Serotypes and Spa types of Erysipelothrix rhusiopathiae isolates from British pigs (1987 to 2015)

'Erysipelothrix' spp. cause a range of clinical signs in pigs and at least 28 different 'Erysipelothrix' spp. serotypes have been identified. In this study, 128 isolates of 'Erysipelothrix' spp. from pigs in Great Britain from 1987 to 2015 were characterised by serotyping and multiplex real time PCR assays targeting the surface protective antigen (Spa) and the main genotypes ('Erysipelothrix rhusiopathiae', 'Erysipelothrix tonsillarum' and 'Erysipelothrix' spp. strain 2). All 128 British isolates were characterised as 'E. rhusiopathiae' and were classified as serotypes 1a (n = 21), 1b (n = 17), 2 (n = 75), 5 (n = 2), 9 (n = 2), 10 (n = 2), 11 (n = 4) and 15 (n = 1), while four isolates were untypeable. All isolates were positive for the spa A gene. Serotypes 1a, 1b and 2 constituted 88.3% of the isolates; current serotype 2 based vaccines should protect against these isolates

Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization

Gravitational waves from compact binaries measured by the LIGO and Virgo detectors are routinely analyzed using Markov Chain Monte Carlo sampling algorithms. Because the evaluation of the likelihood function requires evaluating millions of waveform models that link between signal shapes and the source parameters, running Markov chains until convergence is typically expensive and requires days of computation. In this extended abstract, we provide a proof of concept that demonstrates how the latest advances in neural simulation-based inference can speed up the inference time by up to three orders of magnitude -- from days to minutes -- without impairing the performance. Our approach is based on a convolutional neural network modeling the likelihood-to-evidence ratio and entirely amortizes the computation of the posterior. We find that our model correctly estimates credible intervals for the parameters of simulated gravitational waves.Comment: V1: First version; V2: Updated references; V3: Update references and camera-ready version; V4: Correct figure labels; V5: Updated reference

Genomic and immunogenic protein diversity of Erysipelothrix rhusiopathiae isolated from pigs in Great Britain: implications for vaccine protection

Erysipelas, caused by the bacterium Erysipelothrix rhusiopathiae, is re-emerging in swine and poultry production systems worldwide. While the global genomic diversity of this species has been characterized, how much of this genomic and functional diversity is maintained at smaller scales is unclear. Specifically, while several key immunogenic surface proteins have been identified for E. rhusiopathiae, little is known about their presence among field strains and their divergence from vaccines, which could result in vaccine failure. Here, a comparative genomics approach was taken to determine the diversity of E. rhusiopathiae strains in pigs in Great Britain over nearly three decades, as well as to assess the field strains’ divergence from the vaccine strain most commonly used in British pigs. In addition, the presence/absence and variability of 13 previously described immunogenic surface proteins was determined, including SpaA which is considered a key immunogen. We found a high diversity of E. rhusiopathiae strains in British pigs, similar to the situation described in European poultry but in contrast to swine production systems in Asia. Of the four clades of E. rhusiopathiae found globally, three were represented among British pig isolates, with Clade 2 being the most common. All British pig isolates had one amino acid difference in the immunoprotective domain of the SpaA protein compared to the vaccine strain. However, we were able to confirm using in silico structural protein analyses that this difference is unlikely to compromise vaccine protection. Of 12 other known immunogenic surface proteins of E. rhusiopathiae examined, 11 were found to be present in all British pig isolates and the vaccine strain, but with highly variable degrees of conservation at the amino acid sequence level, ranging from 0.3 to 27% variant positions. Moreover, the phylogenetic incongruence of these proteins suggests that horizontal transfer of genes encoding for antigens is commonplace for this bacterium. We hypothesize that the sequence variants in these proteins could be responsible for differences in the efficacy of the immune response. Our results provide the necessary basis for testing this hypothesis through in vitro and in vivo studies

Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization

Gravitational waves from compact binaries measured by the LIGO and Virgo detectors are routinely analyzed using Markov Chain Monte Carlo sampling algorithms. Because the evaluation of the likelihood function requires evaluating millions of waveform models that link between signal shapes and the source parameters, running Markov chains until convergence is typically expensive and requires days of computation. In this extended abstract, we provide a proof of concept that demonstrates how the latest advances in neural simulation-based inference can speed up the inference time by up to three orders of magnitude – from days to minutes – without impairing the performance. Our approach is based on a convolutional neural network modeling the likelihood-to-evidence ratio and entirely amortizes the computation of the posterior. We find that our model correctly estimates credible intervals for the parameters of simulated gravitational waves

Distinguishing the nature of comparable-mass neutron star binary systems with multimessenger observations: GW170817 case study

The discovery of GW170817 with gravitational waves (GWs) and electromagnetic (EM) radiation is prompting new questions in strong-gravity astrophysics. Importantly, it remains unknown whether the progenitor of the merger comprised two neutron stars (NSs), or a NS and a black hole (BH). Using new numerical-relativity simulations and incorporating modeling uncertainties we produce novel GW and EM observables for NS-BH mergers with similar masses. A joint analysis of GW and EM measurements reveals that if GW170817 is a NS-BH merger, <40% of the binary parameters consistent with the GW data are compatible with EM observations.Comment: 8 page

Collagen-an important fish allergen for improved diagnosis

Background Fish collagen is widely used in medicine, cosmetics, and the food industry. However, its clinical relevance as an allergen is not fully appreciated. This is likely due to collagen insolubility in neutral aqueous solutions, leading to low abundance in commercially available in vitro and skin prick tests for fish allergy. Objective To investigate the relevance of fish collagen as an allergen in a large patient population (n = 101). Methods Acid-soluble collagen type I was extracted from muscle and skin of Atlantic salmon, barramundi, and yellowfin tuna. IgE binding to collagen was analyzed by ELISA for 101 fish-allergic patients. Collagen-sensitized patients' sera were tested for IgE binding to parvalbumin from the same fish species. IgE cross-linking was analyzed by rat basophil leukemia assay and basophil activation test. Protein identities were confirmed by mass spectrometry. Results Purified fish collagen contained type I α1 and α2 chains and their multimers. Twenty-one of 101 patients (21%) were sensitized to collagen. Eight collagen-sensitized patients demonstrated absence of parvalbumin-specific IgE to some fish species. Collagen induced functional IgE cross-linking, as shown by rat basophil leukemia assay performed using 6 patients' sera, and basophil activation test using fresh blood from 1 patient. Collagen type I α chains from barramundi and Atlantic salmon were registered at www.allergen.org as Lat c 6 and Sal s 6, respectively. Conclusions IgE sensitization and IgE cross-linking capacity of fish collagen were demonstrated in fish-allergic patients. Inclusion of relevant collagen allergens in routine diagnosis is indicated to improve the capacity to accurately diagnose fish allergy

The Future of Indiana’s Water Resources: A Report from the Indiana Climate Change Impacts Assessment

This report from the Indiana Climate Change Impacts Assessment (IN CCIA) applies climate change projections for the state to explore how continued changes in Indiana’s climate are going to affect all aspects of water resources, including soil water, evaporation, runoff, snow cover, streamflow, drought, and flooding. As local temperatures continue to rise and rainfall patterns shift, managing the multiple water needs of communities, natural systems, recreation, industry, and agriculture will become increasingly difficult. Ensuring that enough water is available in the right places and at the right times will require awareness of Indiana’s changing water resources and planning at regional and state levels

Single and multiple dose pharmacokinetics of maritime pine bark extract (Pycnogenol) after oral administration to healthy volunteers

BACKGROUND: Since plant extracts are increasingly used as phytotherapeutics or dietary supplements information on bioavailability, bioefficacy and safety are warranted. We elucidated the plasma kinetics of genuine extract components and metabolites after single and multiple ingestion of the standardized maritime pine bark extract Pycnogenol (USP quality) by human volunteers. METHODS: Eleven volunteers received a single dose of 300 mg pine bark extract, five volunteers ingested 200 mg daily for five days to reach steady state concentrations. Plasma samples were obtained before and at defined time points after intake of the extract. Samples were analyzed by HPLC with ion-pair reagents and simultaneous UV and electrochemical detection. RESULTS: We quantified total plasma concentrations of catechin, caffeic acid, ferulic acid, taxifolin and the metabolite M1 (δ-(3,4-dihydroxy-phenyl)-γ-valerolactone). Additionally, we describe plasma time courses and steady state appearance of ten so far unknown compounds, U1 to U10. After single ingestion, compounds derived from the extract were rapidly absorbed and the majority of them were detectable over whole experimental period of 14 h. The analysis of steady state plasma samples revealed significant phase II metabolism. CONCLUSION: We present the first systematic pharmacokinetic analysis of compounds derived from maritime pine bark extract. Beyond the known constituents and metabolites we uncovered the plasma time courses of ten unknown compounds. In concert with our previous detection of anti-inflammatory bioefficacy of these plasma samples ex vivo we suggest that constituents and metabolites of Pycnogenol bear potential for disclosure of novel active principles

Reduced Efficacy of Natural Selection on Codon Usage Bias in Selfing Arabidopsis and Capsella Species

Population genetic theory predicts that the efficacy of natural selection in a self-fertilizing species should be lower than its outcrossing relatives because of the reduction in the effective population size (Ne) in the former brought about by inbreeding. However, previous analyses comparing Arabidopsis thaliana (selfer) with A. lyrata (outcrosser) have not found conclusive support for this prediction. In this study, we addressed this issue by examining silent site polymorphisms (synonymous and intronic), which are expected to be informative about changes in Ne. Two comparisons were made: A. thaliana versus A. lyrata and Capsella rubella (selfer) versus C. grandiflora (outcrosser). Extensive polymorphism data sets were obtained by compiling published data from the literature and by sequencing 354 exon loci in C. rubella and 89 additional loci in C. grandiflora. To extract information from the data effectively for studying these questions, we extended two recently developed models in order to investigate detailed selective differences between synonymous codons, mutational biases, and biased gene conversion (BGC), taking into account the effects of recent changes in population size. We found evidence that selection on synonymous codons is significantly weaker in the selfers compared with the outcrossers and that this difference cannot be fully accounted for by mutational biases or BGC