and other degradation products were quantified in the tissues and chlorosis was observed on days 5 and 9. Finally, the degradation products of enrofloxacin were analyzed, and four possible metabolic pathways of enrofloxacin in E. crassipes were described.

Total synchronous fluorescence spectroscopic data modeled with first- and second-order algorithms for the determination of doxorubicin in human plasma.

In this work, we present the development of a method for the determination of doxorubicin in plasma samples in the presence of an unexpected component (riboflavin) by using total synchronous fluorescence spectroscopic data matrices. To the best of our knowledge, this is the first time that the second-order advantage is obtained with this kind of data. Two strategies including unfolding the data and: (a) processing with multivariate curve resolution coupled to alternating least-squares as first-order data or (b) processing with unfolded partial least-squares and exploiting the second-order advantage by the residual bilinearization procedure were considered. The calibration set was built with human plasma samples spiked with doxorubicin, while the validation set was prepared with human plasma samples spiked with both doxorubicin and riboflavin, a drug whose spectrum highly overlaps with the one corresponding to doxorubicin. Both methodologies reached good indicators of accuracy: recoveries of ca. 100 ± 8% and REP of ca. 5%; and precision: coefficient of variations between 7 and 9%.

Natural deep eutectic solvent: A novelty alternative as multi-walled carbon nanotubes dispersing agent for the determination of paracetamol in urine.

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-H2O-EtOH and MWCNTs-H2O. The linear dependence between the anodic peak currents and the square root of scan rates over the range of 0.010-0.300 Vs-1 demonstrates that the electro oxidation of APAP occurs under diffusional control. The MWCNT-LGH-EG modified GCE displayed an analytical sensitivity of 10.72 mL µg-1 (r = 0.9994) and a detection limit of 100 ng mL-1 for the selective determination of APAP in urine samples. The proposed electrochemical sensor was successfully applied for quantifying APAP in urine samples in the presence of uric acid. In addition, the accuracy and precision of the method was contrasted against a HPLC reference method.