Comparative study of the alignment method on experimental and simulated chromatographic data

One of the major problems in the signal comparison of chromatographic data is the variability of response caused by instrumental drifts and others instabilities. Measures of quality control and evaluation of conformity are inherently sensitive to shift. It is essential to be able to compare test samples to reference samples in an evolutionary analytical environment by offsetting the inevitable drift. Therefore, prior to any multivariate analysis, the alignment of analytical signals is a compulsory preprocessing step. During recent years, many researchers have taken a greater interest in the study of the alignment. The present paper is an updated review on the alignment algorithms, methods, and improvements used in chromatography. The study is dedicated to one‐dimensional signals. Several of the exposed methods have common theoretical bases and can differ through their optimization methods. The main issue for the operator is to choose the appropriate method according to the type of signals to be processed.     

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.     

Recognizing chromatographic peaks with pattern recognition methods III. Application of the algorithm for peak recognition in trace analysis

Summary The application of a newly developed peak recognition algorithm is shown. This algorith is based on the KNN method, one of the pattern recognition methods. It is shown that peaks with a S/N-ratio down to one can be safely recognized. This is also possible if the baseline has not only detector noise, but has other disturbances, e.g., noise signals which are generated by a reaction detector. The recognition ability of the algorithm is demonstrated by a standard chromatogram with three different concentrations and with two different sampling rates. The improvement against the classical algorithm is demonstrated. Some properties of the algorithm are discussed.     

Preprocessing and exploratory analysis of chromatographic profiles of plant extracts

The characterization of herbal extracts to compare samples from different origin is important for robust production and quality control strategies. This characterization is now mainly performed by analysis of selected marker compounds. Metabolic fingerprinting of full metabolite profiles of plant extracts aims at a more rapid and thorough screening or classification of plant material. We will show that HPLC is an appropriate technique for metabolic fingerprinting of secondary metabolites, given that adequate preprocessing of raw profiles is performed. Additional variation, which results from sample preparation and changing measurement conditions, usually obscures the information of interest in these raw profiles. This paper illustrates the importance of preprocessing of chromatographic fingerprinting data. Different alignment methods are discussed as well as the influence of normalization. Weighted principal component analysis is introduced as a valuable alternative to autoscaling of data. LC-UV data on Willow (Salix sp.) extracts is used to evaluate these preprocessing methods and their influence on exploratory data analysis.     

Liquid chromatographic fingerprint of 3-methylflavone-8-carboxylic acid established for its synthesis control analysis

A high-performance liquid chromatographic method was proposed for the separation of relative impurities in industrial 3-methylflavone-8-carboxylic acid (MFCA) and its intermediate methyl 3-propionylsalicylate (MPS). Benzoic acid (BA), MPS, 6-chloro-3-methylflavone-8-carboxylic acid (MFCA-Cl) and methyl 5-chloro-3-propionylsalicylate (MPS-Cl) in MFCA, and MPS-Cl in MPS were respectively quantified by an external standard method. As results showed, the linearity of standard curves was excellent with the relative coefficients of over 0.999 for all the detected components, and the intra- and inter-day precisions of impurities determination were satisfactory with the relative standard deviation of not more than 8.0%. Under the selected experimental condition, the chromatographic fingerprints of MFCA and MPS were drawn synthetically, and the transfer of impurities in the stepwise reactions of MFCA manufacture was elucidated. The fingerprints have great potential in instructing the production of MFCA for industrial use and in conducting the conversion of relative impurities.     

Comprehensive analysis of chromatographic data by using PARAFAC2 and principal components analysis

The most straightforward method to analyze an obtained GC–MS dataset is to integrate those peaks that can be identified by their MS profile and to perform a Principal Component Analysis (PCA). This procedure has some important drawbacks, like baseline drifts being scarcely considered or the fact that integration boundaries are not always well defined (long tails, co-eluted peaks, etc.). To improve the methodology, and therefore, the chromatographic data analysis, this work proposes the modeling of the raw dataset by using PARAFAC2 algorithm in selected areas of the GC profile and using the obtained well-resolved chromatographic profiles to develop a further PCA model. With this working method, not only the problems arising from instrumental artifacts are overcome, but also the detection of new analytes is achieved as well as better understanding of the studied dataset is obtained. As a positive consequence of using the proposed working method human time and work are saved. To exemplify this methodology the aroma profile of 36 apples being ripened were studied. The benefits of the proposed methodology (PARAFAC2 + PCA) are shown in a practitioner perspective, being able to extrapolate the conclusions obtained here to other hyphenated chromatographic datasets.     

Some problems associated with the chromatographic analysis of thiophene hydrodesulphurization products

Summary Adsorption of thiophene on the walls of stainless steel sample loops, even at relatively high temperatures (up to 180°C), is shown to result in significant errors in the chromatographic analysis of thiophene. A chromatographic system is described which allows a good separation of thiophene and C₄ hydrocarbons resulting from the catalytic hydrogenolysis of thiophene.     

Characterization of chromatographic supports for the analysis of basic compounds

Reversed‐phase liquid chromatography (RP‐HPLC) has become a powerful and widely employed technique for the analysis of a great variety of substances and, in particular, of basic compounds. These compounds are present in various areas. In pharmacy, 80% of drugs are estimated to possess a basic function. Basic compounds can strongly interact with free silanol groups on the surface of the silica particles. These ion exchange interactions produce peak tailing which affects resolution, sensitivity, and reproducibility. For these reasons, many new stationary phases have been designed to reduce access to silanol groups. The main problem facing the analyst is to effectively select the best column for a particular type of separation. In order to characterize and evaluate the properties of these packings, several tests are proposed in the literature, which can be divided into two main categories: general tests and particular tests. In this work, a particular test was developed for the characterization of base deactivated RP‐HPLC stationary phases. For this purpose, a set of 14 basic test substances was selected and five different chromatographic supports were tested with three isocratic mobile phases. Furthermore, in order to undertake a complete characterization of these supports, batch and column reproducibility were also studied. Principal Component Analysis was applied to evaluate both the performance of the test compounds and of the stationary phases.     

High‐performance liquid chromatography based chemical fingerprint analysis and chemometric approaches for the identification and distinction of three endangered Panax plants in Southeast Asia

Among Panax genus, only three endangered species Panax notoginseng, P. vietnamensis, and P. stipuleanatus that have a similar morphology are mainly distributed in Southeast Asia. These three plants are usually misidentified or adulterated. To identify them well, their chemical chromatographic fingerprints were established by an effective high‐performance liquid chromatography method. By comparing the chromatograms, the three Panax species could be distinguished easily using the 22 characteristic peaks. Besides, the data of the chromatographic fingerprints aided by chemometric approaches were applied for the identification and investigation the relationship of different samples and species. Using similarity analysis, the chemical components revealed higher similarity between P. vietnamensis and P. stipuleanatus. The results of hierarchical clustering analysis indicated that samples belonging to the same species could be clustered together. The result of principal component analysis was similar with hierarchical clustering analysis and the three principal components accounted for >80.5% of total variability.     

The selective immobilization of ceruloplasmin onto the chromatographic material used for its purification

Summary When mammalian plasma was passed through a chromatographic material containing aminoethyl functional groups, ceruloplasmin was selectively retained. At a specific ionic strength of the eluant buffer, a single chromatographic peak corresponding to the electrophoretically homogeneous purified ceruloplasmin was eluted. This single-step procedure is easy to perform and gave a purification yield of more than 60%. The direct immobilization of the ceruloplasmin, while it was still adsorbed and concentrated at the basal part of the gel bed (last stage of the purification), was achieved by carbodiimide treatment, with coupling yields of 50–70%.The immobilized ceruloplasmin retained about 100% of its enzymatic activity. Kinetic studies have shown a decreased affinity of the immobilized protein for the substrate and a maximal velocity of 81% as compared to the free protein. The immobilized ceruloplasmin was much more resistant to proteolytic attack than the free enzyme which is highly protease sensitive. Using pronase and thermolysine proteases, the activity of free ceruloplasmin was entirely lost in few hours. However, under similar conditions, the immobilized ceruloplasmin exhibited a high stability, maintaining its integral activity even after 24 hours of proteolytic attack.     

Application of unfold principal component analysis and parallel factor analysis to the exploratory analysis of olive oils by means of excitation-emission matrix fluorescence spectroscopy

Discrimination between virgin olive oils and pure olive oils is of primary importance for controlling adulterations. Here, we show the potential usefulness of two multiway methods, unfold principal component analysis (U-PCA) and parallel factor analysis (PARAFAC), for the exploratory analysis of the two types of oils. We applied both methods to the excitation-emission fluorescence matrices (EEM) of olive oils and then compared the results with the ones obtained by multivariate principal component analysis (PCA) based on a fluorescence spectrum recorded at only one excitation wavelength. For U-PCA and PARAFAC, the ranges studied were λ_ex=300-400 nm, λ_em=400-695 nm and λ_ex=300-400 nm, λ_em=400-600 nm. The first range contained chlorophylls, whose peak was much more intense than those of the rest of species. The second range did not contain the chlorophylls peak but only the fluorescence spectra of the remaining compounds (oxidation products and Vitamin E). The three-component PARAFAC model on the second range was found to be the most interpretable. With this model, we could distinguish well between the two groups of oils and we could find the underlying fluorescent spectra of three families of compounds.     

Development and evaluation of gas and liquid chromatographic methods for the analysis of fatty amines

In contrast to the plethora of publications on the separation of fatty acids, analogous studies involving fatty amines are scarce. A recently introduced ionic‐liquid‐based capillary column for GC was used to separate trifluoroacetylated fatty amines focusing on the analysis of a commercial sample. Using the ionic liquid column (isothermal mode at 200°C) it was possible to separate linear primary fatty amines from C₁₂ to C₂₂ chain length in less 25 min with MS identification. The log of the amine retention factors are linearly related to the alkyl chain length with a methylene selectivity of 0.117 kcal/mol for the saturated amines and 0.128 kcal/mol for the mono‐unsaturated amines. The sp² selectivity for unsaturated fatty amines also could be calculated as 0.107 kcal/mol for the ionic liquid column. The commercial sample was quantified by GC with flame ionization detection (FID). An LC method also was developed with a reversed phase gradient separation using acetonitrile/formate buffer mobile phases and ESI‐MS detection. Native amines could be detected and identified by their single ion monitoring chromatograms even when partial coelution was observed. The analysis of the commercial sample returned results coherent with those obtained by GC–FID and with the manufacturer's data.     

Vertex vector sequential projection for the resolution of three-way data

Usually, the PARAFAC2 method is utilized for handling retention time shifts in resolving chromatographic three-way data. It requires all profiles shift the same amount, which, unfortunately, seems unlikely the case in the practice of chromatographic analysis of multi-component samples. The present authors deal with the problem by unfolding the three-way data array along a certain direction into one matrix and setting up a multi-bilinear model. Then, a new method called vertex vector sequential projection (VVSP) is proposed to select pure variables and then the alternating least squares (ALS) procedure is used to iteratively improve the fit of the data to the multi-bilinear model. With a good estimate that is as close as possible to the pure variables, a fast convergence can be expected. Moreover, no prerequisite on the shifting is required and the multi-bilinear model provides a plausible manner to make use of the multi-sample information. An additional advantage is that the present fitting procedure is easier to adjust when constraints such as non-negativity, unimodality, etc., are to be imposed on the loading matrix. The proposed method is evaluated with simulated and real chemical data sets. Satisfactory resolution results are obtained, which demonstrates the performance of the proposed method.     

Building robust calibration models for the analysis of estrogens by gas chromatography with mass spectrometry detection

Five hormonal growth promotants (diethylstilbestrol, hexestrol, dienestrol, 17-β-estradiol and 17-α-ethynylestradiol) have been analysed by gas chromatography with mass spectrometry detection (GC/MS, SIM mode) for four non-consecutive days. The aim is to build models with stable predictions. The strategies applied are internal standardization and global models carried out by gathering signals recorded on several days. Two models were examined: univariate models (with standardized peak area) and PARAFAC2 (the analyte scores were standardized by the scores of the internal standard). Internal standardization has been proved to be efficient for both models of dienestrol and ethynylestradiol. The mean relative error in absolute value when samples recorded on a different day to the calibration set are quantified by PARAFAC2 is 7.00% and 7.11% for dienestrol and ethynylestradiol, respectively. For diethylstilbestrol and estradiol, internal standardization was combined with global calibration models built with signals recorded under several sources of variability (different days). Thus predictions become steadier over time and in the estradiol example, errors decrease from 33.10% to 9.76%. The mean relative error in absolute value with PARAFAC2 updated models oscillates between 6.34% for ethynylestradiol and 10.74% for diethylstilbestrol. For univariate updated models errors range from 6.42% to 14.19% for ethynylestradiol and estradiol respectively. The combination of both strategies has been proved to be efficient independently of the analyte and of the signal order.     

Quantitative analysis combined with chromatographic fingerprint and antioxidant activities for the comprehensive evaluation of Compound Danshen Tablets

The composition of traditional Chinese medicine is extremely complex, so it is difficult to ensure quality consistency. We took Compound Danshen Tablets as the object of the study, by using high‐performance liquid chromatography to establish multiwavelength fusion fingerprints. Characteristic fingerprints of 30 batches of samples were generated at four wavelengths and evaluated by systematic quantified fingerprint method. An on‐line antioxidant determination method was used for the determination of the antioxidant components in Compound Danshen Tablets. The fingerprint analysis of the marker compounds can reflect the content of the marker compounds, which were determined by using the external standard method. This study elucidated that multiwavelength fusion fingerprint profiles and multiple markers compound analysis in conjunction with the assay of antioxidant activity offered a reliable and efficient approach to quantitatively evaluate the quality consistency of the traditional Chinese medicine and herbal preparations.     

Comparison of chemometric methods for the screening of comprehensive two-dimensional liquid chromatographic analysis of wine

Two chemometric methods are compared for the rapid screening of comprehensive two-dimensional liquid chromatographic (LC × LC) analysis of wine. The similarity index and Fisher ratio methods were both found to be able to distinguish geographical variability and to determine potentially significant peaks for further quantitative and qualitative study. An experimental data set consisting of five different wine samples and multiple simulated data sets were analyzed in the investigation of the screening methods. Several statistical analyses are employed in the understanding and verification of the results from the similarity index and Fisher ratio methods. The sum rank difference (SRD) method was used to compare the rankings of the two different methods as applied to the different data sets and to determine the amount of variability associated with the ranking of the peak differences. The major advantage the similarity index method offers is that it is an unsupervised method; no a priori knowledge of the samples (i.e., class identification) is required, while the Fisher ratio method is supervised. Both methods are rapid and require little user intervention other than the determination of a threshold for inclusion/exclusion of compounds from further analysis.     

Practical method for the definition of chromatographic peak parameters in preparative liquid chromatography

A practical method was established for the definition of chromatographic parameters in preparative liquid chromatography. The parameters contained both the peak broadening level under different amounts of sample loading and the concentration distribution of the target compound in the elution. The parameters of the peak broadening level were defined and expressed as a matrix, which consisted of sample loading, the forward broadening and the backward broadening levels. The concentration distribution of the target compound was described by the heat map of the elution profile. The most suitable stationary phase should exhibit the narrower peak broadening and it was best to broaden to both sides to compare to the peak under analytical conditions. Besides, the concentration distribution of the target compounds should be focused on the middle of the elution. The guiding principles were validated by purification of amitriptyline from the mixture of desipramine and amitriptyline. On the selected column, when the content of the impurity desipramine was lower than 0.1%, the recovery of target compound was much higher than the other columns even when the sample loading was as high as 8.03 mg/cm³. The parameters and methods could be used for the evaluation and selection of stationary phases in preparative chromatography.     

Partial least squares model and design of experiments toward the analysis of the metabolome of Jatropha gossypifolia leaves: Extraction and chromatographic fingerprint optimization

A major challenge in metabolomic studies is how to extract and analyze an entire metabolome. So far, no single method was able to clearly complete this task in an efficient and reproducible way. In this work we proposed a sequential strategy for the extraction and chromatographic separation of metabolites from leaves Jatropha gossypifolia using a design of experiments and partial least square model. The effect of 14 different solvents on extraction process was evaluated and an optimized separation condition on liquid chromatography was estimated considering mobile phase composition and analysis time. The initial conditions of extraction using methanol and separation in 30 min between 5 and 100% water/methanol (1:1 v/v) with 0.1% of acetic acid, 20 μL sample volume, 3.0 mL min^?1 flow rate and 25°C column temperature led to 107 chromatographic peaks. After the optimization strategy using i‐propanol/chloroform (1:1 v/v) for extraction, linear gradient elution of 60 min between 5 and 100% water/(acetonitrile/methanol 68:32 v/v with 0.1% of acetic acid), 30 μL sample volume, 2.0 mL min^?1 flow rate, and 30°C column temperature, we detected 140 chromatographic peaks, 30.84% more peaks compared to initial method. This is a reliable strategy using a limited number of experiments for metabolomics protocols.     

Important consequences for gas chromatographic analysis of the Sonogashira cross-coupling reaction

On following the kinetics of the Sonogashira alkynylation reaction of halogenated 2-pyrone 1 with phenylacetylene we have found that turnover continues to occur in sample vials even after quenching by commonly employed silica adsorption methods and product elution with small quantities of CH₂Cl₂. Trace quantities of Pd are carried through the silica plug. Addition of a CH₂Cl₂ solution of 1,2-bis(diphenylphosphino)ethane (dppe) to the quenched sample inhibits the reaction and represents a more reliable method for determining yields and reaction kinetics.