510 resultados para bk: Swahili


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Mode of access: Internet.

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In many neurons, trains of action potentials show frequency-dependent broadening. This broadening results from the voltage-dependent inactivation of K+ currents that contribute to action potential repolarisation. In different neuronal cell types these K+ currents have been shown to be either slowly inactivating delayed rectifier type currents or rapidly inactivating A-type voltage-gated K+ currents. Recent findings show that inactivation of a Ca2+-dependent K+ current, mediated by large conductance BK-type channels, also contributes to spike broadening. Here, using whole-cell recordings in acute slices, we examine spike broadening in lateral amygdala projection neurons. Spike broadening is frequency dependent and is reversed by brief hyperpolarisations. This broadening is reduced by blockade of voltage-gated Ca2+ channels and BK channels. In contrast, broadening is not blocked by high concentrations of 4-aminopyridine (4-AP) or alpha-dendrotoxin. We conclude that while inactivation of BK-type Ca2+-activated K+ channels contributes to spike broadening in lateral amygdala neurons, inactivation of another as yet unidentified outward current also plays a role.

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Human polyomaviruses JCV and BKV can cause several clinical manifestations in immunocompromised hosts, including progressive multifocal leukoencephalopathy (PML) and haemorrhagic cystitis. Molecular detection by polymerase chain reaction (PCR) is recognised as a sensitive and specific method for detecting human polyomaviruses in clinical samples. In this study, we developed a PCR assay using a single primer pair to amplify a segment of the VP1 gene of JCV and BKV. An enzyme linked amplicon hybridisation assay (ELAHA) using species-specific biotinylated oligonucleotide probes was used to differentiate between JCV and BKV. This assay (VP1-PCR-ELAHA) was evaluated and compared to a PCR assay targeting the human polyomavirus T antigen gene (pol-PCR). DNA sequencing was used to confirm the polyomavirus species identified by the VP1-PCR-ELAHA and to determine the subtype of each JCV isolate. A total of 297 urine specimens were tested and human polyomavirus was detected in 105 specimens (35.4%) by both PCR assays. The differentiation of JCV and BKV by the VP1-PCR-ELAHA showed good agreement with the results of DNA sequencing. Further, DNA sequencing of the JCV positive specimens showed the most prevalent JCV subtype in our cohort was 2a (27%) followed by 1b (20%), 1a (15%), 2c (14%), 4 (14%) and 2b (10%). The results of this study show that the VP1-PCR-ELAHA is a sensitive, specific and rapid method for detecting and differentiating human polyomaviruses JC and BK and is highly suitable for routine use in the clinical laboratory. (C) 2004 Wiley-Liss, Inc.

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Perez-Losada et al. [1] analyzed 72 complete genomes corresponding to nine mammalian (67 strains) and 2 avian (5 strains) polyomavirus species using maximum likelihood and Bayesian methods of phylogenetic inference. Because some data of 2 genomes in their work are now not available in GenBank, in this work, we analyze the phylogenetic relationship of the remaining 70 complete genomes corresponding to nine mammalian (65 strains) and two avian (5 strains) polyomavirus species using a dynamical language model approach developed by our group (Yu et al., [26]). This distance method does not require sequence alignment for deriving species phylogeny based on overall similarities of the complete genomes. Our best tree separates the bird polyomaviruses (avian polyomaviruses and goose hemorrhagic polymaviruses) from the mammalian polyomaviruses, which supports the idea of splitting the genus into two subgenera. Such a split is consistent with the different viral life strategies of each group. In the mammalian polyomavirus subgenera, mouse polyomaviruses (MPV), simian viruses 40 (SV40), BK viruses (BKV) and JC viruses (JCV) are grouped as different branches as expected. The topology of our best tree is quite similar to that of the tree constructed by Perez-Losada et al.

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The Analytical Electron Microscope (AEM), with which secondary X-ray emission from a thin (<150nm), electron-transparent material is measured, has rapidly become a versatile instrument for qualitative and quantitative elemental analyses of many materials, including minerals. With due regard for sources of error in experimental procedures, it is possible to obtain high spatial resolution (~20nm diameter) and precise elemental analyses (~3% to 5% relative) from many silicate minerals. In addition, by utilizing the orientational dependence of X-ray emission for certain multi-substituted crystal structures, site occupancies for individual elements within a unit cell can be determined though with lower spatial resolution. The relative ease with which many of these compositional data may be obtained depends in part on the nature of the sample, but, in general, is comparable to other solid state analytical techniques such as X-ray diffraction and electron microprobe analysis. However, the improvement in spatial resolution obtained with the AEM (up to two orders of magnitude in analysis diameter) significantly enhances interpretation of fine-grained assemblages in many terrestrial or extraterrestrial rocks.

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Samples of YBa2Cu3O7-y+20 mol% Y2BaCuO5, with thicknesses ranging between 50-250 μm, have been melt processed and rapidly quenched from temperatures between 985 and 1100°C by immersing them in liquid nitrogen. The phase composition and microstructures of these samples have been characterised using a combination of X-ray diffractometry, optical microscopy and scanning electron microscopy with energy dispersive X-ray spectroscopy. The quenched melt of samples quenched from temperatures greater than 985°C appears relatively homogeneous but consists of Ba2Cu3Ox (BC1.5) and BaCu2O2 (BC2) regions. At about 985°C, BaCuO2 (BC1) crystallises from the melt and most of the BC1.5 decomposes into BC1 and CuO or into BC1 and BC2. The crystallisation of BC1 induces segregation of elements in the melt and this is very significant for the melt texturing of YBCO.

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A general chemo-enzymatic process has been developed to prepare enantiomerically pure L- and D-amino acids in high yield by deracemisation of racemic starting materials. The method has been developed from initial academic studies to be a robust, scalable industrial process. Unnatural amino acids, in high optical purity, are a rapidly growing class of intermediates required for pharmaceuticals, agrochemicals and other fine chemical applications. However, no single method has proven sufficiently adaptable to prepare these compounds generally at large scale. Our approach uses an enantioselective oxidase biocatalyst and a non-selective chemical reducing agent to effect the stereoinversion of one enantiomer and can result in an enantiomeric excess of > 99 % from a starting racemate, and product yields over 90 %. The current approach compares very favourably to resolution methods which have a maximum single pass yield of 50 %. Efficient methods have been developed to adapt the biocatalyst used in this process towards new target compounds and to optimise key factors which improve the process efficiency and offer competitive economics at scale.

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Fashion Thinking: Creative Approaches to the Design Process, F. Dieffenbacher (2013) London: AVA, 224 pp., ISBN: 9782940411719, p/bk, $79.99

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Pesticide use in paddy rice production may contribute to adverse ecological effects in surface waters. Risk assessments conducted for regulatory purposes depend on the use of simulation models to determine predicted environment concentrations (PEC) of pesticides. Often tiered approaches are used, in which assessments at lower tiers are based on relatively simple models with conservative scenarios, while those at higher tiers have more realistic representations of physical and biochemical processes. This chapter reviews models commonly used for predicting the environmental fate of pesticides in rice paddies. Theoretical considerations, unique features, and applications are discussed. This review is expected to provide information to guide model selection for pesticide registration, regulation, and mitigation in rice production areas.

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A simple and practical technique for the discrete representation of reinforcement in two-dimensional boundary element analysis of reinforced concrete structural elements is presented. The bond developed over the surface of contact between the reinforcing steel and concrete is represented using fictitious one-dimensional spring elements. Potentials of the model developed are demonstrated using a number of numerical examples. The results are seen to be in good agreement with the results obtained using standard finite element software.

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Eleven new human polyomaviruses have been recently discovered, yet for most of these viruses, little is known of their biology and clinical impact. Rolling circle amplification (RCA) is an ideal method for the amplification of the circular polyomavirus genome due to its high fidelity amplification of circular DNA. In this study, a modified RCA method was developed to selectively amplify a range of polyomavirus genomes. Initial evaluation showed a multiplexed temperature-graded reaction profile gave the best yield and sensitivity in amplifying BK polyomavirus in a background of human DNA, with up to 1 × 10(8)-fold increases in viral genomes from as little as 10 genome copies per reaction. Furthermore, the method proved to be more sensitive and provided a 200-fold greater yield than that of random hexamers based standard RCA. Application of the method to other novel human polyomaviruses showed successful amplification of TSPyV, HPyV6, HPyV7, and STLPyV from low-viral load positive clinical samples, with viral genome enrichment ranging from 1 × 10(8) up to 1 × 10(10). This directed RCA method can be applied to selectively amplify other low-copy polyomaviral genomes from a background of competing non-specific DNA, and is a useful tool in further research into the rapidly expanding Polyomaviridae family.

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An artificial neural network (ANN) is presented to predict a 28-day compressive strength of a normal and high strength self compacting concrete (SCC) and high performance concrete (HPC) with high volume fly ash. The ANN is trained by the data available in literature on normal volume fly ash because data on SCC with high volume fly ash is not available in sufficient quantity. Further, while predicting the strength of HPC the same data meant for SCC has been used to train in order to economise on computational effort. The compressive strengths of SCC and HPC as well as slump flow of SCC estimated by the proposed neural network are validated by experimental results.