Science based calibration for the extraction of 'analyte-specific' HPLC-DAD chromatograms in environmental analysis

Multivariate science based calibration (SBC) has been applied to the resolution of overlapped peaks in liquid chromatography with diode array detection (LC-DAD). Complex river water samples spiked with 11 pharmaceutical substances resulted in poorly resolved chromatograms containing additional peaks from interfering matrix compounds and a change in the background absorbance due to the mobile phase gradient. Applying the present multivariate approach it was possible to resolve all 11 analytes from overlapping peaks, obtaining linear calibration lines (R² > 0.96). Recovery percentages on spiked samples ranged between 74.6 and 113.5%, which are quite satisfactory taking into account the low concentration ranges considered to 1-7 μg L⁻¹.     

窗口因子分析技术用于重叠色谱峰的解析

采用窗口因子分析（ＷＦＡ）技术完成了稀土元素的高效液相色谱分析中重叠峰的解析。由３种分离条件下不同分离度的色谱数据矩阵解析得到了较好的单组分色谱图与吸收光谱曲线,并进行了定量分析。结果表明：在分离度较好时,ＷＦＡ定量结果与常规方法相近,但随着分离度的降低,ＷＦＡ的定量结果明显优于常规方法。     

Local resolution of two-way data from multicomponent equilibria

A self-modeling curve resolution (SMCR) method is proposed to calculate concentration and spectral profiles for the two-way spectral data from an equilibrium containing several chemical components. The proposed method has three main distinctive steps: (i) fixed size moving window evolving factor analysis (FSMWEFA) is used to identify the selective and zero concentration regions for a desired component, (ii) orthogonal projection resolution (OPR) is used to calculate its concentration profile and (iii) the component striping is done directly to resolve other components. The results of simulated and real polyprotic acid dissociation equilibria showed that the proposed combined method performs well even in situation when the successive stepwise equilibrium constants are close to each other. The applicability of method for resolving the triprotic acid system with rank deficiency due full spectral overlapping of two involved chemical species also is shown.     

Parallel factor analysis of HPLC-DAD data for binary mixtures of lidocaine and prilocaine with different levels of chromatographic separation

A set of 17 samples containing a constant amount of lidocaine (667 μM) and a decreasing amount of prilocaine (667-0.3 μM) was analysed by LC-DAD at three different levels of separation, followed by parallel factor analysis (PARAFAC) of the data obtained. In Case 1 no column was connected, the chromatographic resolution (R_s) therefore being zero, while Cases 2 and 3 had partly separated peaks (R_s=0.7 and 1.0). The results showed that in Case 1, analysed without any separation, the PARAFAC decomposition with a model consisting of two components gave a good estimate of the spectral and concentration profiles of the two compounds. In Cases 2 and 3, the use of PARAFAC models with two components resolved the underlying chromatographic, spectral and concentration profiles. The loadings related to the concentration profile of prilocaine were used for regression and prediction of the prilocaine content. The results showed that prediction of prilocaine content was possible with satisfactory prediction (RMSEP<0.01). This study shows that PARAFAC is a powerful technique for resolving partly separated peaks into their pure chromatographic, spectral and concentration profiles, even with completely overlapping spectra and the absence or very low levels of separation.     

Quantification of target components in complex mixtures using alternative moving window factor analysis and two-step iterative constraint method

Alternative moving window factor analysis (AMWFA) has shown the powerfulness for comprehensive comparison and individual identification of chemical components among different but related mixture systems. However, quantification of these components can only be attained after extraction of all spectra of pure components in samples with least square technique. In this study, a novel two-step iterative constraint method (TICM) is developed for independent quantification of the interested target analytes. The pure chromatographic profiles of the components can be mined out from mixtures with high complexity using a two-step iterative operation and stepwise purification of the targets from interferers. Some effective constraints of chromatographic profiles, such as non-negative and single-peaked properties, as well as zero-concentration outside of elution windows of components, are employed to further improve the efficiency of the method. One of the strong advantages of TICM is simplification of complex mixtures to several sub-systems for processing easily with the help of AMWFA, as well as bi-linear property of data sets obtained from coupled chromatographic instruments. It meets the urgent requirements and challenges of qualitative and quantitative analysis of complicated systems with multi-component in the investigation of herbal medicines (HMs), metabonomics and systems biology. From the results of simulated LC–DAD data, GC–MS data of volatile chemical components in three kinds of ginseng with different growth conditions, and four different medicinal parts of the same herb, good performance of the proposed method is achieved.     

Chemical Fingerprint Analysis for Quality Control of Herba Ephedrae Based on HPLC-DAD Combined with Chemometrics Methods

A method based on high performance liquid chromatography with photodiode array detector (HPLC-DAD) was developed for chemical fingerprinting analysis of Herba Ephedrae. The index of chromatographic fingerprint's information content was utilized to optimize the fingerprint detection conditions, which reduced the time of analysis and increased the veracity of analysis greatly. Then, the similarity analysis of fingerprints was used in quality consistency evaluation of Herba Ephedrae samples. Moreover, hierarchical clustering analysis (HCA) was applied to classify the samples according to their sources and varieties. In addition, the overlapped chromatographic peaks were resolved with the help of heuristic evolving latent projection (HELP) method in order to gain the better quantitative evaluation. The results indicated that the samples could be successfully grouped in accordance with their varieties and sources. Furthermore, five marker constituents were firstly screened out to be the main chemical markers, which importantly contribute to the classification of Herba Ephedrae samples. This investigation shows that the developed methodology can be generalized to the research of quality control of herbal medicines.     

Discrimination of Scrophularia spp. according to geographic origin with HPLC-DAD combined with multivariate analysis

Discrimination of Scrophularia spp. according to the geographic origin was tried in the present study using HPLC-DAD combined with multivariate analysis techniques. Five active constituents, angoroside C, harpagoside, 8-O-(E-p-methoxycinnamoyl)harpagide, E-cinnamic acid and E-p-methoxycinnamic acid, in forty four Scrophularia samples were simultaneously determined using HPLC-DAD. A principal component analysis of the content measurements clustered the samples according to their geographic origins, Andong, Uisung and China. A partial least squares-discrimination analysis was subsequently developed for the effective classification of the samples. This model showed comparatively good prediction ability for samples from Andong or China. The proposed method shows an efficient strategy for quality control of Scrophularia spp.     

Application of multi-way data analysis on excitation-emission spectra for plant identification

The ability to distinguish among diets fed to Damascus goats using excitation-emission luminescence spectra was investigated. These diets consisted of Medicago sativa L. (alfalfa), Trifolium spp. (clover), Pistacia lentiscus, Phyllirea latifolia and Pinus brutia. The three-dimensional luminescence response surface from phosphate buffered saline (PBS) extracts of each material was analyzed using muti-way analysis chemometric tools (MPCA) and parallel factor analysis (PARAFAC). Using three principal components, the spectra from each diet material were distinguished. Additionally, fecal samples from goats fed diets of either alfalfa or clover hays were investigated. The application of MPCA and PARAFAC to these samples using models derived from the pre-digested diet materials was strongly suggestive of the utility of similarly derive training samples for the elucidation of botanical diet composition for animals.     

交替拟合残差算法与高效液相色谱-二极管阵列检测方法结合同时测定两种抗结核药物

本文利用化学计量学交替拟合残差(AFR)算法与高效液相色谱-二极管阵列检测(HPLC-DAD)方法相结合,同时测定两种抗结核药物异烟肼和吡嗪酰胺的含量。该法与交替三线性分解算法(ATLD)、自加权交替三线性分解(SWATLD)算法相比较,从预测均方差、预测相对误差以及平均回收率等结果来看,其预测结果更接近实际值。研究表明,基于交替拟合残差等算法的二阶校正法,可以迅速准确地给出色谱重叠情况下两个组分的预测结果,是复杂体系成分直接定量分析的一个有力的化学计量学工具。     

Simultaneous determination of reaction order and rate constant by rank annihilation factor analysis from kinetic-spectral data

Rank annihilation factor analysis combined with the optimization of kinetic parameter is adopted to resolve the two-way kinetic-spectral data measured online from chemical reactions. To a multi-step reaction whose intermediate process is complicated and reaction order is fractional, the reaction order and rate constant of the first step can be determined without the knowledge of the kinetic model of the reaction. Taken a three-step reaction as an example, the synthetic data has been resolved and its effectiveness was proved. When the approach is applied to the analysis of practical reaction systems such as alkaline hydrolysis of phenyl benzoate, oxidization of sodium bromide by potassium permanganate and electro-degradation of sunset yellow, reliable results are obtained.     

利用红外光谱和窗口因子分析研究加热导致的牛血清白蛋白的二级结构变化

用红外光谱和窗口因子分析(WFA)对加热导致的D2O中牛血清白蛋白(BSA)的二级结构变化进行了研究. 常规光谱分析和WFA的结果表明, BSA的结构变化开始于56 ℃, 而二级结构的剧烈变化发生在68~82 ℃, 与α-螺旋片断相连的短链变化发生的温度比其它二级结构变化的发生温度低10 ℃左右. 研究结果表明, WFA在解析溶液里蛋白质的温度相关红外光谱中起重大作用.     

Fingerprint and multicomponent quantitative analysis for the quality evaluation of Sibiraea angustata leaves by HPLC-DAD and HPLC-ESI-MS/MS combined with chemometrics

Sibiraea angustata leaves, known as a traditional Tibetan medicine, have been specially used in the treatment of indigestion and obesity. In the study, a simple and sensitive high-performance liquid chromatography (HPLC) method with a diode array detector (DAD) was established to solve the problem of lacking quality standard of S. angustata leaves, including the fingerprint analysis and quantification of six characteristic components. The analytical method was validated for linearity, repeatability, stability, recovery, and specificity. Seventeen raw samples and 1 processed sample of S. angustata leaves were collected from different locations of China to establish the fingerprint. The chemometric methods, including similarity analysis (SA), principal component analysis (PCA), and hierarchical clustering analysis (HCA), were applied to distinguish the 18 batches of S. angustata samples. The results successfully sorted these samples into five clusters and kept in line with each other. According to the result of the fingerprint analysis, 21 peaks were extracted to be the common peaks and most of them were identified by mass spectrometry (MS) with electron-spray ionization (ESI) in the negative mode. Meanwhile, the loading plot of PCA further indicated that the peaks of neochlorogenic acid, chlorogenic acid, ferulic acid, rutin, hyperin, and isoquercitrin played a greater role in the discrimination among the 21 peaks. So the six components mentioned above were investigated as index constituents to evaluate the quality of S. angustata leaves from different locations. The study demonstrated that the developed new method was a beneficial approach for authentication and quality evaluation of S. angustata leaves.     

Spectral regions selection to improve prediction ability of PLS models by changeable size moving window partial least squares and searching combination moving window partial least squares

Changeable size moving window partial least squares (CSMWPLS) and searching combination moving window partial least squares (SCMWPLS) are proposed to search for an optimized spectral interval and an optimized combination of spectral regions from informative regions obtained by a previously proposed spectral interval selection method, moving window partial least squares (MWPLSR) [Anal. Chem. 74 (2002) 3555]. The utilization of informative regions aims to construct better PLS models than those based on the whole spectral points. The purpose of CSMWPLS and SCMWPLS is to optimize the informative regions and their combination to further improve the prediction ability of the PLS models. The results of their application to an open-path (OP)/FT-IR spectra data set show that the proposed methods, especially SCMWPLS can find out an optimized combination, with which one can improve, often significantly, the performance of the corresponding PLS model, in terms of low prediction error, root mean square error of prediction (RMSEP) with the reasonable latent variable (LVs) number, comparing with the results obtained using whole spectra or direct combination of informative regions for a compound. Regions consisting of the combinations obtained can easily be explained by the existence of IR absorption bands in those spectral regions.     

Comparing chemical fingerprints of herbal medicines using modified window target-testing factor analysis

A chromatographic fingerprint of a herbal medicine is essentially its chromatographic spectrum: a characteristic representation of its chemical components, some of which are pharmacologically active. Since a wide variety of factors, such as the geographical location, the harvest season, and the part used can influence the chemical constituents (and therefore the pharmacological activity) of any particular herbal medicine and its products, these fingerprints provide a way to compare and contrast the compositions of different variants of the same herbal medicine. In particular, it is possible to ascertain whether particular components present in one herbal fingerprint are also present in another fingerprint. In this work we use a novel method—modified window target-testing factor analysis (MWTTFA), based on the use of target factor analysis (TFA), fixed-size moving window evolving factor analysis (FSMWEFA) and a Gaussian shape correction to the chromatographic profiles—to achieve this end. To demostrate the strategy, the fingerprints of samples from garlics produced in different geographical locations were compared, as well as the fingerprints of samples taken from above-ground and below-ground parts of Houttuynia cordata Thunb. The results from these comparisons clearly show that four chemical components present in Hunan common edible garlic are absent in Xingping base garlic, while seven components are present in Xingping base garlic but absent in Hunan common edible garlic. Also, eleven components are present in the sample from the above-ground part of Houttuynia cordata Thunb but not in the sample from the below-ground part, while seven components are present in the sample from the below-ground part of Houttuynia cordata Thunb that are not present in the sample from the above-ground part. These interesting conclusions should be very useful for future pharmacological and clinical research into these herbal medicines, and the novel MWTTFA technique can also be used for quality control purposes.     

Self-modeling curve resolution method applied for the evaluation of dissolution testing data: A case study of meloxicam-mannitol binary systems

This paper introduces some chemometric methods, i.e., self-modeling curve resolution (SMCR), multivariate curve resolution-alternating least squares (MCR-ALS) and parallel factor analysis (PARAFAC and PARAFAC2), which are used to evaluate in vitro dissolution testing data detected by a UV-vis spectrophotometer on meloxicam-mannitol binary systems. These systems were chosen because of their relative simplicity to apply as part of the validation process illustrating the effectiveness of the developed and applied chemometric method. The paper illustrates the failure of PARAFAC methods used before for pharmaceutical data evaluations as well, and we suggest application of the feasible band form given by SMCR as a more general procedure.Steps to improve the dissolution behavior of drugs have become among the most interesting aspects of pharmaceutical technology, and our results show that a larger particle size of meloxicam is advantageous for dissolution. Instead of the use of only one characteristic wavelength, appropriate chemometric methods can furnish more information from dissolution testing data, i.e., the individual dissolution rate profiles and the individual spectra for all the components can be obtained without resorting to any separation techniques such as HPLC.     

On uniqueness and selectivity in three-component parallel factor analysis

Unambiguous recovery of profiles is a distinguishable advantage of Parallel Factor Analysis (PARAFAC) as a trilinear model and has made it a promising exploratory tool for data analysis. Linear dependency in profiles destroys trilinearity and will increase ambiguity in the curve resolution of three-way data sets. PARAFAC uniqueness deteriorates totally or partially in data sets with linearly dependent loadings. Exploiting a reliable method for determination and direct visualization of feasible bands in the PARAFAC model can be helpful not only in full characterization of uniqueness conditions but also in the investigation of the effects of constraints on the PARAFAC feasible solutions. The purpose of this paper is twofold. First, the calculation of rotational ambiguity in the PARAFAC model extends to three components system. The principle behind the algorithm is described in detail and tested for simulated and real data sets. Completely general and thoroughly investigated results are presented for the three component cases. Secondly, the effects of selective regions in the profiles on the resolution of systems that suffered from the rank deficiency problem, due to rank overlap, are emphasized. In the case of two-way data sets the effect of selectivity constraint on the unique recovery of profiles was investigated and applied. However, to our knowledge, in this report, for the first time, the effect of the presence of selective windows in the profiles, on the unique resolution of three-way data sets has been systematically investigated.     

Rapid analysis of multicomponent pesticide mixture by GC-MS with the aid of chemometric resolution

Applications of hyphenated chromatographic techniques, especially GC-MS technique, have been reported in chemical, biological, environmental, agricultural and medical analysis. The complexity of the samples in these fields is still an obstacle for the technique to be practical and the overlapping of the multicomponent signals induces chemometric methods widely employed. In this work, taking the rapid analysis of pesticide mixture as an example, a chemometric approach was proposed for resolution of multicomponent overlapping GC-MS signal. In the method, a mass spectral library of pesticides was organized at first, then target factor analysis (TFA) was employed for testing the existence of a specific pesticide in the multicomponent overlapping GC-MS signal, and finally the chromatographic information of the pesticide was extracted by a non-negative immune algorithm (IA). A GC-MS signal of a 40-component pesticide mixture eluted within 9 min was analyzed by the method. It was found that the mass spectra and chromatographic profiles of almost all the pesticides can be obtained.     

Variable alignment of high resolution data by cluster analysis

High resolution time-of-flight secondary ion mass spectrometry (HR TOF-SIMS) is a powerful surface analytical method. For complex samples, this technique may yield intricate spectra that are difficult to interpret visually. Chemometric methods are useful for data analysis. However, these methods require that spectra are represented in a matrix format. Variances in mass measurements caused by calibration or instrumental effects may present difficulties in properly aligning mass spectral peaks into the correct columns of the data matrix. Cluster analysis of resolution elements is proposed as an alternative approach to construct the data matrix. An automated method for optimizing the data alignment is presented and evaluated for standard steel samples.     

Independent component analysis as a pretreatment method for parallel factor analysis to eliminate artefacts from multiway data

Parallel factor analysis (PARAFAC) has successfully been used in many applications for the analysis of excitation-emission fluorescence data. However, some measurement “artefacts”, such as Rayleigh or Raman scattering, can pose a problem for the extraction of the PARAFAC components and their interpretation. Replacing the spectral zones corresponding to these signals by missing values in the data is not necessarily a method of choice in the cases where informative signals lie in the same wavelength regions. In this article, independent component analysis (ICA) is used on the unfolded cubic array, and the independent components related to the Rayleigh and Raman scattering are identified and removed prior to the reconstruction of the excitation-emission fluorescence data cube. PARAFAC is then applied on these data reconstructed after selective artefact removal, and satisfactory models can be obtained. This procedure, although particularly useful for 3D fluorescence data, may be applied to other types of data as well.     

A novel approach of initial vectors construction in iterative target transformation factor analysis

The construction of the favorable initial iterative vectors is the key to iterative target transformation factor analysis (ITTFA). A tentative approach to construct the better initial vectors, which is based on the chromatographic information provided by evolving factor analysis (EFA), is proposed. A region, which contains the peak position at maximum height, is determined. Several elements in the region of each initial vector, instead of one element, are initialized as 1. The elements out of the region are initialized as 0. So it is not necessary to determine the exact peak position at maximum height for the resolution of partly overlapping chromatographic profiles, which may avoid the divergence brought by determination of the peak position at maximum height. In addition, it may give acceptable resolution for the embedded peaks. It is applied to resolve 2D-simulated data and experimental liquor GC/MS data, the resolutions are reasonable and improved.