A new third‐order calibration method with application for analysis of four‐way data arrays

A novel third‐order calibration algorithm, alternating weighted residue constraint quadrilinear decomposition (AWRCQLD) based on pseudo‐fully stretched matrix forms of quadrilinear model, was developed for the quantitative analysis of four‐way data arrays. The AWRCQLD algorithm is based on the new scheme that introduces four unique constraint parts to improve the quality of four‐way PARAFAC algorithm. The tested results demonstrated that the AWRCQLD algorithm has the advantage of faster convergence rate and being insensitive to the excess component number adopted in the model compared with four‐way PARAFAC. Moreover, simulated data and real experimental data were analyzed to explore the third‐order advantage over the second‐order counterpart. The results showed that third‐order calibration methods possess third‐order advantages which allow more inherent information to be obtained from four‐way data, so it can improve the resolving and quantitative capability in contrast with second‐order calibration especially in high collinear systems. Copyright © 2011 John Wiley & Sons, Ltd.     

Two‐way and three‐way approaches to ultra high performance liquid chromatography–photodiode array dataset for the quantitative resolution of a two‐component mixture containing ciprofloxacin and ornidazole

Two‐way and three‐way calibration models were applied to ultra high performance liquid chromatography with photodiode array data with coeluted peaks in the same wavelength and time regions for the simultaneous quantitation of ciprofloxacin and ornidazole in tablets. The chromatographic data cube (tensor) was obtained by recording chromatographic spectra of the standard and sample solutions containing ciprofloxacin and ornidazole with sulfadiazine as an internal standard as a function of time and wavelength. Parallel factor analysis and trilinear partial least squares were used as three‐way calibrations for the decomposition of the tensor, whereas three‐way unfolded partial least squares was applied as a two‐way calibration to the unfolded dataset obtained from the data array of ultra high performance liquid chromatography with photodiode array detection. The validity and ability of two‐way and three‐way analysis methods were tested by analyzing validation samples: synthetic mixture, interday and intraday samples, and standard addition samples. Results obtained from two‐way and three‐way calibrations were compared to those provided by traditional ultra high performance liquid chromatography. The proposed methods, parallel factor analysis, trilinear partial least squares, unfolded partial least squares, and traditional ultra high performance liquid chromatography were successfully applied to the quantitative estimation of the solid dosage form containing ciprofloxacin and ornidazole.     

Comparison of PARAFAC and PARALIND in modeling three‐way fluorescence data array with special linear dependences in three modes: a case study in 2‐naphthol

Owing to excited‐state proton transfer in 2‐naphthol solutions, the fluorescence excitation–emission matrices (EEMs) have factors that are highly dependent in three modes. For the first time such EEMs are used to compare the capability of PARALIND (PARAFAC with linear dependence) and conventional PARAFAC in modeling three‐way EEMs having linearly dependent factors in three modes. Two primary conclusions have been drawn. First, the results indicate that a 3‐factor PARAFAC model fit the data better than two PARALIND models (type 1 and 2) in this case while equally well with a specially PARALIND model (type 3); second, a negative core consistency (CC) in the 3‐factor PARAFAC model is reported but the type 3 PARALIND model reports a nearly 100 CC. This work has demonstrated that a properly constrained PARALIND can fit the very special EEMs of 2‐naphthol. The presence of negative CC associated with a perfect PARAFAC model would imply the presence of very special linear dependences in EEMs, which would be used as an “alarm” for the investigators to interpret the data more carefully when dealing with complicated environmental EEMs in the absence of a priori knowledge. Copyright © 2010 John Wiley & Sons, Ltd.     

Generative topographic mapping of binding pocket of β2 receptor and three‐way partial least squares modeling of inhibitory activities

The visualization and characterization of protein pockets is the starting point for many structure‐based drug design projects. The size and shape of protein pockets dictate 3D geometry of ligands that can strongly inhibit the following biological events. Thus, a minimal requirement for inhibition is that a molecule sterically binds the active site with some allowance for induced fit. Methods for direct display of active sites in a protein have become prevalent in recent years. In this study, a new mapping method, generative topographic mapping, is investigated to describe the 3D surface of protein pocket. The β2 receptor protein is used as a benchmark. By mapping the molecular surface points and assigning the associated molecular electrostatic potential (MEP) values, the original 3D structure of the active site is well reproduced by the 2D latent map in generative topographic mapping. The distributions of MEP values of two 2D latent maps derived from the inhibitor and the β2 receptor protein are well complemented. Using three‐way partial least squares modeling, a predictive model linking the inhibitory activity and their MEP values can be constructed, which was not feasible in the previous spherical self‐organizing map studies. The resulting regression coefficient matrix of the three‐way partial least squares model has many insights for understanding the structural requirements for β2 inhibitory activity. Copyright © 2014 John Wiley & Sons, Ltd.     

Theoretical analysis of vibrational spectra and scaling‐factor of 2‐aryl‐1,3,4‐oxadiazole derivatives

In this study, the direct molecular structure implementations for calculating vibrational spectra and scaling factors, and infrared intensities at both the Hartree–Fock (HF) and density functional (B3LYP) levels of theory with 6‐31G(d), 6‐311G(d), 6‐31++G(d,p), and 6‐311++G(d,p) basis sets are presented. Also, vibrational frequencies have been investigated as dependence on the choice of method and basis set. The parameters of molecular geometry and vibrational frequencies values of 2‐aryl‐1,3,4‐oxadiazoles 5a–g in the ground state have been calculated. Theoretical determination of vibrational frequencies is quite useful both in understanding the relationship between the molecular structures and scaling factor. The data of 2‐aryl‐1,3,4‐oxadiazoles 5a–g display significant electronic properties provide the basis for future design of efficient materials having the oxadiazole core and theoretical IR studies. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2009     

Mitigating dead‐time effects during multivariate analysis of ToF‐SIMS spectral images

ToF‐SIMS spectra are formed by bombarding a surface with a pulse of primary ions and detecting the resultant ionized surface species using a time‐of‐flight mass spectrometer. Typically, the detector is a time‐to‐digital converter. Once an ion is detected using such detectors, the detector becomes insensitive to the arrival of additional ions for a period termed as the (detector) dead‐time. Under commonly used ToF‐SIMS data acquisition conditions, the time interval over which ions arising from a single chemical species reach the detector is on the order of the detector dead‐time. Thus, only the first ion reaching the detector at any given mass is counted. The event registered by the data acquisition system, then, is the arrival of one or more ions at the detector. This behavior causes ToF‐SIMS data to violate, in the general case, the assumption of linear additivity that underlies many multivariate statistical analysis techniques. In this article, we show that high‐mass‐resolution ToF‐SIMS spectral‐image data follow a generalized linear model, and we propose a data transformation and scaling procedure that enables such data sets to be successfully analyzed using standard methods of multivariate image analysis. Copyright © 2008 John Wiley & Sons, Ltd.     

Combining targeted and nontargeted data analysis for liquid chromatography/high‐resolution mass spectrometric analyses

Increasing importation of food and the diversity of potential contaminants have necessitated more analytical testing of these foods. Historically, mass spectrometric methods for testing foods were confined to monitoring selected ions (SIM or MRM), achieving sensitivity by focusing on targeted ion signals. A limiting factor in this approach is that any contaminants not included on the target list are not typically identified and retrospective data mining is limited. A potential solution is to utilize high‐resolution MS to acquire accurate mass full‐scan data. Based on the instrumental resolution, these data can be correlated to the actual mass of a contaminant, which would allow for identification of both target compounds and compounds that are not on a target list (nontargets). The focus of this research was to develop software algorithms to provide rapid and accurate data processing of LC/MS data to identify both targeted and nontargeted analytes. Software from a commercial vendor was developed to process LC/MS data and the results were compared to an alternate, vendor‐supplied solution. The commercial software performed well and demonstrated the potential for a fully automated processing solution.     

Probabilistic model‐based discriminant analysis and clustering methods in chemometrics

In chemometrics, the supervised and unsupervised classification of high‐dimensional data has become a recurrent problem. Model‐based techniques for discriminant analysis and clustering are popular tools, which are renowned for their probabilistic foundations and their flexibility. However, classical model‐based techniques show a disappointing behaviour in high‐dimensional spaces, which up to now have been limited in their use within chemometrics. The recent developments in model‐based classification overcame these drawbacks and enabled the efficient classification of high‐dimensional data, even in the ‘small n / large p’ condition. This work presents a comprehensive review of these recent approaches, including regularization‐based techniques, parsimonious modelling, subspace classification methods and classification methods based on variable selection. The use of these model‐based methods is also illustrated on real‐world classification problems in chemometrics using R packages. Copyright © 2013 John Wiley & Sons, Ltd.     

Topological analysis of the three‐dimensional coordination polymer poly[(μ4‐azido)[μ4‐5‐(pyridin‐4‐yl)tetrazolido]disilver(I)]

The title compound, [Ag₂(C₆H₄N₄)(N₃₎]_n, was obtained under hydrothermal conditions at 433 K. The asymmetric unit of the orthorhombic space group (Pna2₁) consists of two Ag⁺ cations, an anionic 5‐(pyridin‐4‐yl)tetrazolide (4‐ptz⁻) ligand and an anionic azide ligand. Both Ag⁺ centres are coordinated by four N atoms, forming a distorted tetrahedral coordination environment. When all the component ions are viewed as 4‐connected nodes, the whole three‐dimensional network can be regarded topologically as a new kind of 4,4,4,4‐connected net with the Schläfli symbol (4.8⁵)(4².8⁴)(4³.8³)₂.     

Imputation of left‐censored data for cluster analysis

A new method of imputation for left‐censored datasets is reported. This method is evaluated by examining datasets in which the true values of the censored data are known so that the quality of the imputation can be assessed both visually and by means of cluster analysis. Its performance in retaining certain data structures on imputation is compared with that of three other imputation algorithms by using cluster analysis on the imputed data. It is found that the new imputation method benefits a subsequent model‐based cluster analysis performed on the left‐censored data. The stochastic nature of the imputations performed in the new method can provide multiple imputed sets from the same incomplete data. The analysis of these provides an estimate of the uncertainty of the cluster analysis. Results from clustering suggest that the imputation is robust, with smaller uncertainty than that obtained from other multiple imputation methods applied to the same data. In addition, the use of the new method avoids problems with ill‐conditioning of group covariances during imputation as well as in the subsequent clustering based on expectation–maximization. The strong imputation performance of the proposed method on simulated datasets becomes more apparent as the groups in the mixture models are increasingly overlapped. Results from real datasets suggest that the best performance occurs when the requirement of normality of each group is fulfilled, which is the main assumption of the new method. Copyright © 2013 John Wiley & Sons, Ltd.     

Fast quantitative analysis of four tyrosine kinase inhibitors in different human plasma samples using three‐way calibration‐ assisted liquid chromatography with diode array detection

A simple method has been developed by combining high‐performance liquid chromatography with diode array detection with the alternating trilinear decomposition method for simultaneous determination of four tyrosine kinase inhibitors in different human plasma samples. Chromatographic separation of the analytes was performed on a reversed‐phase column with methanol (65%, v/v, A) and 0.1% aqueous solution of formic acid (35%, v/v, B). Analysis time was 5.0 min per run and analytes could be completely eluted within 2.8??3.8 min. The calibration concentration ranges of vandetanib, pazopanib, afatinib and dasatinib were designed as 0.50–6.10, 0.50–6.10, 0.70–7.00 and 0.70–7.00 μg·mL^?1, respectively. The intra‐ and inter‐day RSDs ranged between 0.1 and 8.9%. Quantitative information could be extracted from the unsegregated interferences of different human plasma samples with the aid of the “second‐order advantage” of three‐way (second‐order) calibration methods. All results demonstrated that the proposed method for direct quantitative analysis of four tyrosine kinase inhibitors in different complex systems possessed good characteristics of rapidity, sensitivity and efficiency, and it is expected to be an attractive choice in the fast analysis of clinical samples.     

DCMB that combines divide‐and‐conquer and mixed‐basis set methods for accurate geometry optimizations,total energies,and vibrational frequencies of large molecules

We present a method, named DCMB, for the calculations of large molecules. It is a combination of a parallel divide‐and‐conquer (DC) method and a mixed‐basis (MB) set scheme. In this approach, atomic forces, total energy and vibrational frequencies are obtained from a series of MB calculations, which are derived from the target system utilizing the DC concept. Unlike the fragmentation based methods, all DCMB calculations are performed over the whole target system and no artificial caps are introduced so that it is particularly useful for charged and/or delocalized systems. By comparing the DCMB results with those from the conventional method, we demonstrate that DCMB is capable of providing accurate prediction of molecular geometries, total energies, and vibrational frequencies of molecules of general interest. We also demonstrate that the high efficiency of the parallel DCMB code holds the promise for a routine geometry optimization of large complex systems. © 2012 Wiley Periodicals, Inc.     

Evaluation of matrix effects in the analysis of volatile organic compounds in whole blood with solid‐phase microextraction

The complexity and matrix variability of biological samples requires an accurate evaluation of matrix effects. The dilution of the biological sample is the simplest way to reduce or avoid the matrix effect. In the present study, a set of volatile organic compounds with different volatilities was used to assess the effect of the dilution of blood samples on the extraction efficiency by headspace solid‐phase microextraction. It was found that there was a significant matrix effect but that this effect differs significantly depending on the volatility of the compound. A 1:2 (blood/water) dilution was enough to allow quantitative recoveries of those compounds with boiling points <100°C. For compounds with boiling points between 100 and 150°C, the matrix effect was stronger and a 1:5 dilution was required. The dilution of blood samples proved to be inefficient for quantitative recovery of compounds with boiling points >150°C. A 1:5 dilution of the sample allowed detection limits in the range of nanogram per liter to be obtained. This was sufficient to detect the main volatile compounds present in blood and contamination after exposure.     

Selective J‐resolved‐HMQC‐1 and ‐2, new methods for measuring proton–proton coupling constants in strongly coupled spin systems

Efficient pulse sequences for measuring ¹H–¹H coupling constants (J_HH) in strongly coupled spin systems, named selective J‐resolved‐HMQC‐1 and ‐2, have been developed. In the strongly coupled spin systems such as ‐CH₂‐CH_A(OH)‐CH_B(OH)‐CH₂‐, measurements of ³J_HAHB are generally difficult owing to the complicated splitting caused by the adjacent CH₂ protons. For easier and accurate measurements of ³J_HAHB in such a spin system, a selective excitation pulse is incorporated into the J‐resolved HMQC pulse sequence. In the proposed methods, only two strongly coupled protons, H_A and H_B which are excited by a selective pulse, are observed as J‐resolved HMQC signals. The cross peaks of H_A and H_B appear as doublets owing to ³J_HAHB along the F₁ dimension in the selective J‐resolved HMQC‐1 and ‐2 experiments. The efficiency of the proposed pulse sequences has been demonstrated in application to the stereochemical studies of the complicated natural product, monazomycin. Copyright © 2011 John Wiley & Sons, Ltd.     

Application of a genomic model for high‐dimensional chemometric analysis

The rapid development of new technologies for large‐scale analysis of genetic variation in the genomes of individuals and populations has presented statistical geneticists with a grand challenge to develop efficient methods for identifying the small proportion of all identified genetic polymorphisms that have effects on traits of interest. To address such a “large p small n” problem, we have developed a heteroscedastic effects model (HEM) that has been shown to be powerful in high‐throughput genetic analyses. Here, we describe how this whole‐genome model can also be utilized in chemometric analysis. As a proof of concept, we use HEM to predict analyte concentrations in silage using Fourier transform infrared spectroscopy signals. The results show that HEM often outperforms the classic methods and in addition to this presents a substantial computational advantage in the analyses of such high‐dimensional data. The results thus show the value of taking an interdisciplinary approach to chemometric analysis and indicate that large‐scale genomic models can be a promising new approach for chemometric analysis that deserve to be evaluated more by experts in the field. The software used for our analyses is freely available as an R package at http://cran.r‐project.org/web/packages/bigRR/ . Copyright © 2014 John Wiley & Sons, Ltd.     

Remarkable solvent effects in the hydro‐ and solvothermal synthesis of copper‐1,10‐phenanthroline complexes

Compound {[Cu(II)/Cu(I)]₂(ophen)₄(Htpt)}^?2H₂O ( 1 ) was obtained by hydrothermal reaction. Compound 1 is a mixed‐valence copper coordination complex with a different coordination environment. The X‐ray structural analysis of 1 revealed two crystallographically independent dimeric [Cu₂(ophen)₂]⁺ units bridged by two µ₁‐carboxylate groups of the tpt ligand into a butterfly‐shaped molecule in the crystal structure. Compound [Cu(I)₃(CN)₃(phen)₃] ( 2 ) was synthesized using ethanol instead of water, and consisted of an infinite helix chain formed from [Cu(I)(phen)]⁺ units bridged by cyano groups. Copyright © 2007 John Wiley & Sons, Ltd.     

Improving surface‐analysis methods for characterization of advanced materials by development of standards,reference data,and interlaboratory comparisons

This paper summarizes the results of two surveys examining current needs for improved analyses of surfaces. Surfaces and interfaces are increasingly important to science and technologies associated with nanoparticles, nano‐structured materials and other complex materials including those associated with information systems and medical or biological applications. Adequate characterization of advanced materials frequently requires application of more than one analysis method along with the need to analyze data in increasingly sophisticated and sometimes interrelated ways. It is useful for both new and experienced analysts to have ready access to best practices for obtaining accurate and useful information from a variety of different analysis tools. The International Organization for Standardization (ISO) Committee TC 201 on surface chemical analysis and the ASTM Committee E‐42 on surface analysis are working to address these needs by assembling guides and standards reflecting the collective experience and wisdom of experts in this community. Published in 2007 by John Wiley & Sons, Ltd     

One‐, two‐, and three‐electron bonding: An “in vitro” theoretical study using noninteger nuclear charges evidences the crucial role of electronegativity in the strength of symmetrical bonds

Fictitious hydrogen atoms H*_A of variable nuclear charge 0.5 ≤ Z_A ≤ 2 (and thus of variable electronegativity) are used to study the intrinsic dependency of chemical bonding on electronegativity. Dissociation energy and equilibrium distance are reported for symmetrical 1‐, 2‐ and 3‐electron H*_AH*_A systems and 2‐electron dissymmetrical H*_A‐H ones. Dealing with symmetrical systems, the strongest two‐electron bonds are found for Z_A ≈ 1.2. Oneelectron and three‐electron strongest bonds occur respectively with low (ca. 0.7) and high (ca. 1.7) Z_A values and can become stronger than the corresponding 2‐electron system. Comparison with data on real systems leads to conclude that electronegativity is a prevailing atomic property in the control of the dissociation energy of symmetrical 1‐, 2‐ and 3‐electron bonds. A simplified mathematical model at Hartree‐Fock or Heitler‐London level with a minimal basis set reproduces these trends semi‐quantitatively and provides the overall shape of the dissociation curves. Finally some points are qualitatively discussed from MO analysis, which emphasize the dependence of the bonding/antibonding properties on the nucleus charge Z_A and their occupancy number. © 2011 Wiley Periodicals, Inc. Int J Quantum Chem, 2011     

Evaluation of matrix effects in different multipesticide residue analysis methods using liquid chromatography–tandem mass spectrometry,including an automated two‐dimensional cleanup approach

Pesticide residue analysis is an important part of food quality control. Three of the most widely used methods are the DFG S19 (extraction with acetone), the ChemElut method (extraction with methanol), and QuEChERS (quick, easy, cheap, effective, rugged, safe; acetonitrile‐based). Despite many developments in the field of sample preparation, matrix effects are still one of the most disturbing problems in routine analysis. In this study, we compare the matrix effects in LC–MS analysis after using these three methods in pesticide analysis. Using postcolumn infusion, we were able to visualize all suppressions over the whole chromatogram in matrix‐effect profiles. Recently, we also presented a system for the determination of up to 300 pesticides from various kinds of fruit and vegetables. For the measurement, we injected an aliquot of a raw acetonitrile extract. The subsequent cleanup was carried out fully automated by a multidimensional LC. Matrix compounds and analytes are separated in the first dimension on a hydrophilic interaction LC column. In this study, we also compared this new approach with the classical methods. The matrix‐effect profiles showed less suppression with the hydrophilic interaction LC‐based cleanup. A final evaluation of the partitioning steps of all methods confirmed the benefits of the chromatographic cleanup approach.