Anna de Juan

Multivariate Curve Resolution (MCR) from 2000: Progress in Concepts and Applications

This work is mainly oriented to give an overview of the progress of multivariate curve resolution methods in the last 5 years. Conceived as a review that combines theory and practice, it will present the basics needed to understand what is the use, prospects and limitations of this family of chemometric methods with the latest trends in theoretical contributions and in the field of analytical applications.

Combining hard- and soft-modelling to solve kinetic problems

Abstract A novel approach mixing the qualities of hard-modelling and soft-modelling methods is proposed to analyse kinetic data monitored spectrometrically. Taking as a basis the Multivariate Curve Resolution–Alternating Least Squares method (MCR–ALS), which obtains the pure concentration profiles and spectra of all absorbing species present in the raw measurements by using typical soft-modelling constraints, a new hard constraint is introduced to force some or all the concentration profiles to fulfill a kinetic model, which is refined at each iterative cycle of the optimisation process. This modification of MCR–ALS drastically decreases the rotational ambiguity associated with the kinetic profiles obtained using exclusively soft-modelling constraints. The optional inclusion of some or all the absorbing species into the kinetic model allows the successful treatment of data matrices whose instrumental response is not exclusively due to the chemical components involved in the kinetic process, an impossible scenario for classical hard-modelling approaches. Moreover, the possible distinct constraint of each of the matrices in a three-way data set allows for the simultaneous analysis of kinetic runs with diverse kinetic models and rate constants. Thus, the introduction of model-based and model-free features in the treatment of kinetic data sets yields more satisfactory results than the application of pure hard- or pure soft-modelling approaches. Simulated and real examples are used to confirm this statement.

Spectroscopic imaging and chemometrics: a powerful combination for global and local sample analysis

Merging spectroscopic imaging and chemometrics enhances the outcomes of instrumental technology and data analysis. Multivariate exploratory and resolution methods can be adapted to image analysis and provide global and local information about pure compounds in an imaged sample. Knowing in detail how the chemical compounds are distributed over the scanned surface gives valuable information about essential issues in the manufacture and the characterization of products, such as evenness of composition and, therefore, homogeneity of the sample. The power to detect and to locate impurities is also greatly enhanced because these unwanted compounds could show locally large concentrations (and signals), even though their abundance on the surface is very low. The capabilities of this combination are shown in an example of pharmaceutical product control, where analysis of the end product requires chemical characterization and quantitative information at global and local levels. The approach used and the kind of information obtained is general and can be applied to the analysis of images in other fields.

Multivariate Curve Resolution (MCR). Solving the mixture analysis problem

This article is a tutorial that focuses on the main aspects to be considered when applying Multivariate Curve Resolution to analyze multicomponent systems, particularly when the Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) algorithm is used. These aspects include general MCR comments on the potential fields of application and construction of data structures and details linked to each of the steps in the application workflow of the MCR-ALS algorithm (e.g., selection of initial estimates, choice and application of constraints, quality parameters of models and assessment of ambiguity,…). Two examples with downloadable data sets are shown for orientation on the practical use of this methodology.

Vibrational spectroscopic image analysis of biological material using multivariate curve resolution–alternating least squares (MCR-ALS)

Raman and Fourier transform IR (FTIR) microspectroscopic images of biological material (tissue sections) contain detailed information about their chemical composition. The challenge lies in identifying changes in chemical composition, as well as locating and assigning these changes to different conditions (pathology, anatomy, environmental or genetic factors). Multivariate data analysis techniques are ideal for decrypting such information from the data. This protocol provides a user-friendly pipeline and graphical user interface (GUI) for data pre-processing and unmixing of pixel spectra into their contributing pure components by multivariate curve resolution–alternating least squares (MCR-ALS) analysis. The analysis considers the full spectral profile in order to identify the chemical compounds and to visualize their distribution across the sample to categorize chemically distinct areas. Results are rapidly achieved (usually <30–60 min per image), and they are easy to interpret and evaluate both in terms of chemistry and biology, making the method generally more powerful than principal component analysis (PCA) or heat maps of single-band intensities. In addition, chemical and biological evaluation of the results by means of reference matching and segmentation maps (based on k-means clustering) is possible.

Application of chemometric methods to environmental analysis of organic pollutants: A review

Organic pollutants include a very wide variety of chemical compounds with different structures, properties, functions and origins, which may produce diverse damages to the ecosystem and the human beings. This review presents the recent progress on the use of chemometrics to evaluate the occurrence of these substances in the environment. The main topics addressed are: (a) the problems related to the interpretation of the analytical measurements used in the determination of organic pollutants (quantitative analytical determinations section), (b) the profiling of the related environmental pollution sources through their compositional, geographical and temporal distribution patterns (environmental exploratory studies section) and (c) the prediction of the toxicological activity of these substances through models based on the use of structural or physical/chemical descriptors (toxicity studies section). Each section includes selected works related to pesticides, polycyclic aromatic hydrocarbons and other organic pollutants.

Application of a novel resolution approach combining soft- and hard-modelling features to investigate temperature-dependent kinetic processes

Abstract A new resolution method based on the combination of hard- and soft-modelling is applied to the analytical study of spectrometrically monitored kinetic processes. This method results from the modification of the iterative soft-modelling multivariate curve resolution-alternating least-squares method (MCR-ALS) by the inclusion of a new hard constraint that forces some or all the concentration profiles to fulfil a kinetic model. In this way, strengths of both soft- and hard-modelling data analysis methods are combined and limitations linked to the application of only one of these pure approaches are overcome. The new method is applied to a real example of cyclometallation reaction. This is a challenging case where the extent of the process changes with temperature and the spectra of the different species formed do not differ extremely from each other. Besides, due to the lability of the initial reagent, the nature and the concentrations of all the reacting components present at the beginning of the process are not always known. The example presented is representative of many other complex kinetic problems, which could not be solved by the use of traditional methods based exclusively on the straightforward fitting of kinetic models.

Comparison between the direct trilinear decomposition and the multivariate curve resolution-alternating least squares methods for the resolution of three-way data sets

Abstract Direct trilinear decomposition (DTD) and multivariate curve resolution-alternating least squares (MCR-ALS) methods are two of the most representative three-way resolution procedures. The former, non-iterative, is based on the resolution of the generalized eigenvector/eigenvalue problem and the latter, iterative, is focused on the optimization of initial estimates by using data structure and chemical constraints. DTD and MCR-ALS have been tested on a variety of three-way simulated data sets having common sources of variation in real response profiles, such as signal shift, broadening or shape distortions caused by noise. The effect of these factors on the resolution results has been evaluated through the analysis of several parameters related to the recovery of both qualitative and quantitative information and to the quality of the overall data description. Conclusions inferred from the simulated examples help to clarify the performance of both methods on a real example and to provide some general guidelines to understand better the potential of each method.

Photodegradation study of decabromodiphenyl ether by UV spectrophotometry and a hybrid hard- and soft-modelling approach.

This work presents an exploratory study of the photochemical degradation process of decabromodiphenyl ether (decaBDE) and gives an interpretation of the kinetic pathway, species and effects of the key factors involved in the degradation process. Use of lowly brominated diphenyl ethers (PBDE) has been banned by the EU and there seems to be evidence of the photolytic degradation of highly brominated PBDEs into lowly brominated congeners. Hence, the importance of knowing the photodegradation process of decaBDE. The photodegradation was investigated under UV light by UV-spectrophotometric monitoring. A novel hybrid data analysis approach, based on the combination of hard- and soft-spectrophotometric multivariate curve resolution, was applied to elucidate the mechanism of the degradation process, to resolve kinetic profiles and pure spectra of the photodegradation products and to evaluate the rate constants. The photodegradation process could be described with a kinetic model based on three consecutive first-order reactions and a decrease of the degradation process was observed as solvent polarity increased. Complementary identification of photodegradation products by gas chromatography coupled to mass spectrometry using negative chemical ionization (GC-NCI-MS) is attempted. This work presents a novel attempt of describing in a comprehensive way the photochemical degradation process of decaBDE, with all successive steps and related rate constants. This study proves also the potential of the proposed hybrid data analysis methodology as a general strategy to interpret the evolution of these photochemical reactions.

Three-way data analysis applied to multispectroscopic monitoring of protein folding

Multivariate curve resolution-alternating least squares (MCR-ALS) is proposed as a three-way analysis method to deal with multispectroscopic monitoring of protein folding. MCR-ALS provides the concentration profiles associated with the different protein conformations occurring during the process and their related spectra. The concentration profiles describe the folding mechanism and the spectra provide the structural information of the conformations involved. Analysis either of the protein folding process monitored with different techniques (i.e. a row-wise augmented data matrix) or of several experiments done in different conditions using the same technique (i.e. a column-wise augmented matrix) or both possibilities at the same time (i.e. a row- and column-wise augmented matrix), can be performed. Thermal unfolding and refolding of α-lactalbumin, monitored using far- and near-UV circular dichroism, fluorescence and UV spectrometry, is shown as example. Information related to changes in the tertiary and the secondary structure of the protein, to the presence of intermediates along the protein folding process and to the reversibility of the thermal process can be obtained.