VIGOR, an annotation program for small viral genomes

<p>Abstract</p> <p>Background</p> <p>The decrease in cost for sequencing and improvement in technologies has made it easier and more common for the re-sequencing of large genomes as well as parallel sequencing of small genomes. It is possible to completely sequence a small genome within days and this increases the number of publicly available genomes. Among the types of genomes being rapidly sequenced are those of microbial and viral genomes responsible for infectious diseases. However, accurate gene prediction is a challenge that persists for decoding a newly sequenced genome. Therefore, accurate and efficient gene prediction programs are highly desired for rapid and cost effective surveillance of RNA viruses through full genome sequencing.</p> <p>Results</p> <p>We have developed VIGOR (Viral Genome ORF Reader), a web application tool for gene prediction in influenza virus, rotavirus, rhinovirus and coronavirus subtypes. VIGOR detects protein coding regions based on sequence similarity searches and can accurately detect genome specific features such as frame shifts, overlapping genes, embedded genes, and can predict mature peptides within the context of a single polypeptide open reading frame. Genotyping capability for influenza and rotavirus is built into the program. We compared VIGOR to previously described gene prediction programs, ZCURVE_V, GeneMarkS and FLAN. The specificity and sensitivity of VIGOR are greater than 99% for the RNA viral genomes tested.</p> <p>Conclusions</p> <p>VIGOR is a user friendly web-based genome annotation program for five different viral agents, influenza, rotavirus, rhinovirus, coronavirus and SARS coronavirus. This is the first gene prediction program for rotavirus and rhinovirus for public access. VIGOR is able to accurately predict protein coding genes for the above five viral types and has the capability to assign function to the predicted open reading frames and genotype influenza virus. The prediction software was designed for performing high throughput annotation and closure validation in a post-sequencing production pipeline.</p

Novel non-invasive algorithm to identify the origins of re-entry and ectopic foci in the atria from 64-lead ECGs: A computational study.

Atrial tachy-arrhytmias, such as atrial fibrillation (AF), are characterised by irregular electrical activity in the atria, generally associated with erratic excitation underlain by re-entrant scroll waves, fibrillatory conduction of multiple wavelets or rapid focal activity. Epidemiological studies have shown an increase in AF prevalence in the developed world associated with an ageing society, highlighting the need for effective treatment options. Catheter ablation therapy, commonly used in the treatment of AF, requires spatial information on atrial electrical excitation. The standard 12-lead electrocardiogram (ECG) provides a method for non-invasive identification of the presence of arrhythmia, due to irregularity in the ECG signal associated with atrial activation compared to sinus rhythm, but has limitations in providing specific spatial information. There is therefore a pressing need to develop novel methods to identify and locate the origin of arrhythmic excitation. Invasive methods provide direct information on atrial activity, but may induce clinical complications. Non-invasive methods avoid such complications, but their development presents a greater challenge due to the non-direct nature of monitoring. Algorithms based on the ECG signals in multiple leads (e.g. a 64-lead vest) may provide a viable approach. In this study, we used a biophysically detailed model of the human atria and torso to investigate the correlation between the morphology of the ECG signals from a 64-lead vest and the location of the origin of rapid atrial excitation arising from rapid focal activity and/or re-entrant scroll waves. A focus-location algorithm was then constructed from this correlation. The algorithm had success rates of 93% and 76% for correctly identifying the origin of focal and re-entrant excitation with a spatial resolution of 40 mm, respectively. The general approach allows its application to any multi-lead ECG system. This represents a significant extension to our previously developed algorithms to predict the AF origins in association with focal activities

An overview of burst, buckling, durability and corrosion analysis of lightweight FRP composite pipes and their applicability

© 2019 Elsevier Ltd. All rights reserved.The main aim of this review article was to address the performance of filament wound fibre reinforced polymer (FRP) composite pipes and their critical properties, such as burst, buckling, durability and corrosion. The importance of process parameters concerning merits and demerits of the manufacturing methods was discussed for the better-quality performance. Burst analysis revealed that the winding angle of ±55° was observed to be optimum with minimum failure mechanisms, such as matrix cracking, whitening, leakage and fracture. The reduction of buckling effect was reported in case of lower hoop stress value in the hoop to axial stress ratio against axial, compression and torsion. A significant improvement in energy absorption was observed in the hybrid composite pipes with the effect of thermal treatment. However, the varying winding angle in FRP pipe fabrication was reported as an influencing factor affecting all the aforementioned properties. Almost 90% of the reviewed studies was done using E-glass/epoxy materials for the composite pipe production. By overcoming associated limitations, such as replacing synthetic materials, designing new material combinations and cost-benefit analysis, the production cost of the lightweight FRP composite pipes can be decreased for the real-time applications.Peer reviewe

A Bayesian hierarchical approach for spatial analysis of climate model bias in multi-model ensembles

Coupled atmosphere–ocean general circulation models are key tools to investigate climate dynamics and the climatic response to external forcings, to predict climate evolution and to generate future climate projections. Current general circulation models are, however, undisputedly affected by substantial systematic errors in their outputs compared to observations. The assessment of these so-called biases, both individually and collectively, is crucial for the models’ evaluation prior to their predictive use. We present a Bayesian hierarchical model for a unified assessment of spatially referenced climate model biases in a multi-model framework. A key feature of our approach is that the model quantifies an overall common bias that is obtained by synthesizing bias across the different climate models in the ensemble, further determining the contribution of each model to the overall bias. Moreover, we determine model-specific individual bias components by characterizing them as non-stationary spatial fields. The approach is illustrated based on the case of near-surface air temperature bias in the tropical Atlantic and bordering regions from a multi-model ensemble of historical simulations from the fifth phase of the Coupled Model Intercomparison Project. The results demonstrate the improved quantification of the bias and interpretative advantages allowed by the posterior distributions derived from the proposed Bayesian hierarchical framework, whose generality favors its broader application within climate model assessment

Spermiogenesis deficiency and germ-cell apoptosis in CREM-mutant mice

Spermiogenesis is a complex process by which postmeiotic male germ cells differentiate into mature spermatozoa. This process involves remarkable structural and biochemical changes including nuclear DNA compaction and acrosome formation(1,2). Transcriptional activator CREM (cyclic AMP-responsive element modulator) is highly expressed in postmeiotic cells(3-5), and CREM may be responsible for the activation of several haploid germ cell-specific genes involved in the structuring of the spermatozoon(5-7). The specific role of CREM in spermiogenesis was addressed using CREM-mutant mice generated by homologous recombination. Analysis of the seminiferous epithelium in mutant male mice reveals postmeiotic arrest at the first step of spermiogenesis. Late spermatids are completely absent, and there is a significant increase in apoptotic germ cells. We show that CREM deficiency results in the lack of postmeiotic cell-specific gene expression. The complete lack of spermatozoa in the mutant mice is reminiscent of cases of human infertility