967 resultados para Quantification


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Erosão dos solos em Cabo Verde: estudo dos processos e quantificação à escala de três bacias hidrográficas O arquipélago de Cabo Verde é constituído por 10 ilhas vulcânicas pertence à zona do Sahel que se estende do Atlântico ao Mar Vermelho. Desde então, várias décadas, Cabo Verde é afectado pela desertificação causada principalmente pela recessão climatica e a erosão do solo. Esses fatores, aliados à alta pressão humana sobre os recursos, a topografia acidentada e chuvas tropicais por vezes torrenciais, causam sérios danos aos solos. No entanto, desde sua independência em 1975, o Governo realizou um amplo programa de arborização, recuperação de áreas degradadas e a correcção dos leitos das ribeiras. No entanto, a investigação, muito pouco foi realizada para avaliar as acções de protecção e conservação do solo e da água. Portanto, não há dados sobre o problema da degradação das terras nem balanços. Como parte deste trabalho, foram estudados vários factores que controlam a erosão do solo pela água. Especificamente, buscou-se diferenciar os efeitos das actividades humanas, incluindo a agricultura, os factores climáticos, como chuva e geração de escoamento. Também estabeleceu os primeiros balanços das exportações de matérias em suspensão e em solução no contexto do arquipélago de Cabo Verde. O estudo foi realizado em três bacias hidrográficas da ilha de Santiago, Cabo Verde. Estas três bacias hidrográficas (Longueira, Grande e Godim) estão localizadas na parte central da ilha de Santiago e representam os diversos tipos de uso da terra e as diferentes zonas bioclimaticas da ilha. Existe um gradiente climático entre as três bacias hidrográficas. Na verdade, Longueira que abrange uma área de 4,18 km2, tem um declive médio de 47 %, uma zona florestada de 69% e uma área agrícola de 17 %. Grande com uma área de 1,87 km2, é localizada numa zona sub humida com um declive médio de 50%, é essencialmente agrícola. Godim, com uma área de 2,0 km2, é localizado numa zona semi-árida com um declive médio de 32%, é particularmente uma zona agricola. Para estes três bacias hidrográficas, as cheias foram medidas e amostradas de 2004 a 2009. A bacia de Longueira teve um maior acompanhamento, nomeadamente em termos de amostragem e monitoramento dos escoamentos. Em cada amostra foram feitas a determinação da concentração de matérias em suspensão e a análise dos principais elementos quimicos. Os resultados mostram que a erosão mecânica nas três bacias hidrográficas é caracterizada por uma forte variabilidade espacial e temporal. Durante o período de 2005-2009, o balanço anual média para as bacias hidrográficas de Longueira, Grande e Godim é: 4266, 157 e 10,1 t.km2.an-1, respectivamente. A estação das chuvas de 2006 foi a mais erosiva para as três bacias, particularmente em Longueira, com 2 cheias excepcionais, que têm gerado uma concentração média de sólidos em suspensão superior a 100 g / l. Porém, as estações do ano de 2005 e 2008 foram de uma forma geral menos erosivas porque as concentrações médias não inferiores a 20 g / l. Além disso, não houve cheias para as temporadas 2005 e 2007 para a bacia do Godim. Na bacia de Longueira, o estudo dos fenómenos de histerese na caracterização das cheias mostrou que a evolução temporal das exportações de sólidos em suspensão durante a temporada é fortemente influenciada pelas atividades agrícolas. Na verdade, a primeira cheia causou uma exportação maciça de sedimento disponível e localizado no leito da ribeira. Assim, a segunda cheia exportou menos sedimentos. Um mês após as primeiras chuvas, a prática da monda que reduz a densidade da cobertura vegetal e destructura a camada superficial do solo, gerou uma grande quantidade de sedimento que novamente permitiu uma exportação muito forte de sedimentos durante a terceira forte cheia. Os resultados da erosão química na bacia de Longueira indicam que a taxa de erosão é de 45 t.km2.an-1 com uma forte variabilidade temporal. Na verdade, as temporadas de 2006 e 2007 são as mais erosivas, enquanto 2005 teve uma exportação de matérias disolvidas baixa. A utilização do modelo EMMA (End- Members Mixing Analysis) mostra que os escoamentos hipodermico e profundo, alimentandos os fluxos de elementos dissolvidos são os principais factores da erosão química. É mostrado que esses fluxos causam mais de 90% dos fluxos de erosão química. O escoamento superficial, que contribui com cerca de 70% na formação das cheias, é o maior factor da erosão mecânica do solo.

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A previous study has shown the possibility to identify methane (CH4 ) using headspace-GC-MS and quantify it with a stable isotope as internal standard. The main drawback of the GC-MS methods discussed in literature for CH4 measurement is the absence of a specific internal standard necessary to perform quantification. However, it becomes essential to develop a safer method to limit the manipulation of gaseous CH4 and to precisely control the injected amount of gas for spiking and calibration by comparison with external calibration. To avoid the manipulation of a stable isotope-labeled gas, we have chosen to generate a labeled gas as an internal standard in a vial on the basis of the formation of CH4 by the reaction of Grignard reagent methylmagnesium chloride with deuterated water. This method allows precise measurement of CH4 concentrations in gaseous sample as well as in a solid or a liquid sample after a thermodesorption step in a headspace vial. A full accuracy profile validation of this method is then presented.

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The only currently available method to measure brain glycogen in vivo is 13C NMR spectroscopy. Incorporation of 13C-labeled glucose (Glc) is necessary to allow glycogen measurement, but might be affected by turnover changes. Our aim was to measure glycogen absolute concentration in the rat brain by eliminating label turnover as variable. The approach is based on establishing an increased, constant 13C isotopic enrichment (IE). 13C-Glc infusion is then performed at the IE of brain glycogen. As glycogen IE cannot be assessed in vivo, we validated that it can be inferred from that of N-acetyl-aspartate IE in vivo: After [1-13C]-Glc ingestion, glycogen IE was 2.2 +/- 0.1 fold that of N-acetyl-aspartate (n = 11, R(2) = 0.77). After subsequent Glc infusion, glycogen IE equaled brain Glc IE (n = 6, paired t-test, p = 0.37), implying isotopic steady-state achievement and complete turnover of the glycogen molecule. Glycogen concentration measured in vivo by 13C NMR (mean +/- SD: 5.8 +/- 0.7 micromol/g) was in excellent agreement with that in vitro (6.4 +/- 0.6 micromol/g, n = 5). When insulin was administered, the stability of glycogen concentration was analogous to previous biochemical measurements implying that glycogen turnover is activated by insulin. We conclude that the entire glycogen molecule is turned over and that insulin activates glycogen turnover.

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The urinary steroid profile is constituted by anabolic androgenic steroids, including testosterone and its relatives, that are extensively metabolized into phase II sulfated or glucuronidated steroids. The use of liquid chromatography coupled to mass spectrometry (LC-MS) is an issue for the direct analysis of conjugated steroids, which can be used as urinary markers of exogenous steroid administration in doping analysis, without hydrolysis of the conjugated moiety. In this study, a sensitive and selective ultra high-pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometer (UHPLC-QTOF-MS) method was developed to quantify major urinary metabolites simultaneously after testosterone intake. The sample preparation of the urine (1 mL) was performed by solid-phase extraction on Oasis HLB sorbent using a 96-well plate format. The conjugated steroids were analyzed by UHPLC-QTOF-MS(E) with a single-gradient elution of 36 min (including re-equilibration time) in the negative electrospray ionization mode. MS(E) analysis involved parallel alternating acquisitions of both low- and high-collision energy functions. The method was validated and applied to samples collected from a clinical study performed with a group of healthy human volunteers who had taken testosterone, which were compared with samples from a placebo group. Quantitative results were also compared to GC-MS and LC-MS/MS measurements, and the correlations between data were found appropriate. The acquisition of full mass spectra over the entire mass range with QTOF mass analyzers gives promise of the opportunity to extend the steroid profile to a higher number of conjugated steroids.

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Résumé La protéomique basée sur la spectrométrie de masse est l'étude du proteome l'ensemble des protéines exprimées au sein d'une cellule, d'un tissu ou d'un organisme - par cette technique. Les protéines sont coupées à l'aide d'enzymes en plus petits morceaux -les peptides -, et, séparées par différentes techniques. Les différentes fractions contenant quelques centaines de peptides sont ensuite analysées dans un spectromètre de masse. La masse des peptides est enregistrée et chaque peptide est séquentiellement fragmenté pour en obtenir sa séquence. L'information de masse et séquence est ensuite comparée à une base de données de protéines afin d'identifier la protéine d'origine. Dans une première partie, la thèse décrit le développement de méthodes d'identification. Elle montre l'importance de l'enrichissement de protéines comme moyen d'accès à des protéines de moyenne à faible abondance dans le lait humain. Elle utilise des injections répétées pour augmenter la couverture en protéines et la confiance dans l'identification. L'impacte de nouvelle version de base de données sur la liste des protéines identifiées est aussi démontré. De plus, elle utilise avec succès la spectrométrie de masse comme alternative aux anticorps, pour valider la présence de 34 constructions de protéines pathogéniques du staphylocoque doré exprimées dans une souche de lactocoque. Dans une deuxième partie, la thèse décrit le développement de méthodes de quantification. Elle expose de nouvelles approches de marquage des terminus des protéines aux isotopes stables et décrit la première méthode de marquage des groupements carboxyliques au niveau protéine à l'aide de réactifs composé de carbone 13. De plus, une nouvelle méthode, appelée ANIBAL, marquant tous les groupements amines et carboxyliques au niveau de la protéine, est exposée. Summary Mass spectrometry-based proteomics is the study of the proteome -the set of all expressed proteins in a cell, tissue or organism -using mass spectrometry. Proteins are cut into smaller pieces - peptides - using proteolytic enzymes and separated using different separation techniques. The different fractions containing several hundreds of peptides are than analyzed by mass spectrometry. The mass of the peptides entering the instrument are recorded and each peptide is sequentially fragmented to obtain its amino acid sequence. Each peptide sequence with its corresponding mass is then searched against a protein database to identify the protein to which it belongs. This thesis presents new method developments in this field. In a first part, the thesis describes development of identification methods. It shows the importance of protein enrichment methods to gain access to medium-to-low abundant proteins in a human milk sample. It uses repeated injection to increase protein coverage and confidence in identification and demonstrates the impact of new database releases on protein identification lists. In addition, it successfully uses mass spectrometry as an alternative to antibody-based assays to validate the presence of 34 different recombinant constructs of Staphylococcus aureus pathogenic proteins expressed in a Lactococcus lactis strain. In a second part, development of quantification methods is described. It shows new stable isotope labeling approaches based on N- and C-terminus labeling of proteins and describes the first method of labeling of carboxylic groups at the protein level using 13C stable isotopes. In addition, a new quantitative approach called ANIBAL is explained that labels all amino and carboxylic groups at the protein level.

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Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. The paper considers a data driven approach in modelling uncertainty in spatial predictions. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic features and describe stochastic variability and non-uniqueness of spatial properties. It is able to capture and preserve key spatial dependencies such as connectivity, which is often difficult to achieve with two-point geostatistical models. Semi-supervised SVR is designed to integrate various kinds of conditioning data and learn dependences from them. A stochastic semi-supervised SVR model is integrated into a Bayesian framework to quantify uncertainty with multiple models fitted to dynamic observations. The developed approach is illustrated with a reservoir case study. The resulting probabilistic production forecasts are described by uncertainty envelopes.

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We have recently shown that at isotopic steady state (13)C NMR can provide a direct measurement of glycogen concentration changes, but that the turnover of glycogen was not accessible with this protocol. The aim of the present study was to design, implement and apply a novel dual-tracer infusion protocol to simultaneously measure glycogen concentration and turnover. After reaching isotopic steady state for glycogen C1 using [1-(13)C] glucose administration, [1,6-(13)C(2)] glucose was infused such that isotopic steady state was maintained at the C1 position, but the C6 position reflected (13)C label incorporation. To overcome the large chemical shift displacement error between the C1 and C6 resonances of glycogen, we implemented 2D gradient based localization using the Fourier series window approach, in conjunction with time-domain analysis of the resulting FIDs using jMRUI. The glycogen concentration of 5.1 +/- 1.6 mM measured from the C1 position was in excellent agreement with concomitant biochemical determinations. Glycogen turnover measured from the rate of label incorporation into the C6 position of glycogen in the alpha-chloralose anesthetized rat was 0.7 micromol/g/h.

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Normal ageing is associated with characteristic changes in brain microstructure. Although in vivo neuroimaging captures spatial and temporal patterns of age-related changes of anatomy at the macroscopic scale, our knowledge of the underlying (patho)physiological processes at cellular and molecular levels is still limited. The aim of this study is to explore brain tissue properties in normal ageing using quantitative magnetic resonance imaging (MRI) alongside conventional morphological assessment. Using a whole-brain approach in a cohort of 26 adults, aged 18-85years, we performed voxel-based morphometric (VBM) analysis and voxel-based quantification (VBQ) of diffusion tensor, magnetization transfer (MT), R1, and R2* relaxation parameters. We found age-related reductions in cortical and subcortical grey matter volume paralleled by changes in fractional anisotropy (FA), mean diffusivity (MD), MT and R2*. The latter were regionally specific depending on their differential sensitivity to microscopic tissue properties. VBQ of white matter revealed distinct anatomical patterns of age-related change in microstructure. Widespread and profound reduction in MT contrasted with local FA decreases paralleled by MD increases. R1 reductions and R2* increases were observed to a smaller extent in overlapping occipito-parietal white matter regions. We interpret our findings, based on current biophysical models, as a fingerprint of age-dependent brain atrophy and underlying microstructural changes in myelin, iron deposits and water. The VBQ approach we present allows for systematic unbiased exploration of the interaction between imaging parameters and extends current methods for detection of neurodegenerative processes in the brain. The demonstrated parameter-specific distribution patterns offer insights into age-related brain structure changes in vivo and provide essential baseline data for studying disease against a background of healthy ageing.

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The presence of human adenoviruses in recreational water might cause disease in the population upon exposure. Human adenoviruses detected by PCR could also serve as indicators of the virological water quality. In order to assess the applicability of human adenoviruses to the evaluation of the faecal contamination in European bathing waters, a real-time quantitative PCR assay was developed for the quantification of human adenoviruses in 132 samples collected from 24 different recreational marine and freshwater sites in nine European countries.Selected samples presenting positive nested-PCR results for human adenoviruses were analyzed using quantitative PCR and 80 samples from a total of 132 produced quantitative results with mean values of 3.2x102 10 per 100 ml of water, human adenovirus 41 being the most prevalent serotype. Human adenoviruses were quantified in samples from all 15 surveillance laboratories. Statistical analysis showed no homogeneous linear relation between humanadenoviruses and E. coli, intestinal enterococci or somatic coliphages concentrations in the tested samples when considering all the data together. Significant correlations between human adenoviruses and at least one of the other indicators were observed only when data from individual Laboratories were considered. The quantification of human adenoviruses may provide complementary information in relation to the use of bacterial standards in the control of water quality in bathing water.

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In groundwater applications, Monte Carlo methods are employed to model the uncertainty on geological parameters. However, their brute-force application becomes computationally prohibitive for highly detailed geological descriptions, complex physical processes, and a large number of realizations. The Distance Kernel Method (DKM) overcomes this issue by clustering the realizations in a multidimensional space based on the flow responses obtained by means of an approximate (computationally cheaper) model; then, the uncertainty is estimated from the exact responses that are computed only for one representative realization per cluster (the medoid). Usually, DKM is employed to decrease the size of the sample of realizations that are considered to estimate the uncertainty. We propose to use the information from the approximate responses for uncertainty quantification. The subset of exact solutions provided by DKM is then employed to construct an error model and correct the potential bias of the approximate model. Two error models are devised that both employ the difference between approximate and exact medoid solutions, but differ in the way medoid errors are interpolated to correct the whole set of realizations. The Local Error Model rests upon the clustering defined by DKM and can be seen as a natural way to account for intra-cluster variability; the Global Error Model employs a linear interpolation of all medoid errors regardless of the cluster to which the single realization belongs. These error models are evaluated for an idealized pollution problem in which the uncertainty of the breakthrough curve needs to be estimated. For this numerical test case, we demonstrate that the error models improve the uncertainty quantification provided by the DKM algorithm and are effective in correcting the bias of the estimate computed solely from the MsFV results. The framework presented here is not specific to the methods considered and can be applied to other combinations of approximate models and techniques to select a subset of realizations

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Short-TE MRS has been proposed recently as a method for the in vivo detection and quantification of γ-aminobutyric acid (GABA) in the human brain at 3 T. In this study, we investigated the accuracy and reproducibility of short-TE MRS measurements of GABA at 3 T using both simulations and experiments. LCModel analysis was performed on a large number of simulated spectra with known metabolite input concentrations. Simulated spectra were generated using a range of spectral linewidths and signal-to-noise ratios to investigate the effect of varying experimental conditions, and analyses were performed using two different baseline models to investigate the effect of an inaccurate baseline model on GABA quantification. The results of these analyses indicated that, under experimental conditions corresponding to those typically observed in the occipital cortex, GABA concentration estimates are reproducible (mean reproducibility error, <20%), even when an incorrect baseline model is used. However, simulations indicate that the accuracy of GABA concentration estimates depends strongly on the experimental conditions (linewidth and signal-to-noise ratio). In addition to simulations, in vivo GABA measurements were performed using both spectral editing and short-TE MRS in the occipital cortex of 14 healthy volunteers. Short-TE MRS measurements of GABA exhibited a significant positive correlation with edited GABA measurements (R = 0.58, p < 0.05), suggesting that short-TE measurements of GABA correspond well with measurements made using spectral editing techniques. Finally, within-session reproducibility was assessed in the same 14 subjects using four consecutive short-TE GABA measurements in the occipital cortex. Across all subjects, the average coefficient of variation of these four GABA measurements was 8.7 ± 4.9%. This study demonstrates that, under some experimental conditions, short-TE MRS can be employed for the reproducible detection of GABA at 3 T, but that the technique should be used with caution, as the results are dependent on the experimental conditions. Copyright © 2013 John Wiley & Sons, Ltd.

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Sophisticated magnetic resonance tagging techniques provide powerful tools for the non-invasive assessment of the local heartwall motion towards a deeper fundamental understanding of local heart function. For the extraction of motion data from the time series of magnetic resonance tagged images and for the visualization of the local heartwall motion a new image analysis procedure has been developed. New parameters have been derived which allows quantification of the motion patterns and are highly sensitive to any changes in these patterns. The new procedure has been applied for heart motion analysis in healthy volunteers and in patient collectives with different heart diseases. The achieved results are summarized and discussed.