Insights into the unique characteristics of hepatitis C virus genotype 3 revealed by development of a robust sub-genomic DBN3a replicon

Hepatitis C virus (HCV) is an important human pathogen causing 400 000 chronic liver disease-related deaths annually. Until recently, the majority of laboratory-based investigations into the biology of HCV have focused on the genotype 2 isolate, JFH-1, involving replicons and infectious cell culture systems. However, genotype 2 is one of eight major genotypes of HCV and there is great sequence variation among these genotypes (>30 % nucleotide divergence). In this regard, genotype 3 is the second most common genotype and accounts for 30 % of global HCV cases. Further, genotype 3 is associated with both high levels of inherent resistance to direct-acting antiviral (DAA) therapy, and a more rapid progression to chronic liver diseases. Neither of these two attributes are fully understood, thus robust genotype 3 culture systems to unravel viral replication are required. Here we describe the generation of robust genotype 3 sub-genomic replicons (SGRs) based on the adapted HCV NS3-NS5B replicase from the DBN3a cell culture infectious clone. Such infectious cell culture-adaptive mutations could potentially promote the development of robust SGRs for other HCV strains and genotypes. The novel genotype 3 SGRs have been used both transiently and to establish stable SGR-harbouring cell lines. We show that these resources can be used to investigate aspects of genotype 3 biology, including NS5A function and DAA resistance. They will be useful tools for these studies, circumventing the need to work under the biosafety level 3 (BSL3) containment required in many countries

A new model for the characterization of infection risk in gunshot injuries:Technology, principal consideration and clinical implementation

<p>Abstract</p> <p>Introduction</p> <p>The extent of wound contamination in gunshot injuries is still a topic of controversial debate. The purpose of the present study is to develop a model that illustrates the contamination of wounds with exogenous particles along the bullet path.</p> <p>Material and methods</p> <p>To simulate bacteria, radio-opaque barium titanate (3-6 μm in diameter) was atomized in a dust chamber. Full metal jacket or soft point bullets caliber .222 (n = 12, v₀= 1096 m/s) were fired through the chamber into a gelatin block directly behind it. After that, the gelatin block underwent multi-slice CT in order to analyze the permanent and temporary wound cavity.</p> <p>Results</p> <p>The permanent cavity caused by both types of projectiles showed deposits of barium titanate distributed over the entire bullet path. Full metal jacket bullets left only few traces of barium titanate in the temporary cavity. In contrast, the soft point bullets disintegrated completely, and barium titanate covered the entire wound cavity.</p> <p>Discussion</p> <p>Deep penetration of potential exogenous bacteria can be simulated easily and reproducibly with barium titanate particles shot into a gelatin block. Additionally, this procedure permits conclusions to be drawn about the distribution of possible contaminants and thus can yield essential findings in terms of necessary therapeutic procedures.</p

Attributes and predictors of Long-COVID: analysis of COVID cases and their symptoms collected by the Covid Symptoms Study App

Reports of “Long-COVID”, are rising but little is known about prevalence, risk factors, or whether it is possible to predict a protracted course early in the disease. We analysed data from 4182 incident cases of COVID-19 who logged their symptoms prospectively in the COVID Symptom Study app. 558 (13.3%) had symptoms lasting >=28 days, 189 (4.5%) for >=8 weeks and 95 (2.3%) for >=12 weeks. Long-COVID was characterised by symptoms of fatigue, headache, dyspnoea and anosmia and was more likely with increasing age, BMI and female sex. Experiencing more than five symptoms during the first week of illness was associated with Long-COVID, OR=3.53 [2.76;4.50]. A simple model to distinguish between short and long-COVID at 7 days, which gained a ROC-AUC of 76%, was replicated in an independent sample of 2472 antibody positive individuals. This model could be used to identify individuals for clinical trials to reduce long-term symptoms and target education and rehabilitation services

Attributes and predictors of long COVID

Reports of long-lasting coronavirus disease 2019 (COVID-19) symptoms, the so-called ‘long COVID’, are rising but little is known about prevalence, risk factors or whether it is possible to predict a protracted course early in the disease. We analyzed data from 4,182 incident cases of COVID-19 in which individuals self-reported their symptoms prospectively in the COVID Symptom Study app. A total of 558 (13.3%) participants reported symptoms lasting ≥28 days, 189 (4.5%) for ≥8 weeks and 95 (2.3%) for ≥12 weeks. Long COVID was characterized by symptoms of fatigue, headache, dyspnea and anosmia and was more likely with increasing age and body mass index and female sex. Experiencing more than five symptoms during the first week of illness was associated with long COVID (odds ratio = 3.53 (2.76–4.50)). A simple model to distinguish between short COVID and long COVID at 7 days (total sample size, n = 2,149) showed an area under the curve of the receiver operating characteristic curve of 76%, with replication in an independent sample of 2,472 individuals who were positive for severe acute respiratory syndrome coronavirus 2. This model could be used to identify individuals at risk of long COVID for trials of prevention or treatment and to plan education and rehabilitation services

Symptom clusters in COVID-19: A potential clinical prediction tool from the COVID Symptom Study app

As no one symptom can predict disease severity or the need for dedicated medical support in coronavirus disease 2019 (COVID-19), we asked whether documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between 1 and 28 May 2020. Using the first 5 days of symptom logging, the ROC-AUC (receiver operating characteristic - area under the curve) of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required

X-Ray Spectroscopy of Stars

(abridged) Non-degenerate stars of essentially all spectral classes are soft X-ray sources. Low-mass stars on the cooler part of the main sequence and their pre-main sequence predecessors define the dominant stellar population in the galaxy by number. Their X-ray spectra are reminiscent, in the broadest sense, of X-ray spectra from the solar corona. X-ray emission from cool stars is indeed ascribed to magnetically trapped hot gas analogous to the solar coronal plasma. Coronal structure, its thermal stratification and geometric extent can be interpreted based on various spectral diagnostics. New features have been identified in pre-main sequence stars; some of these may be related to accretion shocks on the stellar surface, fluorescence on circumstellar disks due to X-ray irradiation, or shock heating in stellar outflows. Massive, hot stars clearly dominate the interaction with the galactic interstellar medium: they are the main sources of ionizing radiation, mechanical energy and chemical enrichment in galaxies. High-energy emission permits to probe some of the most important processes at work in these stars, and put constraints on their most peculiar feature: the stellar wind. Here, we review recent advances in our understanding of cool and hot stars through the study of X-ray spectra, in particular high-resolution spectra now available from XMM-Newton and Chandra. We address issues related to coronal structure, flares, the composition of coronal plasma, X-ray production in accretion streams and outflows, X-rays from single OB-type stars, massive binaries, magnetic hot objects and evolved WR stars.Comment: accepted for Astron. Astrophys. Rev., 98 journal pages, 30 figures (partly multiple); some corrections made after proof stag

X-ray Absorption and Reflection in Active Galactic Nuclei

X-ray spectroscopy offers an opportunity to study the complex mixture of emitting and absorbing components in the circumnuclear regions of active galactic nuclei, and to learn about the accretion process that fuels AGN and the feedback of material to their host galaxies. We describe the spectral signatures that may be studied and review the X-ray spectra and spectral variability of active galaxies, concentrating on progress from recent Chandra, XMM-Newton and Suzaku data for local type 1 AGN. We describe the evidence for absorption covering a wide range of column densities, ionization and dynamics, and discuss the growing evidence for partial-covering absorption from data at energies > 10 keV. Such absorption can also explain the observed X-ray spectral curvature and variability in AGN at lower energies and is likely an important factor in shaping the observed properties of this class of source. Consideration of self-consistent models for local AGN indicates that X-ray spectra likely comprise a combination of absorption and reflection effects from material originating within a few light days of the black hole as well as on larger scales. It is likely that AGN X-ray spectra may be strongly affected by the presence of disk-wind outflows that are expected in systems with high accretion rates, and we describe models that attempt to predict the effects of radiative transfer through such winds, and discuss the prospects for new data to test and address these ideas.Comment: Accepted for publication in the Astronomy and Astrophysics Review. 58 pages, 9 figures. V2 has fixed an error in footnote

Policy challenges for the pediatric rheumatology workforce: Part I. Education and economics

For children with rheumatic conditions, the available pediatric rheumatology workforce mitigates their access to care. While the subspecialty experiences steady growth, a critical workforce shortage constrains access. This three-part review proposes both national and international interim policy solutions for the multiple causes of the existing unacceptable shortfall. Part I explores the impact of current educational deficits and economic obstacles which constrain appropriate access to care. Proposed policy solutions follow each identified barrier