Analytical and Bioanalytical Chemistry (v.399, #6)

Mediterranean chemometrics by Luis Cuadros-Rodríguez; Juan M. Bosque-Sendra (1925-1927).
is full professor of the Department of Analytical Chemistry at the University of Granada (Spain), expert in the field of the Chemical Metrology and Qualimetrics (CMQ), and technical advisor in quality management for chemical testing laboratories. His most significant R&D area of interest is the development of quality-assurance protocols (equipment and method calibration, method validation, uncertainty estimation, etc.) for the processes involved in the analysis of food pesticide residues and water pollutants. He has also developed the use of multivariate process optimization by applying statistically designed experiments to analytical methods. His main field of research is currently focused on analytical control for food quality, particularly the characterization and authentication of vegetable (olive) oil, not only by chromatographic and spectrometric analysis, also by application of chemometrics tools. is currently Associate Professor of the Department of Analytical Chemistry at the University of Granada (Spain). His main areas of research are the development of quality-assurance protocols for analytical processes, multivariate optimization of analytical processes by use of experimental designs, and the characterization of foods using chemometrics tools. He has been involved in the development of new analytical methods for analysis of pesticides and antibiotic residues based on CE–MS.

Alternative common bases and signal compression for wavelets application in chemometrics by Michele Forina; Paolo Oliveri; Monica Casale (1929-1939).
Representation or compression of data sets in the wavelet space is usually performed to retain the maximum variance of the original or pretreated data, like in the compression by means of principal components. In order to represent together a number of objects in the wavelet space, a common basis is required, and this common basis is usually obtained by means of the variance spectrum or of the variance wavelet tree. In this study, the use of alternative common bases is suggested, both for classification and regression problems. In the case of classification or class-modeling, the suggested common bases are based on the spectrum of the Fisher weights (a measure of the between-class to within-class variance ratio) or on the spectrum of the SIMCA discriminant weights. In the case of regression, the suggested common bases are obtained by the correlation spectrum (the correlation coefficients of the predictor variables with a response variable) or by the PLS (Partial Least Squares regression) importance of the predictors (the product between the absolute value of the regression coefficient of the predictor in the PLS model and its standard deviation). Other alternative strategies apply the Gram–Schmidt supervised orthogonalization to the wavelet coefficients. The results indicate that, both in classification and regression, the information retained after compression in the wavelets space can be more efficient than that retained with a common basis obtained by variance.
Keywords: Wavelets; Common best basis; Fisher weight; SIMCA discriminant power; Complete validation

In class-modelling problems, which are again becoming increasingly important, there are two parameters to value the quality of the class-model built for a category, namely sensitivity and specificity. Using them as criteria, in this paper, two different approaches to class-modelling problems are presented, approaches that differ from other usual methods in the fact that they provide not just one class-model per category but a set of different class-models that accounts for the possible pairs of sensitivity–specificity values attainable for a given data set. One of the proposals is partial least squares class-modelling (PLS-CM) that, by the joint use of PLS with binary responses and the posterior statistical modelling of the distribution of the computed responses, permits the estimation of the risks related to the decision of assigning a sample into a class, and thus, the values of sensitivity and specificity. The other proposed method, Pareto-optimal front in class-modelling, is an analytical approach posed in a multi-response optimization framework, the one that corresponds to trying to simultaneously maximise the sensitivity and specificity of a class-model. Additionally, the whole family of computed class-models is validated in prediction by using cross-validation, showing the stability of both methods for prediction. The case-studies show the complementariness of both approaches and, in particular, that the joint use of both techniques allows the user to detect possible structures in the data set especially inadequate for PLS. The results, i.e. the whole set of sensitivity–specificity values achievable for a given problem, are graphically represented to improve its study and make it easy to make a decision about the model. Figure Hypothesis test as class-modelling: PLS-CM
Keywords: Class-modelling; Sensitivity; Specificity; PLS-CM; Pareto-optimal front

Computer-assisted modelling and optimisation of reversed-phase high-temperature liquid chromatographic (RP-HTLC) separations by J. García-Lavandeira; P. Oliveri; J. A. Martínez-Pontevedra; M. H. Bollaín; M. Forina; R. Cela (1951-1964).
The use of high temperatures (above 100 °C) in reversed-phase liquid chromatography (RP-HTLC) has opened up novel and enhanced applications for this essential separation technique. Although the favourable effects of temperature on LC have been extensively studied both theoretically and practically, its potential application to method development has barely been investigated. These favourable effects include enhanced speed, efficiency, resolution and detectability, as well as changes in selectivity, especially for polar and ionisable compounds, and the emergence of new options such as temperature programming and the concomitant use of solvent and temperature gradients, green separations, and so on. The recent availability of silica-based columns that routinely support high temperatures in addition to more conventional temperature-resistant columns (based on graphitised carbon, polymers and zirconium oxide) and dedicated column ovens that allow accurate temperature control up to 200 °C makes it possible to conceive of RP-HTLC as a routine separation technique in the modern analytical laboratory. On the other hand, the addition of temperature as a new optimisable parameter to RPLC adds further complexity to method development. Thus, new computer-assisted optimisation tools that extend the capabilities of current computer-assisted tools are being specifically developed for this type of separation. A new specially developed computer-assisted method development (CAMD) tool is presented herein, and its efficiency is demonstrated. This CAMD is based on the development of a rugged retention model for peaks, allowing the simulation of any kind of RP-HTLC separation, including isocratic, linear, curved, multilinear and stepwise gradients of solvent composition concomitant with constant, linear and multilinear temperature gradients. Both the retention models and the unattended optimisation of separations are driven by evolutionary algorithms, thus providing negligible-cost, rapid, highly efficient, and user-friendly optimisation processes.
Keywords: Optimisation; Reversed-phase high-temperature liquid chromatography; RP-HTLC; Computer-assisted method development; Simulation

Minimisation of instrumental noise in the acquisition of FT-NIR spectra of bread wheat using experimental design and signal processing techniques by G. Foca; C. Ferrari; N. Sinelli; M. Mariotti; M. Lucisano; R. Caramanico; A. Ulrici (1965-1973).
Spectral resolution (R) and number of repeated scans (S) have a significant effect on the S/N ratio of Fourier transform-near infrared (FT-NIR) spectra, but the optimal values of these two parameters have to be determined empirically for a specific problem, considering separately both the nature of the analysed matrix and the specific instrumental setup. To achieve this aim, the instrumental noise of replicated FT-NIR spectra of wheat samples was modelled as a function of R and S by means of the Doehlert design. The noise amounts in correspondence to different experimental conditions were estimated by analysing the variance signals derived from replicate measurements with two different signal processing tools, Savitzky–Golay (SG) filtering and fast wavelet transform (FWT), in order to separate the “pure” instrumental noise from other variability sources, which are essentially connected to sample inhomogeneity. Results confirmed that R and S values leading to minimum instrumental noise can vary considerably depending on the type of analysed food matrix and on the different instrumental setups, and helped in the selection of the optimal measuring conditions for the subsequent acquisition of a wide spectral dataset.
Keywords: Doehlert design; Fast wavelet transform; FT-NIR; Noise removal; Savitsky–Golay filtering

Aza-Michael reaction with enone-modified vegetable oils: evidence of the keto–enolic equilibrium by NIR chemical imaging and evolving factor analysis by Idoia Martí-Aluja; Itziar Ruisánchez; Virginia Cádiz; Santiago Maspoch; Maria Soledad Larrechi (1975-1982).
The existence of an enone–dienol tautomerism in enone-containing triglyceride, obtained from high oleic sunflower oil, was detected in an image set captured at 95 °C by fixed-size image window-evolving factor analysis. A 1H NMR spectrum and a UV–Visible spectrum of the enone-containing triglyceride at 25 °C and at 95 °C were measured to corroborate the presence of the enol form. The presence of this equilibrium explains the different behaviour of the curing reaction between an enone-containing triglyceride and diaminodiphenylmethane, which was evaluated following the spectral evolution of two pixels that differ in the presence or absence of the enol form. As the enol form acts as a inert species in the reaction, it leads to different degree of advance depending on which growing zone is observed.
Keywords: NIR chemical imaging; Crosslinking reaction; Enone-containing triglyceride; Fixed-size image window-evolving factor analysis; Chemometrics; Tautomerism equilibrium

Chemical equilibria studies using multivariate analysis methods by Joaquim Jaumot; Ramon Eritja; Raimundo Gargallo (1983-1997).
Chemical multiequilibria systems can be monitored efficiently with the aid of spectroscopic techniques. Both hard- and soft-modeling are effective and powerful tools to extract chemical information from spectroscopic data. Recently, hybrid approaches that combine the flexibility of soft-modeling with the precise solutions provided by hard-modeling have been proposed. Here, we tested the performance of these three chemometric approaches for the analysis of several simulated data sets. In addition, experimental data recorded during the study of the acid–base equilibria of two DNA structures (G-quadruplex and i-motif) corresponding to two short sequences of the k-ras oncogene were studied. Finally, we also analyzed the interaction of the two DNA sequences with the model ligand TMPyP4. The results obtained from the analysis of these data sets may be useful to determine the most appropriate use of each approach. Whenever the presence of optically active interferences or unknown drifts can be neglected and a chemical model can easily be proposed and fitted, the hard-modeling method shows the best performance. If any of these conditions is not fulfilled, a hybrid-modeling approach may be a better option because all the contributions (chemical and unknown) can be modeled and the ambiguities inherent to soft-modeling methods show minor effects. Figure Schematic representation of the application of multivariate modeling methods to the analysis of spectroscopic data
Keywords: Multivariate data analysis; Chemical equilibria; Hard-modeling; Soft-modeling; Hybrid-modeling; k-ras

Two-dimensional correlation analysis was carried out in combination with multivariate curve resolution–alternating least squares (MCR-ALS) to analyse time-resolved infrared (IR) difference spectra probing photo-induced ubiquinol formation in detergent-isolated reaction centres from Rhodobacter sphaeroides. The dynamic 2D IR correlation spectra have not only allowed the determination of the concomitance or non-concomitance of different chemical events through known marker bands but also have helped identify new vibrational bands related to the complex series of photochemical and redox reactions. In particular, a strong positive band located at 1565 cm−1 was found to be synchronous with the process of ubiquinol formation. In addition, a tailored MCR-ALS analysis was performed using a priori chemical knowledge of the system, in particular including the pure spectrum of one species obtained from an external measurement. Enhancing the MCR-ALS performance in this way in time-dependent processes is relevant, especially when other essential pieces of information, such as kinetic models, are unavailable. The results give evidence of four independent spectral contributions. Three of them show marker bands for a monoelectronic reduction of the primary quinone QA (Q A /QA transition, first contribution), for a monoelectronic reduction of a secondary quinone QB (Q B /QB transition, second contribution) and for ubiquinol formation (third contribution). The results obtained also confirm that a key rate-limiting factor is the slow ubiquinone and ubiquinol exchange among micelles, which strongly influences the kinetic profiles of the involved species.
Keywords: Chemometrics; Multivariate curve resolution; 2D correlation spectroscopy; Rapid-scan FTIR; Purple bacteria

Multiway and multiset data analysis extensions of the multivariate curve resolution alternating least squares (MCR-ALS) method are proposed for the investigation of the temporal distribution of the pollution by nitric oxide (NO) and ozone (O3) in one sampling station in the urban centre of Barcelona (Catalonia, Spain), during the years 2000–2006. Different specific studies were performed considering the annual and pluriannual contamination by these two contaminants, individually or in combination using different data matrix augmentation strategies and multiway and multiset data analysis models. Daily, hourly and annual profiles were estimated describing different patterns and summarising the main contamination processes. The daily and night trends found were mainly attributed to traffic and photochemical processes favoured by light radiation. Moreover, winter–summer seasonal trends were also clearly detected and their changes over different years assessed. The extension MCR-ALS method to multiset data analysis using different constraints like non-negativity, trilinearity and interaction among components is confirmed to be a powerful method to improve the interpretability of the different contamination patterns in atmospheric contamination studies.
Keywords: Chemometrics; Multiway data analysis methods; Multiset data analysis methods; Multivariate curve resolution alternating least squares; Air pollution; Nitric oxide; Ozone

Assessment of the sequential principal component analysis chemometric tool to identify the soluble atmospheric pollutants in rainwater by Rocío Montoya-Mayor; Antonio José Fernández-Espinosa; Miguel Ternero-Rodríguez (2031-2041).
In this study a new method of principal component (PC) analysis, sequential PC analysis (SPCA), is proposed and assessed on real samples. The aim was to identify the atmospheric emission sources of soluble compounds in rainwater samples, and the sample collection was performed with an automatic sampler. Anions and cations were separated and quantified by ion chromatography, whereas trace metals and metalloids were determined by inductively coupled plasma mass spectrometry. SPCA results showed eight interfering PCs and ten significant PCs. The interfering cases originated from different atmospheric sources, such as resuspended crustal particles, marine aerosols, urban traffic and a fertilizer factory. The significant PCs explained 84.6% of the total variance; 28.1% accounted for the main contribution, which was resuspended industrial soil from a fertilizer factory containing NO 2 - , NH 4 + , NO 3 - , SO 4 2- , F-, Al, K+, Mn, Sb and Ca2+ as indicators of the fertilizer factory. Another important source (15.0%) was found for Na+, Mg2+, K+, Cl- and SO 4 2- , which represents the marine influence from south and southwest directions. Emissions of Ba2+, Pb, Sr2+, Sb and Mo, which represent a traffic source deposited in soils, were identified as another abundant contribution (12.1%) to the rainwater composition. Other important contributions to the rainwater samples that were identified through SPCA included the following: different urban emissions (Cu, As, Cd, Zn, Mo and Co, 18.1%), emissions from vegetation (HCOO-, 7.7%) and emissions from industrial combustion processes (Ni, V 15.6%). The application of SPCA proved to be a useful tool to identify the complete information on rainwater samples as indicators of urban air pollution in a city influenced mainly by vehicle traffic emissions and resuspended polluted soils.
Keywords: Rainwater; Principal component analysis; Trace metals; Bioavailability; Sources identification; Traffic pollution

This work compares two miniaturised sample preparation methods, solid phase microextraction (SPME) and hollow fiber liquid phase microextraction (HF-LPME), in combination with gas chromatography coupled to tandem mass spectrometry with a triple quadrupole analyzer for the determination of 77 pesticides in drinking water. In the case of SPME, extraction temperature and time were optimized by experimental design, although other parameters, as desorption time, pH, and ionic strength, were also evaluated. The extraction and desorption solvents [octanol/dihexyl ether (75:25, v/v) and cyclohexane, respectively], as well as the extraction and desorption time, ionic strength, and pH, were studied for the HF-LPME procedure. Under the optimal conditions, recoveries (70.2–113.5% for SPME and 70.0–119.5% for HF-LPME), intra-day precision (2.1–19.4% for SPME and 4.3–22.5% for HF-LPME), inter-day precision (5.2–21.5% for SPME and 8.4–27.3% for HF-LPME), and limits of detection, between 0.1 and 28.8 ng/L for SPME and 0.2 and 47.1 ng/L for HF-LPME and overall uncertainty (9.6–25.2% for SPME and 13.3–27.5% for HF-LPME) were established for both extraction procedures. Finally, the proposed methods were successfully applied to the analysis of 41 drinking water samples, and similar results were obtained with both extraction approaches. Figure Determination of pesticides in tap water applying microextraction techniques coupled to GC-QqQ-MS/MS.
Keywords: SPME; HF-LPME; Pesticides; Gas chromatography–mass spectrometry; Triple quadrupole

Fourier-transform mid-infrared (FT-MIR) spectroscopy, combined with partial least-squares (PLS) regression and IPW as feature selection method, was used to develop reduced-spectrum calibration models based on a few IR bands to provide near-real-time predictions of two key parameters for the characterization of finished red wines, which are essential from a quality assurance standpoint: total and volatile acidity. Separate PLS calibration models, correlating IR data (only considering those regions showing a high signal to noise ratio) with each response studied, were developed. Wavenumber selection was also performed applying IPW-PLS to take into account only significant predictors, in an attempt to improve the quality of the final models constructed. Using both PLS and IPW-PLS regression, prediction of the two responses modelled was performed with very high reliability, with RMSECV and RMSEP values on the order of 1% (comparable in terms of accuracy to the results provided by the respective reference analysis methods). An important advantage derived from the application of the IPW-PLS method had to do with the low number of original variables needed for modelling both total acidity (22 significant wavenumbers) and volatile acidity (only 11 selected predictor variables), in such a way that variable selection contributed to enhance the stability and parsimony properties of the final calibration models. The high quality of the calibration models proposed encourages the feasibility of implementing them as a fast and reliable tool in routine analysis for the determination of critical parameters for wine quality.
Keywords: FT-MIR spectroscopy; Variable selection; IPW-PLS; Quality assurance; Acidity; Red wine

Characterization and classification of the aroma of beer samples by means of an MS e-nose and chemometric tools by L. Vera; L. Aceña; J. Guasch; R. Boqué; M. Mestres; O. Busto (2073-2081).
An electronic nose based on coupling of headspace (HS) with a mass spectrometer (MS) has been used in this study to classify and characterize a series of beers according to their production site and chemical composition. With this objective, we analyzed 67 beers of the same brand and preparation process but produced in different factories. The samples were also subjected to sensory evaluation by a panel of experts. Linear discriminant analysis (LDA) was used as the classification technique and stepwise LDA based on Wilk’s lambda criterion was used to select the most discriminating variables. To interpret the aroma characteristics of the beers from the m/z ions obtained, score and loading bi-plots were obtained by applying canonical variables. Because the beers analyzed were marketed with the same name and brand, we expected to be working with the same product irrespective of its origin. However, results from both sensory evaluation and use of the e-nose revealed differences between factories. With the e-nose it was possible to relate these differences to the presence (and abundance) of characteristic ions of different compounds typically found in beer. These results demonstrate that the HS–MS e-nose is not only an aroma sensor capable to classify and/or differentiate samples but it can also provide information about the compounds responsible for this differentiation.
Keywords: MS e-nose; Beer; Volatile compounds; Classification; Characterization; LDA

Discriminating olive and non-olive oils using HPLC-CAD and chemometrics by P. de la Mata-Espinosa; J. M. Bosque-Sendra; R. Bro; L. Cuadros-Rodríguez (2083-2092).
This work presents a method for an efficient differentiation of olive oil and several types of vegetable oils using chemometric tools. Triacylglycerides (TAGs) profiles of 126 samples of different categories and varieties of olive oils, and types of edible oils, including corn, sunflower, peanut, soybean, rapeseed, canola, seed, sesame, grape seed, and some mixed oils, have been analyzed. High-performance liquid chromatography coupled to a charged aerosol detector was used to characterize TAGs. The complete chromatograms were evaluated by PCA, PLS-DA, and MCR in combination with suitable preprocessing. The chromatographic data show two clusters; one for olive oil samples and another for the non-olive oils. Commercial oil blends are located between the groups, depending on the concentration of olive oil in the sample. As a result, a good classification among olive oils and non-olive oils and a chemical justification of such classification was achieved. Figure PCA scores plot of oil samples. Olive oils (asterisk), non-olive oils (filled square) and oil blends (filled inverse triangle)
Keywords: Olive oil authentication; Pattern recognition; Principal component analysis; Partial least square-discriminant analysis; Multivariate curve resolution; Liquid chromatography

Multivariate analysis of HT/GC-(IT)MS chromatographic profiles of triacylglycerol for classification of olive oil varieties by Cristina Ruiz-Samblás; Luis Cuadros-Rodríguez; Antonio González-Casado; Francisco de Paula Rodríguez García; Paulina de la Mata-Espinosa; Juan Manuel Bosque-Sendra (2093-2103).
The ability of multivariate analysis methods such as hierarchical cluster analysis, principal component analysis and partial least squares-discriminant analysis (PLS-DA) to achieve olive oil classification based on the olive fruit varieties from their triacylglycerols profile, have been investigated. The variations in the raw chromatographic data sets of 56 olive oil samples were studied by high-temperature gas chromatography with (ion trap) mass spectrometry detection. The olive oil samples were of four different categories (“extra-virgin olive oil”, “virgin olive oil”, “olive oil” and “olive-pomace” oil), and for the “extra-virgin” category, six different well-identified olive oil varieties (“hojiblanca”, “manzanilla”, “picual”, “cornicabra”, “arbequina” and “frantoio”) and some blends of unidentified varieties. Moreover, by pre-processing methods of chemometric (to linearise the response of the variables) such as peak-shifting, baseline (weighted least squares) and mean centering, it was possible to improve the model and grouping between different varieties of olive oils. By using the first three principal components, it was possible to account for 79.50% of the information on the original data. The fitted PLS-DA model succeeded in classifying the samples. Correct classification rates were assessed by cross-validation.
Keywords: Triacylglycerols; Olive oil varieties; High-temperature gas chromatography–mass spectrometry; Chemometric multivariate classification

Comparison between classical and innovative class-modelling techniques for the characterisation of a PDO olive oil by Paolo Oliveri; Monica Casale; M. Chiara Casolino; M. Antonietta Baldo; Fiammetta Nizzi Grifi; Michele Forina (2105-2113).
An authentication study of the Italian PDO (protected designation of origin) olive oil Chianti Classico, based on near-infrared and UV–Visible spectroscopy, an artificial nose and an artificial tongue, with a set of samples representative of the whole Chianti Classico production and a considerable number of samples from a close production area (Maremma) was performed. The non-specific signals provided by the four fingerprinting analytical techniques, after a proper pre-processing, were used for building class models for Chianti Classico oils. The outcomes of classical class-modelling techniques like soft independent modelling of class analogy and quadratic discriminant analysis—unequal dispersed classes were compared with those of two techniques recently introduced into Chemometrics: multivariate range modelling and CAIMAN analogues modelling methods.
Keywords: Chianti Classico PDO olive oil; Food authentication; Class-modelling; Fingerprinting analysis; NIR and UV–Vis spectroscopy; Artificial nose and tongue

The composition of volatile components of subcutaneous fat from Iberian pig has been studied. Purge and trap gas chromatography−mass spectrometry has been used. The composition of the volatile fraction of subcutaneous fat has been used for authentication purposes of different types of Iberian pig fat. Three types of this product have been considered, montanera, extensive cebo and intensive cebo. With classification purposes, several pattern recognition techniques have been applied. In order to find out possible tendencies in the sample distribution as well as the discriminant power of the variables, principal component analysis was applied as visualisation technique. Linear discriminant analysis (LDA) and soft independent modelling by class analogy (SIMCA) were used to obtain suitable classification models. LDA and SIMCA allowed the differentiation of three fattening diets by using the contents in 2,2,4,6,6-pentamethyl-heptane, m-xylene, 2,4-dimethyl-heptane, 6-methyl-tridecane, 1-methoxy-2-propanol, isopropyl alcohol, o-xylene, 3-ethyl-2,2-dimethyl-oxirane, 2,6-dimethyl-undecane, 3-methyl-3-pentanol and limonene. Figure Iberian pigs in outdoor rearing system (Montanera)
Keywords: Iberian pig; Subcutaneous fat; Volatile compounds; Gas chromatography−mass spectrometry; Pattern recognition

Determination of marker pteridines in urine by HPLC with fluorimetric detection and second-order multivariate calibration using MCR-ALS by A. Mancha de Llanos; M. M. De Zan; M. J. Culzoni; A. Espinosa-Mansilla; F. Cañada-Cañada; A. Muñoz de la Peña; H. C. Goicoechea (2123-2135).
A liquid chromatographic method has been developed, in combination with the multivariate curve resolution-alternating least squares algorithm (MCR-ALS), for the simultaneous determination of marker pteridines in urine samples. A central composite design has been applied to optimize the factors influencing the separation (buffer concentration, buffer pH, flow rate, oven temperature, mobile-phase composition). A set of 15 calibration samples were randomly prepared, in a concentration range of 0.5–10.5 ng mL−1 for neopterin, biopterin, and pterin; 4.0–8.0 ng mL−1 for xanthopterin; and 0.5–4.5 ng mL−1 for isoxanthopterin. The validation was carried out with fortified urine samples from healthy adults. The optimized conditions were a mobile-phase composition of 10 mM citric buffer at pH 5.44 and acetonitrile (94.5/5.5, v/v), a flow rate of 1.0 mL min−1, and an oven temperature of 25 °C. The detection system consisted of a fast-scanning spectrofluorimeter, which allows obtaining of second-order data matrices containing the fluorescence intensity as a function of retention time and emission wavelength. In this work, MCR-ALS was used to cope with coeluting interferences, on account of the second-order advantage inherent to this algorithm which, in addition, is able to handle data sets deviating from trilinearity, like the high-performance liquid chromatography data analyzed in the present report. The developed approach enabled us to determine five pteridines, some of them with overlapped profiles, reducing the experimental time and reagent consumption. Ratio values for pteridines/creatinine in urine, for infected children with different pathologies, are reported in this work.
Keywords: Pteridines; Creatinine (CREA); High-performance liquid chromatography (HPLC); Urine

Comparison of different chemometric and analytical methods for the prediction of particle size distribution in pharmaceutical powders by Mafalda C. Sarraguça; Ana V. Cruz; Helena R. Amaral; Paulo C. Costa; João A. Lopes (2137-2147).
This work compares the estimation of the particle size distribution of a pharmaceutical powder using near-infrared spectroscopy (NIRS), powder flowability properties, and components concentration. The estimations were made by considering the former data blocks separately and together using a multi-block approach. The powders were based on a formulation of paracetamol as the pharmaceutical active ingredient. The reference method used to determine particle size distribution was sieving. Partial least squares methods were used to estimate the multivariate regression models, and the results were compared in terms of figures of merit. It was shown that the partial least squares methods gave similar prediction errors. Regarding the data blocks used, the NIRS block was proven the most advantageous to estimate the particle size distribution. The prediction error of the NIRS block was similar to the other data blocks with additional advantages such as less generalization problems and the possibility of its use to predict additional physical and chemical properties with an improvement to analysis time. The multi-block approach produced the worst results but nevertheless allowed a deeper understanding of the individual contributions of the data blocks in the prediction of the particle size distribution.
Keywords: Pharmaceutical powders; Particle size distribution; Near-infrared spectroscopy; Flowability properties; Partial least squares 1; Partial least squares 2; Multi-block partial least squares

10th European workshop on laser ablation by D. Garbe-Schönberg; J. Fietzke; D. Günther (2149-2151).
is a Senior Researcher and Head of the ICP–MS Laboratory at the Institute of Geosciences, Christian-Albrechts-Universität Kiel, Germany. His research focuses on the geochemistry of trace elements during formation and subduction of the oceanic lithosphere, and related hydrothermal processes. He has been involved with the development of both solution-based and laser ablation ICP–MS for more than 20 years. received his PhD in physics from Heidelberg University in 2000. Working as a laboratory manager at IFM-GEOMAR, Kiel, Germany, his research focuses on the application of LA–ICP–MS in studies of non-traditional stable isotopes in biogenic carbonates. is full professor for Trace Element and Micro Analysis in the Laboratory of Inorganic Chemistry at ETH Zurich and currently Chair of the Department for Chemistry and Applied Biosciences. His research program focuses on fundamental and applied studies in inductively coupled plasma–mass spectrometry (ICP–MS) and laser ablation–inductively coupled plasma–mass spectrometry (LA–ICP–MS), which includes studies on laser-sample interaction, aerosol transport, and plasma-related excitation processes. The fundamental understanding of UV-ns and UV-fs laser ablation in combination with Q–ICP–MS, SF–ICP–MS, ICP–TOFMS and more recently MC–ICP–MS and alternative excitation sources has been demonstrated in a wide variety of applications, e.g. analysis of fluid inclusions, gemstones, metals, minerals, ceramics, and other industrial materials.

Direct analysis of trace elements in crude oils by high-repetition-rate femtosecond laser ablation coupled to ICPMS detection by Estelle Ricard; Christophe Pécheyran; Georgia Sanabria Ortega; Alain Prinzhofer; Olivier F. X. Donard (2153-2165).
IR-femtosecond pulses were used at high repetition rates (up to 10 kHz) to ablate viscous crude oils for the determination of trace elements by ICPMS. A special internal glass cap was fitted into the ablation cell to minimise oil splashes and remove big particles that would be otherwise spread into the cell. Laser ablation in static and dynamic conditions (i.e. the laser beam being moved rapidly at the surface of the sample) was studied together with some fundamental parameters like repetition rate and fluence. Signal sensitivity and stability were found to be strongly affected by repetition rate and fluence, though not in linear manner, and in some circumstances by the laser beam velocity. Sample transport efficiency was found to decrease with increasing repetition rate, probably due to stronger particle agglomeration when increasing the density of primary particles. ICPMS plasma atomisation/ionisation efficiency was also found to be affected to some extent at the highest repetition rates. Moderate repetition rate (1 kHz), high fluence (24 J cm−2) and fast scanning velocity (100 mm s−1) were preferred taking into account signal intensity and stability. Sample transport elemental fractionation was also evidenced, particularly as regards to carbon due to volatilisation of volatile organic species. Matrix effect occurring when comparing the ablation of transparent (base oil) and opaque (crude oil) samples could not be completely suppressed by the use of IR femtosecond pulses, requiring a matrix matching or a standard addition calibration approach. This approach provided good accuracy and very low detection limits in the crude oil, in the range of ng g−1.
Keywords: High repetition rate; Femtosecond laser ablation; Crude oil

Femtosecond laser ablation inductively coupled plasma mass spectrometry was used for the quantification of 23 metallurgical relevant elements in unalloyed, alloyed and highly alloyed steels, and super alloys. It was shown that by using scanning mode ablation with large ablation spot diameters (250 μm), stable and representative sampling can be achieved for the majority of elements, except for bismuth and lead. For Bi and Pb up to 46%, temporal relative standard deviation (TRSD) was encountered, whereas for most other elements, the TRSDs were below 10%. Calibration with matrix-matched and non-matrix-matched standards provided similar agreement within the uncertainty of the certified values. However, the non-matrix-matched standard-based quantification was more influenced by interferences rather than ablation- or excitation-related matrix effects. The method was validated using 34 certified reference materials. 52Cr, 51V, or 55Mn were used as internal standards due to the fact that the Fe concentration was not certified for the majority of reference materials. The determined concentrations for major and minor elements indicate that the total matrix internal standardization (100 wt.%) is applicable, which requires no knowledge about the steel samples prior to analysis. Figure CRM chips embedded in epoxy resin
Keywords: Laser ablation; Mass spectrometry/ICP-MS; Metals/heavy metals; Femtosecond laser ablation ICP-MS; High alloyed steel; Trace contaminants

Temperature dependency of element incorporation into European eel (Anguilla anguilla) otoliths by Lasse Marohn; Volker Hilge; Karsten Zumholz; Andreas Klügel; Heike Anders; Reinhold Hanel (2175-2184).
The present study experimentally tested the influence of water temperature on the inclusion of 15 elements into juvenile European eel (Anguilla anguilla) otoliths in freshwater. It should be investigated (1) if temperature effects on otolith Sr/Ca might impair the interpretation of migration studies and (2) if the elemental composition of otoliths can be used to reconstruct experienced temperature histories of eels. Therefore, eels were kept under full experimental conditions at three different water temperatures (14 °C, 19 °C and 24 °C) for 105 days. Thereafter, laser ablation inductively coupled mass spectrometry (LA-ICPMS) was conducted on the outer edge of their otoliths. Our analyses revealed significant temperature effects on otolith Na/Ca, Sr/Ca, Mg/Ca, Mn/Ca, Ba/Ca, Zr/Ca and Y/Ca ratios. Variations of Sr/Ca caused by temperature were far below those used to detect eel movements between waters of different salinities and will therefore not affect the interpretation of migration studies. Elemental fingerprints of Sr/Ca, Mg/Ca, Mn/Ca and Ba/Ca ratios resulted in clearly separated groups according to temperature treatments, indicating that changes in water temperature might lead to characteristic changes in otolith element composition. However, the successful application of elemental fingerprints to reconstruct moderate changes of water temperature seems doubtful because the influence of somatic growth on otolith microchemistry still remains unclear, and temperature-induced variations could be overlaid by changes of water element concentrations during growth periods. Nevertheless, our results contribute to the completion of knowledge about factors influencing element incorporation and help to explain variations in element composition of fish otoliths. Figure Juvenile European eels (Anguilla anguilla)
Keywords: Anguilla anguilla ; Otolith; Microchemistry; LA-ICPMS; Temperature effect

The performance of a laser ablation mass analyser designed for in-situ exploration of the chemical composition of planetary surfaces has been investigated. The instrument measures the elemental and isotopic composition of raw solid materials with high spatial resolution. The initial studies were performed on NIST standard materials using IR laser irradiance (< 1 GW cm−2) at which a high temporal stability of ion formation and sufficiently low sample consumption was achieved. Measurements of highly averaged spectra could be performed with typical mass resolution of mm ≈ 600 in an effective dynamic range spanning seven decades. Sensitive detection of several trace elements can be achieved at the ~ ppm level and lower. The isotopic composition is usually reproduced with 1% accuracy, implying good performance of the instrument for quantitative analysis of the isotopic fractionation effects caused by natural processes. Using the IR laser, significant elemental fractionation effects were observed for light elements and elements with a high ionization potential. Several diatomic clusters of major and minor elements could also be measured, and sometimes these interfere with the detection of trace elements at the same nominal mass. The potential of the mass analyser for application to sensitive detection of elements and their isotopes in realistic samples is exemplified by measurements of minerals. The high resolution and large dynamic range of the spectra makes detection limits of ~100 ppb possible. Figure The mass spectrum of Allende meteorite measured by a miniature laser ablation mass spectrometer. Similar mass spectra of planetary materials in-situ could be measured with spatial resolution of 10-100 μm (white circles) providing means for chemical analysis of planetary surfaces
Keywords: Time-of-flight mass spectrometer; Laser ablation; Elemental analysis; Meteorite composition; Planetary surfaces

Online electrothermal heating of laser-generated aerosols: effects on aerosol particle size and signal intensities in ICPMS by Robert Brogioli; Bodo Hattendorf; Joachim Koch; Helmar Wiltsche; Luca Flamigni; Detlef Günther (2201-2209).
To achieve separation of isobaric interferences and minimization of matrix related interferences for laser ablation-inductively coupled plasma mass spectrometry (LA-ICPMS) electrothermal heating of laser generated aerosols was investigated by analyzing a range of solid samples: NIST SRM 610, MBH B26, BAM M381, BAM M601 and Tantalum. ICPMS measurements showed that individual elements can be removed from the laser-generated aerosol at characteristic temperatures for different solid materials. Signal reduction as high as 3 orders of magnitude were achieved for volatile elements, such as Ag and Cd when heating laser-generated aerosol of NIST SRM 610 silicate glass. A signal reduction of more than 99% was obtained for Rb while Sr remained practically unaffected. A temperature- and matrix-dependent change of particle size distribution after aerosol heating was observed by means of laser light scattering (direct aerosol visualization) and scanning electron microscopy. In the temperature range between 900 and 1,200 °C, element unspecific signal suppression was observed, which could be related to a change of the particle size distributions.
Keywords: ETV; ICPMS; Laser ablation; Element separation; Spectral interferences; Particle size distribution; 87Rb/87Sr separation

Calibration of analytical methods using laser ablation for sample introduction is often problematic. The availability of matrix-adapted standard materials is a crucial factor in the analysis of biological samples in particular. In this work a method for preparation of thin-film references for LA–ICP–MS is presented which is inexpensive, relatively simple and generally practicable. Aqueous solutions of agarose spiked with defined amounts of the analytes were cast on a carrier and then dried. When the thin-film references were characterized the average thickness of the films was 0.03 mm in the centre of the film and the relative standard deviation was 8%. Nebulization ICP–MS analysis after acid digestion of the agarose film was used to investigate the effectiveness of the spiking procedure. Recovery of the spiked elements was frequently in the range 90–110% (for rare earth elements 97–102%). Laser ablation ICP–MS analysis was used to investigate the distribution of the spiked elements in the film. When the laser was scanned across the gel the measured intensities were not constant, but had a peak-shaped profile with a flat top. Use of this flat-top region for analytical purposes, after its characterization by laser ablation ICP–MS, is proposed. Analysis of cell cultures was carried out by direct laser ablation-ICP–MS with the calibration method described. The results were in accordance with values previously achieved by nebulization ICP–MS.
Keywords: Laser ablation inductively coupled plasma mass spectrometry (LA–ICP–MS); Calibration; Agarose thin-film references; Total consumption laser ablation; Trace element detection

Peter S. Hooda (Ed.): Trace elements in soils by Isabelle Lamy (2219-2220).

Assessment of sample preservation techniques for pharmaceuticals, personal care products, and steroids in surface and drinking water by Brett J. Vanderford; Douglas B. Mawhinney; Rebecca A. Trenholm; Janie C. Zeigler-Holady; Shane A. Snyder (2227-2234).
Proper collection and preservation techniques are necessary to ensure sample integrity and maintain the stability of analytes until analysis. Data from improperly collected and preserved samples could lead to faulty conclusions and misinterpretation of the occurrence and fate of the compounds being studied. Because contaminants of emerging concern, such as pharmaceuticals and personal care products (PPCPs) and steroids, generally occur in surface and drinking water at ng/L levels, these compounds in particular require such protocols to accurately assess their concentrations. In this study, sample bottle types, residual oxidant quenching agents, preservation agents, and hold times were assessed for 21 PPCPs and steroids in surface water and finished drinking water. Amber glass bottles were found to have the least effect on target analyte concentrations, while high-density polyethylene bottles had the most impact. Ascorbic acid, sodium thiosulfate, and sodium sulfite were determined to be acceptable quenching agents and preservation with sodium azide at 4 °C led to the stability of the most target compounds. A combination of amber glass bottles, ascorbic acid, and sodium azide preserved analyte concentrations for 28 days in the tested matrices when held at 4 °C. Samples without a preservation agent were determined to be stable for all but two of the analytes when stored in amber glass bottles at 4 °C for 72 h. Results suggest that if improper protocols are utilized, reported concentrations of target PPCPs and steroids may be inaccurate.
Keywords: Preservation; Sample collection; Pharmaceuticals; Endocrine disruptors; Emerging contaminants; Water

Detection of DNA damage in yolk-sac larvae of the Japanese Medaka, Oryzias latipes, by the comet assay by Bénédicte Morin; Julien Filatreau; Ludovic Vicquelin; Iris Barjhoux; Sylvain Guinel; Joelle Leray-Forget; Jérôme Cachot (2235-2242).
This study was set up to determine the suitability of the early life stage (ELS) alkaline comet assay for the detection of DNA strand breaks induced by genotoxicants in whole organism. This assay was performed on cells of medaka 2 days posthatch (dph). An efficient procedure for cell dissociation using enzymatic and mechanical digestion was developed. This protocol ensures 80% viability of cells and low DNA damage background. Cells from 2 dph medaka larvae were exposed in vitro to model genotoxicants, hydrogen peroxide, cadmium, and fluoranthene, followed by comet assay analysis. Results show a significant increase in the percentage of DNA damage of dissociated cells by all the tested compounds when compared to controls. The assay was also performed in vivo on medaka larvae (2 dph) exposed for 24 h to waterborne cadmium or fluoranthene. Significant induction of DNA damage levels were observed following larvae exposure to cadmium and fluoranthene at concentrations of 0.1 and 50 μM, respectively. This study demonstrates that cells of embryo life stage medaka respond to known DNA damaging agents and that the ELS comet assay may be a useful biomarker to detect DNA strand breakage in whole body of pluricellular organism induced by a range of agents. This technique may provide a sensitive, nonspecific endpoint of genotoxicity as part of ELS toxicity test.
Keywords: DNA damage; Medaka larvae; Early life-stage (ELS); Comet assay

Liquid chromatography–tandem mass spectrometry (LC/APCI-MS/MS) methods for the quantification of captan and folpet phthalimide metabolites in human plasma and urine by Aurélie Berthet; Michèle Bouchard; Patrick Schüpfer; David Vernez; Brigitta Danuser; Cong Khanh Huynh (2243-2255).
Captan and folpet are fungicides largely used in agriculture. They have similar chemical structures, except that folpet has an aromatic ring unlike captan. Their half-lives in blood are very short, given that they are readily broken down to tetrahydrophthalimide (THPI) and phthalimide (PI), respectively. Few authors measured these biomarkers in plasma or urine, and analysis was conducted either by gas chromatography coupled to mass spectrometry or liquid chromatography with UV detection. The objective of this study was thus to develop simple, sensitive and specific liquid chromatography–atmospheric pressure chemical ionization-tandem mass spectrometry (LC/APCI-MS/MS) methods to quantify both THPI and PI in human plasma and urine. Briefly, deuterated THPI was added as an internal standard and purification was performed by solid-phase extraction followed by LC/APCI-MS/MS analysis in negative ion mode for both compounds. Validation of the methods was conducted using spiked blank plasma and urine samples at concentrations ranging from 1 to 250 μg/L and 1 to 50 μg/L, respectively, along with samples of volunteers and workers exposed to captan or folpet. The methods showed a good linearity (R 2 > 0.99), recovery (on average 90% for THPI and 75% for PI), intra- and inter-day precision (RSD, <15%) and accuracy (<20%), and stability. The limit of detection was 0.58 μg/L in urine and 1.47 μg/L in plasma for THPI and 1.14 and 2.17 μg/L, respectively, for PI. The described methods proved to be accurate and suitable to determine the toxicokinetics of both metabolites in human plasma and urine. Figure Representative chromatograms of THPI, PI, and THPI-d in the urine of a volunteer exposed orally to captan (a) or folpet (b)
Keywords: Tetrahydrophthalimide; Phthalimide; LC/APCI-MS/MS; Plasma; Urine

A multi-residual method is described for the simultaneous determination of 23 personal care products (PCPs), which display a wide range of physicochemical properties, present at trace levels in water samples. A one-step procedure was developed based on solid-phase microextraction (SPME) coupled with GC-MS analysis. A chemometric approach consisting of an experimental design (design of experiments) was applied to systematically investigate how four operating parameters—extraction temperature and time and desorption temperature and time—affect extraction recovery of PCPs in water. The optimum SPME procedure operating conditions, those yielding the highest extraction recovery for all the compounds, were determined; they correspond to an extraction time of 90 min and temperature of 80 °C and a desorption time of 11 min and temperature of 260 °C. Under these optimized conditions, the SPME procedure shows good analytical performance characterized by high reproducibility (RSD% intra-day accuracy varying in the 0.01–1.3% range) as well as good linearity and low detection limits (LODs lower than 2 ppb for most of the investigated PCPs). Figure A one-step procedure based on solid phase micro extraction (SPME) coupled with GC-MS analysis achieves the simultaneous determination of 23 PCPs.
Keywords: Personal care products; Solid-phase microextraction; Gas chromatography–mass spectrometry; Multi-residue method; Response surface model

Determination of protein-bound methionine oxidationin the hippocampus of adult and old rats by LC-ESI-ITMS method after microwave-assisted proteolysis by Li-Hong Long; Peng-Fei Wu; Xin-Lei Guan; Jun-Qi Zhang; You Jin; Zui Zhang; Yue Wang; Yi-Yong Li; Jian-Guo Chen; Fang Wang (2267-2274).
Protein-bound methionine (Met) oxidation has been associated with normal aging and a variety of age-related diseases, including Alzheimer’s disease and Parkinson’s disease. Monitoring the changes of protein-bound methionine content in the brain in response to normal aging and oxidative stress is of great interest and could be used as an indicator of oxidative stress of rats in pathological conditions. We have developed a rapid analytical method for the determination of oxidized products of protein-bound methionine in rat brain. The assay involved rapid acid proteolysis with microwave irradiation and solid-phase extraction of the free amino acids followed by LC-ESI-ITMS analysis. Detection was achieved in positive ionization with an ion trap mass spectrometer operating in multiple-reaction monitoring mode. The calibration curves of the analytes were linear (r 2 > 0.99) in the range between 0.098 and 1.560 μg/mL. Intra- and inter-day relative standard deviation percentages were <9% and <8%, respectively. The assay performance was sufficient to support a rapid analytical tool for monitoring brain protein-bound methionine oxidation levels. The content of protein-bound Met and methionine sulfoxide (MetO) in the hippocampus of adult and old rats with or without H2O2 treatment was determined by employing the new method. The content of protein-bound MetO was significantly increased in old rats after exposure to H2O2. This result indicates increased sensitivity to Met oxidation in the hippocampus of old rats.
Keywords: Protein-bound methionine; LC-ESI-ITMS; Microwave-assisted acid hydrolysis; Rat hippocampus

Development of a fluorescence polarization immunoassay for the detection of melamine in milk and milk powder by Qiang Wang; Simon A. Haughey; Yuan-Ming Sun; Sergei A. Eremin; Zhen-Feng Li; Hui Liu; Zhen-Lin Xu; Yu-Dong Shen; Hong-Tao Lei (2275-2284).
A fluorescence polarization immunoassay (FPIA) based on a polyclonal antibody was developed for the determination of melamine in milk. To obtain an antibody with improved sensitivity and specificity, 6-hydrazinyl-1,3,5-triazine-2,4-diamine was coupled to bovine serum albumin and used as the immunogen for the rabbit immunization. Three fluorescein-labeled melamine tracers with different structures and spacer bridges were synthesized. The structural effect of the tracers on the assay characteristics was investigated. 6-(4,6-Diamino-1,3,5-triazin-2-ylamino)-N-(2-(3-(3′,6′-dihydroxy-3-oxo-2,3-dihydrospiro[indene-1,9′-xanthene]-5-yl)thioureido)ethyl)hexanamide demonstrated better sensitivity than 5-(2-(4,6-diamino-1,3,5-triazin-2-yl)hydrazinecarbothioamido)-2-(6-hydroxy-3-oxo-3H-xanthen-9-yl)benzoic acid and 3-(4,6-diamino-1,3,5-triazin-2-ylthio)-N-(2-(3-(3′,6′-dihydroxy-3-oxo-3H-spiro[isobenzofuran-1,9′-xanthene]-5-yl)thioureido)ethyl)propanamide. The limit of detection (10% inhibition) of the FPIA was 9.3 ng mL-1 and the IC50 (50% inhibition) value was 164.7 ng mL-1. The antibody in the FPIA showed 21.2% cross-reactivity to the fly-killing insecticide cyromazine, but had no cross-reactivity to other natural structurally related compounds. Recoveries, measured in spiked milk and milk powder samples, ranged from 79.4 to 119.0%. Milk samples fortified with melamine were analyzed by this method and confirmed by high-performance liquid chromatography–mass spectrometry. Excellent recoveries and correlation with spiked levels were observed, suggesting that this immunoassay could be applied to the screening of melamine residues in milk and milk powder after a simple dilution procedure. Figure Figure Performance comparison of tree tracers and two antibodies. (a), antibody A; (b) antibody B
Keywords: Melamine; Fluorescence polarization immunoassay; Polyclonal antibody; Milk

A new method for the determination of free l-carnitine in serum samples based on high field single quantum coherence filtering 1H-NMR spectroscopy by Constantinos G. Tsiafoulis; Vassiliki Exarchou; Polyxeni P. Tziova; Eleni Bairaktari; Ioannis P. Gerothanassis; Anastassios N. Troganis (2285-2294).
The rapid and accurate determination of specific metabolites present in biofluids is a very demanding task which is essential in both medicine and chemistry. l-carnitine (3-hydroxy-4-N-trimethylammonium butyrate) is an important metabolite which participates in a series of biological paths and therefore its determination is of diagnostic importance. A single quantum coherence filtering 1H NMR methodology was used for the accurate and rapid determination of l-carnitine in human serum samples. The methodology is based on spectral simplification, and specifically on the distinction of the N-methyl proton signal of l-carnitine that is greatly overlapped in the 1H-NMR spectrum of serum. The quantitative results provided by the proposed method are in excellent agreement with those obtained by the enzymatic method, which is widely used. The proposed method is rapid (~20 min of experimental time), selective, sensitive, and has good analytical characteristics (accuracy, reproducibility). Selected protein precipitation methods were also investigated and sample pretreatment with EtOH is suggested.
Keywords: l-Carnitine; Serum; 1H-NMR; Single quantum coherence filtering 1H-NMR; Protein precipitation

Aminated dendritic surfaces characterization: a rapid and versatile colorimetric assay for estimating the amine density and coating stability by G. Coussot; C. Faye; A. Ibrahim; M. Ramonda; M. Dobrijevic; A. Le Postollec; F. Granier; O. Vandenabeele-Trambouze (2295-2302).
The functionalization of surfaces with amino groups is used in many application areas such as in industrial biocatalytic processes for the development of medical biomaterials and in the environment for removing pollutants from water. Amino group density and grafting stability are often related to functionalized material performances; thus, their characterizations are of prime importance. The determination of amino density and grafting stability on polymeric material (e.g. polypropylene, polystyrene and cylco olefin copolymer) is often time consuming and sometimes presents technical constraints, more particularly with non-flat materials. In this paper, we report a novel colorimetric assay using the Coomassie Brilliant Blue dye for both amino density determination and grafting stability measurement. The assay named ADECA for “Amino Density Estimation by Colorimetric Assay” is sensitive, rapid, robust and versatile. We demonstrate that ADECA makes the evaluation of aminated materials performances possible for numerous material compositions, formats and chemistries used for grafting. Our study focuses on dendrigraft of poly-l-lysine and poly(amidoamine) dendrimers dendritic materials. Figure Animated surfaces characterization
Keywords: Colorimetric assay; Aminated surfaces; Solid support characterization; Dendrimers; Coating stability; ADECA