An optimized methodology for the determination of multiclass organic ultraviolet sunscreens and metabolites in human milk through chromatographic and chemometric resolution.

Organic UV filters (UVFS) are used to mitigate the dermal effects associated with health risks from UV radiation, making them essential in personal care products. UVFS are frequently identified in environmental samples due to their high lipophilicity and persistence, underscoring the urgency of comprehensive assessments and regulatory measures aimed at safeguarding ecosystems and human health. The present study reports a multiclass analytical method for determining 16 UV sunscreens and metabolites in breast milk based on an ultrasound-assisted-dispersive liquid-liquid micro-extraction (UA-DLLME) with further chromatographic and chemometric resolution. The experimental conditions of the UA-DLLME were optimized through the implementation of the Design of Experiment tools. To model the responses, least-squares and artificial neural network methodologies were implemented. The optimal conditions were found by employing the desirability function. The samples were analyzed through reverse-phase liquid chromatographic separation, UV diode array, and fast-scanning fluorescence detection. The chromatographic analysis enabled the resolution of 16 analytes in a total time of 13.0 min. Multivariate curve resolution-alternating least-square (MCR-ALS) modelling was implemented to resolve analytes that were not fully resolved and to determine analytes that coeluted with endogenous components of the breast milk samples. An enrichment factor of 5-fold concentration was obtained with this methodology, reaching recoveries between 65 % and 105 % for 13 multiclass UV sunscreens and metabolites in breast milk samples with RSD % and REP % lower than 12 %.

A micellar-enhanced fluorescence photoinduced four-way calibration method for the determination of multiclass pesticides in lemon juice.

In this work, a four-way multivariate calibration method for the simultaneous determination of four pesticides - carbendazim (CBZ), thiabendazole (TBZ), pirimiphos-methyl (PMM), and clothianidin (CLT) - in lemon juice is presented. Third-order data were acquired by registering the photoinduced fluorescence of the analytes as excitation-emission matrices at different times of UV-light irradiation, in the presence of organized media (direct micelles) as fluorescence enhancers. The optimal experimental conditions (pH 11.5 and 32 mmol L-1 hexadecyltrimethylammonium chloride surfactant) were determined through a central composite design using the response surface methodology. The analytes were individually calibrated, except for TBZ and CBZ due to the inner filter effect of TBZ on CBZ. Test samples containing all analytes and imidacloprid (as potential interference) were analysed. PARAFAC was utilized to evaluate both the trilinearity and quadrilinearity of the third-order data and four-way arrays, respectively. PMM was successfully determined with quadrilinear PARAFAC decomposition, whereas CLT, TBZ, and CBZ were satisfactorily modelled using U-PLS/RTL due to the loss of quadrilinearity caused by different phenomena. The profitable applicability of the analytical method in the CBZ, TBZ, PMM, and CLT determination in lemon juice samples was demonstrated, achieving limits of detection below the maximum residue levels reported by the European Commission, and mean recoveries at 90 ± 5%.

Mammary gland development in male rats perinatally exposed to propiconazole, glyphosate, or their mixture.

This study aimed to assess whether perinatal exposure to propiconazole (PRO), glyphosate (GLY) or their mixture (PROGLY) alters key endocrine pathways and the development of the male rat mammary gland. To this end, pregnant rats were orally exposed to vehicle, PRO, GLY, or a mixture of PRO and GLY from gestation day 9 until weaning. Male offspring were euthanized on postnatal day (PND) 21 and PND60. On PND21, GLY-exposed rats showed reduced mammary epithelial cell proliferation, whereas PRO-exposed ones showed increased ductal p-Erk1/2 expression without histomorphological alterations. On PND60, GLY-exposed rats showed reduced mammary gland area and estrogen receptor alpha expression and increased aromatase expression, whereas PRO-exposed ones showed enhanced lobuloalveolar development and increased lobular hyperplasia. However, PROGLY did not modify any of the endpoints evaluated. In summary, PRO and GLY modified the expression of key molecules and the development of the male mammary gland individually but not together.

Application of Quantum Cascade Laser-Infrared Spectroscopy and Chemometrics for In-Line Discrimination of Coeluting Proteins from Preparative Size Exclusion Chromatography.

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

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.

Prospective inference of bioprocess cell viability through chemometric modeling of fluorescence multiway data.

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%.

Exploring the potential of combining chemometric approaches to model non-linear multi-way data with quantitative purposes - A case study.

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%).

pH titration of ß-lactoglobulin monitored by laser-based Mid-IR transmission spectroscopy coupled to chemometric analysis.

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

On second-order calibration based on multivariate curve resolution in the presence of highly overlapped profiles.

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

Four- and five-way excitation-emission luminescence-based data acquisition and modeling for analytical applications. A review.

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.

Resolution of intermediate surface species by combining modulated infrared spectroscopy and chemometrics.

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.

Multiway analysis through direct excitation-emission matrix imaging.

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

Exploiting the synergistic effect of concurrent data signals: Low-level fusion of liquid chromatographic with dual detection data.

A low-level data fusion strategy was developed and implemented for data processing of second-order liquid chromatographic data with dual detection, i.e. absorbance and fluorescence monitoring. The synergistic effect of coupling individual information provided by two different detectors was evaluated by analyzing the results gathered after the application of a series of data preprocessing steps and chemometric resolution. The chemometric modeling involved data analysis by MCR-ALS, PARAFAC and N-PLS. Their ability to handle the new data block was assessed through the estimation of the analytical figures of merits achieved in the prediction of a validation set containing fifteen fluorescent and non-fluorescent veterinary active ingredients that can be found in poultry litter. Eventually, the feasibility of the application of the fusion strategy to real poultry litter samples containing the studied compounds was verified.

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.

Application of MCR-ALS to reveal intermediate conformations in the thermally induced α-ß transition of poly-l-lysine monitored by FT-IR spectroscopy.

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 ß-sheet structure, an additional intermediate PLL conformation was identified and attributed to a transient ß-sheet structure.

External cavity-quantum cascade laser infrared spectroscopy for secondary structure analysis of proteins at low concentrations.

Fourier transform infrared (FTIR) and circular dichroism (CD) spectroscopy are analytical techniques employed for the analysis of protein secondary structure. The use of CD spectroscopy is limited to low protein concentrations (<2 mg ml(-1)), while FTIR spectroscopy is commonly used in a higher concentration range (>5 mg ml(-1)). Here we introduce a quantum cascade laser (QCL)-based IR transmission setup for analysis of protein and polypeptide secondary structure at concentrations as low as 0.25 mg ml(-1) in deuterated buffer solution. We present dynamic QCL-IR spectra of the temperature-induced α-helix to ß-sheet transition of poly-L-lysine. The concentration dependence of the α-ß transition temperature between 0.25 and 10 mg ml(-1) was investigated by QCL-IR, FTIR and CD spectroscopy. By using QCL-IR spectroscopy it is possible to perform IR spectroscopic analysis in the same concentration range as CD spectroscopy, thus enabling a combined analysis of biomolecules secondary structure by CD and IR spectroscopy.

EC-QCL mid-IR transmission spectroscopy for monitoring dynamic changes of protein secondary structure in aqueous solution on the example of ß-aggregation in alcohol-denaturated α-chymotrypsin.

In this work, a novel EC-QCL-based setup for mid-IR transmission measurements in the amide I region is introduced for monitoring dynamic changes in secondary structure of proteins. For this purpose, α-chymotrypsin (aCT) acts as a model protein, which gradually forms intermolecular ß-sheet aggregates after adopting a non-native α-helical structure induced by exposure to 50 % TFE. In order to showcase the versatility of the presented setup, the effects of varying pH values and protein concentration on the rate of ß-aggregation were studied. The influence of the pH value on the initial reaction rate was studied in the range of pH 5.8-8.2. Results indicate an increased aggregation rate at elevated pH values. Furthermore, the widely accessible concentration range of the laser-based IR transmission setup was utilized to investigate ß-aggregation across a concentration range of 5-60 mg mL(-1). For concentrations lower than 20 mg mL(-1), the aggregation rate appears to be independent of concentration. At higher values, the reaction rate increases linearly with protein concentration. Extended MCR-ALS was employed to obtain pure spectral and concentration profiles of the temporal transition between α-helices and intermolecular ß-sheets. Comparison of the global solutions obtained by the modelled data with results acquired by the laser-based IR transmission setup at different conditions shows excellent agreement. This demonstrates the potential and versatility of the EC-QCL-based IR transmission setup to monitor dynamic changes of protein secondary structure in aqueous solution at varying conditions and across a wide concentration range. Graphical abstract EC-QCL IR spectroscopy for monitoring protein conformation change.

Enhanced fluorescence sensitivity by coupling yttrium-analyte complexes and three-way fast high-performance liquid chromatography data modeling.

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

External-Cavity Quantum Cascade Laser Spectroscopy for Mid-IR Transmission Measurements of Proteins in Aqueous Solution.

In this work, we report mid-IR transmission measurements of the protein amide I band in aqueous solution at large optical paths. A tunable external-cavity quantum cascade laser (EC-QCL) operated in pulsed mode at room temperature allowed one to apply a path length of up to 38 µm, which is four times larger than that applicable with conventional FT-IR spectrometers. To minimize temperature-induced variations caused by background absorption of the ν2-vibration of water (HOH-bending) overlapping with the amide I region, a highly stable temperature control unit with relative temperature stability within 0.005 °C was developed. An advanced data processing protocol was established to overcome fluctuations in the fine structure of the emission curve that are inherent to the employed EC-QCL due to its mechanical instabilities. To allow for wavenumber accuracy, a spectral calibration method has been elaborated to reference the acquired IR spectra to the absolute positions of the water vapor absorption bands. Employing this setup, characteristic spectral features of five well-studied proteins exhibiting different secondary structures could be measured at concentrations as low as 2.5 mg mL(-1). This concentration range could previously only be accessed by IR measurements in D2O. Mathematical evaluation of the spectral overlap and comparison of second derivative spectra confirm excellent agreement of the QCL transmission measurements with protein spectra acquired by FT-IR spectroscopy. This proves the potential of the applied setup to monitor secondary structure changes of proteins in aqueous solution at extended optical path lengths, which allow experiments in flow through configuration.

Modeling excitation-emission fluorescence matrices with pattern recognition algorithms for classification of Argentine white wines according grape variety.

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