Chemometric Procedures Research Articles

The analytical and chemometric procedures used to profile illicit drug seizures

Over the last 20 years there has been an increasing interest in the development of robust systems, both analytical and statistical, to enable the linkage of seizures of illicit drug to each other. Much of this work has concentrated on the analysis of synthetic drugs, such as amphetamine and its analogues. In recent years, the analysis of both organic and elemental impurities as well as isotope ratios has advanced the usefulness of the techniques available. The application of specific chemometric methods to the derived analytical data has begun to provide the possibility of robust methods by which the resultant information can be interrogated.

Differentiation of apple juice samples on the basis of heat treatment and variety using chemometric analysis of MIR and NIR data

The potential of mid-infrared (MIR) and near-infrared (NIR) spectroscopy for their ability to differentiate between apple juice samples on the basis of apple variety and applied heat-treatment was evaluated. The heat-treatment involved exposure of juice samples (15 ml) for 30 s in a 900 W microwave oven and the apple varieties used to produce the juice samples were Bramley, Elstar, Golden Delicious and Jonagold. The chemometric procedures applied to the MIR and NIR data were partial least squares regression (PLS1 for differentiation on the basis of heat-treatment, PLS2 for varietal differentiation) and linear discriminant analysis (LDA) applied to principal component (PC) scores. PLS1 and PLS2 gave the highest level of correct classification of the apple juice samples according to heat-treatment (77.2% for both MIR and NIR data) and variety (78.3–100% for MIR data; 82.4–100% for NIR data), respectively.

Simultaneous spectrofluorimetric and spectrophotometric determination of melatonin and pyridoxine in pharmaceutical preparations by multivariate calibration methods

Partial least-squares (PLS) calibration and principal component regression (PCR) methods were utilized for the simultaneous spectrofluorimetric and spectrophotometric determination of pyridoxine (PY) and melatonin (MT). Since emission and adsorption spectra of these drugs overlap, PY and MT cannot be directly determined by fluorimetric nor by spectrophotometric methods. Full-spectrum multivariate calibration PLS and PCR methods were developed for both fluorimetry and spectrophotometry. The conditions were optimized for fluorimetric as well as for spectrophotometric determination of both drugs. The simultaneous determination of PY and MT was carried out in mixtures by recording the emission fluorescence spectrum between 324 and 500 nm ( λ ex 285 nm) for fluorimetry, and by recording the absorption spectrum between 250 and 350 nm for spectrophotometry ( λ max(PY) 310 nm, λ max(MT) 278 nm). The experimental calibration matrixes were designed orthogonally. At the optimum conditions, dynamic ranges were 0.04–1.3 and 0.1–4 μg ml –1 for fluorimetry and 1–22 and 1–24 μg ml –1 for spectrophotometry for MT and PY, respectively. The calibration concentrations were prepared in the dynamic ranges. The parameters of the chemometrics procedure for the simultaneous determination of MT and PY were optimized, and the proposed methods were validated with prediction set. Finally the procedures were successfully applied to simultaneous spectrofluorimetric and spectrophotometric determination of PY and MT in synthetic mixtures and in a pharmaceutical formulation.

Preliminary Studies for the Differentiation of Apple Juice Samples by Chemometric Analysis of Solid-Phase Microextraction−Gas Chromatographic Data

A combination of gas chromatography (GC) and chemometrics was evaluated for its ability to differentiate between apple juice samples on the basis of apple variety and applied heat treatment. The heat treatment involved exposure of 15 mL juice samples for 30 s in a 900 W domestic microwave oven. The chromatographic results were subjected to two chemometric procedures: (1) partial least squares (PLS) regression and (2) linear discriminant analysis (LDA) applied to principal component (PC) scores. The percent correct classification of samples were obtained from PLS and LDA in terms of separation on the basis of apple variety and applied heat treatment. PLS gave the highest level of correct classification of the apple juice samples according to both variety and heat treatment, 92.5% correct classification in each case. When LDA was performed on the PC scores obtained from GC analysis, 87.5% and 80% of samples were correctly classified according to apple variety used and applied heat treatment, respectively.

Chromatographic and Spectroscopic Methods for the Determination of Solvent Properties of Room Temperature Ionic Liquids

AbstractFor Abstract see ChemInform Abstract in Full Text.

Chemometric procedure for the study of fractionated wastewater ingredients using RP-HPLC/diode array spectrophotometer.

A fast screening method of domestic wastewater is reported based on fractionation with RP-HPLC and diode array absorption detection implemented by chemometric treatment of the spectra using cluster analysis, deconvolution, simulation, and multiple regression statistical techniques. The proposed method is limited to constituents that absorb in the UV-Vis region which include most of the toxic organic pollutants.

Classification of ecstasy tablets using trace metal analysis with the application of chemometric procedures and artificial neural network algorithms.

This work is concerned with an investigation into the practicalities of using ICP-MS data obtained from the analysis of ecstasy tablets to provide linkage information from seizure to seizure. The generated data was analysed using different statistical techniques, namely principal component analysis, Hierarchical clustering and artificial neural networks. The relative merits of these different techniques are discussed.

Decoding of complex isothermal chromatograms: Application to chromatograms recovered from space missions

AbstractIn gas chromatographic isothermal separations of multicomponent mixtures, i.e., mixtures where the number of components is high and unknown, the efficiency is low and not enough to allow a complete separation with a consequent severe peak overlapping in the chromatogram. The consequence is a significant loss in analytical information content. Therefore it is practically mandatory to use a chemometric procedure to decode the complex chromatogram, i. e. to deconvolve the overlapping signal to extract from it information on the mixture and the separation system. Isothermal separations are not very popular, due to their low efficiency, but they are very common in in situ analyses during space missions, as a consequence of flight constraints on instrumentation complexity and power (energy saving). In this work a chemometric approach based on Fourier analysis is applied to chromatograms obtained under isothermal or low temperature programming conditions. These conditions simulate those employed in space missions. The procedure has been applied to standard mixtures containing compounds representative of the planetary atmospheres that will be investigated in the near future: in particular, those related to Titan's atmosphere (Cassini‐Huygens mission) and a cometary nucleus (Rosetta mission), i. e., hydrocarbons and oxygenated compounds with carbon atom numbers ranging from 2 to 8. The original approach, developed for constant peak width, is extended to variable peak width, in particular to the case of peak width linearly increasing with retention time, representing isothermal separations. The proposed approach is able to characterise complex isothermal chromatograms in terms of number of components present in the mixture and of separation efficiency: such results are useful in interpreting data recovered from space missions and for optimising analysis conditions compatible with flight constraints.

Honey characterization and adulteration detection by pattern recognition applied on HPAEC-PAD profiles. 1. Honey floral species characterization.

An improved COFRAC (COmité FRançais d'ACréditation) method for the analysis and evaluation of the quality of honey by high-performance anion-exchange chromatography of sugar profiles is proposed. With this method, both minor and major sugars are simultaneously analyzed and the technique is integrated in a new chemometric approach, which uses the entire chromatographic sugars profile of each analyzed sample to characterize honey floral species. Sixty-eight authentic honey samples (6 varieties) were analyzed by high-performance anion-exchange chromatography-pulsed amperometric detection. A new algorithm was developed to create automatically the corresponding normalized data matrix, ready-to-use in various chemometric procedures. This algorithm transforms the analytical profiles to produce the corresponding calibrated table of the surfaces or intensities according to retention times of peaks. The possibility of taking into account unknown peaks (those for which no standards are available) allows the maximum chemical information provided by the chromatograms to be retained. The parallel application of principal component analysis (PCA)/linear discriminant analysis (LDA) and artificial neural networks (ANN) shows a high capability in the classification of the analyzed samples (LDA, 93%; ANN, 100%) and a very good discrimination of honey groups. This work is the starting point of the elaboration of a new system designed for the automatic pattern recognition of food samples (first application on honey samples) from chromatographic analyses for food characterization and adulteration detection.

Band composition analysis: a new procedure for deconvolution of the mass spectra of organometallic compounds.

A new chemometric procedure called band composition analysis (BCA) designed for the deconvolution of mass spectra of organometallics is proposed. BCA generates theoretical bands T(i), then combines them to obtain a model band M, which is finally compared with the experimental band E. All of these steps are realized with computer assistance. This modeling yields four parameters characterizing the experimental band: theoretical and model variances s(2) (theor) and s(2) (model), a fit factor alpha and a contribution x(i) from the theoretical band. If s(2) (theor) > 20 the band is deemed complex and needs modeling. The values alpha > 90 indicate that there is good agreement between the experimental and model bands. BCA is particularly effective for the modeling of complex isotopic bands often present in organometallics. Two illustrations of BCA for tetrabutyltin, C(16)H(36)Sn, and 1,1',2,2',3,3'-hexachloroferrocene, C(10)H(4)Cl(6)Fe, are shown.

Spectrometry-based Estimation of Parameters of the Anticooperative Complex Formation Involving Polymer Molecules

A scheme for the analysis of the multivariate dependences observed on spectrometric titrationof polynucleotides was proposed. The chemometric procedure employed is applicable for studying the anti-cooperative complex formation involving ideal infinite biopolymers.

Chemometric detection of thermally degraded samples in the analysis of drugs of abuse with gas chromatography–Fourier-transform infrared spectroscopy

We present a chemometric procedure for the identification of the reference standard chromatographic peak in cases where the GC–FTIR analysis of commercial standards results in the appearance of more than one peak in the GC chromatogram. The procedure has been designed for phenethylamines, which represent the class with the largest number of individual molecules on the illicit drug market, and which are abused for their stimulant and/or hallucinogenic effects. The similarity between their vapor-phase FTIR spectra was modeled using principal component analysis (PCA), and class identity was assigned on the basis of soft independent modeling of class analogy (SIMCA). Additional peaks could be assigned to impurities in the standards, but most often they were artifacts formed during the GC–FTIR analysis of thermolabile or chemically unstable compounds. The latter case is illustrated by the identification of the reference standard chromatographic peak and FTIR spectrum of the potent psychotropic amphetamine derivative N-methyl-1-(3,4-methylenedioxyphenyl)-2-butanamine (MBDB), and by the elucidation of the chemical changes that occur in the molecule of MBDB due to thermal degradation.

Chemical authentication of extra virgin olive oil varieties by supervised chemometric procedures.

This work has focused on discriminating extra virgin olive oils from Sabina (Lazio, Italy) by olive fruit variety (cultivar). A set of oils from five of the most widespread cultivars (Carboncella, Frantoio, Leccino, Moraiolo, and Pendolino) in this geographical area was analyzed for chemical composition using only the Official Analytical Methods, recognized for the quality control and commercial classification of this product. The obtained data set was converted into a computer-compatible format, and principal component analysis (PCA) and a method based on the Fisher F ratio were used to reduce the number of variables without a significant loss of chemical information. Then, to differentiate these samples, two supervised chemometric procedures were applied to process the experimental data: linear discriminant analysis (LDA) and artificial neural network (ANN) using the back-propagation algorithm. It was found that both of these techniques were able to generalize and correctly predict all of the samples in the test set. However, these results were obtained using 10 variables for LDA and 6 (the major fatty acid percentages, determined by a single gas chromatogram) for ANN, which, in this case, appears to provide a better prediction ability and a simpler chemical analysis. Finally, it is pointed out that, to achieve the correct authentication of all samples, the selected training set must be representative of the whole data set.

Near-infrared libraries in the pharmaceutical industry: a solution for identity confirmation.

The construction of near-infrared spectral libraries as an alternative to qualitative analysis methods for identifying pharmaceutical raw materials is proposed. Various conceptual and practical aspects of library construction are assessed and discussed. The procedure is demonstrated by constructing a library including NIR spectra for 125 different raw materials using the correlation coefficient as the discriminating criterion. Compounds with very similar spectra can be identified by constructing sub-cascading libraries branching off the main one that are developed by using chemometric procedures with higher discriminating ability. The construction of sub-libraries and their performance and discriminating power in three different situations are illustrated. The proposed methodology affords the expeditious unequivocal identification of all the compounds included in a library.

Study of the interaction of a cis-dichloroaminopyrrolidine Pt(II) complex and the polynucleotide poly(I)–poly(C) acid by means of [formula omitted]-NMR and multivariate curve resolution

Multivariate curve resolution is proposed for the analysis of spectroscopic data obtained from kinetic studies on the interaction of compounds analogous to cis-platinum (cisplatin) and nucleic acids. In particular, the interaction between the cis-dichloro-(1,2-diethyl-3-aminopyrrolidine) Pt(II) compound (Ptpyrr) and the polynucleotides poly(inosinic) (poly(I)), poly(cytidylic) (poly(C)) and poly(I)–poly(C) acids were monitored by 1 H -NMR spectroscopy. Multivariate curve resolution was applied for the first time to analyze 1 H -NMR spectroscopic data, which allowed to determine the number of interaction complexes and the recovery of both kinetic concentration profiles and pure NMR spectra for all the detected species. For poly(I) and poly(C), two complexes were detected upon interaction with Ptpyrr, which corresponded to the mono-adduct and to the bis-adduct complex formation. For poly(I)–poly(C), three components were detected, which corresponded to: (a) the initial non-platinated double-stranded polynucleotide, (b) to a mixture of non-platinated single-stranded poly(C) and platinated poly(I), and (c) to a mixture of poly(C) and poly(I), both platinated. Multivariate curve resolution chemometric procedure based on an alternating least-squares optimization (MCR–ALS) is, thus, proposed as a useful tool for the recovery of analytical information from 1 H -NMR data.

Differentiation of used motor oils on the basis of their IR spectra with application of cluster analysis

Two brands of motor oils, Elf and Castrol, were examined for criminalistic purposes. The aim was to distinguish between oil samples of varying degree of use. The chemical composition of the oils expressed by their infrared spectra was the basis of investigations. The mathematical approach applied to processing and interpretation of the physicochemical data was a chemometric procedure consisting of a few stages and including such methods as factor and cluster analysis. It was shown that the procedure presented can be recommended as very helpful for qualitative estimation of the effects examined.

SIMULTANEOUS SPECTROPHOTOMETRIC DETERMINATION OF CALCIUM AND MAGNESIUM IN DIALYSIS FLUIDS USING MULTIVARIATE CALIBRATION METHODS

A method for simultaneous spectrophotometric determination of calcium and magnesium in dialysis fluids using multivariate calibration methods is proposed. The method is based on the development of the reaction between the analytes and Eriochrome Black T at pH 10.1. The parameters of chemometric procedure such as the spectral region and the number of factors were optimized. Three more convenient models of PCR, PLS-1 and PLS-2 were applied and the results were compared. A series of synthetic solutions containing different concentrations of calcium and magnesium were used to check the prediction ability of these chemometric methods. The optimum method was applied to the analysis of commercial dialysis fluids and the accuracy of proposed procedure was compared with that obtained by the USP reference method. These measurements carried out with good precision and RSD of real samples analysis (n = 3) were found to be less than 1.85%. It was also observed that the presence of the other components frequently added to dosage forms caused no interference effect in the proposed method.

Atomic Spectrometry Update. Advances in atomic emission, absorption, and fluorescence spectrometry, and related techniques

Several trends have been evident during the review period. There was a marked decrease in the number of papers describing applications of chemometric procedures, speciation using gas chromatography (though not speciation using liquid chromatography) and solid sampling using arcs and sparks. The number of publications describing applications involving some form of sample pretreatment, either on-line or batch, such as matrix removal, preconcentration or vapour generation, was similar to previous years. Similarly, applications involving lasers maintained their popularity. There were very few novel developments in instrumentation, with the only significant trend of note being that towards miniaturisation.

QSAR study and VolSurf characterization of anti-HIV quinolone library.

Antiviral quinolones are promising compounds in the search for new therapeutically effective agents for the treatment of AIDS. To rationalize the SAR for this new interesting class of anti-HIV derivatives, we performed a 3D-QSAR study on a library of 101 6-fluoro and 6-desfluoroquinolones, taken either from the literature or synthesized by us. The chemometric procedure involved a fully semiempirical minimization of the molecular structures by the AMSOL program, which takes into account the solvatation effect, and their 3D characterization by the VolSurf/GRID program. The QSAR analysis, based on PCA and PLS methods, shows the key structural features responsible for the antiviral activity.

Chemometric rationalization of the structural and physicochemical basis for selective cyclooxygenase-2 inhibition: toward more specific ligands.

The discovery that proinflammatory prostaglandins are produced by cyclooxygenase-2 (COX-2), an inducible isoform of the constitutive cyclooxygenase-1 (COX-1), opened a new frontier in the treatment of inflammatory diseases, because the selective inhibition of COX-2 can lead to therapeutically effective compounds which do not have the common side effects of classical non-steroidal antiinflammatory drugs (NSAIDs). Different crystallographic structures of both free COX-1 and COX-2 as well as complexes with inhibitors have been solved. Because of the great similarity between the two enzymes, it is difficult to detect the most important structural and physicochemical features that would be useful for designing inhibitors with an improved selectivity. In this paper we describe the application of a chemometric procedure to the study of COX-2 selective inhibition. This method, developed to reveal the most suitable regions of isoenzymes for the design of selective ligands, also has a very practical utility. GRID multivariate characterization of the enzymes and subsequent Principal Component Analysis (PCA) of the descriptor variables allow the identification of chemical groups that could be added to a core template structure to increase ligand selectivity.