Abstract
Transition discs are prime targets to look for protoplanets and study planet–disc interactions. We present VLT/SINFONI observations of PDS 70, a transition disc with a recently claimed ...embedded protoplanet. We take advantage of the angular and spectral diversity present in our data for an optimal PSF modelling and subtraction using principal component analysis (PCA). We report the redetection of PDS 70 b, both the front and far side of the outer disc edge, and the detection of several extended features in the annular gap. We compare spectral differential imaging applied before (PCA-SADI), and after (PCA-ASDI) angular differential imaging. Our tests suggest that PCA-SADI better recovers extended features, while PCA-ASDI is more sensitive to point sources. We adapted the negative fake companion (NEGFC) technique to infer the astrometry of the companion, and derived r = 193.5 ± 4.9 mas and PA =158.7○ ± 3.0○. We used both NEGFC and ANDROMEDA to infer the K-band spectro-photometry of the protoplanet, and found results consistent with recent VLT/SPHERE observations, except for their 2018/02 epoch measurement in the K2 filter. Finally, we derived an upper limit of $\dot{M_b} \lt 1.26 \times 10^{-7} \big \frac{5 M_{\rm Jup}}{M_b} \big \big \frac{R_b}{R_{\rm Jup}}\big M_{\rm Jup}$ yr−1 for the accretion rate of the companion based on an adaptation of PCA-SADI/PCA-ASDI around the Brγ line (assuming no extinction).
The ankle brachial index (ABI) is related to risk of cardiovascular events independent of the Framingham risk score (FRS). The aim of this study was to develop and evaluate a risk model for ...cardiovascular events incorporating the ABI and FRS.
An analysis of participant data from 18 cohorts in which 24,375 men and 20,377 women free of coronary heart disease had ABI measured and were followed up for events.
Subjects were divided into a development and internal validation dataset and an external validation dataset. Two models, comprising FRS and FRS + ABI, were fitted for the primary outcome of major coronary events.
In predicting events in the external validation dataset, C-index for the FRS was 0.672 (95% CI 0.599 to 0.737) in men and 0.578 (95% CI 0.492 to 0.661) in women. The FRS + ABI led to a small increase in C-index in men to 0.685 (95% CI 0.612 to 0.749) and large increase in women to 0.690 (95% CI 0.605 to 0.764) with net reclassification improvement (NRI) of 4.3% (95% CI 0.0 to 7.6%, p = 0.050) and 9.6% (95% CI 6.1 to 16.4%, p < 0.001), respectively. Restricting the FRS + ABI model to those with FRS intermediate 10-year risk of 10 to 19% resulted in higher NRI of 15.9% (95% CI 6.1 to 20.6%, p < 0.001) in men and 23.3% (95% CI 13.8 to 62.5%, p = 0.002) in women. However, incorporating ABI in an improved newly fitted risk factor model had a nonsignificant effect: NRI 2.0% (95% CI 2.3 to 4.2%, p = 0.567) in men and 1.1% (95% CI 1.9 to 4.0%, p = 0.483) in women.
An ABI risk model may improve prediction especially in individuals at intermediate risk and when performance of the base risk factor model is modest.
Salmonella is a widespread foodborne pathogen that can exhibit multidrug resistance (MDR; resistance to ≥3 antimicrobial classes). Therefore, the development of new preventative measures against MDR ...Salmonella is highly important. Bacterial antibiotic resistance is commonly mediated by efflux pumps. In this study, two compounds that block efflux pump activity, 1-(1-Naphthylmethyl)-Piperazine (NMP) and Phenylalanine-arginine β-naphthylamide (PaβN), were tested with the antibiotic tetracycline to determine if a synergistic reduction in resistance could be achieved in tetracycline-resistant Salmonella. The efflux pump inhibitors (EPIs) reduced Salmonella resistance to tetracycline by 16 to 32-fold in several tetracycline resistant isolates. For example, the tetracycline minimum inhibitory concentration (MIC) for MDR Salmonella enterica serovar I 4,5,12:i:- USDA15WA-1 (SX 238) was 256 μg/mL. However, in the presence of NMP (250 μg/mL), the MIC dropped to 8 μg/mL which is below the Clinical Laboratory Standards Institute (CLSI) breakpoint for tetracycline resistance in Salmonella (≥16 μg/mL). Confocal and transmission electron microscopy revealed NMP-mediated damage to Salmonella membranes at a higher concentration (1000 μg/mL), implying that the EPI disrupts membrane morphology which can lead to cell death; however, this effect was dependent on NMP concentration, as NMP blocked efflux activity with less of a membrane-disrupting effect at a lower concentration (250 μg/mL). These findings suggest that the use of EPIs can reduce the MIC of tetracycline and restore the effectiveness of the antibiotic against tetracycline-resistant Salmonella.
•NMP synergistically reduced tetracycline resistance in Salmonella.•Efflux pump inhibition restored tetracycline efficacy against resistant Salmonella.•NMP caused membrane destabilization in Salmonella at higher concentrations.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
About the Authors: Jonathan D. Edgeworth * E-mail: jonathan.edgeworth@gstt.nhs.uk (JDE); michael.malim@kcl.ac.uk (MHM) Affiliations Centre for Clinical Infection and Diagnostics Research, Department ...of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom, Viapath, London, United Kingdom Rahul Batra Affiliations Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom Gaia Nebbia Affiliations Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom ORCID logo http://orcid.org/0000-0002-7524-1947 Karen Bisnauthsing Affiliations Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom ORCID logo http://orcid.org/0000-0001-9045-1064 Eithne MacMahon Affiliations Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom, Viapath, London, United Kingdom Malur Sudhanva Affiliations Viapath, London, United Kingdom, Department of Virology, King’s College Hospital, London, United Kingdom Sam Douthwaite Affiliations Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom Simon Goldenberg Affiliations Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom ORCID logo http://orcid.org/0000-0003-0837-7382 Geraldine O’Hara Affiliations Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom Manu Shankar-Hari Affiliation: Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom Katie J. Doores Affiliation: Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom Rocio Martinez-Nunez Affiliation: Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom ORCID logo http://orcid.org/0000-0003-2507-4738 Carolyn Hemsley Affiliations Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom ORCID logo http://orcid.org/0000-0002-0558-3984 Nicholas M. Price Affiliations Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, Department of Infectious Diseases, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom ORCID logo http://orcid.org/0000-0001-7573-3709 Jill Lockett Affiliation: King’s Health Partners, London, United Kingdom Robert I. Lechler Affiliation: King’s Health Partners, London, United Kingdom Stuart J. D. Neil Affiliation: Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom Michael H. Malim * E-mail: jonathan.edgeworth@gstt.nhs.uk (JDE); michael.malim@kcl.ac.uk (MHM) Affiliations Centre for Clinical Infection and Diagnostics Research, Department of Infectious Diseases, School of Immunology and Microbial Sciences, King’s College London, London, United Kingdom, King’s Health Partners, London, United Kingdom ORCID logo http://orcid.org/0000-0002-7699-2064 Citation: Edgeworth JD, Batra R, Nebbia G, Bisnauthsing K, MacMahon E, Sudhanva M, et al. Here, we draw out some potentially common themes that emerged on our journey to introducing and scaling up delivery and development of novel diagnostic tests and services whilst also recruiting patients into clinical trials, commencing disease pathogenesis research projects, contributing data and samples for nationally coordinated projects, and responding to rapidly changing clinical service needs, presumably an agenda that colleagues in analogous organisations around the world will be facing. Setting up a COVID-19 diagnostics and translational research group Who are we? (1) King’s College London research scientists with expertise in virology, molecular biology, and human immunology on an ambulatory and elective surgery site juxtaposed with the central hub of our comprehensive BRC (Guy’s Hospital) 4; (2) ISO15189-accredited diagnostic bacteriology and virology laboratories run by our pathology provider, Viapath www.viapath.co.uk, on 2 acute care academic hospital sites (St Thomas’ and King’s College Hospitals); (3) clinical virology and infectious diseases departments on both acute hospital sites with, relevant to COVID-19, a translational diagnostics research group adjacent to the diagnostic laboratories and a nationally commissioned centre for respiratory high consequences infectious diseases. ...like many multisite healthcare organisations, people and resources were located on different sites managed by different sovereign organisations, each about 1 mile apart.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
1 Microbial Genomics and Bioprocessing Research Unit, National Center for Agricultural Utilization Research, Agricultural Research Service, US Department of Agriculture, Peoria, IL 61604, USA
2 ...Bioproducts and Biocatalysis Research Unit, National Center for Agricultural Utilization Research, Agricultural Research Service, US Department of Agriculture, Peoria, IL 61604, USA
3 Counterterrorism and Forensic Science Research Unit, Federal Bureau of Investigation Academy, Quantico, VA 22135, USA
4 Chemical-Biological Sciences Unit, Laboratory Division, Federal Bureau of Investigation, Quantico, VA 22135, USA
Correspondence Alejandro P. Rooney alejandro.rooney{at}ars.usda.gov
The Bacillus subtilis species complex is a tight assemblage of closely related species. For many years, it has been recognized that these species cannot be differentiated on the basis of phenotypic characteristics. Recently, it has been shown that phylogenetic analysis of the 16S rRNA gene also fails to differentiate species within the complex due to the highly conserved nature of the gene, yet DNA–DNA hybridization values fall well below 70 % for the same species comparisons. As a complementary approach, we propose that phylogenetic analysis of multiple protein-coding loci can be used as a means to detect and differentiate novel Bacillus taxa. Indeed, our phylogenetic analyses revealed the existence of a previously unknown group of strains closely related to, but distinct from, Bacillus subtilis subsp. spizizenii . Results of matrix-assisted laser desorption ionization-time of flight mass spectrometry analyses revealed that the group produces a novel surfactin-like lipopeptide with mass m / z 1120.8 that is not produced by the other currently recognized subspecies. In addition, the group displayed differences in the total cellular content of the fatty acids C 16 : 0 and iso-C 17 : 1 10 c that distinguish it from the closely related B. subtilis subsp. spizizenii . Consequently, the correlation of these novel phenotypic traits with the phylogenetic distinctiveness of this previously unknown subspecies group showed that phylogenetic analysis of multiple protein-coding loci can be used as a means to detect and differentiate novel Bacillus taxa. Therefore, we propose that this new group should be recognized as representing a novel taxon, Bacillus subtilis subsp. inaquosorum subsp. nov., with the type strain NRRL B-23052 T (=KCTC 13429 T =BGSC 3A28 T ).
Abbreviations: FAME, fatty acid methyl ester; MALDI-TOF MS, matrix-assisted laser desorption ionization-time of flight mass spectrometry; NJ, neighbour-joining; ML, maximum-likelihood; MP, maximum-parsimony
The GenBank/EMBL/DDBJ accession numbers for the sequences generated in this study are EU138452 –EU138865.
A maximum-parsimony cladogram of the Bacillus subtilis species complex and tables showing the mean values of synonymous and non-synonymous substitutions per site among protein-coding genes and the geographical origins, isolation substrates and maximum growth temperatures for B. subtilis subsp. inaquosorum subsp. nov., B. subtilis subsp. spizizenii and B. subtilis subsp. subtilis are available as supplementary material with the online version of this paper.
In two previous papers (Papers I and II), we have described an algorithm for solving the equations of Magnetohydrodynamics (MHD) using the Smoothed Particle Hydrodynamics (SPH) method. The algorithm ...uses dissipative terms in order to capture shocks and has been tested on a wide range of one-dimensional problems in both adiabatic and isothermal MHD. In this paper, we investigate multidimensional aspects of the algorithm, refining many of the aspects considered in Papers I and II and paying particular attention to the code's ability to maintain the ∇·B= 0 constraint associated with the magnetic field. In particular, we implement a hyperbolic divergence cleaning method recently proposed by Dedner et al. in combination with the consistent formulation of the MHD equations in the presence of non-zero magnetic divergence derived in Papers I and II. Various projection methods for maintaining the divergence-free condition are also examined. Finally, the algorithm is tested against a wide range of multidimensional problems used to test recent grid-based MHD codes. A particular finding of these tests is that in Smoothed Particle Magnetohydrodynamics (SPMHD), the magnitude of the divergence error is dependent on the number of neighbours used to calculate a particle's properties and only weakly dependent on the total number of particles. Whilst many improvements could still be made to the algorithm, our results suggest that the method is ripe for application to problems of current theoretical interest, such as that of star formation.
ABSTRACT
To date weak gravitational lensing surveys have typically been restricted to small fields of view, such that the flat-sky approximation has been sufficiently satisfied. However, with Stage ...IV surveys (e.g. LSST and Euclid) imminent, extending mass-mapping techniques to the sphere is a fundamental necessity. As such, we extend the sparse hierarchical Bayesian mass-mapping formalism presented in previous work to the spherical sky. For the first time, this allows us to construct maximum a posteriori spherical weak lensing dark-matter mass-maps, with principled Bayesian uncertainties, without imposing or assuming Gaussianty. We solve the spherical mass-mapping inverse problem in the analysis setting adopting a sparsity promoting Laplace-type wavelet prior, though this theoretical framework supports all log-concave posteriors. Our spherical mass-mapping formalism facilitates principled statistical interpretation of reconstructions. We apply our framework to convergence reconstruction on high resolution N-body simulations with pseudo-Euclid masking, polluted with a variety of realistic noise levels, and show a significant increase in reconstruction fidelity compared to standard approaches. Furthermore, we perform the largest joint reconstruction to date of the majority of publicly available shear observational data sets (combining DESY1, KiDS450, and CFHTLens) and find that our formalism recovers a convergence map with significantly enhanced small-scale detail. Within our Bayesian framework we validate, in a statistically rigorous manner, the community’s intuition regarding the need to smooth spherical Kaiser-Squires estimates to provide physically meaningful convergence maps. Such approaches cannot reveal the small-scale physical structures that we recover within our framework.
The INCOMPASS field campaign combines airborne and ground measurements of the 2016 Indian monsoon, towards the ultimate goal of better predicting monsoon rainfall. The monsoon supplies the majority ...of water in South Asia, but forecasting from days to the season ahead is limited by large, rapidly developing errors in model parametrizations. The lack of detailed observations prevents thorough understanding of the monsoon circulation and its interaction with the land surface: a process governed by boundary‐layer and convective‐cloud dynamics. INCOMPASS used the UK Facility for Airborne Atmospheric Measurements (FAAM) BAe‐146 aircraft for the first project of this scale in India, to accrue almost 100 h of observations in June and July 2016. Flights from Lucknow in the northern plains sampled the dramatic contrast in surface and boundary‐layer structures between dry desert air in the west and the humid environment over the northern Bay of Bengal. These flights were repeated in pre‐monsoon and monsoon conditions. Flights from a second base at Bengaluru in southern India measured atmospheric contrasts from the Arabian Sea, over the Western Ghats mountains, to the rain shadow of southeast India and the south Bay of Bengal. Flight planning was aided by forecasts from bespoke 4 km convection‐permitting limited‐area models at the Met Office and India's NCMRWF. On the ground, INCOMPASS installed eddy‐covariance flux towers on a range of surface types, to provide detailed measurements of surface fluxes and their modulation by diurnal and seasonal cycles. These data will be used to better quantify the impacts of the atmosphere on the land surface, and vice versa. INCOMPASS also installed ground instrumentation supersites at Kanpur and Bhubaneswar. Here we motivate and describe the INCOMPASS field campaign. We use examples from two flights to illustrate contrasts in atmospheric structure, in particular the retreating mid‐level dry intrusion during the monsoon onset.
Although the monsoon is vital for supplying water to more than a billion people in India, models used for weather forecasting and climate projection still suffer from large biases. These biases stem from poorly resolved physical processes and inadequate parametrization schemes. The 2016 INCOMPASS field campaign, described in this paper, used an atmospheric research aircraft and a suite of ground measurements including surface flux towers to contribute to improved physical understanding of the monsoon.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Residual feed intake (RFI) is the difference between the actual and expected feed intake of an animal based on its BW and growth rate over a specified period. The biological mechanisms underlying the ...variation in feed efficiency in animals with similar BW and growth rate are not well understood. This study determined the relationship of feedlot feed efficiency, performance, and feeding behavior with digestion and energy partitioning of 27 steers. The steers were selected from a total of 306 animals based on their RFI following feedlot tests at the University of Alberta Kinsella Research Station. Selected steers were ranked into high RFI (RFI >0.5 SD above the mean, n = 11), medium RFI (RFI ± 0.5 SD above and below the mean, n = 8), and low RFI (RFI <-0.5 SD below the mean, n = 8). The respective BW ± SD for the RFI groups were 495.6 ± 12.7, 529.1 ± 18.6, and 501.2 ± 15.5 kg. Digestibility and calorimetry trials were performed on a corn-or barley-based concentrate diet in yr 1 and 2, respectively, at 2.5 x maintenance requirements. Mean DMI (g/kg of BWsuperscript 0.75) during the measurements for high-, medium-, and low-RFI groups, respectively, were 82.7 ± 2.0, 78.8 ± 2.6, and 81.8 ± 2.5 and did not differ (P > 0.10). Residual feed intake was correlated with daily methane production and energy lost as methane (r = 0.44; P < 0.05). Methane production was 28 and 24% less in low-RFI animals compared with high- and medium-RFI animals, respectively. Residual feed intake tended to be associated (P < 0.10) with apparent digestibilities of DM (r = -0.33) and CP (r = -0.34). The RFI of steers was correlated with DE (r = -0.41; P < 0.05), ME (r = -0.44; P < 0.05), heat production (HP; r = 0.68; P < 0.001), and retained energy (RE; r = -0.67; P < 0.001; energy values are expressed in kcal/kg of BWsuperscript 0.75). Feedlot partial efficiency of growth was correlated (P < 0.01) with methane production (r = -0.55), DE (r = 0.46), ME (r = 0.49), HP (r = -0.50), and RE (r = 0.62). With the exception of HP (r = 0.37; P < 0.05), feed conversion ratio was unrelated to the traits considered in the study. Feeding duration was correlated (P < 0.01) with apparent digestibility of DM (r = -0.55), CP (r = -0.47), methane production (r = 0.51), DE (r = -0.52), ME (r = -0.55), and RE (r = -0.60). These results have practical implications for the selection of animals that eat less at a similar BW and growth rate and for the environmental sustainability of beef production.
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