Mixture design optimization of extraction and mobile phase media for fingerprint analysis of Bauhinia variegata L

Two statistical mixture designs were used to optimize the proportions of solvents used in both the extraction medium and the reversed liquid chromatographic mobile phase to improve the quality of chromatographic fingerprints of Bauhinia variegata L extracts. For modeling, the number of peaks was used as a measure of fingerprint information. Three mobile phases, each with a chromatographic strength of two, gave good results. A methanol/water (77:23 v/v) mixture resulted in 17 peaks in the chromatographic fingerprint whereas acetonitrile/water (64.5:35.5 v/v) and methanol/acetonitrile/water (35:35:30 v/v/v) mixtures resulted in 18 and 20 peaks, respectively. The corresponding optimum solvent compositions to extract chemical substances for these three mobile phases were ethanol/acetone (25:75 v/v/v) and dichloromethane/acetone (70:30 v/v) mixtures, and pure dichloromethane, respectively. The mixture designs are useful for understanding the influence of different solvents on the strengths of the extraction medium and the mobile phase.     

Mixture Design PARAFAC HPLC-DAD Metabolomic Fingerprints of Fractionated Organic and Basic Extracts from <Emphasis Type="Italic">Erythrina speciosa</Emphasis> Andrews Leaves

HPLC-DAD analysis of statistical mixture design extracts of Erythrina speciosa Andrews leaves provided chromatographic and UV–visible profiles of their basic and organic fractions that were treated with the PARAFAC multivariate method. The design extracts provided greater varieties and amounts of metabolites than could be obtained by classical extraction methods. Fractionation provided more diverse fingerprint information than obtained previously from only the crude extract. The two largest chromatographic peaks, one with a 4.8 min elution time having an intense spectral band at 235 nm and the other a 5.8 min peak with an intense 238 nm band for the basic fraction were obtained with the ternary 1:1:1 ethanol–dichloromethane–hexane mixture. These can be assigned to diene-type and lactonic alkaloids. Peaks with the same retention times are also found in the organic fraction but are extracted with different mixtures and have distinct spectral behavior in the 235 nm region, probably being aromatic alkaloids. The above strategy permits a more unambiguous assignment of metabolic groups to specific chromatographic peaks. This can be expected to provide higher quality chromatographic fingerprints for natural products’ chemistry.     

Methods for the exploratory analysis of two-dimensional chromatographic signals

In this article several approaches for the exploratory analysis of two-dimensional chromatographic signals (fingerprints) are presented. Their usefulness is illustrated on experimental chromatographic data obtained from high performance liquid chromatography using the photodiode-array detector (HPLC-DAD). Among the methods discussed are principal component analysis (PCA), hierarchical clustering methods and several N-way techniques such as PARAFAC, PARAFAC2 and Tucker3. In addition to the N-way methods, other approaches that allow for comparing samples represented by two-dimensional fingerprints are also presented (the Rv coefficient, the STATIS approach and ‘fuzzy’ variants of the similarity matrix). Exploratory analysis of the HPLC-DAD data with peak shifts is also discussed.     

Statistical mixture design selective extraction of compounds with antioxidant activity and total polyphenol content from Trichilia catigua

Statistical design mixtures of water, methanol, acetone and ethanol were used to extract material from Trichilia catigua (Meliaceae) barks to study the effects of different solvents and their mixtures on its yield, total polyphenol content and antioxidant activity. The experimental results and their response surface models showed that quaternary mixtures with approximately equal proportions of all four solvents provided the highest yields, total polyphenol contents and antioxidant activities of the crude extracts followed by ternary design mixtures. Principal component and hierarchical clustering analysis of the HPLC–DAD spectra of the chromatographic peaks of 1:1:1:1 water–methanol–acetone–ethanol mixture extracts indicate the presence of cinchonains, gallic acid derivatives, natural polyphenols, flavanoids, catechins, and epicatechins.     

Experimental designs characterizing seasonal variations and solvent effects on the quantities of coumarin and related metabolites from Mikania laevigata

Statistical design mixtures of acetone, chloroform, dichloromethane and ethanol were used to study the effects of different solvents and their mixtures on the quantities of coumarin and related metabolites extracted from Mikania laevigata samples harvested in each of the four seasons. RP-HPLC-DAD and both positive and negative modes of UPLC-MS analyses were used to determine relative quantities of coumarin, o-coumaric acid and melilotic acids in each season for all the mixture design extracts. The existence and measurement of the relative abundances of melilotic acid in Mikania laevigata have not been reported previously. Highest coumarin concentrations were encountered in the summer whereas its o-coumaric acid precursor and melilotic acid were most abundant in the spring. O-coumaric and melilotic acids concentrations were strongly correlated during the year. Also solvent effects were seen to be significant. Ethanol and 1:1 binary mixtures of ethanol and acetone extracted the largest quantities of coumarin whereas ethanolic binary and ternary mixtures with chloroform and dichloromethane provided the best yields of o-coumaric and melilotic acids. Statistical mixture models indicated that synergic binary interactions, especially those involving ethanol with acetone or chloroform, are important in the Mikania extraction process.     

Statistical mixture design investigation of fractionated and total extracts from Erythrina speciosa Andrews leaves

The simplex centroid mixture design for the ethanol, dichloromethane, hexane and acetone solvents has been applied to the extraction of crude mass and the fiber, organic, neutral and basic fractions as well as the fractionation residues of Erythrina speciosa Andrews leaves. Binary and ternary synergic solvent interactions are seen to provide dominant contributions to the extraction of both crude mass and all the fractions. Quadratic and special cubic mixture models precisely predict the extracted quantities of each fraction and the residue as a function of the proportions of the four solvents. Different solvent mixtures are found to be the most efficient extractors for the different fractions: binary dichloromethane‐hexane mixtures for the fiber fraction, ternary ethanol‐dichloromethane‐acetone mixtures for the neutral fraction, binary ethanol‐dichloromethane mixtures for the organic fraction, crude extract and residue values and ternary ethanol‐dichloromethane‐hexane mixtures for the basic fraction. Principal component analysis shows that the ethanol‐dichloromethane mixtures are important for extracting large quantities of the basic and organic fractions as well as of the residue and crude masses.     

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.     

Development of a solid phase extraction procedure for HPLC-DAD determination of several angiotensin II receptor antagonists in human urine using mixture design

The optimisation of a solid phase extraction procedure involves several variables whose influence has been widely studied. However, in most cases, only process variables are taken into account. In this work, the influence of those process variables together with the fact of using mixtures of solvents during the elution step of the solid phase extraction of four angiotensin II receptor antagonist drugs has been studied. Since the influence on the extraction efficiency of several process variables were simultaneously tested, a D-optimal design was constructed. The composition of the elution solvent (a mixture of methanol, acetonitrile, ethanol and acetone at different proportions from 0 to 100% each solvent), the percentage and pH of the buffer solution added to the urine samples at the beginning of the extraction procedure; the percentage of the organic component and the volume of the washing solution, the drying time and the volume of the elution solvent were the studied variables. The chromatographic separation was carried out by gradient elution mode with 0.026% trifluoroacetic acid (TFA) in the organic phase and 0.031% TFA in the aqueous phase using an Atlantis dC18, 100 mm × 3.9 mm I.D. chromatographic column at a flow rate of 1 mL/min and a column temperature of 35 ± 0.2 °C. For detection a diode array detector set at 232 nm was used. The extraction procedure for spiked human urine samples was developed using C8 cartridges, phosphate buffer pH 6.8 as conditioning agent, a drying step of 10 min, a washing step with methanol-phosphate buffer (20:80, v/v) and methanol as eluent. Recovery percentages obtained: 84% for eprosartan, 74% for telmisartan, 74% for irbesartan and 89% for valsartan allow the determination of these drugs concentration levels in urine.     

Determination of terpenoids in wines by solid phase extraction and gas chromatography

A new method for determination of volatile terpenoids in wine is proposed. An off-line solid phase extraction—gas chromatographic method has been used for the determination. The influence of several extraction variables was studied, including the solid phase employed (C-18 versus divinylbenzene-based), eluting solvent (n-pentane, dichloromethane, ethanol and methanol), volume of eluting solvent (1-4 ml) and drying time (0-20 min). Complete recovery of volatile terpenoids from several kinds of wines was obtained under the optimized conditions.     

Quartz crystal microbalance sensor array for the detection of volatile organic compounds

A sensor array system consisting of five quartz crystal microbalance (QCM) sensors (four for measuring and one for reference) and an artificial neural network (ANN) method is presented for on-line detection of volatile organic compounds. Three ionic liquids, 1-butyl-3-methylimidazolium chloride (C₄mimCl), 1-butyl-3-methylimidazolium hexafluorophosphate (C₄mimPF₆), 1-dedocyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (C₄mimNTf₂), and silicone oil II, which is widely used as gas chromatographic stationary phase, have been selected as sensitive coatings on the quartz surface allowing the sensor array effective to identify chemical vapors, such as toluene, ethanol, acetone and dichloromethane. The success rate for the qualitative recognition reached 100%. Quantitative analysis has also been investigated, within the concentration range of 0.6-6.1 mg/L for toluene, 0.9-7.5 mg/L for ethanol, 2.8-117 mg/L for dichloromethane, and 0.7-38 mg/L for acetone, with a prediction error lower than 8%.     

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.     

Synthetic oligomer analysis using atmospheric pressure photoionization mass spectrometry at different photon energies

Atmospheric pressure photoionization (APPI) followed by mass spectrometric detection was used to ionize a variety of polymers: polyethylene glycol, polymethyl methacrylate, polystyrene, and polysiloxane. In most cases, whatever the polymer or the solvent used (dichloromethane, tetrahydrofuran, hexane, acetone or toluene), only negative ion mode produced intact ions such as chlorinated adducts, with no or few fragmentations, in contrast to the positive ion mode that frequently led to important in-source fragmentations. In addition, it was shown that optimal detection of polymer distributions require a fine tuning of other source parameters such as temperature and ion transfer voltage. Series of mass spectra were recorded in the negative mode, in various solvents (dichloromethane, tetrahydrofuran, hexane, toluene, and acetone), by varying the photon energy from 8 eV up to 10.6 eV using synchrotron radiation. To these solvents, addition of a classical APPI dopant (toluene or acetone) was not necessary. Courtesy of the synchrotron radiation, it was demonstrated that the photon energy required for an efficient ionization of the polymer was correlated to the ionization energy of the solvent. As commercial APPI sources typically use krypton lamps with energy fixed at 10 eV and 10.6 eV, the study of the ionization of polymers over a wavelength range allowed to confirm and refine the previously proposed ionization mechanisms. Moreover, the APPI source can efficiently be used as an interface between size exclusion chromatography or reverse phase liquid chromatography and MS for the study of synthetic oligomers. However, the photoionization at fixed wavelength of polymer standards with different molecular weights showed that it was difficult to obtain intact ionized oligomers with molecular weights above a few thousands.     

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.     

Analysis of lipoproteins using 2D diffusion-edited NMR spectroscopy and multi-way chemometrics

This study represents the first application of multi-way calibration by N-PLS and multi-way curve resolution by PARAFAC to 2D diffusion-edited ¹H NMR spectra. The aim of the analysis was to evaluate the potential for quantification of lipoprotein main- and subfractions in human plasma samples. Multi-way N-PLS calibrations relating the methyl and methylene peaks of lipoprotein lipids to concentrations of the four main lipoprotein fractions as well as 11 subfractions were developed with high correlations (R = 0.75-0.98). Furthermore, a PARAFAC model with four chemically meaningful components was calculated from the 2D diffusion-edited spectra of the methylene peak of lipids. Although the four extracted PARAFAC components represent molecules of sizes that correspond to the four main fractions of lipoproteins, the corresponding concentrations of the four PARAFAC components proved not to be correlated to the reference concentrations of these four fractions in the plasma samples as determined by ultracentrifugation. These results indicate that NMR provides complementary information on the classification of lipoprotein fractions compared to ultracentrifugation.     

Three-way models and detection capability of a gas chromatography-mass spectrometry method for the determination of clenbuterol in several biological matrices: the 2002/657/EC European Decision

Clenbuterol has been extracted by mixed solid-phase extraction from two biological matrices (bovine hair and urine) and detected by GC/MS (selected ion monitoring (SIM) and full-SCAN modes). The analytical signal has been modelled with univariate and three-way models, namely DTLD, PARAFAC, PARAFAC2, Tucker3 and trilinear PLS. Since clenbuterol is a banned substance a comparative study of the capability of detection (CCβ, X₀=0) has been performed as a function of the sample (hair, 74 μg kg⁻¹ and urine, 0.36 μg l⁻¹), the mode in which the signals are monitored (SCAN, 283 μg kg⁻¹ and SIM, 74 μg kg⁻¹) and the statistical model (univariate, 283 μg kg⁻¹ and trilinear PLS, 20.91 μg kg⁻¹). The capability of detection has been calculated as stated in ISO 11843 and Decision 2002/657/EC setting in all cases the probabilities of false positive and of false negative at 0.05.The identification of the mass spectra must be done to confirm the presence of clenbuterol and has been carried out through PARAFAC. The correlation coefficient between the spectra estimated by PARAFAC and the library spectra is 0.96 (hair, SCAN mode) and 1.00 (hair and urine, SIM mode).The Decision 2002/657/EC advocates the use of independent mass fragments to identify banned compounds. These recommendations together with the effect of the number of ions registered on the capability of detection have lead us to select five uncorrelated fragments (86, 243, 262, 264 and 277) from the data set of 210 ions by hierarchical clustering of variables.     

A Tucker model based approach for analysis of complex oil biodegradation data

A novel method based on gas chromatography–mass spectrometry in selected ion monitoring mode (GC–MS/SIM) and Tucker models is developed to evaluate the effects of oil type, microbial treatments and incubation time on the biodegradation of petroleum hydrocarbons. The data set consists of sections of the m/z 180, 192 and 198 GC–MS/SIM chromatograms of oil extracts from a biodegradation experiment where four oil types were exposed to four microbial treatments over a period of one year. The chosen sections, which are specific to methylfluorenes, phenanthrenes and dibenzothiophenes, were combined in a 4-way array (incubation time × oil type × treatment × combined chromatographic retention times) that was analyzed using both principal component analysis and the Tucker model. Several conclusions could be reached: the light fuel oil was the least degradable of those tested, 2- and 3-methyl isomers were more easily degraded compared to the 4-methyl isomers, the mixture of surfactant producers and PAC degraders provided the most effective degradation and the largest part of the degradation occurred between 54 and 132 days.     

Investigation of polar organic solvents compatible with Corona Charged Aerosol Detection and their use for the determination of sugars by hydrophilic interaction liquid chromatography

A range of organic solvents (ethanol, isopropanol and acetone) has been investigated as alternatives to acetonitrile and methanol when used in conjunction with Corona Charged Aerosol Detection (Corona CAD). These solvents have been evaluated with regard to their effect on the response of the Corona CAD. Three dimensional response surfaces were constructed using raw data showing the relationship between detector response, analyte concentration and percentage of organic solvent in the mobile phase, using sucralose or quinine as the test analyte. The detector response was non-linear in terms of analyte concentration for all solvents tested. However, detector response varied in an approximately linear manner with percentage of organic solvent over the range 0–40% for ethanol or isopropanol and 0–80% for acetone and methanol. The chromatographic performance of the various solvents when used as aqueous–organic mobile phases was evaluated for isocratic and gradient separations of sugars and sugar alcohols by hydrophilic interaction liquid chromatography (HILIC) using an Asahipak NH2P-504E column coupled with Corona CAD detection. It was found that whilst acetonitrile provided the highest column efficiencies and lowest detection limits of the solvents studied, acetone also performed well and could be used to resolve the same number of analytes as was possible with acetonitrile. Typical efficiencies and detection limits of 5330 plates m⁻¹ and 1.25 μg mL⁻¹, respectively, were achieved when acetone was used as the organic modifier. Acetone was utilised successfully as an organic modifier in the HILIC separation of carbohydrates in a beer sample and also for a partially digested dextran sample.     

Crystallization-based optical resolution of 1,1′-binaphthalene-2,2′-dicarboxylic acid via 1-phenylethylamides: control by the molecular structure and dielectric property of solvent

In the recrystallization of a diastereomeric mixture of amides (RS_a,S)-1 formed from racemic 1,1′-binaphthalene-2,2′-dicarboxylic acid and (S)-1-phenylethylamine, either of the diastereomers crystallizes out as a diastereomerically pure form, depending on the solvent employed; sterically undemanding solvents, acetone, dichloromethane, and acetonitrile, afford crystals formulated as (S_a,S)-1·solvent with an exception of ethanol, which affords (R_a,S)-1·EtOH, while sterically bulkier solvents afford (R_a,S)-1 including no solvent. The stereoselectivity can be rationalized by the crystal structures. A dielectrically controlled resolution (DCR) can also be carried out by using mixed solvents, which contain, for example, 25 vol % of acetone and varying ratios of hexane and 1-propanol in total 75 vol %; (S_a,S)-1·acetone is deposited as crystals from the solvents with a dielectric constant (ε) range 8.9 ? ε ? 10.2, while (R_a,S)-1 is deposited from the solvents with 14.8 ? ε ? 20.3.     

Statistical mixture design optimization of extraction media and mobile phase compositions for the characterization of green tea

The influence of different solvents on the extraction medium and the RP-HPLC mobile phase composition were investigated by statistical mixture designs to optimize solvent proportions to prepare the fingerprint of a medicinal herbal extract. For modeling, the number of peaks was used as a measure of fingerprint information. The optimum compositions of solvent to extract chemical substances from green tea and for mobile phase chromatographic analysis were ethyl acetate/ ethanol/dichloromethane (20:5:75 v/v/v) and MeOH/ACN/water (7.5:57.5:35 v/v/v), respectively. This system results in 26 peaks in the chromatographic fingerprint. These results show that an incorrect choice of modifiers for mobile phase composition and solvent extraction hampers the detection of a maximum number of peaks and produces a poor chromatographic fingerprint.     

Multi-way modeling of hydro-chemical data of an alluvial river system--a case study

A large data set pertaining to water quality of an alluvial river was analyzed using multi-way data analysis methods with a view to extract the hidden information, spatial and temporal variation trends in the river water quality. Four-way data (8 monitoring sites × 22 water quality variables × 10 monitoring years × 12 sampling months) analysis was performed using PARAFAC and Tucker3 models. A two component PARAFAC model, although explained 35.1% of the data variance, could not fit to the data set. Tucker3 model of optimum complexity (2,3,1,3) explaining 39.7% of the data variance, allowed interpretation of the data information in four modes. The model explained spatial and temporal variation trends in terms of water quality variables during the study period and revealed that sampling sites in mid-stretch of the river were dominated mainly by the variables of anthropogenic origin. The results delineated the mid stretch of the river as critical from pollution point of view and also identified summer months as having high influence on river water quality in this stretch. The information regarding spatial and temporal variations in water quality generated by the four-way modeling of data would be useful in developing long-term water resources management strategies in the river basin.