943 resultados para SYNTHETIC SPECTRA
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Ion Mobility Spectrometry coupled with Multi Capillary Columns (MCC -IMS) is a fast analytical technique working at atmospheric pressure with high sensitivity and selectivity making it suitable for the analysis of complex biological matrices. MCC-IMS analysis generates its information through a 3D spectrum with peaks, corresponding to each of the substances detected, providing quantitative and qualitative information. Sometimes peaks of different substances overlap, making the quantification of substances present in the biological matrices a difficult process. In the present work we use peaks of isoprene and acetone as a model for this problem. These two volatile organic compounds (VOCs) that when detected by MCC-IMS produce two overlapping peaks. In this work it’s proposed an algorithm to identify and quantify these two peaks. This algorithm uses image processing techniques to treat the spectra and to detect the position of the peaks, and then fits the data to a custom model in order to separate the peaks. Once the peaks are separated it calculates the contribution of each peak to the data.
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Environmental pollution is one of the major and most important problems of the modern world. In order to fulfill the needs and demands of the overgrowing human population, developments in agriculture, medicine, energy sources, and all chemical industries are necessary (Ali 2010). Over the last century, the increased industrialization and continued population growth led to an augmented production of environmental pollutants that are released into air, water, and soil, with significant impact in the degradation of various ecosystems (Ali 2010, Khan et al. 2013).(...)
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Cyanobacteria are photoautotrophic microorganisms with great potential for the biotechnological industry due to their low nutrient requirements, photosynthetic capacities and metabolic plasticity. In biotechnology, the energy sector is one of the main targets for their utilization, especially to produce the so called third generation biofuels, which are regarded as one of the best replacements for petroleum-based fuels. Although, several issues could be solved, others arise from the use of cyanobacteria, namely the need for high amounts of freshwater and contamination/predation by other microorganisms that affect cultivation efficiencies. The cultivation of cyanobacteria in seawater could solve this issue, since it has a very stable and rich chemical composition. Among cyanobacteria, the model microorganism Synechocystis sp. PCC 6803 is one of the most studied with its genome fully sequenced and genomic, transcriptomic and proteomic data available to better predict its phenotypic behaviors/characteristics. Despite suitable for genetic engineering and implementation as a microbial cell factory, Synechocystis’ growth rate is negatively affected by increasing salinity levels. Therefore, it is important to improve. To achieve this, several strategies involving the constitutive overexpression of the native genes encoding the proteins involved in the production of the compatible solute glucosylglycerol were implemented, following synthetic biology principles. A preliminary transcription analysis of selected mutants revealed that the assembled synthetic devices are functional at the transcriptional level. However, under different salinities, the mutants did not show improved robustness to salinity in terms of growth, compared with the wild-type. Nevertheless, some mutants carrying synthetic devices appear to have a better physiological response under seawater’s NaCl concentration than in 0% (w/v) NaCl.
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Charged-particle spectra obtained in 0.15nb−1 of Pb+Pb interactions at sNN−−−√=2.76TeV and 4.2pb−1 of pp interactions at s√=2.76TeV with the ATLAS detector at the LHC are presented in a wide transverse momentum (0.5
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Secondary metabolites from plants are important sources of high-value chemicals, many of them being pharmacologically active. These metabolites are commonly isolated through inefficient extractions from natural biological sources and are often difficult to synthesize chemically. Therefore, their production using engineered organisms has lately attracted an increased attention. Curcuminoids, an example of such metabolites, are produced in Curcuma longa and exhibit anti-cancer and anti-inflammatory activities. Herein we report the construction of an artificial biosynthetic pathway for the curcuminoids production in Escherichia coli. Different 4-coumaroyl-CoA ligases (4CL) and polyketide synthases (diketide-CoA synthase (DCS), curcumin synthase (CURS) and curcuminoid synthase) were tested. The highest curcumin production (70 mg/L) was obtained by feeding ferulic acid and with the Arabidopsis thaliana 4CL1 and C. longa DCS and CURS enzymes. Other curcuminoids (bisdemethoxy- and demethoxycurcumin) were also produced by feeding coumaric acid or a mixture of coumaric and ferulic acids, respectively. Curcuminoids, including curcumin, were also produced from tyrosine through the caffeic acid pathway. To produce caffeic acid, tyrosine ammonia lyase and 4-coumarate 3-hydroxylase were used. Caffeoyl-CoA O-methyltransferase was used to convert caffeoyl-CoA to feruloyl-CoA. This pathway represents an improvement of the curcuminoids heterologous production. The construction of this pathway in another model organism is being considered, as well as the introduction of alternative enzymes.
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Synthesis gas, a mixture of CO, H2, and CO2, is a promising renewable feedstock for bio-based production of organic chemicals. Production of medium-chain fatty acids can be performed via chain elongation, utilizing acetate and ethanol as main substrates. Acetate and ethanol are main products of syngas fermentation by acetogens. Therefore, syngas can be indirectly used as a substrate for the chain elongation process.
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Fundação para a Ciência e a Tecnologia, Grant SFRH/BPD/46515/2008. Jiajia Fu acknowledges the support of Jiangsu Provincial Natural Science Foundation of China (No. BK2012112) and the National Natural Science Foundation of China under Grant No. 3120113
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Dissertation for Ph.D. degree in Biomedical Engineering.
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A study has been undertaken of the published literature on the Fries rearrangement, thermal, photo and microwave, since its discovery in 1908. A resume of these publications and especially of those pertaining to the thia-Fries rearrangement of sulfamate esters, has been compiled. Phenyl sulfamate, phenyl N,N-dimethylsulfamate, phenyl N,N-diethylsulfamate and phenyl N,N-di-n-propylsulfamate and many of their substituted compounds have been synthesised and purified, a total of thirty nine esters. The sulfamates have been characterised by mp / bp, infrared, C, H and N microanalysis and mass spectrum. Many of these sulfamates, twenty six in total, have been rearranged to sulfonamides in the thia-Fries rearrangement, and subsequently purified. The products were characterised by mp / bp, infrared, C, H and N microanalysis and mass spectrum. Mechanistic studies of the sulfamates have been investigated, particularly phenyl N,N-dimethylsulfamate. The rearrangement with various catalysts and catalytic ratios, the effect of solvents on the rearrangement and many crossover experiments have been carried out to determine the molecularity i.e. whether it is an inter-, intra- or bimolecular reaction. The microwave induced thia-Fries rearrangement has been examined to determine what effect this irradiation has on the rearrangement. Photo thia-Fries rearrangement has also been investigated.
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Actualment, la resposta de la majoria d’instrumentació operacional i dels dosímetres personals utilitzats en radioprotecció per a la dosimetria neutrònica és altament dependent de l’energia dels espectres neutrònics a analitzar, especialment amb camps neutrònics amb una important component intermitja. En conseqüència, la interpretació de les lectures d’aquests aparells es complicada si no es té un coneixement previ de la distribució espectral de la fluència neutrònica en els punts d’interès. El Grup de Física de les Radiacions de la Universitat Autònoma de Barcelona (GFR-UAB) ha desenvolupat en els últims anys un espectròmetre de neutrons basat en un Sistema d’Esferes Bonner (BSS) amb un contador proporcional d’3He com a detector actiu. Els principals avantatges dels espectròmetres de neutrons per BSS són: la seva resposta isotròpica, la possibilitat de discriminar la component neutrònica de la gamma en camps mixtos, i la seva alta sensibilitat neutrònica als nivells de dosi analitzats. Amb aquestes característiques, els espectròmetres neutrònics per BSS compleixen amb els estándards de les últimes recomanacions de la ICRP i poden ser utilitzats també en el camp de la dosimetria neutrònica per a la mesura de dosis en el rang d’energia que va dels tèrmics fins als 20 MeV, en nou ordres de magnitud. En el marc de la col•laboració entre el GFR - UAB i el Laboratorio Nazionale di Frascati – Istituto Nazionale di Fisica Nucleare (LNF-INFN), ha tingut lloc una experiència comparativa d’espectrometria per BSS amb els feixos quasi monoenergètics de 2.5 MeV i 14 MeV del Fast Neutron Generator de l’ENEA. En l’exercici s’ha determinat l’espectre neutrònic a diferents distàncies del blanc de l’accelerador, aprofitant el codi FRUIT recentment desenvolupat pel grup LNF. Els resultats obtinguts mostren una bona coherència entre els dos espectròmetres i les dades mesurades i simulades.
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The recent developments in high magnetic field 13C magnetic resonance spectroscopy with improved localization and shimming techniques have led to important gains in sensitivity and spectral resolution of 13C in vivo spectra in the rodent brain, enabling the separation of several 13C isotopomers of glutamate and glutamine. In this context, the assumptions used in spectral quantification might have a significant impact on the determination of the 13C concentrations and the related metabolic fluxes. In this study, the time domain spectral quantification algorithm AMARES (advanced method for accurate, robust and efficient spectral fitting) was applied to 13 C magnetic resonance spectroscopy spectra acquired in the rat brain at 9.4 T, following infusion of [1,6-(13)C2 ] glucose. Using both Monte Carlo simulations and in vivo data, the goal of this work was: (1) to validate the quantification of in vivo 13C isotopomers using AMARES; (2) to assess the impact of the prior knowledge on the quantification of in vivo 13C isotopomers using AMARES; (3) to compare AMARES and LCModel (linear combination of model spectra) for the quantification of in vivo 13C spectra. AMARES led to accurate and reliable 13C spectral quantification similar to those obtained using LCModel, when the frequency shifts, J-coupling constants and phase patterns of the different 13C isotopomers were included as prior knowledge in the analysis.
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Vaccines have been used as a successful tool in medicine by way of controlling many major diseases. In spite of this, vaccines today represent only a handful of all infectious diseases. Therefore, there is a pressing demand for improvements of existing vaccines with particular reference to higher efficacy and undisputed safety profiles. To this effect, as an alternative to available vaccine technologies, there has been a drive to develop vaccine candidate polypeptides by chemical synthesis. In our laboratory, we have recently developed a technology to manufacture long synthetic peptides of up to 130 residues, which are correctly folded and biologically active. This paper discusses the advantages of the molecularly defined, long synthetic peptide approach in the context of vaccine design, development and use in human vaccination.
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The review covers the development of synthetic peptides as vaccine candidates for Plasmodium falciparum- and Plasmodium vivax-induced malaria from its beginning up to date and the concomitant progress of solid phase peptide synthesis (SPPS) that enables the production of long peptides in a routine fashion. The review also stresses the development of other complementary tools and actions in order to achieve the long sought goal of an efficacious malaria vaccine.
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The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm−1 and 2730-3600 cm−1, provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.