Identification and Differentiation of the Twenty Six Bluetongue Virus Serotypes by RT–PCR Amplification of the Serotype-Specific Genome Segment 2

Bluetongue (BT) is an arthropod-borne viral disease, which primarily affects ruminants in tropical and temperate regions of the world. Twenty six bluetongue virus (BTV) serotypes have been recognised worldwide, including nine from Europe and fifteen in the United States. Identification of BTV serotype is important for vaccination programmes and for BTV epidemiology studies. Traditional typing methods (virus isolation and serum or virus neutralisation tests (SNT or VNT)) are slow (taking weeks, depend on availability of reference virus-strains or antisera) and can be inconclusive. Nucleotide sequence analyses and phylogenetic comparisons of genome segment 2 (Seg-2) encoding BTV outer-capsid protein VP2 (the primary determinant of virus serotype) were completed for reference strains of BTV-1 to 26, as well as multiple additional isolates from different geographic and temporal origins. The resulting Seg-2 database has been used to develop rapid (within 24 h) and reliable RT–PCR-based typing assays for each BTV type. Multiple primer-pairs (at least three designed for each serotype) were widely tested, providing an initial identification of serotype by amplification of a cDNA product of the expected size. Serotype was confirmed by sequencing of the cDNA amplicons and phylogenetic comparisons to previously characterised reference strains. The results from RT-PCR and sequencing were in perfect agreement with VNT for reference strains of all 26 BTV serotypes, as well as the field isolates tested. The serotype-specific primers showed no cross-amplification with reference strains of the remaining 25 serotypes, or multiple other isolates of the more closely related heterologous BTV types. The primers and RT–PCR assays developed in this study provide a rapid, sensitive and reliable method for the identification and differentiation of the twenty-six BTV serotypes, and will be updated periodically to maintain their relevance to current BTV distribution and epidemiology (http://www.reoviridae.org/dsRNA_virus_proteins/ReoID/rt-pcr-primers.htm)

Use of mixed methods designs in substance research: a methodological necessity in Nigeria

The utility of mixed methods (qualitative and quantitative) is becoming increasingly accepted in health sciences, but substance studies are yet to substantially benefit from such utilities. While there is a growing number of mixed methods alcohol articles concerning developed countries, developing nations are yet to embrace this method. In the Nigerian context, the importance of mixed methods research is yet to be acknowledged. This article therefore, draws on alcohol studies to argue that mixed methods designs will better equip scholars to understand, explore, describe and explain why alcohol consumption and its related problems are increasing in Nigeria. It argues that as motives for consuming alcohol in contemporary Nigeria are multiple, complex and evolving, mixed method approaches that provide multiple pathways for proffering solutions to problems should be embraced

Solitary waves in the Nonlinear Dirac Equation

In the present work, we consider the existence, stability, and dynamics of solitary waves in the nonlinear Dirac equation. We start by introducing the Soler model of self-interacting spinors, and discuss its localized waveforms in one, two, and three spatial dimensions and the equations they satisfy. We present the associated explicit solutions in one dimension and numerically obtain their analogues in higher dimensions. The stability is subsequently discussed from a theoretical perspective and then complemented with numerical computations. Finally, the dynamics of the solutions is explored and compared to its non-relativistic analogue, which is the nonlinear Schr{\"o}dinger equation. A few special topics are also explored, including the discrete variant of the nonlinear Dirac equation and its solitary wave properties, as well as the PT-symmetric variant of the model

Childhood leukaemia: long-term excess mortality and the proportion ‘cured'

Survival from childhood leukaemia has increased, but the proportion of children cured is unknown. The proportion ‘cured' is defined as the proportion of survivors for whom, as a group, there is no longer excess mortality compared to the general population. Average time to cure is defined as the time since diagnosis at which the excess mortality rate has declined to or below a predetermined small value. Data on children diagnosed with leukaemia during 1971–2000 in Great Britain were used to estimate trends in survival, the proportion cured and the average time to cure. Five-year survival for all types of leukaemia combined rose from 33 to 79% by 2000. The percentage cured rose from 25 to 68% by 1995; it is predicted to increase to 73% for those diagnosed more recently. Average time to cure increased from 12 years (95% confidence interval (CI): 11–14) to 19 years (95% CI: 14–26) for lymphoid leukaemia (average annual increase of 0.3 years; P<0.001), but remained at about 5 years for acute nonlymphoblastic leukaemia. The proportion of children cured of leukaemia has risen dramatically, but the period of excess mortality associated with lymphoid leukaemia has also increased, possibly because of late relapse, secondary malignancy and toxicity from treatment

Safety, tolerability and sustained weight loss over 2 years with the once-daily human GLP-1 analog, liraglutide

Objective: Having demonstrated short-term weight loss with liraglutide in this group of obese adults, we now evaluate safety/tolerability (primary outcome) and long-term efficacy for sustaining weight loss (secondary outcome) over 2 years. &lt;p/&gt;Design: A randomized, double-blind, placebo-controlled 20-week study with 2-year extension (sponsor unblinded at 20 weeks, participants/investigators at 1 year) in 19 European clinical research centers. &lt;p/&gt;Subjects: A total of 564 adults (n=90–98 per group; body mass index 30–40 kg m−2) enrolled, 398 entered the extension and 268 completed the 2-year trial. Participants received diet (500 kcal deficit per day) and exercise counseling during 2-week run-in, before being randomly assigned (with a telephone or web-based system) to once-daily subcutaneous liraglutide (1.2, 1.8, 2.4 or 3.0 mg, n=90–95), placebo (n=98) or open-label orlistat (120 mg × 3, n=95). After 1 year, liraglutide/placebo recipients switched to liraglutide 2.4 mg, then 3.0 mg (based on 20-week and 1-year results, respectively). The trial ran from January 2007–April 2009 and is registered with Clinicaltrials.gov, number NCT00480909. &lt;p/&gt;Results: From randomization to year 1, liraglutide 3.0 mg recipients lost 5.8 kg (95% confidence interval 3.7–8.0) more weight than those on placebo and 3.8 kg (1.6–6.0) more than those on orlistat (Pless than or equal to0.0001; intention-to-treat, last-observation-carried-forward). At year 2, participants on liraglutide 2.4/3.0 mg for the full 2 years (pooled group, n=184) lost 3.0 kg (1.3–4.7) more weight than those on orlistat (n=95; P&#60;0.001). Completers on liraglutide 2.4/3.0 mg (n=92) maintained a 2-year weight loss of 7.8 kg from screening. With liraglutide 3.0 mg, 20-week body fat decreased by 15.4% and lean tissue by 2.0%. The most frequent drug-related side effects were mild to moderate, transient nausea and vomiting. With liraglutide 2.4/3.0 mg, the 2-year prevalence of prediabetes and metabolic syndrome decreased by 52 and 59%, with improvements in blood pressure and lipids. &lt;p/&gt;Conclusion: Liraglutide is well tolerated, sustains weight loss over 2 years and improves cardiovascular risk factors

Analysis of laser radiation using the Nonlinear Fourier transform

Modern high-power lasers exhibit a rich diversity of nonlinear dynamics, often featuring nontrivial co-existence of linear dispersive waves and coherent structures. While the classical Fourier method adequately describes extended dispersive waves, the analysis of time-localised and/or non-stationary signals call for more nuanced approaches. Yet, mathematical methods that can be used for simultaneous characterisation of localized and extended fields are not yet well developed. Here, we demonstrate how the Nonlinear Fourier transform (NFT) based on the Zakharov-Shabat spectral problem can be applied as a signal processing tool for representation and analysis of coherent structures embedded into dispersive radiation. We use full-field, real-time experimental measurements of mode-locked pulses to compute the nonlinear pulse spectra. For the classification of lasing regimes, we present the concept of eigenvalue probability distributions. We present two field normalisation approaches, and show the NFT can yield an effective model of the laser radiation under appropriate signal normalisation conditions

Using combined diagnostic test results to hindcast trends of infection from cross-sectional data

Infectious disease surveillance is key to limiting the consequences from infectious pathogens and maintaining animal and public health. Following the detection of a disease outbreak, a response in proportion to the severity of the outbreak is required. It is thus critical to obtain accurate information concerning the origin of the outbreak and its forward trajectory. However, there is often a lack of situational awareness that may lead to over- or under-reaction. There is a widening range of tests available for detecting pathogens, with typically different temporal characteristics, e.g. in terms of when peak test response occurs relative to time of exposure. We have developed a statistical framework that combines response level data from multiple diagnostic tests and is able to ‘hindcast’ (infer the historical trend of) an infectious disease epidemic. Assuming diagnostic test data from a cross-sectional sample of individuals infected with a pathogen during an outbreak, we use a Bayesian Markov Chain Monte Carlo (MCMC) approach to estimate time of exposure, and the overall epidemic trend in the population prior to the time of sampling. We evaluate the performance of this statistical framework on simulated data from epidemic trend curves and show that we can recover the parameter values of those trends. We also apply the framework to epidemic trend curves taken from two historical outbreaks: a bluetongue outbreak in cattle, and a whooping cough outbreak in humans. Together, these results show that hindcasting can estimate the time since infection for individuals and provide accurate estimates of epidemic trends, and can be used to distinguish whether an outbreak is increasing or past its peak. We conclude that if temporal characteristics of diagnostics are known, it is possible to recover epidemic trends of both human and animal pathogens from cross-sectional data collected at a single point in time

Multi-model seascape genomics identifies distinct environmental drivers of selection among sympatric marine species

Background As global change and anthropogenic pressures continue to increase, conservation and management increasingly needs to consider species’ potential to adapt to novel environmental conditions. Therefore, it is imperative to characterise the main selective forces acting on ecosystems, and how these may influence the evolutionary potential of populations and species. Using a multi-model seascape genomics approach, we compare putative environmental drivers of selection in three sympatric southern African marine invertebrates with contrasting ecology and life histories: Cape urchin (Parechinus angulosus), Common shore crab (Cyclograpsus punctatus), and Granular limpet (Scutellastra granularis). Results Using pooled (Pool-seq), restriction-site associated DNA sequencing (RAD-seq), and seven outlier detection methods, we characterise genomic variation between populations along a strong biogeographical gradient. Of the three species, only S. granularis showed significant isolation-by-distance, and isolation-by-environment driven by sea surface temperatures (SST). In contrast, sea surface salinity (SSS) and range in air temperature correlated more strongly with genomic variation in C. punctatus and P. angulosus. Differences were also found in genomic structuring between the three species, with outlier loci contributing to two clusters in the East and West Coasts for S. granularis and P. angulosus, but not for C. punctatus. Conclusion The findings illustrate distinct evolutionary potential across species, suggesting that species-specific habitat requirements and responses to environmental stresses may be better predictors of evolutionary patterns than the strong environmental gradients within the region. We also found large discrepancies between outlier detection methodologies, and thus offer a novel multi-model approach to identifying the principal environmental selection forces acting on species. Overall, this work highlights how adding a comparative approach to seascape genomics (both with multiple models and species) can elucidate the intricate evolutionary responses of ecosystems to global change