965 resultados para carbon quantification methods


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Posaconazole (POS) is a new antifungal agent for prevention and therapy of mycoses in immunocompromised patients. Variable POS pharmacokinetics after oral dosing may influence efficacy: a trough threshold of 0.5 ?g/ml has been recently proposed. Measurement of POS plasma concentrations by complex chromatographic techniques may thus contribute to optimize prevention and management of life-threatening infections. No microbiological analytical method is available. The objective of this study was to develop and validate a new simplified ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) method and a sensitive bioassay for quantification of POS over the clinical plasma concentration range. The UPLC-MS/MS equipment consisted of a triple quadrupole mass spectrometer, an electrospray ionization (ESI) source, and a C(18) analytical column. The Candida albicans POS-hypersusceptible mutant (MIC of 0.002 ?g/ml) ?cdr1 ?cdr2 ?flu ?mdr1 ?can constructed by targeted deletion of multidrug efflux transporters and calcineurin genes was used for the bioassay. POS was extracted from plasma by protein precipitation with acetonitrile-methanol (75%/25%, vol/vol). Reproducible standard curves were obtained over the range 0.014 to 12 (UPLC-MS/MS) and 0.028 to 12 ?g/ml (bioassay). Intra- and interrun accuracy levels were 106% ± 2% and 103% ± 4% for UPLC-MS/MS and 102% ± 8% and 104% ± 1% for bioassay, respectively. The intra- and interrun coefficients of variation were 7% ± 4% and 7% ± 3% for UPLC-MS/MS and 5% ± 3% and 4% ± 2% for bioassay, respectively. An excellent correlation between POS plasma concentrations measured by UPLC-MS/MS and bioassay was found (concordance, 0.96). In 26 hemato-oncological patients receiving oral POS, 27/69 (39%) trough plasma concentrations were lower than 0.5 ?g/ml. The UPLC-MS/MS method and sensitive bioassay offer alternative tools for accurate and precise quantification of the plasma concentrations in patients receiving oral posaconazole.

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A study of the partial USEPA 3050B and total ISO 14869-1:2001 digestion methods of sediments was performed. USEPA 3050B was recommended as the simpler method with less operational risk. However, the extraction ability of the method should be taken in account for the best environmental interpretation of the results. FAAS was used to quantify metal concentrations in sediment solutions. The alternative use of ICP-OES quantification should be conditioned by a previous detailed investigation and eventual correction of the matrix effect. For the first time, the EID method was employed for the detection and correction of the matrix effect in sediment ICP-OES analysis. Finally, some considerations were made about the level of metal contamination in the area under study.

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This paper describes the optimization of a multiresidue chromatographic analysis for the identification and quantification of 20 pesticides in bovine milk, including three carbamates, a carbamate oxime, six organophosphates, two strobilurins, a pyrethroid, an oxazolidinedione, an aryloxyphenoxypropionate acid/ester, a neonicotinoid, a dicarboximide, and three triazoles. The influences of different chromatographic columns and gradients were evaluated. Furthermore, four different extraction methods were evaluated; each utilized both different solvents, including ethyl acetate, methanol, and acetonitrile, and different workup steps. The best results were obtained by a modified QuEChERS method that lacked a workup step, and that included freezing the sample for 2 hours at -20 ºC. The results were satisfactory, yielding coefficients of variation of less than 20%, with the exception of the 50 µg L-1 sample of famoxadone, and recoveries between 70 and 120%, with the exception of acephate and bifenthrin; however, both analytes exhibited coefficients of variation of less than 20%.

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New luminometric particle-based methods were developed to quantify protein and to count cells. The developed methods rely on the interaction of the sample with nano- or microparticles and different principles of detection. In fluorescence quenching, timeresolved luminescence resonance energy transfer (TR-LRET), and two-photon excitation fluorescence (TPX) methods, the sample prevents the adsorption of labeled protein to the particles. Depending on the system, the addition of the analyte increases or decreases the luminescence. In the dissociation method, the adsorbed protein protects the Eu(III) chelate on the surface of the particles from dissociation at a low pH. The experimental setups are user-friendly and rapid and do not require hazardous test compounds and elevated temperatures. The sensitivity of the quantification of protein (from 40 to 500 pg bovine serum albumin in a sample) was 20-500-fold better than in most sensitive commercial methods. The quenching method exhibited low protein-to-protein variability and the dissociation method insensitivity to the assay contaminants commonly found in biological samples. Less than ten eukaryotic cells were detected and quantified with all the developed methods under optimized assay conditions. Furthermore, two applications, the method for detection of the aggregation of protein and the cell viability test, were developed by utilizing the TR-LRET method. The detection of the aggregation of protein was allowed at a more than 10,000 times lower concentration, 30 μg/L, compared to the known methods of UV240 absorbance and dynamic light scattering. The TR-LRET method was combined with a nucleic acid assay with cell-impermeable dye to measure the percentage of dead cells in a single tube test with cell counts below 1000 cells/tube.

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The aim of this study was to compare two methods of tear sampling for protein quantification. Tear samples were collected from 29 healthy dogs (58 eyes) using Schirmer tear test (STT) strip and microcapillary tubes. The samples were frozen at -80ºC and analyzed by the Bradford method. Results were analyzed by Student's t test. The average protein concentration and standard deviation from tears collected with microcapillary tube were 4.45mg/mL ±0.35 and 4,52mg/mL ±0.29 for right and left eyes respectively. The average protein concentration and standard deviation from tears collected with Schirmer Tear Test (STT) strip were and 54.5mg/mL ±0.63 and 54.15mg/mL ±0.65 to right and left eyes respectively. Statistically significant differences (p<0.001) were found between the methods. In the conditions in which this study was conducted, the average protein concentration obtained with the Bradford test from tear samples obtained by Schirmer Tear Test (STT) strip showed values higher than those obtained with microcapillary tube. It is important that concentration of tear protein pattern values should be analyzed according the method used to collect tear samples.

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The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts. The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop–climate modeling. The implications of trends in computer power, including supercomputers, are also discussed.

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Soil organic carbon (SOC) plays a vital role in ecosystem function, determining soil fertility, water holding capacity and susceptibility to land degradation. In addition, SOC is related to atmospheric CO, levels with soils having the potential for C release or sequestration, depending on land use, land management and climate. The United Nations Convention on Climate Change and its Kyoto Protocol, and other United Nations Conventions to Combat Desertification and on Biodiversity all recognize the importance of SOC and point to the need for quantification of SOC stocks and changes. An understanding of SOC stocks and changes at the national and regional scale is necessary to further our understanding of the global C cycle, to assess the responses of terrestrial ecosystems to climate change and to aid policy makers in making land use/management decisions. Several studies have considered SOC stocks at the plot scale, but these are site specific and of limited value in making inferences about larger areas. Some studies have used empirical methods to estimate SOC stocks and changes at the regional scale, but such studies are limited in their ability to project future changes, and most have been carried out using temperate data sets. The computational method outlined by the Intergovernmental Panel on Climate Change (IPCC) has been used to estimate SOC stock changes at the regional scale in several studies, including a recent study considering five contrasting eco regions. This 'one step' approach fails to account for the dynamic manner in which SOC changes are likely to occur following changes in land use and land management. A dynamic modelling approach allows estimates to be made in a manner that accounts for the underlying processes leading to SOC change. Ecosystem models, designed for site scale applications can be linked to spatial databases, giving spatially explicit results that allow geographic areas of change in SOC stocks to be identified. Some studies have used variations on this approach to estimate SOC stock changes at the sub-national and national scale for areas of the USA and Europe and at the watershed scale for areas of Mexico and Cuba. However, a need remained for a national and regional scale, spatially explicit system that is generically applicable and can be applied to as wide a range of soil types, climates and land uses as possible. The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System was developed in response to this need. The GEFSOC system allows estimates of SOC stocks and changes to be made for diverse conditions, providing essential information for countries wishing to take part in an emerging C market, and bringing us closer to an understanding of the future role of soils in the global C cycle. (C) 2007 Elsevier B.V. All rights reserved.

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The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

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Replacement, expansion and upgrading of assets in the electricity network represents financial investment for the distribution utilities. Network Investment Deferral (NID) is a well discussed benefit of wider adoption of Distributed Generation (DG). There have been many attempts to quantify and evaluate the financial benefit for the distribution utilities. While the carbon benefits of NID are commonly mentioned, there is little attempt to quantify these impacts. This paper explores the quantitative methods previously used to evaluate financial benefits in order to discuss the carbon impacts. These carbon impacts are important for companies owning DG equipment for internal reporting and emissions reductions ambitions. Currently, a GB wide approach is taken as a means for discussing more regional and local methods to be used in future work. By investigating these principles, the paper offers a novel approach to quantifying carbon emissions from various DG technologies.

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A methodology to define favorable areas in petroleum and mineral exploration is applied, which consists in weighting the exploratory variables, in order to characterize their importance as exploration guides. The exploration data are spatially integrated in the selected area to establish the association between variables and deposits, and the relationships among distribution, topology, and indicator pattern of all variables. Two methods of statistical analysis were compared. The first one is the Weights of Evidence Modeling, a conditional probability approach (Agterberg, 1989a), and the second one is the Principal Components Analysis (Pan, 1993). In the conditional method, the favorability estimation is based on the probability of deposit and variable joint occurrence, with the weights being defined as natural logarithms of likelihood ratios. In the multivariate analysis, the cells which contain deposits are selected as control cells and the weights are determined by eigendecomposition, being represented by the coefficients of the eigenvector related to the system's largest eigenvalue. The two techniques of weighting and complementary procedures were tested on two case studies: 1. Recôncavo Basin, Northeast Brazil (for Petroleum) and 2. Itaiacoca Formation of Ribeira Belt, Southeast Brazil (for Pb-Zn Mississippi Valley Type deposits). The applied methodology proved to be easy to use and of great assistance to predict the favorability in large areas, particularly in the initial phase of exploration programs. © 1998 International Association for Mathematical Geology.

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Chromatographic and electroanalytical methods were developed to detect and quantify Sudan II (SD-II) dye in fuel ethanol samples. Sudan II is reduced at +0.50 V vs. Ag/AgCl on a glassy carbon electrode using Britton-Robinson buffer (pH 4.0) and N,N-dimethylformamide (70:30, v/v) + sodium dioctyl sulfosuccinate surfactant as supporting electrolyte, due to the azo group. This is the basis for its determination by square-wave voltammetry (SWV). Using the optimized conditions, it is possible to get a linear calibration curve from 3.00×10-6 to 1.80×10-5 mol L-1 (r = 0.998) with limits of detection (LOD) and quantification (LOQ) of 2.05×10-6 and 6.76×10-6 mol L-1, respectively. In addition, the hydroxyl substituent in the SD-II dye is also oxidized at +0.85 V vs. Ag/AgCl, which was conveniently used for its determination by high-performance liquid chromatography coupled to electrochemical detection (HPLC-ED). Under the optimized condition, the SD-II dye was eluted and separated using a reversed-phase column (cyanopropyl, CN) using isocratic elution with the mobile phase containing acetonitrile and aqueous lithium chloride (5.00×10-4 mol L-1) at 70:30 (v/v) and a flow rate of 1.2 mL min-1. Linear calibration curves were obtained from 3.00×10-7 to 2.00×10-6 mol L-1 (r = 0.999) with LOD and LOQ of 3.10×10-8 and 1.05×10-7 mol L-1, respectively. Both methods were simple, fast and suitable to detect and quantify the dye in fuel ethanol samples at recovery values between 83.0 to 102% (SWV) and 88.0 to 112% (HPLC-ED) with satisfactory precision and accuracy.

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An eletroanalytical method for determination of arsenic in sugar cane brandy using an electrode consisting of carbon paste modified with carbon nanotubes (CNTPE) and mineral oil has been developed. The cyclic (CV) and linear sweep voltammetry modes (LSV) with cathodic stripping were employed for CNTPE containing mineral oil. The analytical curves were linear from 30.0 to 80.0 µg L-1 for LSV. The limit of detection (L.O.D.) was 10.45 μg L-1 and limit of quantification (L.O.Q.) was 34.33 μg L-1. The developed method was applied to the determination of arsenic in tree commercial sugar cane brandy samples. The results were in good agreement with those obtained by HGAAS, showing that CNTPE containing mineral oil can be successfully employed to the simultaneous determination of arsenic in sugar cane brandy samples.

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Darunavir, a protease inhibitor used in the treatment of HIV infection, presents few methods for its determination in pharmaceuticals. Infrared (IR) spectroscopy offers the possibility of obtaining spectra relatively quickly, providing interesting information, analytically, qualitatively or quantitatively. Capillary electrophoresis (CE) performs separations of high efficiency in shorter time with reagents and samples in small quantity. These two methods are cost-benefitted when we evaluate the green level and the cost of analysis. Faster and cheaper methods without generating organic waste by IR and CE for the quantification of darunavir were developed and validated, focusing socioeconomic impact of analytical decisions. If the cost of acquisition, maintenance, production, analysis and conditioning of drugs and pharmaceuticals is high, consequently the price of this product in the market will be higher and it cannot be accessible to the patient. Treatment failure not only affects the quality of life of patients, but also contributes significantly to the economic burden of the health system. In this context there is a tool called Analysis of the Life Cycle, which comes to make us think in a multidimensional way focusing the whole, the parts and especially the interaction among the parts of a system.

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We describe work in which gold nanoparticles were formed in diamond-like carbon (DLC), thereby generating a Au-DLC nanocomposite. A high-quality, hydrogen-free DLC thin film was formed by filtered vacuum arc plasma deposition, into which gold nanoparticles were introduced using two different methods. The first method was gold ion implantation into the DLC film at a number of decreasing ion energies, distributing the gold over a controllable depth range within the DLC. The second method was co-deposition of gold and carbon, using two separate vacuum arc plasma guns with suitably interleaved repetitive pulsing. Transmission electron microscope images show that the size of the gold nanoparticles obtained by ion implantation is 3-5 nm. For the Au-DLC composite obtained by co-deposition, there were two different nanoparticle sizes, most about 2 nm with some 6-7 nm. Raman spectroscopy indicates that the implanted sample contains a smaller fraction of sp(3) bonding for the DLC, demonstrating that some sp(3) bonds are destroyed by the gold implantation. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4757029]