990 resultados para Complex matrices


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Sephadex-binding RNA ligands (aptamers) were obtained through in vitro selection. They could be classified into two groups based on their consensus sequences and the aptamers from both groups showed strong binding to Sephadex G-100. One of the highest affinity aptamers, D8, was chosen for further characterization. Aptamer D8 bound to dextran B512, the soluble base material of Sephadex, but not to isomaltose, isomaltotriose and isomaltotetraose, suggesting that its optimal binding site might consist of more than four glucose residues linked via α-1,6 linkages. The aptamer was very specific to the Sephadex matrix and did not bind appreciably to other supporting matrices, such as Sepharose, Sephacryl, cellulose or pustulan. Using Sephadex G-100, the aptamer could be purified from a complex mixture of cellular RNA, giving an enrichment of at least 60 000-fold, compared with a non-specific control RNA. These RNA aptamers can be used as affinity tags for RNAs or RNA subunits of ribonucleoproteins to allow rapid purification from complex mixtures of RNA using only Sephadex.

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Using methods of statistical physics, we study the average number and kernel size of general sparse random matrices over GF(q), with a given connectivity profile, in the thermodynamical limit of large matrices. We introduce a mapping of GF(q) matrices onto spin systems using the representation of the cyclic group of order q as the q-th complex roots of unity. This representation facilitates the derivation of the average kernel size of random matrices using the replica approach, under the replica symmetric ansatz, resulting in saddle point equations for general connectivity distributions. Numerical solutions are then obtained for particular cases by population dynamics. Similar techniques also allow us to obtain an expression for the exact and average number of random matrices for any general connectivity profile. We present numerical results for particular distributions.

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The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.

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New psychoactive substances (NPSs) have appeared on the recreational drug market at an unprecedented rate in recent years. Many are not new drugs but failed products of the pharmaceutical industry. The speed and variety of drugs entering the market poses a new complex challenge for the forensic toxicology community. The detection of these substances in biological matrices can be difficult as the exact compounds of interest may not be known. Many NPS are sold under the same brand name and therefore users themselves may not know what substances they have ingested. The majority of analytical methods for the detection of NPSs tend to focus on a specific class of compounds rather than a wide variety. In response to this, a robust and sensitive method was developed for the analysis of various NPS by solid phase extraction (SPE) with gas chromatography mass spectrometry (GCMS). Sample preparation and derivatisation were optimised testing a range of SPE cartridges and derivatising agents, as well as derivatisation incubation time and temperature. The final gas chromatography mass spectrometry method was validated in accordance with SWGTOX 2013 guidelines over a wide concentration range for both blood and urine for 23 and 25 analytes respectively. This included the validation of 8 NBOMe compounds in blood and 10 NBOMe compounds in urine. This GC-MS method was then applied to 8 authentic samples with concentrations compared to those originally identified by NMS laboratories. The rapid influx of NPSs has resulted in the re-analysis of samples and thus, the stability of these substances is crucial information. The stability of mephedrone was investigated, examining the effect that storage temperatures and preservatives had on analyte stability daily for 1 week and then weekly for 10 weeks. Several laboratories identified NPSs use through the cross-reactivity of these substances with existing screening protocols such as ELISA. The application of Immunalysis ketamine, methamphetamine and amphetamine ELISA kits for the detection of NPS was evaluated. The aim of this work was to determine if any cross-reactivity from NPS substances was observed, and to determine whether these existing kits would identify NPS use within biological samples. The cross- reactivity of methoxetamine, 3-MeO-PCE and 3-MeO-PCP for different commercially point of care test (POCT) was also assessed for urine. One of the newest groups of compounds to appear on the NPS market is the NBOMe series. These drugs pose a serious threat to public health due to their high potency, with fatalities already reported in the literature. These compounds are falsely marketed as LSD which increases the chance of adverse effects due to the potency differences between these 2 substances. A liquid chromatography tandem mass spectrometry (LC-MS/MS) method was validated in accordance with SWGTOX 2013 guidelines for the detection for 25B, 25C and 25I-NBOMe in urine and hair. Long-Evans rats were administered 25B-, 25C- and 25I-NBOMe at doses ranging from 30-300 µg/kg over a period of 10 days. Tail flick tests were then carried out on the rats in order to determine whether any analgesic effects were observed as a result of dosing. Rats were also shaved prior to their first dose and reshaved after the 10-day period. Hair was separated by colour (black and white) and analysed using the validated LC-MS/MS method, assessing the impact hair colour has on the incorporation of these drugs. Urine was collected from the rats, analysed using the validated LC-MS/MS method and screened for potential metabolites using both LC-MS/MS and quadrupole time of flight (QToF) instrumentation.

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Novel magnetic carbon xerogels consisting of interconnected carbon microspheres with iron and/or cobalt microparticles embedded in their structure were developed by a simple route. As inferred from the characterization data, materials with distinctive properties may be directly obtained upon inclusion of iron and/or cobalt precursors during the sol-gel polymerization of resorcinol and formaldehyde, followed by thermal annealing. The unique properties of these magnetic carbon xerogels were explored in the catalytic wet peroxide oxidation (CWPO) of an antimicrobial agent typically found throughout the urban water cycle – sulfamethoxazole (SMX). A clear synergistic effect arises from the inclusion of cobalt and iron in carbon xerogels (CX/CoFe),the resulting magnetic material revealing a better performance in the CWPO of SMX at the ppb level(500 microg L−1) when compared to that of monometallic carbon xerogels containing only iron or cobalt.This effect was ascribed to the increased accessibility of highly active iron species promoted by the simultaneous incorporation of cobalt.The performance of the CWPO process in the presence of CX/CoFe was also evaluated in environmentally relevant water matrices, namely in drinking water and secondary treated wastewater, considered in addition to ultrapure water. It was found that the performance decreases when applied to more complex water and wastewater samples. Nevertheless, the ability of the CWPO technology for the elimination of SMX in secondary treated wastewater was unequivocally shown, with 96.8% of its initial content being removed after 6 h of reaction in the presence of CX/CoFe, at atmospheric pressure, room temperature(T = 25◦C), pH = 3, [H2O2]0= 500 mg L−1and catalyst load = 80 mg L−1. A similar performance (97.8% SMX removal) is obtained in 30 min when the reaction temperature is slightly increased up to 60◦C in an ultra-pure water matrix. Synthetic water containing humic acid, bicarbonate, sulphate or chloride, was also tested. The results suggest the scavenging effect of the different anions considered, as well as the negative impact of dissolved organic matter typically found in secondary treated wastewater, as simulated by the presence of humic acid.An in-situ magnetic separation procedure was applied for catalyst recovery and re-use during reusability cycles performed to mimic real-scale applications. CWPO runs performed with increased SMX concentration (10 mg L−1), under a water treatment process intensification approach, allowed to evalu-ate the mineralization levels obtained, the antimicrobial activity of the treated water, and to propose adegradation mechanism for the CWPO of SMX.

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The application of spectroscopy to the study of contaminants in soils is important. Among the many contaminants is arsenic, which is highly labile and may leach to non-contaminated areas. Minerals of arsenate may form depending upon the availability of specific cations for example calcium and iron. Such minerals include carminite, pharmacosiderite and talmessite. Each of these arsenate minerals can be identified by its characteristic Raman spectrum enabling identification.

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Linear algebra provides theory and technology that are the cornerstones of a range of cutting edge mathematical applications, from designing computer games to complex industrial problems, as well as more traditional applications in statistics and mathematical modelling. Once past introductions to matrices and vectors, the challenges of balancing theory, applications and computational work across mathematical and statistical topics and problems are considerable, particularly given the diversity of abilities and interests in typical cohorts. This paper considers two such cohorts in a second level linear algebra course in different years. The course objectives and materials were almost the same, but some changes were made in the assessment package. In addition to considering effects of these changes, the links with achievement in first year courses are analysed, together with achievement in a following computational mathematics course. Some results that may initially appear surprising provide insight into the components of student learning in linear algebra.