The complete nucleotide sequence of subterranean clover mottle virus

The complete nucleotide sequence of Subterranean clover mottle virus (SCMoV) genomic RNA has been determined. The SCMoV genome is 4,258 nucleotides in length. It shares most nucleotide and amino acid sequence identity with the genome of Lucerne transient streak virus (LTSV). SCMoV RNA encodes four overlapping open reading frames and has a genome organisation similar to that of Cocksfoot mottle virus (CfMV). ORF1 and ORF4 are predicted to encode single proteins. ORF2 is predicted to encode two proteins that are derived from a -1 translational frameshift between two overlapping reading frames (ORF2a and ORF2b). A search of amino acid databases did not find a significant match for ORF1 and the function of this protein remains unclear. ORF2a contains a motif typical of chymotrypsin-like serine proteases and ORF2b has motifs characteristically present in positive-stranded RNA-dependent RNA polymerases. ORF4 is likely to be expressed from a subgenomic RNA and encodes the viral coat protein. The ORF2a/ORF2b overlapping gene expression strategy used by SCMoV and CfMV is similar to that of the poleroviruses and differ from that of other published sobemoviruses. These results suggest that the sobemoviruses could now be divided into two distinct subgroups based on those that express the RNA-dependent RNA polymerase from a single, in-frame polyprotein, and those that express it via a -1 translational frameshifting mechanism.

Nucleotide sequence of coat protein gene for GPV isolate of barley yellow dwarf virus and construction of expression plasmid for plant

GPV is a Chinese serotype isolate of barley yellow dwarf virus (BYDV) that has no reaction with antiserum of MAV, PAV, SGV, RPV and RMV The sequence of the coat protein (CP) of GPV isolate of BYDV was identified and its amino acid sequence was deduced. The coding region for the putative GPV CP is 603 bases nucleotides and encodes a Mr 22 218 (22 ku) protein. The same as MAV, PAV and RPV, GPV contained a second ORF within the coat protein coding region. This protein of 17 024 Mr (17 ku) is thought to correspond to the Virion protein genome linked (Vpg). Sequence comparisons of the CP coding region between the GPV isolate of BYDV and other isolates of BYDV have been done. The nucleotide and amino acid sequence homology of GPV has a greater identity to the sequence of RPV than those of PAV and MAV. The GPV CP sequence stored 83.7% of nucleotide similarity and 77.5% of deduced amino acid similarity, whereas that of the PAV and MAV shared 56.9%, 53.2% and 44.1%, 43.8% respectively. According to BYDV-GPV CP sequence, two primers were designed. The cDNA of CP was produced by RT-PCR. Full-length cDNA of CP was inserted into plasmid to construct expression plasmids named pPPI1, pPPI2 and pPPI5 based on different promoters. The recombinant plasmids were identified by using α-32P-dATP labelled CP probe, α-32P-ATP labelled GPV RNA probe and sequencing to confirm real GPV CP gene cDNA in plasmids.

Sequence and identification of the barley yellow dwarf virus coat protein gene

The nucleotide sequence of the coat protein gene of barley yellow dwarf virus (BYDV, PAV serotype) was determined, and the amino acid sequence was deduced. The open reading frame, encoding a protein of relative molecular mass (Mr) 22,047, was confirmed as the coat protein gene by comparison with amino acid sequences of tryptic peptides derived from dissociated virions. In addition, a fragment of this gene expressed in Escherichia coli produced a product which was recognized by antibodies prepared against purified BYDV virions. An overlapping reading frame encoding an Mr 17,147 protein is contained completely within the coat protein gene. © 1988.

Quality based frame selection for face clustering in news video

Clustering identities in a broadcast video is a useful task to aid in video annotation and retrieval. Quality based frame selection is a crucial task in video face clustering, to both improve the clustering performance and reduce the computational cost. We present a frame work that selects the highest quality frames available in a video to cluster the face. This frame selection technique is based on low level and high level features (face symmetry, sharpness, contrast and brightness) to select the highest quality facial images available in a face sequence for clustering. We also consider the temporal distribution of the faces to ensure that selected faces are taken at times distributed throughout the sequence. Normalized feature scores are fused and frames with high quality scores are used in a Local Gabor Binary Pattern Histogram Sequence based face clustering system. We present a news video database to evaluate the clustering system performance. Experiments on the newly created news database show that the proposed method selects the best quality face images in the video sequence, resulting in improved clustering performance.

Towards condition-invariant, top-down visual place recognition

In this paper we present a novel place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images (although we use a cohort normalization score to exploit temporal frame information), alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We demonstrate the algorithm on the challenging Alderley sunny day – rainy night dataset, which has only been previously solved by integrating over 320 frame long image sequences. The system is able to achieve 21.24% recall at 100% precision, matching drastically different day and night-time images of places while successfully rejecting match hypotheses between highly aliased images of different places. The results provide a new benchmark for single image, condition-invariant place recognition.

Hot spot detection and spatio-temporal dispersion of dengue fever in Hanoi, Vietnam

INTRODUCTION Dengue fever (DF) in Vietnam remains a serious emerging arboviral disease, which generates significant concerns among international health authorities. Incidence rates of DF have increased significantly during the last few years in many provinces and cities, especially Hanoi. The purpose of this study was to detect DF hot spots and identify the disease dynamics dispersion of DF over the period between 2004 and 2009 in Hanoi, Vietnam. METHODS Daily data on DF cases and population data for each postcode area of Hanoi between January 1998 and December 2009 were obtained from the Hanoi Center for Preventive Health and the General Statistic Office of Vietnam. Moran's I statistic was used to assess the spatial autocorrelation of reported DF. Spatial scan statistics and logistic regression were used to identify space-time clusters and dispersion of DF. RESULTS The study revealed a clear trend of geographic expansion of DF transmission in Hanoi through the study periods (OR 1.17, 95% CI 1.02-1.34). The spatial scan statistics showed that 6/14 (42.9%) districts in Hanoi had significant cluster patterns, which lasted 29 days and were limited to a radius of 1,000 m. The study also demonstrated that most DF cases occurred between June and November, during which the rainfall and temperatures are highest. CONCLUSIONS There is evidence for the existence of statistically significant clusters of DF in Hanoi, and that the geographical distribution of DF has expanded over recent years. This finding provides a foundation for further investigation into the social and environmental factors responsible for changing disease patterns, and provides data to inform program planning for DF control.

Supplementary information : weighted tree kernels for sequence analysis

Genomic sequences are fundamentally text documents, admitting various representations according to need and tokenization. Gene expression depends crucially on binding of enzymes to the DNA sequence at small, poorly conserved binding sites, limiting the utility of standard pattern search. However, one may exploit the regular syntactic structure of the enzyme's component proteins and the corresponding binding sites, framing the problem as one of detecting grammatically correct genomic phrases. In this paper we propose new kernels based on weighted tree structures, traversing the paths within them to capture the features which underpin the task. Experimentally, we and that these kernels provide performance comparable with state of the art approaches for this problem, while offering significant computational advantages over earlier methods. The methods proposed may be applied to a broad range of sequence or tree-structured data in molecular biology and other domains.

Multilocus sequence analysis provides insights into molecular epidemiology of Chlamydia pecorum infections in Australian sheep, cattle and koalas

Chlamydia pecorum is a significant pathogen of domestic livestock and wildlife. We have developed a C. pecorum-specific multilocus sequence analysis (MLSA) scheme to examine the genetic diversity of and relationships between Australian sheep, cattle, and koala isolates. An MLSA of seven concatenated housekeeping gene fragments was performed using 35 isolates, including 18 livestock isolates (11 Australian sheep, one Australian cow, and six U.S. livestock isolates) and 17 Australian koala isolates. Phylogenetic analyses showed that the koala isolates formed a distinct clade, with limited clustering with C. pecorum isolates from Australian sheep. We identified 11 MLSA sequence types (STs) among Australian C. pecorum isolates, 10 of them novel, with koala and sheep sharing at least one identical ST (designated ST2013Aa). ST23, previously identified in global C. pecorum livestock isolates, was observed here in a subset of Australian bovine and sheep isolates. Most notably, ST23 was found in association with multiple disease states and hosts, providing insights into the transmission of this pathogen between livestock hosts. The complexity of the epidemiology of this disease was further highlighted by the observation that at least two examples of sheep were infected with different C. pecorum STs in the eyes and gastrointestinal tract. We have demonstrated the feasibility of our MLSA scheme for understanding the host relationship that exists between Australian C. pecorum strains and provide the first molecular epidemiological data on infections in Australian livestock hosts.

Visualization of predictive distributions for discrete spatial-temporal log Cox processes approximated with MCMC

An important aspect of decision support systems involves applying sophisticated and flexible statistical models to real datasets and communicating these results to decision makers in interpretable ways. An important class of problem is the modelling of incidence such as fire, disease etc. Models of incidence known as point processes or Cox processes are particularly challenging as they are ‘doubly stochastic’ i.e. obtaining the probability mass function of incidents requires two integrals to be evaluated. Existing approaches to the problem either use simple models that obtain predictions using plug-in point estimates and do not distinguish between Cox processes and density estimation but do use sophisticated 3D visualization for interpretation. Alternatively other work employs sophisticated non-parametric Bayesian Cox process models, but do not use visualization to render interpretable complex spatial temporal forecasts. The contribution here is to fill this gap by inferring predictive distributions of Gaussian-log Cox processes and rendering them using state of the art 3D visualization techniques. This requires performing inference on an approximation of the model on a discretized grid of large scale and adapting an existing spatial-diurnal kernel to the log Gaussian Cox process context.

An additive model for spatio-temporal smoothing of cancer mortality rates

In this paper, a Bayesian hierarchical model is used to anaylze the female breast cancer mortality rates for the State of Missouri from 1969 through 2001. The logit transformations of the mortality rates are assumed to be linear over the time with additive spatial and age effects as intercepts and slopes. Objective priors of the hierarchical model are explored. The Bayesian estimates are quite robustness in terms change of the hyperparamaters. The spatial correlations are appeared in both intercepts and slopes.

Temporal and functional changes in glycosaminoglycan expression during osteogenesis

Heparan sulfate proteoglycans (HSPGs) are complex and labile macromolecular moieties on the surfaces of cells that control the activities of a range of extracellular proteins, particularly those driving growth and regeneration. Here, we examine the biosynthesis of heparan sulfate (HS) sugars produced by cultured MC3T3-E1 mouse calvarial pre-osteoblast cells in order to explore the idea that changes in HS activity in turn drive phenotypic development during osteogenesis. Cells grown for 5 days under proliferating conditions were compared to cells grown for 20 days under mineralizing conditions with respect to their phenotype, the forms of HS core protein produced, and their HS sulfotransferase biosynthetic enzyme levels. RQ-PCR data was supported by the results from the purification of day 5 and day 20 HS forms by anionic exchange chromatography. The data show that cells in active growth phases produce more complex forms of sugar than cells that have become relatively quiescent during active mineralization, and that these in turn can differentially influence rates of cell growth when added exogenously back to preosteoblasts.

An efficient synthesis of (±)-frondosin B using a Stille–Heck reaction sequence

A concise, convergent synthesis of (±)-frondosin B has been developed based on the application of a Stille–Heck reaction sequence of 2-chloro-5-methoxybenzo[b]furan-3-yl triflate and 2-(3-butenyl)-3-(trimethylstannyl)cyclohex-2-enone giving the racemic natural product in a 34% overall yield.

Heterogeneity of clinical and environmental isolates of Mycobacterium fortuitum using repetitive element sequence-based PCR: municipal water an unlikely source of community-acquired infections

M. fortuitum is a rapidly growing mycobacterium associated with community-acquired and nosocomial wound, soft tissue, and pulmonary infections. It has been postulated that water has been the source of infection especially in the hospital setting. The aim of this study was to determine if municipal water may be the source of community-acquired or nosocomial infections in the Brisbane area. Between 2007 and 2009, 20 strains of M. fortuitum were recovered from municipal water and 53 patients’ isolates were submitted to the reference laboratory. A wide variation in strain types was identified using repetitive element sequence-based PCR, with 13 clusters of ≥2 indistinguishable isolates, and 28 patterns consisting of individual isolates. The clusters could be grouped into seven similar groups (>95% similarity). Municipal water and clinical isolates collected during the same time period and from the same geographical area consisted of different strain types, making municipal water an unlikely source of sporadic human infection.

Tracking spatio temporal movement of human in terms of space utilization using media access control address data

Using Media-Access-Control (MAC) address for data collection and tracking is a capable and cost effective approach as the traditional ways such as surveys and video surveillance have numerous drawbacks and limitations. Positioning cell-phones by Global System for Mobile communication was considered an attack on people's privacy. MAC addresses just keep a unique log of a WiFi or Bluetooth enabled device for connecting to another device that has not potential privacy infringements. This paper presents the use of MAC address data collection approach for analysis of spatio-temporal dynamics of human in terms of shared space utilization. This paper firstly discuses the critical challenges and key benefits of MAC address data as a tracking technology for monitoring human movement. Here, proximity-based MAC address tracking is postulated as an effective methodology for analysing the complex spatio-temporal dynamics of human movements at shared zones such as lounge and office areas. A case study of university staff lounge area is described in detail and results indicates a significant added value of the methodology for human movement tracking. By analysis of MAC address data in the study area, clear statistics such as staff’s utilisation frequency, utilisation peak periods, and staff time spent is obtained. The analyses also reveal staff’s socialising profiles in terms of group and solo gathering. The paper is concluded with a discussion on why MAC address tracking offers significant advantages for tracking human behaviour in terms of shared space utilisation with respect to other and more prominent technologies, and outlines some of its remaining deficiencies.