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Yersiniosis is caused by Y. enterocolitica and Y. pseudotuberculosis mostly presenting as intestinal infection. The infection is usually acquired from contaminated food. The aim of this study was to determine the seroprevalence of anti-Yersinia antibodies in Austrians. Sera of 750 healthy Austrians from all nine states were tested for anti-Yersinia IgG antibodies using the recomBlot Yersinia Westernblot® kit. Overall seroprevalence was 29.7%. Seroprevalence increased significantly with age from 24.7% in the group of the 19 to 24 year olds to 38.5% in the group of persons older than 44 years. The seroprevalence of anti-Yersinia antibodies varied within the states between 18% and 43.5%. The high seroprevalence of anti-Yersinia antibodies in contrast to only approximately 100 reported yersiniosis cases per year points to the fact that the majority of infections is either subclinical or mild.

Background: Burkholderia mallei is a potential biological agent that causes glanders or farcy in solipeds, a disease notifiable to the Office International des Epizooties (OIE). The number of reported outbreaks has increased steadily during the last decade, but diagnosis is hampered by the low bacterial load in infected tissues and excretions. Methods: We developed a B. mallei-specific 5′-nuclease real-time PCR assay that targets the fliP gene of B. mallei and includes an internal amplification control. Specificity was assessed with 19 B. mallei strains, 27 Burkholderia pseudomallei strains, other Burkholderia strains of 29 species, and clinically relevant non-Burkholderia organisms. Results: Amplification products were observed in all B. mallei strains but in no other bacteria. The linear range of the B. mallei real-time PCR covered concentrations from 240 pg to 70 fg of bacterial DNA/reaction. The detection limit was 60 fg of B. mallei DNA. The clinical applicability of the assay was demonstrated by use of organ samples from diseased horses of a recent outbreak that was reported to the OIE by the United Arab Emirates in 2004. Conclusions: Compared with conventional PCR, our rapid 5′-nuclease real-time PCR assay for the specific identification of B. mallei has a lower risk of carryover contamination and eliminates the need for post-PCR manipulations. This real-time PCR assay also shortens the turnaround time for results and has the potential for automation.

Attribution in its general definition aims to quantify drivers of change in a system. According to IPCC Working Group II (WGII) a change in a natural, human or managed system is attributed to climate change by quantifying the difference between the observed state of the system and a counterfactual baseline that characterizes the system's behavior in the absence of climate change, where “climate change refers to any long-term trend in climate, irrespective of its cause” (IPCC, 2014). Impact attribution following this definition remains a challenge because the counterfactual baseline, which characterizes the system behavior in the hypothetical absence of climate change, cannot be observed. Process-based and empirical impact models can fill this gap as they allow us to simulate the counterfactual climate impact baseline. In those simulations, the models are forced by observed direct (human) drivers such as land use changes, changes in water or agricultural management but a counterfactual climate without long-term changes. We here present ATTRICI (ATTRIbuting Climate Impacts), an approach to construct the required counterfactual stationary climate data from observational (factual) climate data. Our method identifies the long-term shifts in the considered daily climate variables that are correlated to global mean temperature change assuming a smooth annual cycle of the associated scaling coefficients for each day of the year. The produced counterfactual climate datasets are used as forcing data within the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). Our method preserves the internal variability of the observed data in the sense that factual and counterfactual data for a given day have the same rank in their respective statistical distributions. The associated impact model simulations allow for quantifying the contribution of climate change to observed long-term changes in impact indicators and for quantifying the contribution of the observed trend in climate to the magnitude of individual impact events. Attribution of climate impacts to anthropogenic forcing would need an additional step separating anthropogenic climate forcing from other sources of climate trends, which is not covered by our method.

Multiple surgical targets for treating obsessive-compulsive disorder with deep brain stimulation (DBS) have been proposed. However, different targets may modulate the same neural network responsible for clinical improvement. We analyzed data from four cohorts of patients ( N  = 50) that underwent DBS to the anterior limb of the internal capsule (ALIC), the nucleus accumbens or the subthalamic nucleus (STN). The same fiber bundle was associated with optimal clinical response in cohorts targeting either structure. This bundle connected frontal regions to the STN. When informing the tract target based on the first cohort, clinical improvements in the second could be significantly predicted, and vice versa. To further confirm results, clinical improvements in eight patients from a third center and six patients from a fourth center were significantly predicted based on their stimulation overlap with this tract. Our results show that connectivity-derived models may inform clinical improvements across DBS targets, surgeons and centers. The identified tract target is openly available in atlas form. Li et al. analyzed structural connectivity of deep brain stimulation electrodes in 50 patients suffering from obsessive-compulsive disorder operated at four centers. Connectivity to a specific tract within the anterior limb of the internal capsule was associated with optimal treatment response across cohorts, surgeons and centers.

The core-collapse supernova of a massive star rapidly brightens when a shock, produced following the collapse of its core, reaches the stellar surface. As the shock-heated star subsequently expands and cools, its early-time light curve should have a simple dependence on the size of the progenitor 1 and therefore final evolutionary state. Measurements of the radius of the progenitor from early light curves exist for only a small sample of nearby supernovae 2 – 14 , and almost all lack constraining ultraviolet observations within a day of explosion. The several-day time delays and magnifying ability of galaxy-scale gravitational lenses, however, should provide a powerful tool for measuring the early light curves of distant supernovae, and thereby studying massive stellar populations at high redshift. Here we analyse individual rest-frame exposures in the ultraviolet to the optical taken with the Hubble Space Telescope, which simultaneously capture, in three separate gravitationally lensed images, the early phases of a supernova at redshift z  ≈ 3 beginning within 5.8 ± 3.1 hours of explosion. The supernova, seen at a lookback time of approximately 11.5 billion years, is strongly lensed by an early-type galaxy in the Abell 370 cluster. We constrain the pre-explosion radius to be 53 3 − 119 + 154  solar radii, consistent with a red supergiant. Highly confined and massive circumstellar material at the same radius can also reproduce the light curve, but because no similar low-redshift examples are known, this is unlikely. The early stages of a lensed supernova at redshift 3 are found in images taken by the Hubble Space Telescope, with observations beginning from around 5.8 hours after the explosion.

Multiply lensed images of a same source experience a relative time delay in the arrival of photons due to the path length difference and the different gravitational potentials the photons travel through. This effect can be used to measure absolute distances and the Hubble constant ( H 0 ) and is known as time-delay cosmography. The method is independent of the local distance ladder and early-universe physics and provides a precise and competitive measurement of H 0 . With upcoming observatories, time-delay cosmography can provide a 1% precision measurement of H 0 and can decisively shed light on the current reported ‘Hubble tension’. This manuscript details the general methodology developed over the past decades in time-delay cosmography, discusses recent advances and results, and, foremost, provides a foundation and outlook for the next decade in providing accurate and ever more precise measurements with increased sample size and improved observational techniques.

The burden of acute bacterial skin and skin structure infections (ABSSSI) continue to plague the healthcare system. One approach to managing moderate-to-severe ABSSSI in low-risk patients involves use of a single dose lipoglycopeptide (LGP), dalbavancin or oritavancin, in the emergency department (ED) and discharge to home with follow-up care. Limited ED studies indicate decreased hospital stays, ED revisits, readmissions, and healthcare costs, as well as improved patient satisfaction with use of these antibiotics. However, existing literature has limitations and gaps, such as insufficient quantifiable data on patient selection criteria, outcome predictors, and risk factors leading to treatment failure. Moreover, there is lack of research on the impact of LGPs on organizational productivity, patient quality of life, and utility in indications beyond ABSSSI. This review focuses on the role of long-acting LGPs in the ED setting for select patients presenting with ABSSSI, aiming to avoid hospitalizations, expedite patient discharge, and prevent readmissions while acknowledging potential limitations of therapy. Additionally, it provides insights into strategies and considerations specifically relevant to implementing this therapeutic approach in the ED.

Background Microorganisms in biogas reactors are essential for degradation of organic matter and methane production. However, a comprehensive genome-centric comparison, including relevant metadata for each sample, is still needed to identify the globally distributed biogas community members and serve as a reliable repository. Results Here, 134 publicly available metagenomes derived from different biogas reactors were used to recover 1635 metagenome-assembled genomes (MAGs) representing different biogas bacterial and archaeal species. All genomes were estimated to be > 50% complete and nearly half ≥ 90% complete with ≤ 5% contamination. In most samples, specialized microbial communities were established, while only a few taxa were widespread among the different reactor systems. Metabolic reconstruction of the MAGs enabled the prediction of functional traits related to biomass degradation and methane production from waste biomass. An extensive evaluation of the replication index provided an estimation of the growth dynamics for microbes involved in different steps of the food chain. Conclusions The outcome of this study highlights a high flexibility of the biogas microbiome, allowing it to modify its composition and to adapt to the environmental conditions, including temperatures and a wide range of substrates. Our findings enhance our mechanistic understanding of the AD microbiome and substantially extend the existing repository of genomes. The established database represents a relevant resource for future studies related to this engineered ecosystem.

Prevailing recommendations call for restricting intake of dietary cholesterol and eggs for those at risk of heart disease, despite accumulating evidence challenging this association. Our prior studies showed no short-term adverse effects of daily egg intake on cardiac risk factors in at-risk adults. We conducted this study to determine effects of daily egg consumption in adults with established coronary artery disease (CAD). Randomized, controlled, single-blind, crossover trial of 32 adults (mean age, 67 years; 6 women, 26 men) with CAD assigned to 1 of 6 possible sequence permutations of 3 different treatments (breakfast with 2 eggs, breakfast with ½ cup Egg Beaters, ConAgra Foods, St. Louis, MO, or a high-carbohydrate breakfast part of an ad libitum diet) for 6 weeks, with 4-week washout periods. The primary outcome measure was endothelial function measured as flow-mediated dilatation. Compared with the control breakfast (ie, high-carbohydrate breakfast), daily consumption of eggs showed no adverse effects on flow-mediated dilatation (7.2% ± 2.9% vs 7.5% ± 2.9%, P = .33), lipids (total cholesterol: 158.3 ± 28.6 mg/dL vs 156.2 ± 27.4 mg/dL, P = .49), blood pressure (systolic blood pressure: 132.8 ± 14.1 mm Hg or vs 135.5 ± 14.9 mm Hg, P = .52; diastolic blood pressure: 77.2 ± 6.1 mm Hg vs 76.7 ± 6.9 mm Hg, P = .86), or body weight (90.8 ± 17.5 kg vs 91.8 ± 17.1 kg, P = .92). No outcomes differed (P > .05) between eggs and Egg Beaters. We found no evidence of adverse effects of daily egg ingestion on any cardiac risk factors in adults with CAD over a span of 6 weeks.

Most prior studies on the prognostic significance of newly-diagnosed atrial fibrillation (AF) in COVID-19 did not differentiate newly-diagnosed AF from pre-existing AF. To determine the association between newly-diagnosed AF and in-hospital and 30-day mortality among regular users of Veterans Health Administration using data linked to Medicare. We identified Veterans aged ≥ 65 years who were hospitalized for ≥ 24 h with COVID-19 from 06/01/2020 to 1/31/2022 and had ≥ 2 primary care visits within 24 months prior to the index hospitalization. We performed multivariable logistic regression analyses to estimate adjusted risks, risk differences (RD), and odds ratios (OR) for the association between newly-diagnosed AF and the mortality outcomes adjusting for patient demographics, baseline comorbidities, and presence of acute organ dysfunction on admission. Of 23,299 patients in the study cohort, 5.3% had newly-diagnosed AF, and 29.2% had pre-existing AF. In newly-diagnosed AF adjusted in-hospital and 30-day mortality were 16.5% and 22.7%, respectively. Newly-diagnosed AF was associated with increased mortality compared to pre-existing AF (in-hospital: OR 2.02, 95% confidence interval [CI] 1.72–2.37; RD 7.58%, 95% CI 5.54–9.62) (30-day: OR 1.86; 95% CI 1.60–2.16; RD 9.04%, 95% CI 6.61–11.5) or no AF (in-hospital: OR 2.24, 95% CI 1.93–2.60; RD 8.40%, 95% CI 6.44–10.4) (30-day: 2.07, 95% CI 1.80–2.37; RD 10.2%, 95% CI 7.89–12.6). There was a smaller association between pre-existing AF and the mortality outcomes. Newly-diagnosed AF is an important prognostic marker for patients hospitalized with COVID-19. Whether prevention or treatment of AF improves clinical outcomes in these patients remains unknown.