Virulence Genes of Pathogenic Escherichia coli in Wild Red Foxes (Vulpes vulpes)

Different pathotypes of Escherichia coli can cause severe diseases in animals and humans. Wildlife may contribute to the circulation of pathogenic pathotypes, including enteropathogenic E. coli (EPEC), Shiga toxin-producing E. coli (STEC), and enterohemorrhagic E. coli (EHEC). This study analyzed 109 DNA samples previously extracted from fecal specimens collected from red foxes (Vulpes vulpes) to detect E. coli virulence genes eaeA, hlyA, stx1, and stx2, that characterize the EPEC, STEC, and EHEC strains. Thirty-one (28.4%) samples were positive for at least one investigated virulence gene: eaeA gene was detected in 21 (19.2%) samples, hlyA in 10 (9.1%), stx1 in 6 (5.5%), and stx2 in 4 (3.6%). Nine DNA samples resulted positive for two or three virulence genes: five (4.6%) samples were positive for eaeA and hlyA genes, two (1.8%) for eaeA and stx1, one (0.9%) for hlyA and stx1, one (0.9%) for eaeA, hlyA and stx2. Red foxes seem to be involved in the epidemiology of these infections and their role could be relevant because they may be source of pathogenic E. coli for other wild animals, as well as domestic animals and humans

(Epi)genetic profiling of extraembryonic and postnatal tissues from female monozygotic twins discordant for Beckwith–Wiedemann syndrome

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Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

Abstract The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.Peer reviewe

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Infezioni da Enterococchi in Avifauna selvatica Italiana

Gli Enterococchi fanno parte del microbiota intestinale di numerose specie animali, compreso l’uomo. Sono particolarmente presenti nella microflora intestinale di molte specie aviarie, in cui una loro infezione si verifica in seguito a una patologia secondaria. Gli uccelli selvatici, essendo alcune specie migratorie con una complessa ecologia ed estese fonti alimentari, sono ideali indicatori per la sorveglianza della diffusione di batteri farmaco resistenti. In questo studio sono stati analizzati 99 campioni intestinali di esemplari appartenenti a diverse specie aviarie e provenienti dalle province Toscane di Lucca, Livorno, Pisa e Prato. Sono stati isolati 88 ceppi di Enterococcus spp. per i quali è stato valutato il profilo antibiotico resistente e la minima concentrazione inibente per determinare la resistenza a Vancomicina, Ampicillina e ad alti livelli di Aminoglicosidi (Streptomicina e Gentamicina). Il 100% dei ceppi è risultato essere resistente all’Oxacillina. È stata rilevata anche una elevata resistenza verso gli Aminoglicosidi: 92,04% alla Neomicina, 97,72% Streptomicina e il 70,45% alla Gentamicina. Tre ceppi, resistenti a tutte e 21 le molecole antibiotiche testate, sono stati classificati come PDR (pandrug resistance), 20 ceppi XDR (extensively drug‐resistance) e 64 MDR (multidrug resistance). I risultati ottenuti mostrano il ruolo degli uccelli selvatici come diffusori nell’ambiente di batteri antibiotico-resistenti che possono avere ripercussioni sulla salute pubblica. Enterococci are part of the gut microbiota of numerous animal species, including humans. They are particularly present in the intestinal microflora of many avian species, in which their infection occurs as a result of a secondary pathology. Wild birds, being some migratory species with a complex ecology and extensive food sources, are ideal indicators for monitoring the spread of drug-resistant bacteria. In this study 99 intestinal samples of specimens belonging to different avian species from the Tuscan provinces of Lucca, Livorno, Pisa and Prato were analysed. 88 strains of Enterococcus spp. have been isolated for which the resistant antibiotic profile and minimum inhibitory concentration have been evaluated to determine resistance to Vancomycin, Ampicillin and high levels of Aminoglycosides (Streptomycin and Gentamicin). 100% of the strains were found to be resistant to Oxacillin. There was also a high resistance to amino glycosides: 92.04% Neomycin, 97.72% Streptomycin and 70.45% Gentamycin. Three strains, resistant to all 21 antibiotic molecules tested, were classified as PDR (pandrug resistance), 20 strains XDR (extensively drug resistance) and 64 MDR (multidrug resistance). The results obtained show the role of wild birds as diffusers in the environment of antibiotic-resistant bacteria that can have an impact on public health