Quantification of glucuronidated and sulfated steroids in human urine by ultra-high pressure liquid chromatography quadrupole time-of-flight mass spectrometry.

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.

Identification and quantification techniques in mass spectrometry-based proteomics

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.

Uncertainty Quantification with Support Vector Regression Prediction Models

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.

Quantification of brain glycogen concentration and turnover through localized 13C NMR of both the C1 and C6 resonances.

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.

Classification of acid sulphate soils of Finland according to Soil Taxonomy and the FAO/Unesco legend

Selostus: Suomen happamien sulfaattimaiden kansainvälinen luokittelu

Regional specificity of MRI contrast parameter changes in normal ageing revealed by voxel-based quantification (VBQ).

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.

Quantification of human adenoviruses in European recreational waters

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.

Local and global error models to improve uncertainty quantification

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

Unedited in vivo detection and quantification of γ-aminobutyric acid in the occipital cortex using short-TE MRS at 3 T.

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.

Quantification of the local heartwall motion by magnetic resonance myocardial tagging.

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.

Simultaneous quantification of selective serotonin reuptake inhibitors and metabolites in human plasma by liquid chromatography-electrospray mass spectrometry for therapeutic drug monitoring.

A simple and sensitive liquid chromatography-electrospray ionization mass spectrometry method was developed for the simultaneous quantification in human plasma of all selective serotonin reuptake inhibitors (citalopram, fluoxetine, fluvoxamine, paroxetine and sertraline) and their main active metabolites (desmethyl-citalopram and norfluoxetine). A stable isotope-labeled internal standard was used for each analyte to compensate for the global method variability, including extraction and ionization variations. After sample (250μl) pre-treatment with acetonitrile (500μl) to precipitate proteins, a fast solid-phase extraction procedure was performed using mixed mode Oasis MCX 96-well plate. Chromatographic separation was achieved in less than 9.0min on a XBridge C18 column (2.1×100mm; 3.5μm) using a gradient of ammonium acetate (pH 8.1; 50mM) and acetonitrile as mobile phase at a flow rate of 0.3ml/min. The method was fully validated according to Société Française des Sciences et Techniques Pharmaceutiques protocols and the latest Food and Drug Administration guidelines. Six point calibration curves were used to cover a large concentration range of 1-500ng/ml for citalopram, desmethyl-citalopram, paroxetine and sertraline, 1-1000ng/ml for fluoxetine and fluvoxamine, and 2-1000ng/ml for norfluoxetine. Good quantitative performances were achieved in terms of trueness (84.2-109.6%), repeatability (0.9-14.6%) and intermediate precision (1.8-18.0%) in the entire assay range including the lower limit of quantification. Internal standard-normalized matrix effects were lower than 13%. The accuracy profiles (total error) were mainly included in the acceptance limits of ±30% for biological samples. The method was successfully applied for routine therapeutic drug monitoring of more than 1600 patient plasma samples over 9 months. The β-expectation tolerance intervals determined during the validation phase were coherent with the results of quality control samples analyzed during routine use. This method is therefore precise and suitable both for therapeutic drug monitoring and pharmacokinetic studies in most clinical laboratories.

Spectroscopic quantification of soil phosphorus forms by 31p-nmr after nine years of organic or mineral fertilization

Long-standing applications of mineral fertilizers or types of organic wastes such as manure can cause phosphorus (P) accumulation and changes in the accumulated P forms in the soil. The objective of this research was to evaluate the forms of P accumulated in soils treated with mineral fertilizer or different types of manure in a long-term experiment. Soil was sampled from the 0-5 cm layer of plots fertilized with five different nutrient sources for nine years: 1) control without fertilizer; 2) mineral fertilizer at recommended rates for local conditions; 3) 5 t ha-1 year-1 of moist poultry litter; 4) 60 m³ ha-1 year-1 of liquid cattle manure and 5) 40 m³ ha-1 year-1 of liquid swine manure. The 31P-NMR spectra of soil extracts detected the following P compounds: orthophosphate, pyrophosphate, inositol phosphate, glycerophosphate, and DNA. The use of organic or mineral fertilizer over nine years did not change the soil P forms but influenced their concentration. Fertilization with mineral or organic fertilizers stimulated P accumulation in inorganic forms. Highest inositol phosphate levels were observed after fertilization with any kind of manure and highest organic P concentration in glycerophosphate form in after mineral or no fertilization.

Quantification of aluminium in soil of the Solimões Formation, Acre State, Brazil

The variety of soils in the State of Acre is wide and their chemical profiles are still not fully understood. The nature of the material of origin of these soils is indicated by the high aluminium (Al) content, commonly associated with high calcium (Ca) and magnesium (Mg) contents. The study objective was to use different methods to quantify Al in soils from toposequences formed from material of a sedimentary nature originating from the Solimões Formation, in Acre, Brazil. Trenches were opened at three distinct points in the landscape: shoulder, backslope and footslope positions. Soil samples were collected for physical, chemical, mineralogical analyses. The Al content was quantified using different methods. High Al contents were found in most of these horizons, associated with high Ca and Mg levels, representing the predominant cations in the sum of exchangeable bases. The mineralogy indicates that the soils are still in a low weathering phase, with the presence of significant quantities of 2:1 minerals. Similar Al contents were determined by the methods of NaOH titration, xylenol orange spectrometry and inductively coupled plasma optical emission spectrometry. However, no consistent data were obtained by the pyrocatechol violet method. Extraction with KCl overestimated the exchangeable Al content due to its ability to extract the non-exchangeable Al present in the smectite interlayers. It was observed that high Al contents are related to the instability of the hydroxyl-Al smectite interlayers.