Rapid discrimination of fatty acid composition in fats and oils by electrospray ionization mass spectrometry.

Fatty acids in 42 types of saponified vegetable and animal oils were analyzed by electrospray ionization mass spectrometry (ESI-MS) for the development of their rapid discrimination. The compositions were compared with those analyzed by gas chromatography-mass spectrometry (GC-MS), a more conventional method used in the discrimination of fats and oils. Fatty acids extracted with 2-propanol were-detected as deprotonated molecular ions ([M-H]-) in the ESI-MS spectra of the negative-ion mode. The composition obtained by ESI-MS corresponded to the data of the total ion chromatograms by GC-MS. The ESI-MS analysis discriminated the fats and oils within only one minute after starting the measurement. The detection limit for the analysis was approximately 10(-10) g as a sample amount analyzed for one minute. This result showed that the ESI-MS analysis discriminated the fats and oils much more rapidly and sensitively than the GC-MS analysis, which requires several tens of minutes and approximately 10(-9) g. Accordingly, the ESI-MS analysis was found to be suitable for a screening procedure for the discrimination of fats and oils.     

Use of amino acid analysis for estimating the individual concentrations of proteins in mixtures

The concentrations of five individual proteins in a mixture were determined from one amino acid analysis of the mixture by solving for each protein using simultaneous equations. Dried casein and whey were separated into five individual protein components using reversed-phase HPLC. Individual proteins were collected and analyzed for amino acid composition. These data were used as standards. Mixtures of purified proteins were analyzed for total amino acid composition and the concentrations of individual proteins in the mixtures were determined by solving simultaneous equations based on the amino acid analysis composition of the standards.     

Unbiased and biased chemometric analysis of LC-MS data from human urine following coffee intake

We carried out a human volunteer study with 14 participants, eight of whom were asked to consume one cup of coffee at four different time points. Urine samples were collected at eight time points and analyzed by HPLC-MS analysis. The LC-MS data were subjected to unsupervised multivariate statistical analysis (principal component analysis) followed by supervised multivariate analysis (linear discriminant analysis). In an unbiased approach, in the absence of data preselection and filtering, the most important features explaining differences between coffee consumers and the control group observed showed variations in endogenous human hormonal steroid metabolites as well as xanthine derivatives. Only after a biased data treatment data revealed differences between the sample groups based on literature reported chlorogenic acid metabolites resulting directly from coffee intake. Such analysis could confirm the presence of 21 previously reported chlorogenic acid plasma metabolites as urinary metabolites. The application of tandem MS molecular networking revealed the presence of five bioavailable chlorogenic acid derivatives in urine previously not reported, including both quinic acid lactone and dimethoxy caffeoyl esters. Selected cinnamic acids were quantified in urine.     

An algorithm for data processing in neutron activation analysis

An algorithm for processing NAA data is described. Input data are the output data from a multichannel pulse-height analyzer with a microprocessor. This algorithm permits to calculate the concentrations of the analyzed elements (using a standard or a standard curve), the error of concentrations in the analysis of one or several parallel samples and the sensitivity of the analysis according to Currie's criteria in counts, g and g/g. Some other intermediate data (e.g. corrected net area of the peaks, parameters of the standard curve) may have individual importance in differenct cases.     

Top-Down Proteomics and Direct Surface Sampling of Neonatal Dried Blood Spots: Diagnosis of Unknown Hemoglobin Variants

We have previously shown that liquid microjunction surface sampling of dried blood spots coupled with high resolution top-down mass spectrometry may be used for screening of common hemoglobin variants HbS, HbC, and HbD. In order to test the robustness of the approach, we have applied the approach to unknown hemoglobin variants. Six neonatal dried blood spot samples that had been identified as variants, but which could not be diagnosed by current screening methods, were analyzed by direct surface sampling top-down mass spectrometry. Both collision-induced dissociation and electron transfer dissociation mass spectrometry were employed. Four of the samples were identified as ??-chain variants: two were heterozygous Hb D-Iran, one was heterozygous Hb Headington, and one was heterozygous Hb J-Baltimore. The fifth sample was identified as the ??-chain variant heterozygous Hb Phnom Penh. Analysis of the sixth sample suggested that it did not in fact contain a variant. Adoption of the approach in the clinic would require speed in both data collection and interpretation. To address that issue, we have compared manual data analysis with freely available data analysis software (ProsightPTM). The results demonstrate the power of top-down proteomics for hemoglobin variant analysis in newborn samples.     

Analysis of environmental samples by application of multivariate curve resolution on fused high-performance liquid chromatography-diode array detection mass spectrometry data

Multivariate curve resolution-alternating least squares (MCR-ALS) is applied to solve coelution problems in liquid chromatograpy with diode array detection (DAD) and mass spectrometry (MS). Fusion of DAD and MS detector signals improved results versus those obtained using only one of the two detector signals. Application of wavelet transform to MS data before its fusion with DAD data, further help to facilitate the resolution and quantitation of the coeluted compounds under study, besides a decrease of time of analysis. Mixtures of biocide compounds in standard mixtures and in environmental samples (sediment and wastewater samples) were analyzed with estimated quantitation errors below 12%.     

Simultaneous spectrofluorometric determination of piroxicam and pyridoxine using generalized rank annihilation method.

The application of generalized rank annihilation method (GRAM) to the analysis of fluorescence excitation-emission matrices of mixtures of piroxicam and pyridoxine is described. The input of GRAM consists of two bilinear data matrices, i.e. one for unknown and one for the calibration sample. The excitation wavelength range was from 290 to 340 nm and the emission was recorded from 370 to 560 nm. Piroxicam and pyridoxine were determined in the concentration ranges 0.33 - 4.00 microg ml(-1) and 0.66 - 8.00 microg ml(-1), respectively. To check the accuracy of the proposed method, several binary synthetic mixtures and one real sample were analyzed successfully. No matrix effect was observed in mixture analysis, so a single external calibration sample was used for each analyte. The ability of GRAM to quantify the studied compounds and the comparability of GRAM results were evaluated by comparing them with those of PLS regression as a standard first-order calibration.     

Simultaneous Carbohydrate Chromatography and Unsuppressed Ion Chromatography in Detecting Fruit Juices Adulteration

This paper is the first one investigating the simultaneous use of carbohydrate chromatography and ion chromatography to obtain in one run conclusive data on juice’s authenticity. A hybrid liquid chromatographic system with conductivity and differential refractive index detection, equipped with an Universal Cation 7u column for cation analysis and with a EC 250/4 Nucleodur 100-5 NH₂ RP column for carbohydrate analysis, was designed for this study. In less than 18 min, this configuration can separate simultaneously six cations (lithium, sodium, ammonium, potassium, magnesium and calcium) and four carbohydrates (fructose, glucose, saccharose and maltose). Commercial orange and apple juices obtained from the Romanian market were analyzed during this research.     

Fast GC for the analysis of fats and oils

Fast and conventional GC techniques were both applied to ten different lipidic matrices and the results then compared. The fats and oils were of fish, animal, and vegetable origin and were all simultaneously transesterified with acidic methanol before performing batch analysis of the fatty acid methyl esters (FAMEs) obtained. All FAMEs samples were consecutively analyzed three times by each method. The fast method significantly reduced the time required for analysis by a factor of 5 while maintaining a similar resolution. Furthermore, the reproducibility of relative quantitative data was measured on going from one method to the other. Peak identification was achieved through conventional GC‐MS in combination with linear retention index values contained in a home library and information derived from comprehensive 2D GC group patterns.     

The use of GC×GC/TOF MS with multivariate analysis for the characterization of foodborne pathogen bacteria profiles

The cellular fatty acid profiles of eight strains of Bacillus, Staphylococcus, and Enterobacteriacae (Escherichia coli and Salmonella) were analyzed by comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry. A novel template method was developed to standardize the raw two-dimensional gas chromatography retention data through the use of a chemical indexing mixture. Analyte retention coordinates were normalized in the primary dimension with respect to a series of n-alkanes (Kovats index) and in the secondary dimension with respect to a series of aromatic hydrocarbons (Lee index). Fatty acid profiles extracted from the templates were compared by multidimensional scaling and principal component analysis. Differences in the profiles of Gram-positive and Gram-negative bacteria were observed, and a series of heterogeneous mixtures comprising different fractions (containing one Gram-positive and one Gram-negative bacteria strain) were also distinguished from their homogeneous constituents.     

Characterization of atmospheric aerosol in Buenos Aires, Argentina

PM10 and PM2.5 samples were taken using a Gent sampler to characterize the atmospheric aerosol of Buenos Aires metropolitan area. A total of 114 samples were collected from October 2005 to October 2006 at one urban site, every third day, for 24 h. Samples were analyzed by neutron activation, and black carbon and mass concentration were determined. In both fractions, elemental and gravimetric mass concentrations were compared with historical data. Enrichment factors, backward trajectories and factor analysis were calculated. The attribution of pollution sources is discussed.     

Multivariate data analysis of some Finnish water courses

Summary The following parameters were analyzed 2 to 4 times a year from 37 sampling sites; T, O₂, O₂%, Turbidity, Suspended solids, Conductivity, Alkalinity, pH, Color, COD_Mn, Total nitrogen, Total phosphorus, Cl, Fe, Mn, Total sulphur, K, Na, Ca, Mg, SiO₂, Total organic chlorine and Total organic bromine. Samples were taken from waters loaded by chemical pulp mills, other industries, municipal waste waters and agriculture. Also waters under natural conditions were included. Water samples have been collected and analyzed in co-operation with the National Board of Waters and the Environment. The data set was analyzed by Principal Component Analysis (PCA) to determine correlations between variables, especially between Total organic chlorine and Total organic bromine and others. Typically Total organic chlorine and Total organic bromine correlated with Na, Cl and Total sulphur. It is interesting to note that Total organic chlorine and Total organic bromine did not follow each other in all components. Total organic chlorine was predicted using other variables and Partial Least Squares (PLS) method. Very satisfactory correlation was obtained between analyzed and predicted lgTOCl values. Optimally three different object classes were found from the whole data using fuzzy clustering analysis. One class represents waters in a natural condition, one water loaded mainly by agriculture and one represent the rest of the waters.     

Comparative study of HMX and CL-20

This study deals with a well-known monocyclic nitramine HMX and a relatively new polycyclic strained-cage nitramine CL-20. Experimental data on the powder morphology, simultaneous thermal analysis (STA) and burning rate of binary formulations Al/HMX and Al/CL-20 are presented. Kinetic modelling for HMX and CL-20 are considered based on analysis of STA data obtained for low heating rates. The processing of STA data by the Kissinger method was shown to need to be supplemented with the construction of a thermokinetic model. The thermal decomposition of HMX is reliably described by the reaction of the first order with the autocatalysis. Obtained kinetic parameters of the HMX thermal decomposition correlate with literature-known data on kinetics of the lead stage of HMX combustion. Two types of aluminium powder, i.e. micron-sized and ultrafine, are used to investigate the interaction with both nitramines. Thermal analysis revealed the higher Al oxidation ability of the solid compounds produced at CL-20 thermolysis, than that one of HMX. Burning rate experiments show the differences in the combustion parameters between CL-20- and HMX-based formulations, specifically along with the burn rate level increase for CL-20 monopropellant as compared to HMX one, the pressure exponent and effect of the aluminium particle size variation are also distinct. Results are analyzed and compared to available literature data.     

Trilinear PARAFAC decomposition of synchronous fluorescence spectra of mixtures of the major metabolites of acetylsalicylic acid

Mixtures of the three major metabolites of acetylsalicylic acid (salicylic, gentisic and salicyluric acid) were analyzed by synchronous molecular fluorescence spectroscopy. Three-way data matrices were generated by acquisition of spectra as a function of the pH (between 2 and 11) and of different relative concentrations of the three components. The PARAFAC trilinear model, without restrictions and using one factor per metabolite, was used in the data analysis. A full decomposition of the data matrices into the spectra, concentration and pH profiles was obtained. This result shows that molecular fluorescence spectroscopy can be used for the development of robust analytical methods for the simultaneous determination of the three major metabolites of acetylsalicylic acid in complex background samples.     

Water quality assessment of Toledo River and determination of metal concentrations by using SR-TXRF technique

The region of Toledo River, Paraná, Brazil is characterized by intense anthropogenic activities. Hence, metal concentrations and physical–chemical parameters of Toledo River water were determined in order to complete an environmental evaluation catalog. Samples were collected monthly during one year period at seven different sites from the source down the river mouth, physical–chemical variables were analyzed, and major metallic ions were measured. Metal analysis was performed by using the synchrotron radiation total reflection X-ray fluorescence technique. A statistical analysis was applied to evaluate the reliability of experimental data. The analysis of obtained results have shown that a strong correlation between physical–chemical parameters existed among sites 1 and 7, suggesting that organic pollutants were mainly responsible for decreasing the Toledo River water quality.     

Extension of AOAC Official Method 996.01 to the analysis of Standard Reference Material (SRM) 1846 and infant formulas.

There is currently no official method for the analysis of fatty acids (including trans fatty acids) in infant formulas. AOAC Official Method 996.01 for Fat Analysis in Cereal Products was extended to the analysis of milk-based infant formula Standard Reference Material (SRM)1846 to determine its applicability for use with infant formulas. Following the analysis of SRM 1846, 2 infant formulas, one milk-based liquid and one soy-based powdered infant formula, were analyzed for total fatty acid composition. Fatty acid methyl esters were prepared and analyzed by gas chromatography. The results of the analysis of SRM 1846 show that the mean analyzed values were highly reproducible as indicated by low coefficients of variation (CV). The CVs were <5% for the major fatty acids. Mean analyzed values for individual fatty acids in SRM 1846 were within +/- 1 standard deviation of the certificate values. The analyzed value for total fat as triglycerides (26.27 +/- 0.25%) agreed well with the certificate value (27.1 +/- 0.59%). Analyses of infant formulas showed that the concentrations of linoleic acid and fat meet the requirements for such formulas.     

Orthogonal array optimization of a multiresidue method for cereal herbicides in soils

Nearly 40 herbicides, commonly used for barley, were selected for analysis in soils of this crop. The primary objective was to develop a multiresidue method taking into account that herbicides belonged to different chemical families. Some preliminary experiments with different solvents in combination with water, acetic acid and ammonium hydroxide, were developed in order to design the predefined region covered by the orthogonal array design used for optimization. Final extracts were splitted in two aliquots, one of them was directly analyzed by gas chromatography-mass spectrometry (GC-MS), and the other one was derivatized before the acidic analyte analysis. Principal component analysis (PCA) was applied to the data generated in the preliminary experiments, in order to clarify the relationships among the different variables studied. According to the obtained results, the following variables were selected: solvent type and ratio, amount of acetic acid and extraction time. The statistical analysis revealed that all the factors were significant being the most important, the type and ratio of solvent for basic and neutral herbicides and the acetic acid percentage for acid herbicides. The final optimized method consisted of shaking previously wet soil samples for 30 min with 30 ml of acetone acidified with 1% acetic acid. Method validation was evaluated following the EU guidelines.     

Application of principal component analysis to the extraction of pure mass spectra in chemical analysis by gas chromatography/mass spectrometry

In this work, we investigated the possibility of the purification of mass spectra of coeluted substances containing at least one characteristic value of m/z using principal component analysis. Simulated and real gas chromatographic/mass spectrometric data were analyzed. For the simulated data, the resolution of the chromatographic peaks varied from 0.075 to 0.75, and the ratio of component concentrations ranged from 0.01 to 100. Noise-free simulated data and simulated data with randomly distributed noise were considered. It was shown that the method gave satisfactory results even when the chromatographic resolution (R _s ) was less than 0.05.     

Simple method for identification of skeletons of aporphine alkaloids from 13C NMR data using artificial neural networks

This paper describes the use of artificial neural networks as a theoretical tool in the structural determination of alkaloids from (13)C NMR chemical shift data, aiming to identify skeletal types of those compounds. For that, 162 aporphine alkaloids belonging to 12 different skeletons were codified with their respective (13)C NMR chemical shifts. Each skeleton pertaining to aporphine alkaloid type was used as output, and the (13)C NMR chemical shifts were used as input data of the net. Analyzing the obtained results, one can then affirm the skeleton to which each one of these compounds belongs with high degree of confidence (over 97%). The relation between the correlation coefficient and the number of epochs and the architecture of net (3-layer MLP or 4-layer MLP) were analyzed, too. The analysis showed that the results predicted by the 3-layer MLP networks trained with a number of the epochs higher than 900 epochs are the best ones. The artificial neural nets were shown to be a simple and efficient tool to solve structural elucidation problems making use of (13)C NMR chemical shift data, even when a similarity between the searched skeletons occurs, offering fast and accurate results to identification of skeletons of organic compounds.     

Application of fission track technique for estimation of uranium concentration in drinking waters of Punjab

Drinking water samples were collected from four different districts, namely Bhatinda, Mansa, Faridkot and Firozpur, of Punjab for ascertaining the U(nat.) concentrations. All samples were preserved, processed and analyzed by laser fluorimetry (LF). To ensure accuracy of the data obtained by LF, few samples (10 nos) from each district were analyzed by alpha spectrometry as well as by fission track analysis (FTA) technique. For FTA technique few μl of water sample was transferred to polythene tube, lexan detector was immersed in it and the other end of the tube was also heat-sealed. Two samples and one uranium standard were irradiated in DHRUVA reactor. Irradiated detectors were chemically etched and tracks counted using an optical microscope. Uranium concentrations in samples ranged from 3.2 to 60.5 ppb and were comparable with those observed by LF.