Comparative genomics of Burkholderia singularis sp. nov., a low G+C content, free-living bacterium that defies taxonomic dissection of the genus Burkholderia

Four Burkholderia pseudomallei-like isolates of human clinical origin were examined by a polyphasic taxonomic approach that included comparative whole genome analyses. The results demonstrated that these isolates represent a rare and unusual, novel Burkholderia species for which we propose the name B. singularis. The type strain is LMG 28154(T) (=CCUG 65685(T)). Its genome sequence has an average mol% G+C content of 64.34%, which is considerably lower than that of other Burkholderia species. The reduced G+C content of strain LMG 28154(T) was characterized by a genome wide AT bias that was not due to reduced GC-biased gene conversion or reductive genome evolution, but might have been caused by an altered DNA base excision repair pathway. B. singularis can be differentiated from other Burkholderia species by multilocus sequence analysis, MALDI-TOF mass spectrometry and a distinctive biochemical profile that includes the absence of nitrate reduction, a mucoid appearance on Columbia sheep blood agar, and a slowly positive oxidase reaction. Comparisons with publicly available whole genome sequences demonstrated that strain TSV85, an Australian water isolate, also represents the same species and therefore, to date, B. singularis has been recovered from human or environmental samples on three continents

A modelling framework for the prediction of the herd-level probability of infection from longitudinal data

International audienceThe collective control programmes (CPs) that exist for many infectious diseases of farm animals rely on the application of diagnostic testing at regular time intervals for the identification of infected animals or herds. The diversity of these CPs complicates the trade of animals between regions or countries because the definition of freedom from infection differs from one CP to another. In this paper, we describe a statistical model for the prediction of herd-level probabilities of infection from longitudinal data collected as part of CPs against infectious diseases of cattle. The model was applied to data collected as part of a CP against bovine viral diarrhoea virus (BVDV) infection in Loire-Atlantique, France. The model represents infection as a herd latent status with a monthly dynamics. This latent status determines test results through test sensitivity and test specificity. The probability of becoming status positive between consecutive months is modelled as a function of risk factors (when available) using logistic regression. Modelling is performed in a Bayesian framework, using either Stan or JAGS. Prior distributions need to be provided for the sensitivities and specificities of the different tests used, for the probability of remaining status positive between months as well as for the probability of becoming positive between months. When risk factors are available, prior distributions need to be provided for the coefficients of the logistic regression, replacing the prior for the probability of becoming positive. From these prior distributions and from the longitudinal data, the model returns posterior probability distributions for being status positive for all herds on the current month. Data from the previous months are used for parameter estimation. The impact of using different prior distributions and model implementations on parameter estimation was evaluated. The main advantage of this model is its ability to predict a probability of being status positive in a month from inputs that can vary in terms of nature of test, frequency of testing and risk factor availability/presence. The main challenge in applying the model to the BVDV CP data was in identifying prior distributions, especially for test characteristics, that corresponded to the latent status of interest, i.e. herds with at least one persistently infected (PI) animal. The model is available on Github as an R package (https://github.com/AurMad/STOCfree) and can be used to carry out output-based evaluation of disease CPs

Existence and Quality of Data on Control Programs for EU Non-regulated Cattle Diseases: Consequences for Estimation and Comparison of the Probability of Freedom From Infection

Some European countries have successfully implemented country-specific control programs (CPs) for infectious cattle diseases that are not regulated or are regulated only to a limited extent at the European Union (EU) level. Examples of such diseases include bovine viral diarrhea (BVD), infectious bovine rhinotracheitis (IBR), and Johne's disease (JD). The CPs vary between countries in the design and quality of collected data as well as methods used to detect infection and estimate prevalence or probability of freedom from infection. Differences in disease status between countries and non-standardized approaches to assess freedom from infection pose a risk for countries with CPs for non-regulated diseases as infected animals may influence the progress of the disease control or eradication program. The implementation of output-based standards allows estimation and comparison of the probability of freedom for non-regulated cattle diseases in European countries. The aim of the current study was to assess the existence and quality of data that could be used for estimating freedom from infection in European countries. The online data collection tool was sent to 32 countries participating in the SOUND control COST Action and was completed by 24 countries. Data on cattle demographics and data from CPs of IBR and BVD exist in more than 50% of the response countries. However, data describing risk factors and CP of JD was reported as existing in < 25% of the countries. The overall quality of data in the sections on demographics and CPs of IBR and BVD were evaluated as "good ", but risk factors and JD data were mostly evaluated as "fair. " Data quality was considered less good mainly due to two quality criteria: accessibility and accuracy. The results of this study show that the quantity and quality of data about cattle populations and CPs are relatively similar in many surveyed countries. The outcome of this work provides an overview of the current situation in the European countries regarding data on EU non-regulated cattle diseases and will further assist in the development and implementation of output-based standards

JWST CEERS probes the role of stellar mass and morphology in obscuring galaxies

A population of massive galaxies invisible or very faint in deep optical/near-infrared surveys, but brighter at longer wavelengths has been uncovered in the past years. However, the nature of these optically dark/faint galaxies (OFGs, among other nomenclatures) is highly uncertain. In this work, we investigate the drivers of dust attenuation in the JWST era. Particularly, we study the role of stellar mass, size, and orientation in obscuring star-forming galaxies (SFGs) at $3 < z < 7.5$, focusing on understanding why galaxies like OFGs are so faint at optical/near-infrared wavelengths. We find that stellar mass is the primary proxy of dust attenuation among those studied. Effective radius and axis ratio do not show a clear link with dust attenuation, with the effect of orientation close to random. However, there is a subset of highly dust attenuated ($A_V > 1$, typically) SFGs, of which OFGs are a specific case. For this subset, we find that the key distinctive feature is their compact size (for massive systems with $\log (M_{*}/M_{\odot}) > 10$), exhibiting 30% smaller effective radius than the average SFGs at the same stellar mass and redshift. On the contrary, they do not exhibit a preference for low axis ratios (i.e., edge-on disks). The results in this work show stellar mass as a primary proxy of dust attenuation and compact stellar light profiles behind thick dust columns obscuring typical massive SFGs.Comment: Submitted to A&A. 13 pages, 9 figure

A framework for assessing confidence in freedom from infection in animal disease control programmes

In the Surveillance Tool for Outcome-based Comparison of FREEdom from infection (STOC free) project (https://www.stocfree.eu), a data collection tool was constructed to facilitate standardised collection of input data, and a model was developed to allow a standardised and harmonised comparison of the outputs of different control programmes (CPs) for cattle diseases. The STOC free model can be used to evaluate the probability of freedom from infection for herds in CPs and to determine whether these CPs comply with the European Union's pre-defined output-based standards. Bovine viral diarrhoea virus (BVDV) was chosen as the case disease for this project because of the diversity in CPs in the six participating countries. Detailed BVDV CP and risk factor information was collected using the data collection tool. For inclusion of the data in the STOC free model, key aspects and default values were quantified. A Bayesian hidden Markov model was deemed appropriate, and a model was developed for BVDV CPs. The model was tested and validated using real BVDV CP data from partner countries, and corresponding computer code was made publicly available. The STOC free model focuses on herd-level data, although that animal-level data can be included after aggregation to herd level. The STOC free model is applicable to diseases that are endemic, given that it needs the presence of some infection to estimate parameters and enable convergence. In countries where infection-free status has been achieved, a scenario tree model could be a better suited tool. Further work is recommended to generalise the STOC free model to other diseases

The E-ELT first light spectrograph HARMONI: capabilities and modes

Trabajo presentado en SPIE Astronomical Telescopes, celebrado en San Diego (California), del 26 de junio al 1 de julio de 2016HARMONI is the E-ELT's first light visible and near-infrared integral field spectrograph. It will provide four different spatial scales, ranging from coarse spaxels of 60 × 30 mas best suited for seeing limited observations, to 4 mas spaxels that Nyquist sample the diffraction limited point spread function of the E-ELT at near-infrared wavelengths. Each spaxel scale may be combined with eleven spectral settings, that provide a range of spectral resolving powers (R 3500, 7500 and 20000) and instantaneous wavelength coverage spanning the 0.5 - 2.4 ¿m wavelength range of the instrument. In autumn 2015, the HARMONI project started the Preliminary Design Phase, following signature of the contract to design, build, test and commission the instrument, signed between the European Southern Observatory and the UK Science and Technology Facilities Council. Crucially, the contract also includes the preliminary design of the HARMONI Laser Tomographic Adaptive Optics system. The instrument's technical specifications were finalized in the period leading up to contract signature. In this paper, we report on the first activity carried out during preliminary design, defining the baseline architecture for the system, and the trade-off studies leading up to the choice of baseline

MUSiC : a model-unspecific search for new physics in proton-proton collisions at root s=13TeV

Results of the Model Unspecific Search in CMS (MUSiC), using proton-proton collision data recorded at the LHC at a centre-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 35.9 fb(-1), are presented. The MUSiC analysis searches for anomalies that could be signatures of physics beyond the standard model. The analysis is based on the comparison of observed data with the standard model prediction, as determined from simulation, in several hundred final states and multiple kinematic distributions. Events containing at least one electron or muon are classified based on their final state topology, and an automated search algorithm surveys the observed data for deviations from the prediction. The sensitivity of the search is validated using multiple methods. No significant deviations from the predictions have been observed. For a wide range of final state topologies, agreement is found between the data and the standard model simulation. This analysis complements dedicated search analyses by significantly expanding the range of final states covered using a model independent approach with the largest data set to date to probe phase space regions beyond the reach of previous general searches.Peer reviewe

Measurement of prompt open-charm production cross sections in proton-proton collisions at root s=13 TeV

The production cross sections for prompt open-charm mesons in proton-proton collisions at a center-of-mass energy of 13TeV are reported. The measurement is performed using a data sample collected by the CMS experiment corresponding to an integrated luminosity of 29 nb(-1). The differential production cross sections of the D*(+/-), D-+/-, and D-0 ((D) over bar (0)) mesons are presented in ranges of transverse momentum and pseudorapidity 4 < p(T) < 100 GeV and vertical bar eta vertical bar < 2.1, respectively. The results are compared to several theoretical calculations and to previous measurements.Peer reviewe