965 resultados para Nuclear-localization Sequence


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Australasian marsupials include three major radiations, the insectivorous/carnivorous Dasyuromorphia, the omnivorous bandicoots (Peramelemorphia), and the largely herbivorous diprotodontians. Morphologists have generally considered the bandicoots and diprotodontians to be closely related, most prominently because they are both syndactylous (with the 2nd and 3rd pedal digits being fused). Molecular studies have been unable to confirm or reject this Syndactyla hypothesis. Here we present new mitochondrial (mt) genomes from a spiny bandicoot (Echymipera rufescens) and two dasyurids, a fat-tailed dunnart (Sminthopsis crassicaudata) and a northern quoll (Dasyurus hallucatus). By comparing trees derived from pairwise base-frequency differences between taxa with standard (absolute, uncorrected) distance trees, we infer that composition bias among mt protein-coding and RNA sequences is sufficient to mislead tree reconstruction. This can explain incongruence between trees obtained from mt and nuclear data sets. However, after excluding major sources of compositional heterogeneity, both the “reduced-bias” mt and nuclear data sets clearly favor a bandicoot plus dasyuromorphian association, as well as a grouping of kangaroos and possums (Phalangeriformes) among diprotodontians. Notably, alternatives to these groupings could only be confidently rejected by combining the mt and nuclear data. Elsewhere on the tree, Dromiciops appears to be sister to the monophyletic Australasian marsupials, whereas the placement of the marsupial mole (Notoryctes) remains problematic. More generally, we contend that it is desirable to combine mt genome and nuclear sequences for inferring vertebrate phylogeny, but as separately modeled process partitions. This strategy depends on detecting and excluding (or accounting for) major sources of nonhistorical signal, such as from compositional nonstationarity.

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The proteasome (multicatalytic proteinase complex) is a large multimeric complex which is found in the nucleus and cytoplasm of eukaryotic cells. It plays a major role in both ubiquitin-dependent and ubiquitin-independent nonlysosomal pathways of protein degradation. Proteasome subunits are encoded by members of the same gene family and can be divided into two groups based on their similarity to the c~ and /3 subunits of the simpler proteasome isolated from Thermoplasma acidophilum. Proteasomes have a cylindrical structure composed of four rings of seven subunits. The 26S form of the proteasome, which is responsible for ubiquitin-dependent proteolysis, contains additional regulatory complexes. Eukaryotic proteasomes have multiple catalytic activities which are catalysed at distinct sites. Since proteasomes are unrelated to other known proteases, there are no clues as to which are the catalytic components from sequence alignments. It has been assumed from studies with yeast mutants that /3-type subunits play a catalytic role. Using a radiolabelled peptidyl chloromethane inhibitor of rat liver proteasomes we have directly identified RC7 as a catalytic component. Interestingly, mutants in Prel, the yeast homologue of RC7, have already been reported to have defective chymotrypsin-like activity. These results taken together confirm a direct catalytic role for these/3-type subunits. Proteasome activities are sensitive to conformational changes and there are several ways in which proteasome function may be modulated in vivo. Our recent studies have shown that in animal cells at least two proteasome subunits can undergo phosphorylation, the level of which is likely to be important for determining proteasome localization, activity or ability to form larger complexes. In addition, we have isolated two isoforms of the 26S proteinase.

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Utilizing a mono-specific antiserum produced in rabbits to hog kidney aromatic L-amino acid decarboxylase (AADC), the enzyme was localized in rat kidney by immunoperoxidase staining. AADC was located predominantly in the proximal convoluted tubules; there was also weak staining in the distal convoluted tubules and collecting ducts. An increase in dietary potassium or sodium intake produced no change in density or distribution of AADC staining in kidney. An assay of AADC enzyme activity showed no difference in cortex or medulla with chronic potassium loading. A change in distribution or activity of renal AADC does not explain the postulated dopaminergic modulation of renal function that occurs with potassium or sodium loading.

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In this paper we use a sequence-based visual localization algorithm to reveal surprising answers to the question, how much visual information is actually needed to conduct effective navigation? The algorithm actively searches for the best local image matches within a sliding window of short route segments or 'sub-routes', and matches sub-routes by searching for coherent sequences of local image matches. In contract to many existing techniques, the technique requires no pre-training or camera parameter calibration. We compare the algorithm's performance to the state-of-the-art FAB-MAP 2.0 algorithm on a 70 km benchmark dataset. Performance matches or exceeds the state of the art feature-based localization technique using images as small as 4 pixels, fields of view reduced by a factor of 250, and pixel bit depths reduced to 2 bits. We present further results demonstrating the system localizing in an office environment with near 100% precision using two 7 bit Lego light sensors, as well as using 16 and 32 pixel images from a motorbike race and a mountain rally car stage. By demonstrating how little image information is required to achieve localization along a route, we hope to stimulate future 'low fidelity' approaches to visual navigation that complement probabilistic feature-based techniques.

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Appearance-based localization can provide loop closure detection at vast scales regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale not only with the size of the environment but also with the operation time of the platform. Additionally, repeated visits to locations will develop multiple competing representations, which will reduce recall performance over time. These properties impose severe restrictions on long-term autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. In this paper we present a graphical extension to CAT-SLAM, a particle filter-based algorithm for appearance-based localization and mapping, to provide constant computation and memory requirements over time and minimal degradation of recall performance during repeated visits to locations. We demonstrate loop closure detection in a large urban environment with capped computation time and memory requirements and performance exceeding previous appearance-based methods by a factor of 2. We discuss the limitations of the algorithm with respect to environment size, appearance change over time and applications in topological planning and navigation for long-term robot operation.

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Webb et al. (2009) described a late Pleistocenecoral sample wherein the diagenetic stabilization of original coral aragonite to meteoric calcite was halted more or less mid-way through the process, allowing direct comparison of pre-diagenetic and post-diagenetic microstructure and trace element distributions. Those authors found that the rare earth elements (REEs) were relatively stable during meteoric diagenesis, unlike divalent cations such as Sr,and it was thus concluded that original, in this case marine, REE distributions potentially could be preserved through the meteoric carbonate stabilization process that must have affected many, if not most, ancient limestones. Although this was not the case in the analysed sample, they noted that where such diagenesis took place in laterally transported groundwater, trace elements derived from that groundwater could be incorporated into diagenetic calcite, thus altering the initial REE distribution (Banner et al., 1988). Hence, the paper was concerned with the diagenetic behaviour of REEs in a groundwater-dominated karst system. The comment offered by Johannesson (2011) does not question those research results, but rather, seeks to clarify an interpretation made by Webb et al. (2009) of an earlier paper, Johannesson et al. (2006).

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Learning and then recognizing a route, whether travelled during the day or at night, in clear or inclement weather, and in summer or winter is a challenging task for state of the art algorithms in computer vision and robotics. In this paper, we present a new approach to visual navigation under changing conditions dubbed SeqSLAM. Instead of calculating the single location most likely given a current image, our approach calculates the best candidate matching location within every local navigation sequence. Localization is then achieved by recognizing coherent sequences of these “local best matches”. This approach removes the need for global matching performance by the vision front-end - instead it must only pick the best match within any short sequence of images. The approach is applicable over environment changes that render traditional feature-based techniques ineffective. Using two car-mounted camera datasets we demonstrate the effectiveness of the algorithm and compare it to one of the most successful feature-based SLAM algorithms, FAB-MAP. The perceptual change in the datasets is extreme; repeated traverses through environments during the day and then in the middle of the night, at times separated by months or years and in opposite seasons, and in clear weather and extremely heavy rain. While the feature-based method fails, the sequence-based algorithm is able to match trajectory segments at 100% precision with recall rates of up to 60%.

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Appearance-based localization is increasingly used for loop closure detection in metric SLAM systems. Since it relies only upon the appearance-based similarity between images from two locations, it can perform loop closure regardless of accumulated metric error. However, the computation time and memory requirements of current appearance-based methods scale linearly not only with the size of the environment but also with the operation time of the platform. These properties impose severe restrictions on longterm autonomy for mobile robots, as loop closure performance will inevitably degrade with increased operation time. We present a set of improvements to the appearance-based SLAM algorithm CAT-SLAM to constrain computation scaling and memory usage with minimal degradation in performance over time. The appearance-based comparison stage is accelerated by exploiting properties of the particle observation update, and nodes in the continuous trajectory map are removed according to minimal information loss criteria. We demonstrate constant time and space loop closure detection in a large urban environment with recall performance exceeding FAB-MAP by a factor of 3 at 100% precision, and investigate the minimum computational and memory requirements for maintaining mapping performance.

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The major limitation of current typing methods for Streptococcus pyogenes, such as emm sequence typing and T typing, is that these are based on regions subject to considerable selective pressure. Multilocus sequence typing (MLST) is a better indicator of the genetic backbone of a strain but is not widely used due to high costs. The objective of this study was to develop a robust and cost-effective alternative to S. pyogenes MLST. A 10-member single nucleotide polymorphism (SNP) set that provides a Simpson’s Index of Diversity (D) of 0.99 with respect to the S. pyogenes MLST database was derived. A typing format involving high-resolution melting (HRM) analysis of small fragments nucleated by each of the resolution-optimized SNPs was developed. The fragments were 59–119 bp in size and, based on differences in G+C content, were predicted to generate three to six resolvable HRM curves. The combination of curves across each of the 10 fragments can be used to generate a melt type (MelT) for each sequence type (ST). The 525 STs currently in the S. pyogenes MLST database are predicted to resolve into 298 distinct MelTs and the method is calculated to provide a D of 0.996 against the MLST database. The MelTs are concordant with the S. pyogenes population structure. To validate the method we examined clinical isolates of S. pyogenes of 70 STs. Curves were generated as predicted by G+C content discriminating the 70 STs into 65 distinct MelTs.

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In this paper we present a fast power line detection and localisation algorithm as well as propose a high-level guidance architecture for active vision-based Unmanned Aerial Vehicle (UAV) guidance. The detection stage is based on steerable filters for edge ridge detection, followed by a line fitting algorithm to refine candidate power lines in images. The guidance architecture assumes an UAV with an onboard Gimbal camera. We first control the position of the Gimbal such that the power line is in the field of view of the camera. Then its pose is used to generate the appropriate control commands such that the aircraft moves and flies above the lines. We present initial experimental results for the detection stage which shows that the proposed algorithm outperforms two state-of-the-art line detection algorithms for power line detection from aerial imagery.

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Purpose – Rehearsing practical site operations is without doubt one of the most effective methods for minimising planning mistakes, because of the learning that takes place during the rehearsal activity. However, real rehearsal is not a practical solution for on-site construction activities, as it not only involves a considerable amount of cost but can also have adverse environmental implications. One approach to overcoming this is by the use of virtual rehearsals. The purpose of this paper is to investigate an approach to simulation of the motion of cranes in order to test the feasibility of associated construction sequencing and generate construction schedules for review and visualisation. Design/methodology/approach – The paper describes a system involving two technologies, virtual prototyping (VP) and four-dimensional (4D) simulation, to assist construction planners in testing the sequence of construction activities when mobile cranes are involved. The system consists of five modules, comprising input, database, equipment, process and output, and is capable of detecting potential collisions. A real-world trial is described in which the system was tested and validated. Findings – Feedback from the planners involved in the trial indicated that they found the system to be useful in its present form and that they would welcome its further development into a fully automated platform for validating construction sequencing decisions. Research limitations/implications – The tool has the potential to provide a cost-effective means of improving construction planning. However, it is limited at present to the specific case of crane movement under special consideration. Originality/value – This paper presents a large-scale, real life case of applying VP technology in planning construction processes and activities.

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The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST) collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup.