bluuebunny/crossref_metadata_2025_split huggingface dataset:
Black bone MRI morphometry for mandibular cortical bone measurement in head and neck cancer patients: Prospective method comparison with CT
Authors:   Joint Head and Neck MRI-Radiotherapy Development Cooperative, van Dijk Lisanne V. , Ventura Juan , Wahid Kareem , Zhu Lin L. , McDonald Brigid A. , Ahmed Sara , Sanders Keith , Stieb Sonja M. , McCoy Lance , Sharafi Christina S. , Preston Kathryn , Fahim Joly , DeArmas Aubryane , Arbab Mona , Ding Yao , Wang Jihong , Rigaud Bastien , Sen Anando , Chambers Mark , Hutcheson Katherine A. , Brock Kristy K. , Lai Stephen Y. , Mohamed Abdallah S. R. , Fuller Clifton D. 
Published: July 2020

AbstractObjectivesTo determine the utility of low-flip angle “black bone” magnetic resonance imaging (MRI) for cortical mandibular bone assessment by comparing interdentium cortical measurements and inter-observer morphometric variability in relation to computed tomography (CT).MethodsQuantification of cortical mandible bone width was performed as per Hamada et al. at 15 cross-sectional interdentium locations on pre-treatment black bone MRI and CT for 15 oropharyngeal cancer patients, with inter-observer analyses on a subset of 3 patients by 11 observers. Bland-Altman limits of agreement and bias estimation, Lin’s concordance correlation (LCC), and Deming orthogonal regression were used to compare CT and MRI measurements. The absolute variance and intraclass correlation coefficient (ICC) were implemented for the inter-observer error quantification.ResultsBoth the Bland Altman and Deming regression analyses showed CT and black bone MRI measurements were comparable within ±0.85 mm limits of agreement, and systematically smaller for MRI. LCC (0.60[0.52;0.67]) showed moderate equivalence between modalities. The average absolute variance between the observers was similar on CT (1.13±0.06 mm) and MRI (1.15 ±0.06 mm). The ICC analyses showed that measurement consistency was significantly higher (p<0.001) for the black bone MRI (0.43[0.32;0.56]) than CT (0.22[0.13;0.35]); nonetheless, the ICC was poor for both modalities.ConclusionsBlack bone MR sequence is usable as an alternative to CT for cortical mandible bone measurements, allowing use for early detection of cortical alteration (e.g. osteonecrosis). The cortical bone measurements showed substantive but equivalent inter-observer variation on both CT and black bone MRI. (Semi)automated measurement may mitigate this in future work.
Healthcare Workers’ Mental Health and Wellbeing During the COVID-19 Pandemic in the UK: Contrasting Guidelines with Experiences in Practice
Authors: Vera San Juan Norha , Aceituno David , Djellouli Nehla , Sumray Kirsi , Regenold Nina , Syversen Aron , Symmons Sophie Mulcahy , Dowrick Anna , Mitchinson Lucy , Singleton Georgina , Vindrola-Padros Cecilia 
Published: July 2020

AbstractBackgroundSubstantial evidence has highlighted the importance of considering healthcare workers’ (HCW) mental health during the COVID-19 pandemic, and several organisations have issued guidelines with recommendations. However, the definition of wellbeing and the evidence-base behind such guidelines remains unclear.ObjectivesAssessing the applicability of wellbeing guidelines in practice; identifying unaddressed HCWs’ needs; and providing recommendations for supporting frontline staff during the current and future pandemics.Methods and DesignThis paper discusses the findings of a qualitative study based on interviews with frontline healthcare staff in the UK and examines them in relation to a rapid review of wellbeing guidelines developed in response to the COVID-19 pandemic.Results14 guidelines were included in the rapid review and 33 interviews with HCWs were conducted in the qualitative study. As a whole, the guidelines placed greater emphasis on wellbeing at an individual level, while HCWs placed greater emphasis on structural conditions at work, such as understaffing and the invaluable support of the community. This in turn had implications for the focus of wellbeing intervention strategies; staff reported an increased availability of formal mental health support, however, understaffing or clashing schedules prevented them from participating in these activities.ConclusionHCWs expressed wellbeing needs which align with social-ecological conceptualisations of wellbeing related to quality of life. This approach to wellbeing has been highlighted in literature about HCWs support in previous health emergencies, yet it has not been monitored during this pandemic. Wellbeing guidelines should explore staff’s needs and contextual characteristics affecting the implementation of recommendations.
High stability of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA under minimal storage conditions for detection by Real-Time PCR
Authors: Summer Sabrina , Schmidt Ralf , Herdina Anna Nele , Krickl Isabella , Madner Julia , Greiner Georg , Mayer Florian J. , Perkmann-Nagele Nicole , Strassl Robert 
Published: July 2020

ABSTRACTReliable diagnosis, executed by Real-Time PCR (RT-PCR), builds the current basis in SARS-CoV-2 containment. Transport and storage conditions are the main indicators determining the quality of respiratory specimens. According to shortages in commercially available viral transport media, the primary aim of this study was to explore the reliability of minimal transport media including saline and CDC Viral Transport Media (HBSS VTM) composition for SARS-CoV-2 diagnosis by Real-time PCR compared to recommended commercially available standard Universal Transport Media (UTM). This study also implicated the stability of other respiratory viruses, including influenza A, respiratory syncytial virus, adenovirus, rhinovirus and human metapneumovirus, providing further evidence for future recommendations on transport and storage of respiratory viruses. Both viral transport media (self-made HBSS VTM and UTM) and saline (0.9% NaCl) allow adequate detection of SARS- CoV-2 and other respiratory viruses, regardless of an increase in storage temperature (up to 28 °C) and time (over 28 days). Treatment of SARS-CoV-2 specimens with varying chlorine concentrations, commonly used in swimming pools, resulted in a significant decrease of viral RNA.ImportanceDetection of respiratory viruses including SARS-CoV-2 depends on the quality of respiratory specimens, predominantly determined by transport and storage conditions. Our study revealed the high resilience of SARS-CoV-2 and other respiratory viruses enabling proper detection in clinical specimens even after long- time storage at high temperatures. This study provides evidence for future recommendations for transport and storage of respiratory viruses, including SARS- CoV-2.Treatment of SARS-CoV-2-positive respiratory specimens with chlorine indicates an early degradation of the virus after the addition of the oxidant, proposing sufficient inactivation of the virus in swimming pool water.
Threshold analyses on combinations of testing, population size, and vaccine coverage for COVID-19 control in a university setting
Authors: Zhao Xinmeng , Tatapudi Hanisha , Corey George , Gopalappa Chaitra 
Published: July 2020

AbstractWe simulated epidemic projections of a potential COVID-19 outbreak in a residential university population in the United States under varying combinations of asymptomatic tests (5% to 33% per day), transmission rates (2.5% to 14%), and contact rates (1 to 25), to identify the contact rate threshold that, if exceeded, would lead to exponential growth in infections. Using this, we extracted contact rate thresholds among non-essential workers, population size thresholds in the absence of vaccines, and vaccine coverage thresholds. We further stream-lined our analyses to transmission rates of 5 to 8%, to correspond to the reported levels of face-mask-use/physical-distancing during the 2020 pandemic.Our results suggest that, in the absence of vaccines, testing alone without reducing population size would not be sufficient to control an outbreak. If the population size is lowered to 34% (or 44%) of the actual population size to maintain contact rates at 4 (or 7) among non-essential workers, mass tests at 25% (or 33%) per day would help control an outbreak. With the availability of vaccines, the campus can be kept at full population provided at least 95% are vaccinated. If vaccines are partially available such that the coverage is lower than 95%, keeping at full population would require asymptomatic testing, either mass tests at 25% per day if vaccine coverage is at 63-79%, or mass tests at 33% per day if vaccine coverage is at 53-68%. If vaccine coverage is below 53%, to control an outbreak, in addition to mass tests at 33% per day, it would also require lowering the population size to 90%, 75%, and 60%, if vaccine coverage is at 38-53%, 23-38%, and below 23%, respectively.Threshold estimates from this study, interpolated over the range of transmission rates, can collectively help inform campus level preparedness plans for adoption of face mask/physical-distancing, testing, remote instructions, and personnel scheduling, during non-availability or partial-availability of vaccines, in the event of SARS-Cov2-type disease outbreaks.
Huntingtin lowering reduces somatic instability at CAG-expanded loci
Authors: Coffey Sydney R. , Andrew Marissa , Ging Heather , Hamilton Joseph , Flower Michael , Kovalenko Marina , Bragg Robert M. , Cantle Jeffrey P. , McHugh Cassandra A. , Carrillo José M. , Rodier Julie-Anne , Marchionini Deanna M. , Wilkinson Hilary A. , Kwak Seung , Howland David S. , Bennett C. Frank , Pinto Ricardo Mouro , Auburger Georg , Zeitlin Scott O. , Kordasiewicz Holly B. , Tabrizi Sarah J. , Wheeler Vanessa C. , Carroll Jeffrey B. 
Published: July 2020

AbstractExpanded trinucleotide repeats cause many human diseases, including Huntington’s disease (HD). Recent studies indicate that somatic instability of these repeats contributes to pathogenesis in several expansion disorders. We find that lowering huntingtin protein (HTT) levels reduces somatic instability of both theHttandAtxn2CAG tracts in knockin mouse models, and theHTTCAG tract in human iPSC-derived neurons, revealing an unexpected role for HTT in regulating somatic instability.
Calcium binding protein Ncs1 is calcineurin-regulated inCryptococcus neoformansand essential for cell division and virulence
Authors: Squizani Eamim Daidrê , Reuwsaat Júlia Catarina Vieira , Lev Sophie , Motta Heryk , Sperotto Julia , Kaufman-Francis Keren , Desmarini Desmarini , Vainstein Marilene Henning , Staats Charley Christian , Djordjevic Julianne T. , Kmetzsch Lívia 
Published: July 2020

AbstractIntracellular calcium (Ca2+) is crucial for signal transduction inCryptococcus neoformans, the major cause of fatal fungal meningitis. The calcineurin pathway is the only Ca2+-requiring signalling cascade implicated in cryptococcal stress adaptation and virulence, with Ca2+-binding mediated by the EF-hand domains of the Ca2+sensor protein calmodulin. In this study, we identified the cryptococcal ortholog of neuronal calcium sensor-1 (Ncs1) as a member of the EF-hand superfamily. We demonstrated that Ncs1 has a role in Ca2+homeostasis under stress and non-stress conditions, as thencs1Δmutant is sensitive to a high Ca2+concentration and has an elevated basal Ca2+level that correlates with increased expression of the Ca2+transporter genes,CCH1andMID1. Furthermore,NCS1expression is induced by Ca2+, with the Ncs1 protein adopting a punctate subcellular distribution. We also demonstrate that, in contrast toSaccharomyces cerevisiae,NCS1expression inC. neoformansis regulated by the calcineurin pathway via the transcription factor Crz1, asNCS1expression is reduced by FK506 treatment andCRZ1deletion. Moreover, thencs1Δmutant shares a high temperature and high Ca2+sensitivity phenotype with the calcineurin and calmodulin mutants (cna1Δ andcam1Δ) and theNCS1promoter contains two calcineurin/Crz1-dependent response elements (CDRE1). Ncs1-deficency coincided with reduced growth, characterized by delayed bud emergence and aberrant cell division, and hypovirulence in a mouse infection model. In summary, our data shows that Ncs1 plays distinct roles in Ca2+sensing inC. neoformansdespite widespread functional conservation of Ncs1 and other regulators of Ca2+homeostasis.ImportanceCryptococcus neoformansis the major cause of fungal meningitis in HIV infected patients. Several studies have highlighted the important contribution of Ca2+signalling and homeostasis to the virulence ofC. neoformans. Here, we identify the cryptococcal ortholog of neuronal calcium sensor-1 (Ncs1) and demonstrate its role in Ca2+homeostasis, bud emergence, cell cycle progression and virulence. We also show that Ncs1 function is regulated by the calcineurin/Crz1 signalling cascade. Our work provides evidence of a link between Ca2+homeostasis and cell cycle progression inC. neoformans.
Four-dimensional characterization of theBabesia divergensasexual life cycle: from the trophozoite to the multiparasite stage
Authors: Conesa José Javier , Sevilla Elena , Terrón María C. , González Luis Miguel , Gray Jeremy , Pérez-Berná Ana J. , Carrascosa José L. , Pereiro Eva , Chichón Francisco Javier , Luque Daniel , Montero Estrella 
Published: July 2020

ABSTRACTBabesiais an apicomplexan parasite of significance that causes the disease known as babesiosis in domestic and wild animals and in humans worldwide.Babesiainfects vertebrate hosts and reproduces asexually by a form of binary fission within erythrocytes/red blood cells (RBCs), yielding a complex pleomorphic population of intraerythrocytic parasites. Seven of them, clearly visible in human RBCs infected withBabesia divergens, are considered the main forms and named single, double and quadruple trophozoites, paired and double paired-pyriforms, tetrad or Maltese Cross, and multiparasite stage. However, these main intraerythrocytic forms coexist with RBCs infected with transient parasite combinations of unclear origin and development. In fact, little is understood about howBabesiabuilds this complex population during its asexual life cycle. By combining the emerging technique cryo soft X-ray tomography and video microscopy, main and transitory parasites were characterized in a native whole cellular context and at nanometric resolution. As a result, the architecture and kinetic of the parasite population has been elucidated. Importantly, the process of multiplication by binary fission, involving budding, was visualized in live parasites for the first time, revealing that fundamental changes in cell shape and continuous rounds of multiplication occur as the parasites go through their asexual multiplication cycle. Based on these observations, a four-dimensional (4D) asexual life cycle model has been designed highlighting the origin of the tetrad, double paired-pyriform and multiparasite stages and the transient morphological forms that, surprisingly, intersperse in a chronological order between one main stage and the next along the cycle.IMPORTANCEBabesiosis is a disease caused by intraerythrocytic Babesia parasites, which possess many clinical features that are similar to those of malaria. This worldwide disease, is increasing in frequency and geographical range, and has a significant impact on human and animal health.Babesia divergensis one of the species responsible for human and cattle babesiosis causing death unless treated promptly. WhenB. divergensinfects its vertebrate hosts it reproduces asexually within red blood cells. During its asexual life cycle,B. divergensbuilds a population of numerous intraerythrocytic (IE) parasites of difficult interpretation. This complex population is largely unexplored, and we have therefore combined three and four dimensional (3D and 4D) imaging techniques to elucidate the origin, architecture, and kinetic of IE parasites. Unveil the nature of these parasites have provided a vision of theB. divergensasexual cycle in unprecedented detail and a key step to develop control strategies against babesiosis
Artificial Intelligence Predicts and Explains West Nile Virus Risks Across Europe: Extraordinary Outbreaks Determined by Climate and Local Factors
Authors: Gayle Albert A 
Published: July 2020

AbstractYear-to-year emergence of West Nile virus has been sporadic and notoriously hard to predict. In Europe, 2018 saw a dramatic increase in the number of cases and locations affected. In this work, we demonstrate a novel method for predicting outbreaks and understanding what drives them. This method creates a simple model for each region that directly explains how each variable affects risk. Behind the scenes, each local explanation model is produced by a state-of-the-art AI engine. This engine unpacks and restructures output from an XGBoost machine learning ensemble. XGBoost, well-known for its predictive accuracy, has always been considered a “black box” system. Not any more. With only minimal data curation and no “tuning”, our model predicted where the 2018 outbreak would occur with an AUC of 97%. This model was trained using data from 2010-2016 that reflected many domains of knowledge. Climate, sociodemographic, economic, and biodiversity data were all included. Our model furthermore explained the specific drivers of the 2018 outbreak for each affected region. These effect predictions were found to be consistent with the research literature in terms of priority, direction, magnitude, and size of effect. Aggregation and statistical analysis of local effects revealed strong cross-scale interactions. From this, we concluded that the 2018 outbreak was driven by large-scale climatic anomalies enhancing the local effect of mosquito vectors. We also identified substantial areas across Europe at risk for sudden outbreak, similar to that experienced in 2018. Taken as a whole, these findings highlight the role of climate in the emergence and transmission of West Nile virus. Furthermore, they demonstrate the crucial role that the emerging “eXplainable AI” (XAI) paradigm will have in predicting and controlling disease.HighlightsThis study shows that the extraordinary 2018 West Nile virus outbreak in Europe was likely due to cross-scale effects between large climatic systems and local mosquito vector populationsWe found that large areas in Europe are similarly vulnerable to large and sudden outbreaksThese findings were powered by a novel AI-driven engine for deriving locally precise models; this explanatory engine was supported by a high-performance XGBoost model (97% AUC).AI-driven local models allow for high-power statistical analyses, including: hypothesis testing,, standardized effect size calculation, multivariate clustering, and tertiary inferential modeling
Systematic evaluation and external validation of 22 prognostic models among hospitalised adults with COVID-19: An observational cohort study
Authors: Gupta Rishi K. , Marks Michael , Samuels Thomas H. A. , Luintel Akish , Rampling Tommy , Chowdhury Humayra , Quartagno Matteo , Nair Arjun , Lipman Marc , Abubakar Ibrahim , Smeden Maarten van , Wong Wai Keong , Williams Bryan , Noursadeghi Mahdad 
Published: July 2020

AbstractBackgroundThe number of proposed prognostic models for COVID-19, which aim to predict disease outcomes, is growing rapidly. It is not known whether any are suitable for widespread clinical implementation. We addressed this question by independent and systematic evaluation of their performance among hospitalised COVID-19 cases.MethodsWe conducted an observational cohort study to assess candidate prognostic models, identified through a living systematic review. We included consecutive adults admitted to a secondary care hospital with PCR-confirmed or clinically diagnosed community-acquired COVID-19 (1stFebruary to 30thApril 2020). We reconstructed candidate models as per their original descriptions and evaluated performance for their original intended outcomes (clinical deterioration or mortality) and time horizons. We assessed discrimination using the area under the receiver operating characteristic curve (AUROC), and calibration using calibration plots, slopes and calibration-in-the-large. We calculated net benefit compared to the default strategies of treating all and no patients, and against the most discriminating predictor in univariable analyses, based on a limited subset ofa prioricandidates.ResultsWe tested 22 candidate prognostic models among a cohort of 411 participants, of whom 180 (43.8%) and 115 (28.0%) met the endpoints of clinical deterioration and mortality, respectively. The highest AUROCs were achieved by the NEWS2 score for prediction of deterioration over 24 hours (0.78; 95% CI 0.73-0.83), and a novel model for prediction of deterioration <14 days from admission (0.78; 0.74-0.82). Calibration appeared generally poor for models that used probability outcomes. In univariable analyses, admission oxygen saturation on room air was the strongest predictor of in-hospital deterioration (AUROC 0.76; 0.71-0.81), while age was the strongest predictor of in-hospital mortality (AUROC 0.76; 0.71-0.81). No prognostic model demonstrated consistently higher net benefit than using the most discriminating univariable predictors to stratify treatment, across a range of threshold probabilities.ConclusionsOxygen saturation on room air and patient age are strong predictors of deterioration and mortality among hospitalised adults with COVID-19, respectively. None of the prognostic models evaluated offer incremental value for patient stratification to these univariable predictors.