Using second-order calibration method based on trilinear decomposition algorithms coupled with high performance liquid chromatography with diode array detector for determination of quinolones in honey samples

A novel strategy that combines the second-order calibration method based on the trilinear decomposition algorithms with high performance liquid chromatography with diode array detector (HPLC-DAD) was developed to mathematically separate the overlapped peaks and to quantify quinolones in honey samples. The HPLC-DAD data were obtained within a short time in isocratic mode. The developed method could be applied to determine 12 quinolones at the same time even in the presence of uncalibrated interfering components in complex background. To access the performance of the proposed strategy for the determination of quinolones in honey samples, the figures of merit were employed. The limits of quantitation for all analytes were within the range 1.2-56.7 μg kg⁻¹. The work presented in this paper illustrated the suitability and interesting potential of combining second-order calibration method with second-order analytical instrument for multi-residue analysis in honey samples.     

Quantitative fluorescence kinetic analysis of NADH and FAD in human plasma using three- and four-way calibration methods capable of providing the second-order advantage

The metabolic coenzymes reduced nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) are the primary electron donor and acceptor respectively, participate in almost all biological metabolic pathways. This study develops a novel method for the quantitative kinetic analysis of the degradation reaction of NADH and the formation reaction of FAD in human plasma containing an uncalibrated interferent, by using three-way calibration based on multi-way fluorescence technique. In the three-way analysis, by using the calibration set in a static manner, we directly predicted the concentrations of both analytes in the mixture at any time after the start of their reactions, even in the presence of an uncalibrated spectral interferent and a varying background interferent. The satisfactory quantitative results indicate that the proposed method allows one to directly monitor the concentration of each analyte in the mixture as the function of time in real-time and nondestructively, instead of determining the concentration after the analytical separation. Thereafter, we fitted the first-order rate law to their concentration data throughout their reactions. Additionally, a four-way calibration procedure is developed as an alternative for highly collinear systems. The results of the four-way analysis confirmed the results of the three-way analysis and revealed that both the degradation reaction of NADH and the formation reaction of FAD in human plasma fit the first-order rate law. The proposed methods could be expected to provide promising tools for simultaneous kinetic analysis of multiple reactions in complex systems in real-time and nondestructively.     

Quantitative analysis of levodopa, carbidopa and methyldopa in human plasma samples using HPLC-DAD combined with second-order calibration based on alternating trilinear decomposition algorithm

An HPLC method combined with second-order calibration based on alternating trilinear decomposition (ATLD) algorithm has been developed for the quantitative analysis of levodopa (LVD), carbidopa (CBD) and methyldopa (MTD) in human plasma samples. Prior to the analysis of the analytes by ATLD algorithm, three time regions of chromatograms were selected purposely for each analyte to avoid serious collinearity. Although the spectra of these analytes were similar and interferents coeluted with the analytes studied in biological samples, good recoveries of the analytes could be obtained with HPLC-DAD coupled with second-order calibration based on ATLD algorithm, additional benefits are decreasing times of analysis and less solvent consumption. The average recoveries achieved from ATLD with the factor number of 3 (N = 3) were 100.1 ± 2.1, 96.8 ± 1.7 and 104.2 ± 2.6% for LVD, CBD and MTD, respectively. In addition, elliptical joint confidence region (EJCR) tests as well as figures of merit (FOM) were employed to evaluate the accuracy of the method.     

Simultaneous determination of naphazoline and pyridoxine in eye drops using excitation–emission matrix fluorescence coupled with second-order calibration method based on alternating trilinear decomposition algorithm

A novel method is developed for the direct determination of naphazoline hydrochloride(NAP) and pyridoxine hydrochloride(VB6) in commercial eye drops. By using excitation–emission matrix(EEM)fluorescence coupled with second-order calibration method based on the alternating trilinear decomposition(ATLD) algorithm, the proposed approach can achieve quantitative analysis successfully even in the presence of unknown and uncalibrated interferences. The method shows good linearity for NAP and VB6 with correlation coefficients greater than 0.99. The results were in good agreement with the labeled contents. To further confirm the feasibility and reliability of the proposed method, the same batch samples were analyzed by multiple reaction monitoring(MRM) based on LC–MS/MS method.T-test demonstrated that there are no significant differences between the prediction results of the two methods. The satisfactory results obtained in this work indicate that the use of the second-order calibration method coupled with the EEM is a promising tool for industrial quality control and pharmaceutical analysis due to its advantages of high sensitivity, low-cost and simple implementation.     

Second-order multivariate calibration procedures applied to high-performance liquid chromatography coupled to fast-scanning fluorescence detection for the determination of fluoroquinolones

Different second-order multivariate calibration algorithms, namely parallel factor analysis (PARAFAC), N-dimensional partial least-squares (N-PLS) and multivariate curve resolution-alternating least-squares (MCR-ALS) have been compared for the analysis of four fluoroquinolones in aqueous solutions, including some human urine samples (additional four fluoroquinolones were simultaneously determined by univariate calibration). Data were measured in a short time with a chromatographic system operating in the isocratic mode. The detection system consisted of a fast-scanning spectrofluorimeter, which allows one to obtain second-order data matrices containing the fluorescence intensity as a function of retention time and emission wavelength. The developed approach enabled us to determine eight analytes, some of them with overlapped profiles, without the necessity of applying an elution gradient, and thus significantly reducing both the experimental time and complexity. The study was employed for the discussion of the scopes of the applied second-order chemometric tools. The quality of the proposed technique coupled to each of the evaluated algorithms was assessed on the basis of the figures of merit for the determination of fluoroquinolones in the analyzed water and urine samples. Univariate calibration of four analytes led to limits of detection in the range 20–40 ng mL⁻¹ and root mean square errors for the validation samples in the range 30–60 ng mL⁻¹ (corresponding to relative prediction errors of 3–8%). The ranges for second-order multivariate calibration (using PARAFAC and N-PLS) of the remaining four analytes were: limit of detection, 2–8 ng mL⁻¹, root mean square errors, 3–50 ng mL⁻¹ and relative prediction errors, 1–5%.     

交替三线性分解算法用于水杨酸和2,5-二羟基苯甲酸的荧光法同时测定

水杨酸 (SA)、2 ,5 二羟基苯甲酸 (GA)和对 氨基苯甲酸 (PABA)的荧光光谱相互重叠。用交替三线性分解二阶校正法对PABA共存下的SA和GA进行了同时荧光测定 ,SA和GA的回收率分别为 (1 0 1 2± 1 9) %和 (97 1 6±1 0 4 ) %。     

A novel algorithm for linear multivariate calibration based on the mixed model of samples

We present a novel algorithm for linear multivariate calibration that can generate good prediction results. This is accomplished by the idea of that testing samples are mixed by the calibration samples in proper proportion. The algorithm is based on the mixed model of samples and is therefore called MMS algorithm. With both theoretical support and analysis of two data sets, it is demonstrated that MMS algorithm produces lower prediction errors than partial least squares (PLS2) model, has similar prediction performance to PLS1. In the anti-interference test of background, MMS algorithm performs better than PLS2. At the condition of the lack of some component information, MMS algorithm shows better robustness than PLS2.     

Quantitative analysis of triazine herbicides in environmental samples by using high performance liquid chromatography and diode array detection combined with second-order calibration based on an alternating penalty trilinear decomposition algorithm

A novel application of second-order calibration method based on an alternating penalty trilinear decomposition (APTLD) algorithm is presented to treat the data from high performance liquid chromatography-diode array detection (HPLC-DAD). The method makes it possible to accurately and reliably analyze atrazine (ATR), ametryn (AME) and prometryne (PRO) contents in soil, river sediment and wastewater samples. Satisfactory results are obtained although the elution and spectral profiles of the analytes are heavily overlapped with the background in environmental samples. The obtained average recoveries for ATR, AME and PRO are 99.7 ± 1.5, 98.4 ± 4.7 and 97.0 ± 4.4% in soil samples, 100.1 ± 3.2, 100.7 ± 3.4 and 96.4 ± 3.8% in river sediment samples, and 100.1 ± 3.5, 101.8 ± 4.2 and 101.4 ± 3.6% in wastewater samples, respectively. Furthermore, the accuracy and precision of the proposed method are evaluated with the elliptical joint confidence region (EJCR) test. It lights a new avenue to determine quantitatively herbicides in environmental samples with a simple pretreatment procedure and provides the scientific basis for an improved environment management through a better understanding of the wastewater-soil-river sediment system as a whole.     

Using the L1 norm to select basis set vectors for multivariate calibration and calibration updating

With projection based calibration approaches, such as partial least squares (PLS) and principal component regression (PCR), the calibration space is spanned by respective basis vectors (latent vectors). Up to rank k basis vectors are formed where k ≤ min(m,n) with m and n denoting the number of calibration samples and measured variables. The user needs to decide how many and which respective basis vectors (tuning parameters). To avoid the second issue, basis vectors are selected top‐down starting with the first and sequentially adding until model criteria are satisfied. Ridge regression (RR) avoids the issues by using the full set of basis vectors. Another approach is to select a subset from the total available. The presented work develops a process based on the L₁ vector norm to select basis vectors. Specifically, the L₁ norm is used to select singular value decomposition (SVD) basis set vectors for PCR (LPCR). Because PCR, PLS, RR, and others can be expressed as linear combination of the SVD basis vectors, the focus is on selection and comparison using the SVD basis set. Results based on respective tuning parameter selections and weights applied to the SVD basis vectors for LPCR, top‐down PCR, correlation PCR (CPCR), PLS, and RR are compared for calibration and calibration updating using spectroscopic data sets. The methods are found to predict equivalently. In particular, the L₁ norm produces similar results to those obtained by the well‐studied CPCR process. Thus, the new method provides a different theoretical framework than CPCR for selecting basis vectors. Copyright © 2016 John Wiley & Sons, Ltd.     

Enhancing the selectivity of liquid chromatography–mass spectrometry by using trilinear decomposition on LC‐MS data: An application to three‐way calibration of coeluting analytes in human plasma

The high selectivities of liquid chromatography and mass spectrometry make liquid chromatography–mass spectrometry one of the most popular tools for quantitative analysis in complex chemical, biological, and environmental systems, while the potential mathematical selectivity of liquid chromatography–mass spectrometry is rarely investigated. This work discussed the mathematical selectivity of liquid chromatography–mass spectrometry by three‐way calibration based on the trilinear model, with an application to quantitative analysis of coeluting aromatic amino acids in human plasma. By the trilinear decomposition of the constructed liquid chromatography–mass spectrometry‐sample trilinear model and individual regression of the decomposed relative intensity versus concentration, the proposed three‐way calibration method successfully achieved quantitative analysis of coeluting aromatic amino acids in human plasma, even in the presence of uncalibrated interferent(s) and a varying background. This analytical method can ease the requirements for sample preparation and complete chromatographic separation of components, reduce the use of organic solvents, decrease the time of chromatographic separation, and increase the peak capacity of liquid chromatography–mass spectrometry. As a “green analytical method”, the liquid chromatography–mass spectrometry three‐way calibration method can provide a promising tool for direct and fast quantitative analysis in complex systems containing uncalibrated spectral interferents, especially for the situation where the coelution problem is difficult to overcome.     

Maintenance of a calibration model for near infrared spectrometry by a combined principal component analysis-partial least squares approach

A novel strategy for building and maintaining calibration models has been developed for use when the future boundaries of the sample set are unknown or likely to change. Such a strategy could have an impact on the economics and time required to obtain and maintain a calibration model for routine analysis. The strategy is based on both principal component analysis (PCA) and partial least squares (PLS) multivariate techniques. The principal action of the strategy is to define how “similar” a new sample is to the samples currently defining the calibration dataset. This step is performed by residuals analysis, following PCA. If the new sample is considered to have a spectrum “similar” to previously available spectra, then the model is assumed able to predict the analyte concentration. Conversely, if the new sample is considered “dissimilar”, then there is new information in this sample, which is unknown to the calibration model and the new sample is added automatically to the calibration set in order to improve the model. The strategy has been applied to a real industrial dataset provided by BP Amoco Chemicals. The data consists of spectra of 102 sequential samples of a raw material. The strategy produced an accurate calibration model for both target components starting with only the first four samples, and required a further 17 reference measurements to maintain the model for the whole sampling sequence, which was over a 1-year period.     

Multilinear gradient elution optimization in reversed-phase liquid chromatography based on logarithmic retention models: application to separation of a set of purines, pyrimidines and nucleosides

The analytical solutions of the fundamental equation of the multilinear gradient elution are derived in two cases, when the dependence of the logarithm of the solute retention (lnk) upon the volume fraction of organic modifier (φ) is a three-parameter logarithmic expression, and when a simple linear relationship between lnk and lnφ is adopted. The derived theoretical expressions for retention times under multilinear gradient conditions are embodied to simple algorithms for fitting gradient data and especially for resolution optimization. Their performance was examined by using a mixture of 16 model compounds chosen among purines, pyrimidine and nucleosides in eluting systems modified by acetonitrile. It was found that the accuracy of the predicted gradient retention times is very satisfactory even if the simple logarithmic expression for the retention behavior of solutes, i.e. the linear dependence of lnk upon lnφ, is used.     

Reaction mechanism of methanol decomposition on Pt‐based model catalysts: A theoretical study

The decomposition mechanisms of methanol on five different Pt surfaces, the flat surface of Pt(111), Pt‐defect, Pt‐step, Pt(110)(1 × 1), and Pt(110)(2 × 1), have been studied with the DFT‐GGA method using the repeated slab model. The adsorption energies under the most stable configuration of the possible species and the activation energy barriers of the possible elementary reactions involved are obtained in this work. Through systematic calculations for the reaction mechanism of methanol decomposition on these surfaces, we found that such a reaction shows the same reaction mechanism on these Pt‐based model catalysts, that is, the final products are all H (H_ads) and CO (CO_ads) via O? H bond breaking in methanol and C? H bond scission in methoxy. These results are in general agreement with the previous experimental observations. © 2010 Wiley Periodicals, Inc. J Comput Chem, 2010.     

Daubechies小波主成分回归法机理及算法研究

将小波变换与主成分回归相结合,提出一种新型多元校正算法---小波基主成分回归法。理论分析和仿真实验表明,该法可更有效地去除噪声,提取有用信息。将其用于氯霉素及甲硝唑实际药物体系分析,与主成分回归法(PCR)相比,得到的回收率总平均相对误差由1.70%下降到0.90%。此外,通过将统计判据和小波多尺度分析相结合,发展了一种新的因子数判定方法。理论和实验研究表明,该法比传统因子数判定法具有更高的可靠性。     

基于遗传算法优化的约束背景双线性分解算法用于改进高效液相色谱灰色分析体系的校正结果

该文采用约束背景双线性分解算法(CBBL)对以高效液相色谱(HPLC)方法分离分析的灰色分析体系进行了多元校正研究。针对采用包括CBBL在内的矩阵校正方法处理HPLC灰色分析体系的固有缺陷,即在相关组分的色谱保留时间重现性较低的情形下多元校正的结果不理想,对CBBL方法进行了改进,即将待测组分的浓度与组分的色谱保留时间同时作为优化的参量引入CBBL,并采用遗传算法(GA)优化CBBL,对于模拟的组分保留时间飘移严重的HPLC灰色分析体系及保留时间重现性不佳的多种酚类化合物组成的实际HPLC灰色分析体系进行了多元校正分析,成功克服了经典CBBL的固有缺陷,取得了较理想的多元校正结果。另外,该研究所建议的方法的校正结果也显著优于传统的残差双线性分解法(RBL)以及秩消失因子分析法(RAFA)。     

Validation of a method for the analysis of nine quinolones in eggs by pressurized liquid extraction and liquid chromatography with fluorescence detection

A multiresidue method for the analysis, in egg matrices, of residues of nine quinolones used in veterinary medicine, has been developed and validated according to the provisions of Council Decision 2002/657. Compounds were extracted by a pressurized liquid extraction (PLE) technique using a 1:1 mixture of acetonitrile and a phosphoric acid buffer (pH 3.0) at 70 °C. The obtained extract was clear enough, so that no further clean-up was necessary. Analytes were determined by liquid chromatography (LC) with fluorescence detection (FL). Two chromatographic columns were compared: a high-purity silica Inertsil C₈ column and a newly developed Kinetex C₁₈ core-shell technology column. Validation was carried out at four concentration levels, using both chromatographic columns. Precision in terms of reproducibility standard deviation was between 7% and 23%, and good recoveries were obtained. Decision limit (CCα) and detection capability (CCβ) values obtained with the Inertsil and Kinetex columns were in the 0.2-19.8 μg kg⁻¹ and 0.4-33.5 μg kg⁻¹ concentration ranges, respectively. The proposed method allows residues of quinolones banned for use with laying hens to be detected and quantified in eggs. About twenty-four samples per day can be processed.     

A simple and generalized model for predicting the density of ionic liquids

A simple and accurate model to predict the density of ionic liquids is presented. The proposed model is based on a generalized correlation that has been conveniently modified and experimental literature data have been used to fit the five model parameters, to finally propose an equation that allows predicting densities of any ionic liquid. The model uses the critical temperature, the critical volume, the normal boiling temperature and the molecular mass to estimate the density at temperatures commonly used in ionic liquid applications (270–360 K). A set of 602 density data for 146 ionic liquids has been used in the study. The results were compared with predictions of ten generalized corresponding states principle correlations available in the literature. These generalized correlations have not been applied to ionic liquids before so the appropriateness and accuracy of these models to ionic liquid density estimation are unknown until now. Results show that the new simple correlation gives low deviations and can be used with confidence in thermodynamic and engineering calculations.     

A balance-evolution artificial bee colony algorithm for protein structure optimization based on a three-dimensional AB off-lattice model

Protein structure prediction is a fundamental issue in the field of computational molecular biology. In this paper, the AB off-lattice model is adopted to transform the original protein structure prediction scheme into a numerical optimization problem. We present a balance-evolution artificial bee colony (BE-ABC) algorithm to address the problem, with the aim of finding the structure for a given protein sequence with the minimal free-energy value. This is achieved through the use of convergence information during the optimization process to adaptively manipulate the search intensity. Besides that, an overall degradation procedure is introduced as part of the BE-ABC algorithm to prevent premature convergence. Comprehensive simulation experiments based on the well-known artificial Fibonacci sequence set and several real sequences from the database of Protein Data Bank have been carried out to compare the performance of BE-ABC against other algorithms. Our numerical results show that the BE-ABC algorithm is able to outperform many state-of-the-art approaches and can be effectively employed for protein structure optimization.