New strategy to identify radicals in a time evolving EPR data set by multivariate curve resolution-alternating least squares

Electron paramagnetic resonance (EPR) spectroscopy is a powerful technique that is able to characterize radicals formed in kinetic reactions. However, spectral characterization of individual chemical species is often limited or even unmanageable due to the severe kinetic and spectral overlap among species in kinetic processes. Therefore, we applied, for the first time, multivariate curve resolution-alternating least squares (MCR-ALS) method to EPR time evolving data sets to model and characterize the different constituents in a kinetic reaction. Here we demonstrate the advantage of multivariate analysis in the investigation of radicals formed along the kinetic process of hydroxycoumarin in alkaline medium. Multiset analysis of several EPR-monitored kinetic experiments performed in different conditions revealed the individual paramagnetic centres as well as their kinetic profiles. The results obtained by MCR-ALS method demonstrate its prominent potential in analysis of EPR time evolved spectra.     

pH- and time-dependent hemoglobin transitions: a case study for process modelling

The study of the pH- and time-dependent transitions of the hemoglobin is presented as a biochemical problem of interest and as a very complete example of the situations that can be encountered in the modelling of complex processes. Therefore, the aim is two-fold: providing a complete explanation of the biochemical phenomena studied and explaining the modelling strategies used to solve this problem that can be generally applied in processes of different origin. Multivariate curve resolution-alternating least squares (MCR-ALS) is the basic method used to recover the process contributions, expressed as the concentration profile and the pure spectrum of each of the compounds involved. What is the benefit of using multitechnique or multiexperiment data arrangements, how constraints should be selected and applied and how hybrid approaches combining hard- and soft-modelling can allow for the use of a partially known model when available are among the main issues presented.     

Analysis of time-dependent conjugation of gold nanoparticles with an antiparkinsonian molecule by using curve resolution methods

In this work, the time-dependent conjugation process between a thiolated molecule (with anti-parkinsonian properties) and gold nanoparticles has been monitored and studied by the combined use of fast acquisition Ultra Violet–Visible (UV–Vis) spectra and the ability of Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) technique. From the highly informative kinetic profiles obtained it was possible to extract quantitative and qualitative information of the conjugation process which includes i) time-dependent concentration profiles and pure spectra of species involved on conjugation process, ii) estimation of molecule concentration necessary for the completeness of the conjugation reaction, iii) molecule footprint and iv) free energy of molecule adsorption.     

Multivariate curve resolution of incomplete fused multiset data from chromatographic and spectrophotometric analyses for drug photostability studies

An advanced and powerful chemometric approach is proposed for the analysis of incomplete multiset data obtained by fusion of hyphenated liquid chromatographic DAD/MS data with UV spectrophotometric data from acid–base titration and kinetic degradation experiments. Column- and row-wise augmented data blocks were combined and simultaneously processed by means of a new version of the multivariate curve resolution-alternating least squares (MCR-ALS) technique, including the simultaneous analysis of incomplete multiset data from different instrumental techniques. The proposed procedure was applied to the detailed study of the kinetic photodegradation process of the amiloride (AML) drug. All chemical species involved in the degradation and equilibrium reactions were resolved and the pH dependent kinetic pathway described.     

Study of ε-caprolactone polymerization by NIR spectroscopy

Near-infrared (NIR) spectroscopy is proposed for the in-line quantitative and kinetic study of the polymerization of ε-caprolactone and eventually to facilitate real-time control of the manufacturing process. Spectra were acquired with a fibre-optic probe operating in transflectance mode immersed in the reactor. The NIR data acquired were processed using a multivariate curve resolution alternating least squares (MCR-ALS) algorithm. The proposed method allows calculation of the concentration and spectral profiles of the species involved in the reaction. The key point of this method is the lack of reference concentrations needed to perform the MCR-ALS method. The use of an extended spectral matrix using both process and pure analyte spectra solves the rank deficiency. The concentration profiles obtained were used to calculate a kinetic fitting of the reaction, but the method was improved by applying kinetic constraints (hard modelling). The rate constants of batches at different temperatures and the energy of activation for this reaction were calculated. Whenever possible, the hard modelling combined with the MCR-ALS method improves the fit of the experimental data: the results show good correlation between the NIR and reference data and allow the collection of high-quality kinetic information on the reaction (rate constants and energy of activation).     

Multivariate resolution of rank-deficient near-infrared spectroscopy data from the reaction of curing epoxy resins using the rank augmentation strategy and multivariate curve resolution alternating least squares approach

A model of the curing reaction between phenyl glycidyl ether (PGE) and aniline as the curing agent was studied isothermally at 95 °C and monitored in situ by near-infrared spectroscopy (NIR). The spectra were recorded every 5 min. The ubiquitous problem of rank deficiency in reaction network systems was solved by assembling an augmented column-wise matrix containing five process runs from different initial conditions. The data were analyzed using a two-way multivariate curve resolution alternating least squares method (MCR-ALS). Initial estimates of spectra required by MCR-ALS were given by a SIMPLe-to-use Interactive Self-modeling Mixture Analysis (SIMPLISMA) approach. The reactants, product and intermediate spectra were successfully resolved and the concentration profiles properly represented the system studied. The performance of the model was evaluated by two parameters: ALS lack of fit (lof=0.88%) and explained variance (R²=99.99%). To validate the MCR-ALS results, the similarity coefficients (r) between the recovered spectra and the pure species spectra were calculated. These were: PGE (r=0.998), aniline (r=0.994) and tertiary amine (r=0.999).     

Two-dimensional correlation spectroscopy and multivariate curve resolution for the study of lipid oxidation in edible oils monitored by FTIR and FT-Raman spectroscopy

Accelerate oxidative degradation of six vegetable oils was monitored using FTIR and FT-Raman spectroscopy. Two-dimensional correlation spectroscopy and multivariate curve resolution alternating least squares (MCR-ALS) were applied to the analysis of the data. The use of hetero-spectral two-dimensional correlation of FTIR and FT-Raman data allowed the use of well established band assignments to interpret less clearly assigned spectral features. With a moving window approach it was possible to obtain simplified two-dimensional correlation maps and to detect compounds evolving with different kinetic. Simultaneous analysis of the oxidation experiments of the six different oils monitored by both spectroscopic techniques was performed using MCR-ALS. Although a complete resolution of the data was not possible, the spectral changes occurring during the oxidative degradation of the oils were described with a five-component model. The two fundamentally different chemometric approaches lead to coincident results.     

Quantitative analysis of the effect of zidovudine,efavirenz, and ritonavir on insulin aggregation by multivariate curve resolution alternating least squares of infrared spectra

Quantification of the effect of antiretroviral drugs on the insulin aggregation process is an important area of research due to the serious metabolic diseases observed in AIDS patients after prolonged treatment with these drugs. In this work, multivariate curve resolution alternating least squares (MCR-ALS) was applied to infrared monitoring of the insulin aggregation process in the presence of three antiretroviral drugs to quantify their effect. To evidence concentration dependence in this process, mixtures at two different insulin:drug molar ratios were used. The interaction between insulin and each drug was analysed by ¹H NMR spectroscopy. In all cases, the aggregation process was monitored during 45 min by infrared spectroscopy. The aggregates were further characterised by scanning electron microscopy (SEM). MCR-ALS provided the spectral and concentration profiles of the different insulin–drug conformations that are involved in the process. Their feasible band boundaries were calculated using the MCR-BANDS methodology. The kinetic profiles describe the aggregation pathway and the spectral profiles characterise the conformations involved. The retrieved results show that each of the three drugs modifies insulin conformation in a different way, promoting the formation of aggregates. Ritonavir shows the strongest promotion of aggregation, followed by efavirenz and zidovudine. In the studied concentration range, concentration dependence was only observed for zidovudine, with shorter aggregation time obtained as the amount of zidovudine increased. This factor also affected the aggregation pathway.     

Investigation of the interaction of carbofuran and DNA by voltammetry and fluorescence with the aid of chemometrics

<正>The interactions of carbofuran and DNA were studied using voltammetry and fluorescence spectroscopy.The formation of carbofuran-DNA makes the current peak of DNA decreased by voltammetry method.The binding number(n) and constant(K_a) for complex carbofuran-DNA were calculated to be 1.06±0.04 and 0.11±0.03mol~(-1) L,respectively by fluorescence measurement.Chemometrics approach,such as singular value decomposition(SVD) was used to evaluate the number of spectral species in the drug-DNA binding process.And the pure spectra and concentration profiles in the kinetic system were clearly deduced by multivariate curve resolution alternating least squares(MCR-ALS) with the initial estimates by evolving factor analysis(EFA).     

Multivariate curve resolution applied to in situ X-ray absorption spectroscopy data: An efficient tool for data processing and analysis

Large datasets containing many spectra commonly associated with in situ or operando experiments call for new data treatment strategies as conventional scan by scan data analysis methods have become a time-consuming bottleneck. Several convenient automated data processing procedures like least square fitting of reference spectra exist but are based on assumptions. Here we present the application of multivariate curve resolution (MCR) as a blind-source separation method to efficiently process a large data set of an in situ X-ray absorption spectroscopy experiment where the sample undergoes a periodic concentration perturbation. MCR was applied to data from a reversible reduction–oxidation reaction of a rhenium promoted cobalt Fischer–Tropsch synthesis catalyst. The MCR algorithm was capable of extracting in a highly automated manner the component spectra with a different kinetic evolution together with their respective concentration profiles without the use of reference spectra. The modulative nature of our experiments allows for averaging of a number of identical periods and hence an increase in the signal to noise ratio (S/N) which is efficiently exploited by MCR. The practical and added value of the approach in extracting information from large and complex datasets, typical for in situ and operando studies, is highlighted.     

Ubiquinol formation in isolated photosynthetic reaction centres monitored by time-resolved differential FTIR in combination with 2D correlation spectroscopy and multivariate curve resolution

Two-dimensional correlation analysis was carried out in combination with multivariate curve resolution–alternating least squares (MCR-ALS) to analyse time-resolved infrared (IR) difference spectra probing photo-induced ubiquinol formation in detergent-isolated reaction centres from Rhodobacter sphaeroides. The dynamic 2D IR correlation spectra have not only allowed the determination of the concomitance or non-concomitance of different chemical events through known marker bands but also have helped identify new vibrational bands related to the complex series of photochemical and redox reactions. In particular, a strong positive band located at 1565 cm⁻¹ was found to be synchronous with the process of ubiquinol formation. In addition, a tailored MCR-ALS analysis was performed using a priori chemical knowledge of the system, in particular including the pure spectrum of one species obtained from an external measurement. Enhancing the MCR-ALS performance in this way in time-dependent processes is relevant, especially when other essential pieces of information, such as kinetic models, are unavailable. The results give evidence of four independent spectral contributions. Three of them show marker bands for a monoelectronic reduction of the primary quinone Q_A (Q_A⁻/Q_A transition, first contribution), for a monoelectronic reduction of a secondary quinone Q_B (Q_B⁻/Q_B transition, second contribution) and for ubiquinol formation (third contribution). The results obtained also confirm that a key rate-limiting factor is the slow ubiquinone and ubiquinol exchange among micelles, which strongly influences the kinetic profiles of the involved species.     

Comprehensive description of the photodegradation of bromophenols using chromatographic monitoring and chemometric tools

A general procedure for the study of complex photodegradation processes of environmental pollutants based on chromatographic monitoring and chemometric method is proposed. The procedure consists of multiset data analysis of aliquots collected at different reaction times and injected in High-Performance Liquid Chromatography coupled to diode array detection and mass spectrometry (HPLC-DAD-MS). In this study, photodegradation of six bromophenols with different degrees of bromination has been investigated in order to find out their photodegradation pathways and kinetics and to show the potential of the procedure proposed. Multivariate curve resolution-alternating least squares (MCR-ALS) has been used to resolve chromatographic elution profiles and pure spectra of species involved in the photodegradation process and, hence, to elucidate the photodegradation mechanism and to propose the chemical structure of the main photoproducts. This study shows that chromatographic monitoring is the preferred option when photochemical systems with large number of components with similar spectra and kinetic evolution are analyzed. This work reveals the advantages of the double DAD and MS detection to provide mechanistic and structural information about these complex photodegradation processes.     

Enzyme kinetics assay in ionic liquid-based reaction media by means of Raman spectroscopy and multivariate curve resolution

Enzymatic hydrolysis of p-nitrophenylphosphate by alkaline phosphatase in binary mixtures of water and 1-ethyl-3-methylimidazolium tetrafluoroborate (emimBF₄) was monitored with Raman microspectroscopy. Concentrations of emimBF₄ in the studied ionic liquid/water solvent systems ranged from 0 to 75% v/v. Multivariate curve resolution-alternating least squares (MCR-ALS) was successfully applied to the recorded Raman spectra in order to retrieve the concentration profiles and pure Raman spectra of the different species involved in the reaction. Michaelis-Menten constant (K_M) and maximum rate (V_max) of the reaction were calculated from the initial reaction phase for the different solvent systems studied, to investigate the effect of increasing concentration of the ionic liquid on the kinetic behavior. From this study, it was found that the ionic liquid inhibits the reaction under study decreasing both V_max and K_M.     

Infrared study of aging of edible oils by oxidative spectroscopic index and MCR-ALS chemometric method

One of the most suitable analytical techniques used for edible oil quality control is Fourier transform mid infrared spectroscopy (FT-MIR). FT-MIR spectroscopy was used to continuously characterize the aging of various edible oils thanks to a specific aging cell. There were differences in the spectra of fresh and aged oils from different vegetable sources, which provide the basis of a method to classify them according to the oxidative spectroscopic index value. The use of chemometric treatment such as multivariate curve resolution-alternative least square (MCR-ALS) made it possible to extract the spectra of main formed and degraded species. The concentration profiles gave interesting information about the ability of the various oils to support the oxidative treatment and showed that all oils present the same aging process. Both methods led to concordant results in terms of induction times determined by the oxidative spectroscopic index and the appearance of oxidation products revealed by MCR-ALS.     

Multivariate curve resolution applied to the simultaneous analysis of electrochemical and spectroscopic data: study of the Cd(II)/glutathione-fragment system by voltammetry and circular dichroism spectroscopy

Multivariate curve resolution with alternating least squares (MCR-ALS) is applied for the first time to the simultaneous analysis of electrochemical and spectroscopic data. Then, a data analysis is done with augmented matrices constituted by Differential Pulse Polarography and Circular Dichroism data submatrices. The use of proper, and different for each submatrix, constrains in the iterative ALS optimization allows to obtain chemically meaningful results constituted by a common matrix containing the concentration profiles, and two matrices with the pure electrochemical and spectroscopic signals. MCR-ALS is applied to the study of the complexation of Cd by Cys-Gly, a glutathione-fragment of great interest for understanding metal-phytochelatins complexation.     

通过红外光谱结合化学计量学方法研究奥克托今的合成机理

通过红外(IR)光谱在线监测醋酐法合成奥克托今(HMX)的反应过程, 采用渐进因子分析(EFA)结合多元曲线分辨-交替最小二乘法(MCR-ALS)以及直观推导式演进特征投影法(HELP)等化学计量学方法对反应过程的光谱数据矩阵进行解析, 获得了各组分浓度变化曲线和对应的IR光谱; 并采用密度泛函理论(DFT)的B3LYP方法, 在6-31G^*基组水平上得到该化合物的全优化结构, 在振动分析的基础上求得体系的振动频率和IR光谱. 通过对比发现, MCR-ALS和HELP法可得出相互验证的一致结论; 将通过量子化学计算的中间体的IR光谱特征吸收峰与2种方法进行比较, 结果吻合, 从而推导出合理的反应机理. 实验结果表明, 化学计量学方法结合在线红外光谱是研究反应机理的有效手段, 对反应路线的选择具有指导意义.     

Process modeling of reduction and acetylation reactions by spectrophotometric and chemometrics methods

Achieving high levels of chemoselectivity is a pivotal feature of chemical synthesis. Although significant progress has been made in this regards, lots of challenges lie ahead. Herein, multivariate curve resolution-alternating least square (MCR-ALS) was employed to overcome the spectral overlapping of the reactants and products in the model reactions of methyl-(4-formyl) benzoate by NaBH₄ and acetylation of p-aminophenol by acetyl chloride. The first-order ultraviolet/visible absorbance spectra were recorded during the addition of different quantities of reagent to the substrate. The absorbing species, coexisting in the system, were detected through employing factor analysis. The soft-modeling analysis of the evolutionary absorbance data by MCR-ALS revealed that both model reactions proceed through a two-step consecutive manner. Using the obtained concentration profiles, one can obtain an idea about the suitable molar ratio of reagent/substrate for selective production of one of the reaction products. Moreover, the pure spectrum of the intermediate species could be estimated.     

Novel combination of non-aqueous capillary electrophoresis and multivariate curve resolution-alternating least squares to determine phenolic acids in virgin olive oil

This paper presents the development of a non-aqueous capillary electrophoresis method coupled to UV detection combined with multivariate curve resolution-alternating least-squares (MCR-ALS) to carry out the resolution and quantitation of a mixture of six phenolic acids in virgin olive oil samples. p-Coumaric, caffeic, ferulic, 3,4-dihydroxyphenylacetic, vanillic and 4-hydroxyphenilacetic acids have been the analytes under study. All of them present different absorption spectra and overlapped time profiles with the olive oil matrix interferences and between them. The modeling strategy involves the building of a single MCR-ALS model composed of matrices augmented in the temporal mode, namely spectra remain invariant while time profiles may change from sample to sample. So MCR-ALS was used to cope with the coeluting interferences, on accounting the second order advantage inherent to this algorithm which, in addition, is able to handle data sets deviating from trilinearity, like the data herein analyzed. The method was firstly applied to resolve standard mixtures of the analytes randomly prepared in 1-propanol and, secondly, in real virgin olive oil samples, getting recovery values near to 100% in all cases. The importance and novelty of this methodology relies on the combination of non-aqueous capillary electrophoresis second-order data and MCR-ALS algorithm which allows performing the resolution of these compounds simplifying the previous sample pretreatment stages.     

Application of Multivariate curve resolution-alternating least square methods on the resolution of overlapping CE peaks from different separation conditions

Discussed in this paper is the development of a new strategy to improve resolution of overlapping CE peaks by using second-order multivariate curve resolution with alternating least square (second-order MCR-ALS) methods. Several kinds of organic reagents are added, respectively, in buffers and sets of overlapping peaks with different separations are obtained. Augmented matrix is formed by the corresponding matrices of the overlapping peaks and is then analyzed by the second-order MCR-ALS method in order to use all data information to improve the precision of the resolution. Similarity between the resolved unit spectrum and the true one is used to assess the quality of the solutions provided by the above method. 3,4-Dihydropyrimidin-2-one derivatives (DHPOs) are used as model components and mixed artificially in order to obtain overlapping peaks. Three different impurity levels, 100, 20, and 10% relative to the main component, are used. With this strategy, the concentration profiles and spectra of impurities, which are no more than 10% of the main component, can be resolved from the overlapping peaks without pure standards participant in the analysis. The effects of the changes in the components spectra in the buffer with different organic reagents on the resolution are also evaluated, which are slight and can thus be ignored in the analysis. Individual data matrices (two-way data) are also analyzed by using MCR-ALS and heuristic evolving latent projections (HELP) methods and their results are compared with those when MCR-ALS is applied to augmented data matrix (three-way data) analysis.     

Protein folding kinetics: barrier effects in chemical and thermal denaturation experiments

Recent experimental work on fast protein folding brings about an intriguing paradox. Microsecond-folding proteins are supposed to fold near or at the folding speed limit (downhill folding), but yet their folding behavior seems to comply with classical two-state analyses, which imply the crossing of high free energy barriers. However, close inspection of chemical and thermal denaturation kinetic experiments in fast-folding proteins reveals systematic deviations from two-state behavior. Using a simple one-dimensional free energy surface approach we find that such deviations are indeed diagnostic of marginal folding barriers. Furthermore, the quantitative analysis of available fast-kinetic data indicates that many microsecond-folding proteins fold downhill in native conditions. All of these proteins are then promising candidates for an atom-by-atom analysis of protein folding using nuclear magnetic resonance.1 We also find that the diffusion coefficient for protein folding is strongly temperature dependent, corresponding to an activation energy of approximately 1 kJ.mol-1 per protein residue. As a consequence, the folding speed limit at room temperature is about an order of magnitude slower than the approximately 1 micros estimates from high-temperature T-jump experiments. Our analysis is quantitatively consistent with the available thermodynamic and kinetic data on slow two-state folding proteins and provides a straightforward explanation for the apparent fast-folding paradox.