956 resultados para Multi-dimensional gas chromatography


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For inviscid fluid flow in any n-dimensional Riemannian manifold, new conserved vorticity integrals generalizing helicity, enstrophy, and entropy circulation are derived for lower-dimensional surfaces that move along fluid streamlines. Conditions are determined for which the integrals yield constants of motion for the fluid. In the case when an inviscid fluid is isentropic, these new constants of motion generalize Kelvin’s circulation theorem from closed loops to closed surfaces of any dimension.

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As Terabyte datasets become the norm, the focus has shifted away from our ability to produce and store ever larger amounts of data, onto its utilization. It is becoming increasingly difficult to gain meaningful insights into the data produced. Also many forms of the data we are currently producing cannot easily fit into traditional visualization methods. This paper presents a new and novel visualization technique based on the concept of a Data Forest. Our Data Forest has been designed to be used with vir tual reality (VR) as its presentation method. VR is a natural medium for investigating large datasets. Our approach can easily be adapted to be used in a variety of different ways, from a stand alone single user environment to large multi-user collaborative environments. A test application is presented using multi-dimensional data to demonstrate the concepts involved.

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A method for the determination of volatile organic compounds (VOCs) in recycled polyethylene terephthalate and high-density polyethylene using headspace sampling by solid-phase microextraction and gas chromatography coupled to mass spectrometry detection is presented. This method was used to evaluate the efficiency of cleaning processes for VOC removal from recycled PET. In addition, the method was also employed to evaluate the level of VOC contamination in multilayer packaging material containing recycled HDPE material. The optimisation of the extraction procedure for volatile compounds was performed and the best extraction conditions were found using a 75 mu m carboxen-polydimethylsiloxane (CAR-PDMS) fibre for 20 min at 60 degrees C. The validation parameters for the established method were linear range, linearity, sensitivity, precision (repeatability), accuracy (recovery) and detection and quantification limits. The results indicated that the method could easily be used in quality control for the production of recycled PET and HDPE. (C) 2011 Elsevier B.V. All rights reserved.

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An analytical procedure for the separation and quantification of ethyl acetate, ethyl butyrate, ethyl hexanoate, ethyl lactate, ethyl octanoate, ethyl nonanoate, ethyl decanoate, isoamyl octanoate, and ethyl laurate in cachaca, rum, and whisky by direct injection gas chromatography-mass spectrometry was developed. The analytical method is simple, selective, and appropriated for the determination of esters in distilled spirits. The limit of detection ranged from 29 (ethyl hexanoate) to 530 (ethyl acetate) mu g L-1, whereas the standard deviation for repeatability was between 0.774% (ethyl hexanoate) and 5.05% (isoamyl octanoate). Relative standard deviation values for accuracy vary from 90.3 to 98.5% for ethyl butyrate and ethyl acetate, respectively. Ethyl acetate was shown to be the major ester in cachaca (median content of 22.6 mg 100 mL(-1) anhydrous alcohol), followed by ethyl lactate (median content of 8.32 mg 100 mL(-1) anhydrous alcohol). Cachaca produced in copper and hybrid alembic present a higher content of ethyl acetate and ethyl lactate than those produced in a stainless-steel column, whereas cachaca produced by distillation in a stainless-steel column present a higher content of ethyl octanoate, ethyl decanoate, and ethyl laurate. As expected, ethyl acetate is the major ester in whiskey and rum, followed by ethyl lactate for samples of rum. Nevertheless, whiskey samples exhibit ethyl lactate at contents lower or at the same order of magnitude of the fatty esters.

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This article presents a method employing stir bar sorptive extraction (SBSE) with in situ derivatization, in combination with either thermal or liquid desorption on-line coupled to gas chromatography-mass spectrometry for the analysis of fluoxetine in plasma samples. Ethyl chloroformate was employed as derivatizing agent producing symmetrical peaks. Parameters such as solvent polarity, time for analyte desorption, and extraction time, were evaluated. During the validation process, the developed method presented specificity, linearity (R-2 > 0.99), precision (R.S.D. < 15%), and limits of quantification (LOQ) of 30 and 1.37 pg mL(-1), when liquid and thermal desorption were employed, respectively. This simple and highly sensitive method showed to be adequate for the measurement-of fluoxetine in typical and trace concentration levels. (c) 2008 Elsevier B.V. All rights reserved.

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A method for the determination of pesticide residues in water and sediment was developed using the QuEChERS method followed by gas chromatography - mass spectrometry. The method was validated in terms of accuracy, specificity, linearity, detection and quantification limits. The recovery percentages obtained for the pesticides in water at different concentrations ranged from 63 to 116%, with relative standard deviations below 12%. The corresponding results from the sediment ranged from 48 to 115% with relative standard deviations below 16%. The limits of detection for the pesticides in water and sediment were below 0.003 mg L(-1) and 0.02 mg kg(-1), respectively.

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Allergicasthmarepresentsanimportantpublichealthissuewithsignificantgrowthovertheyears,especially in the paediatric population. Exhaled breath is a non-invasive, easily performed and rapid method forobtainingsamplesfromthelowerrespiratorytract.Inthepresentmanuscript,themetabolicvolatile profiles of allergic asthma and control children were evaluated by headspace solid-phase microextraction combined with gas chromatography–quadrupole mass spectrometry (HS-SPME/GC–qMS). The lack ofstudiesinbreathofallergicasthmaticchildrenbyHS-SPMEledtothedevelopmentofanexperimental design to optimize SPME parameters. To fulfil this objective, three important HS-SPME experimental parameters that influence the extraction efficiency, namely fibre coating, temperature and time extractions were considered. The selected conditions that promoted higher extraction efficiency corresponding to the higher GC peak areas and number of compounds were: DVB/CAR/PDMS coating fibre, 22◦C and 60min as the extraction temperature and time, respectively. The suitability of two containers, 1L Tedlar® bags and BIOVOC®, for breath collection and intra-individual variability were also investigated. The developed methodology was then applied to the analysis of children exhaled breath with allergicasthma(35),fromwhich13hadalsoallergicrhinitis,andhealthycontrolchildren(15),allowing to identify 44 volatiles distributed over the chemical families of alkanes (linear and ramified) ketones, aromatic hydrocarbons, aldehydes, acids, among others. Multivariate studies were performed by Partial LeastSquares–DiscriminantAnalysis(PLS–DA)usingasetof28selectedmetabolitesanddiscrimination between allergic asthma and control children was attained with a classification rate of 88%. The allergic asthma paediatric population was characterized mainly by the compounds linked to oxidative stress, such as alkanes and aldehydes. Furthermore, more detailed information was achieved combining the volatile metabolic data, suggested by PLS–DA model, and clinical data.

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BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of cancer are of great interest for early cancer detection. Urine is potentially a rich source of volatile organic metabolites (VOMs) that can be used as potential cancer biomarkers. Our aim was to develop a generally reliable, rapid, sensitive, and robust analytical method for screening large numbers of urine samples, resulting in a broad spectrum of native VOMs, as a tool to evaluate the potential of these metabolites in the early diagnosis of cancer. METHODS: To investigate urinary volatile metabolites as potential cancer biomarkers, urine samples from 33 cancer patients (oncological group: 14 leukaemia, 12 colorectal and 7 lymphoma) and 21 healthy (control group, cancer-free) individuals were qualitatively and quantitatively analysed. Dynamic solid-phase microextraction in headspace mode (dHS-SPME) using a carboxenpolydimethylsiloxane (CAR/PDMS) sorbent in combination with GC-qMS-based metabolomics was applied to isolate and identify the volatile metabolites. This method provides a potential non-invasive method for early cancer diagnosis as a first approach. To fulfil this objective, three important dHS-SPME experimental parameters that influence extraction efficiency (fibre coating, extraction time and temperature of sampling) were optimised using a univariate optimisation design. The highest extraction efficiency was obtained when sampling was performed at 501C for 60min using samples with high ionic strengths (17% sodium chloride, wv 1) and under agitation. RESULTS: A total of 82 volatile metabolites belonging to distinct chemical classes were identified in the control and oncological groups. Benzene derivatives, terpenoids and phenols were the most common classes for the oncological group, whereas ketones and sulphur compounds were the main classes that were isolated from the urine headspace of healthy subjects. The results demonstrate that compound concentrations were dramatically different between cancer patients and healthy volunteers. The positive rates of 16 patients among the 82 identified were found to be statistically different (Po0.05). A significant increase in the peak area of 2-methyl3-phenyl-2-propenal, p-cymene, anisole, 4-methyl-phenol and 1,2-dihydro-1,1,6-trimethyl-naphthalene in cancer patients was observed. On average, statistically significant lower abundances of dimethyl disulphide were found in cancer patients. CONCLUSIONS: Gas chromatographic peak areas were submitted to multivariate analysis (principal component analysis and supervised linear discriminant analysis) to visualise clusters within cases and to detect the volatile metabolites that are able to differentiate cancer patients from healthy individuals. Very good discrimination within cancer groups and between cancer and control groups was achieved.

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In this study the effect of the cultivar on the volatile profile of five different banana varieties was evaluated and determined by dynamic headspace solid-phase microextraction (dHS-SPME) combined with one-dimensional gas chromatography–mass spectrometry (1D-GC–qMS). This approach allowed the definition of a volatile metabolite profile to each banana variety and can be used as pertinent criteria of differentiation. The investigated banana varieties (Dwarf Cavendish, Prata, Maçã, Ouro and Platano) have certified botanical origin and belong to the Musaceae family, the most common genomic group cultivated in Madeira Island (Portugal). The influence of dHS-SPME experimental factors, namely, fibre coating, extraction time and extraction temperature, on the equilibrium headspace analysis was investigated and optimised using univariate optimisation design. A total of 68 volatile organic metabolites (VOMs) were tentatively identified and used to profile the volatile composition in different banana cultivars, thus emphasising the sensitivity and applicability of SPME for establishment of the volatile metabolomic pattern of plant secondary metabolites. Ethyl esters were found to comprise the largest chemical class accounting 80.9%, 86.5%, 51.2%, 90.1% and 6.1% of total peak area for Dwarf Cavendish, Prata, Ouro, Maçã and Platano volatile fraction, respectively. Gas chromatographic peak areas were submitted to multivariate statistical analysis (principal component and stepwise linear discriminant analysis) in order to visualise clusters within samples and to detect the volatile metabolites able to differentiate banana cultivars. The application of the multivariate analysis on the VOMs data set resulted in predictive abilities of 90% as evaluated by the cross-validation procedure.

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Dynamic headspace solid-phase microextraction (HS-SPME) followed by thermal desorption gas chromatography-quadrupole mass spectrometry analysis (GC-qMS), was used to investigate the aroma profile of different species of passion fruit samples. The performance of five commercially available SPME fibres: 65 μm polydimethylsiloxane/divinylbenzene, PDMS/DVB; 100 μm polydimethylsiloxane, PDMS; 85 μm polyacrylate, PA; 50/30 μm divinylbenzene/carboxen on polydimethylsiloxane, DVB/CAR/PDMS (StableFlex); and 75 μm carboxen/polydimethylsiloxane, CAR/PDMS; was evaluated and compared. Several extraction times and temperature conditions were also tested to achieve optimum recovery. The SPME fibre coated with 65 μm PDMS/DVB afforded the highest extraction efficiency, when the samples were extracted at 50 °C for 40 min with a constant stirring velocity of 750 rpm, after saturating the sample with NaCl (17%, w/v — 0.2 g). A comparison among different passion fruit species has been established in terms of qualitative and semi-quantitative differences in volatile composition. By using the optimal extraction conditions and GC-qMS it was possible to tentatively identify seventy one different compounds in Passiflora species: 51 volatiles in Passiflora edulis Sims (purple passion fruit), 24 in P. edulis Sims f. flavicarpa (yellow passion fruit) and 21 compounds in Passiflora mollissima (banana passion fruit). It was found that the ethyl esters comprise the largest class of the passion fruit volatiles, including 82.8% in P. edulis variety, 77.4% in P. edulis Sims f. flavicarpa variety and 39.9% in P. mollissima. The semi-quantitative results were then submitted to principal component analysis (PCA) in order to establish relationships between the compounds and the different passion fruit species under investigation.

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In the present study we evaluated the precision of the ELISA method to quantify caffeine in human plasma and compared the results with those obtained by gas chromatography. A total of 58 samples were analyzed by gas chromatography using a nitrogen-phosphorus detector and routine techniques. For the ELISA test, the samples were diluted to obtain a concentration corresponding to 50% of the absorbance of the standard curve. To determine whether the proximity between the I50 of the standard curve and that of the sample would bring about a more precise result, the samples were divided into three blocks according to the criterion of difference, in modulus, of the I50 of the standard curve and of the I50 of the sample. The samples were classified into three groups. The first was composed of 20 samples with I50 up to 1.5 ng/ml, the second consisted of 21 samples with I50 ranging from 1.51 to 3 ng/ml, and the third of 17 samples with I50 ranging from 3.01 to 13 ng/ml. The determination coefficient (R² = 0.999) showed that the data obtained by gas chromatography represented a reliable basis. The results obtained by ELISA were also reliable, with an estimated Pearson correlation coefficient of 0.82 between the two methods. This coefficient for the different groups (0.88, 0.79 and 0.49 for groups 1, 2 and 3, respectively) showed greater reliability for the test with dilutions closer to I50.

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An analytical procedure using supercritical fluid extraction (SFE) and capillary gas chromatography with electron-capture detection was developed to determine simultaneously residues of different pesticides (organochlorine, organophosphorus, organonitrogen and pyrethroid) in honey samples. Fortification experiments were conducted to test conventional extraction (liquid-liquid) and optimize the extraction procedure in SFE by varying the CO2-modifier, temperature, extraction time and pressure. Best efficiency was achieved at 400 bar using acetonitrile as modifier at 90 degreesC. For the clean-up step, Florisil cartridges were used for both methods LLE and SFE. Recoveries for majority of pesticides from fortified samples of honey at fortification level of 0.01-0.10 mg/kg ranged 75-94% from both methods. Limits of detection found were less than 0.01 mg/kg for ECD and confirmation of pesticide identity was performed by gas chromatography-mass spectrometry in selected-ion monitoring mode. The multiresidue methods in real honey samples were applied and the results of developed methods were compared. (C) 2004 Elsevier B.V. All rights reserved.

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The applicability of supercritical fluid extraction (SFE) in pesticide multiresidue analysis (organohalogen, organonitrogen, organophosphorus, and pyrethroid) in soil samples was investigated. Fortification experiments were conducted to test the conventional extraction (solid-liquid) and to optimize the extraction procedure in SFE by varying the CO2 Modifier, temperature, extraction time, and pressure. The best efficiency was achieved at 400 bar using methanol as modifier at 60 degreesC. For the SFE method, C-18 cartridges were used for the cleanup. The analytical screening was performed by gas chromatography equipped with electron-capture detection (ECD). Recoveries for the majority of pesticides from spiked samples of soil at different residence times were 1, 20, and 40 days at the fortification level of 0.04-0.10 mg/kg ranging from 70 to 97% for both methods. The detection limits found were <0.01 mg/kg for ECD, and the confirmation of pesticide identity was performed by gas chromatography-mass spectrometry in a selected-ion monitoring mode. Multiresidue methods were applied in real soil samples, and the results of the methods developed were compared.