bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of a bedside score to predict dengue severity
Authors: Marois Ingrid , Forfait Carole , Inizan Catherine , Klement-Frutos Elise , Valiame Anabelle , Aubert Daina , Gourinat Ann-Claire , Laumond Sylvie , Barsac Emilie , Grangeon Jean-Paul , Cazorla Cécile , Merlet Audrey , Tarantola Arnaud , Dupont-Rouzeyrol Myrielle , Descloux Elodie 
Published: November 2020

AbstractBackgroundIn 2017, New Caledonia experienced an outbreak of severe dengue causing high hospital burden (4,379 cases, 416 hospital admissions, 15 deaths). We decided to build a local operational model predictive of dengue severity, which was needed to ease the healthcare circuit.MethodsWe retrospectively analyzed clinical and biological parameters associated with severe dengue in the cohort of patients hospitalized at the Territorial Hospital between January and July 2017 with confirmed dengue, in order to elaborate a comprehensive patient’s score. Patients were compared in univariate and multivariate analyses. Predictive models for severity were built using a descending step-wise method.ResultsOut of 383 included patients, 130 (34%) developed severe dengue and 13 (3.4%) died. Major risk factors identified in univariate analysis were: age, comorbidities, presence of at least one alert sign, platelets count <30×109/L, prothrombin time <60%, AST and/or ALT >10N, and previous dengue infection. Severity was not influenced by the infecting dengue serotype nor by previous Zika infection. Two models to predict dengue severity were built according to sex. Best models for females and males had respectively a median Area Under the Curve = 0.80 and 0.88, a sensitivity = 84.5% and 84.5%, a specificity = 78.6% and 95.5%, a positive predictive value = 63.3% and 92.9%, a negative predictive value = 92.8% and 91.3%. Models were secondarily validated on 130 patients hospitalized for dengue in 2018.ConclusionWe built robust and efficient models to calculate a bedside score able to predict dengue severity in our setting. We propose the spreadsheet for dengue severity score calculations to health practitioners facing dengue outbreaks of enhanced severity in order to improve patients’ medical management and hospitalization flow.
COVID-19 Workplace Outbreaks by Industry Sector and their Associated Household Transmission, Ontario, Canada, January – June, 2020
Authors: Murti Michelle , Achonu Camille , Smith Brendan T. , Brown Kevin A. , Kim Jin Hee , Johnson James , Ravindran Saranyah , Buchan Sarah A. 
Published: November 2020

AbstractIntroductionWorkplaces requiring in-person attendance of employees for ongoing operations may be susceptible to SARS-CoV-2 outbreaks that impact workers as well as their close contacts. To understand industry sectors impacted by workplace outbreaks in the first wave of the pandemic, and the additional burden of illness through household transmission, we analyzed public health declared workplace outbreaks between January 21 to June 30, 2020, and their associated cases from January 21 to July 28.MethodsNumber, size and duration of outbreaks were described by sector, and outbreak cases were compared to sporadic cases in the same time frame. Address matching identified household cases with onset ≥2 days before, ≥2 days after, or within 1 day of the workplace outbreak case.ResultsThere were 199 outbreaks with 1245 cases, and 68% of outbreaks and 80% of cases belonged to i) Manufacturing, ii) Agriculture, Forestry, Fishing, Hunting, iii) Transportation and Warehousing. Median size of outbreaks was 3 cases (range: 1-140), and lasted median 7days (range: 0-119). Outbreak cases were significantly more likely to be male, younger, healthier, and have better outcomes. There were 608 household cases associated with 339 (31%) outbreak cases with valid addresses, increasing the burden of illness by 56%. The majority of household cases (368, 60%) occurred after the outbreak case.ConclusionsWorkplace outbreaks primarily occurred in three sectors. COVID-19 prevention measures should target industry sectors at risk by preventing introduction from exposed employees, spread in the workplace, and spread outside of the workplace.What is already known about this topic?COVID-19 outbreaks occur within workplaces and can spread to the communityWhat is added by this report?From January 21 – June 30, 2020, there were 199 workplace outbreaks in Ontario, Canada; 68% of outbreaks and 80% of outbreak-associated COVID-19 case were in three industry sectors: Manufacturing, Agriculture/Forestry/Fishing/Hunting, and Transportation/Warehousing. Household transmission occurred among 31% of outbreak cases, resulting in a 56% increase in workplace outbreak-associated cases when burden of household transmission is considered.What are the implications for public health practice?Workplace outbreak prevention measures should be targeted to industry sectors at risk by preventing introduction from exposed employees, spread in the workplace, and transmission to the greater community.
The pathogenic p.R391G ABCC6 displays incomplete penetrance implying the necessity of an interacting partner for the development of pseudoxanthoma elasticum
Authors: Szeri Flora , Miko Agnes , Navasiolava Nastassia , Kaposi Ambrus , Verschuere Shana , Li Qiaoli , Terry Sharon F. , Boraldi Federica , Uitto Jouni , van de Wetering Koen , Martin Ludovic , Quaglino Daniela , Vanakker Olivier M. , Tory Kalman , Aranyi Tamas 
Published: November 2020

AbstractABCC6 promotes the efflux of ATP from hepatocytes to the bloodstream. ATP is then cleaved to AMP and pyrophosphate, a major inhibitor of ectopic calcification. Pathogenic variants of ABCC6 cause pseudoxanthoma elasticum, a recessive ectopic calcification disease of highly variable severity. One of the mechanisms influencing the heterogeneity of a disorder is the penetrance of pathogenic variants. Penetrance shows the proportion of carriers developing the phenotype; hence incomplete penetrance indicates that the disease does not necessarily develop in the presence of specific variants. Here, we investigated whether incomplete penetrance contributes to the heterogeneity of pseudoxanthoma elasticum. By integrating the clinical and genetic data of 589 patients, we created the largest European cohort. Based on allele frequencies compared to a reference cohort, we identified two incomplete penetrant variants, p.V787I and p.R391G, 6.5% and 2% penetrance, respectively. The characterization of the p.R391G variant suggested unaltered severity of the clinical phenotype. Based on our biochemical and localization studies, we hypothesize that the variant becomes deleterious only if an interacting partner is mutated simultaneously. Our data reveal the potential existence of the first interacting partner of ABCC6. Our data are also important for genetic counseling, as they suggest lower disease heritability of some variants.
Estimation and worldwide monitoring of the effective reproductive number of SARS-CoV-2
Authors: Huisman Jana S. , Scire Jérémie , Angst Daniel C. , Li Jinzhou , Neher Richard A. , Maathuis Marloes H. , Bonhoeffer Sebastian , Stadler Tanja 
Published: November 2020

AbstractThe effective reproductive numberReis a key indicator of the growth of an epidemic. Since the start of the SARS-CoV-2 pandemic, many methods and online dashboards have sprung up to monitor this number through time. However, these methods are not always thoroughly tested, correctly placed in time, or are overly confident during high incidence periods. Here, we present a method for timely estimation ofRe, applied to COVID-19 epidemic data from 170 countries. We thoroughly evaluate the method on simulated data, and present an intuitive web interface for interactive data exploration. We show that, in early 2020, in the majority of countries the estimatedRedropped below 1 only after the introduction of major non-pharmaceutical interventions. For Europe the implementation of non-pharmaceutical interventions was broadly associated with reductions in the estimatedRe. Globally though, relaxing non-pharmaceutical interventions had more varied effects on subsequentReestimates. Our framework is useful to inform governments and the general public on the status of epidemics in their country, and is used as the official source ofReestimates for SARS-CoV-2 in Switzerland. It further allows detailed comparison between countries and in relation to covariates such as implemented public health policies, mobility, behaviour, or weather data.
An integrative multi-omics analysis of 16 autoimmune diseases and cancer outcomes highlights immune-cell regulatory mechanisms and shared genetic architecture
Authors: Prince C , Mitchell R. E , Richardson T. G. 
Published: November 2020

AbstractBackgroundDeveloping functional understanding into the causal molecular drivers of immunological disease is a critical challenge in genomic medicine. Here we systematically apply Mendelian randomization (MR), genetic colocalization, immune cell-type enrichment and phenome-wide association methods to investigate the effect of genetically predicted gene expression on 12 autoimmune and 4 cancer outcomes.ResultsUsing whole blood derived estimates for regulatory variants from the eQTLGen consortium (n=31,684) we constructed genetic risk scores (r2<0.1) for 10,104 genes. Applying the inverse-variance weighted Mendelian randomization method transcriptome-wide whilst accounting for linkage disequilibrium structure identified 773 unique genes with evidence of a genetically predicted effect on at least one disease outcome (P<4.81 × 10−5). We next undertook genetic colocalization to investigate whether these effects may be confined to specific cell-types using gene expression data derived from 18 types of immune cells. This highlighted many cell-type dependent effects, such asPRKCQexpression and asthma risk (posterior probability of association (PPA)=0.998), which was T-cell specific, as well asTPM3expression and prostate cancer risk (PPA=0.821), which was restricted to monocytes. Phenome-wide analyses on 320 complex traits allowed us to explore the shared genetic architecture and prioritize key drivers of disease risk, such asCASP10which provided evidence of an effect on 7 cancer-related outcomes. Similarly, these evaluations of pervasive pleiotropy may be valuable for evaluations of therapeutic targets to help identify potential adverse effects.ConclusionsOur atlas of results can be used to characterize known and novel loci in autoimmune disease and cancer susceptibility, both in terms of developing insight into cell-type dependent effects as well as dissecting shared genetic architecture and disease pathways. As exemplar, we have highlighted several key findings in this study, although similar evaluations can be conducted interactively athttp://mrcieu.mrsoftware.org/immuno_MR/.
Proteo-genomic analysis of SARS-CoV-2: A clinical landscape of SNPs, COVID-19 proteome and host responses
Authors: Tushir Sheetal , Kamanna Sathisha , Nath Sujith S , Bhat Aishwarya , Rose Steffimol , Aithal Advait R , Tatu Utpal 
Published: November 2020

ABSTRACTA novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of COVID-19 and continues to be a global health challenge. To understand viral disease biology, we have carried out proteo-genomic analysis using next generation sequencing (NGS) and mass-spectrometry on nasopharyngeal swabs of COVID-19 patients to examine clinical genome and proteome. Our study confirms the hyper mutability of SARS-CoV-2 showing multiple SNPs. NGS analysis detected 27 mutations of which 14 are synonymous, 11 are missense and 2 are extragenic in nature. Phylogenetic analysis of SARS-CoV-2 isolates indicated their close relation to Bangladesh isolate and multiple origins of isolates within a country. Our proteomic analysis, for the first time identified 13 different SARS-CoV-2 proteins from the clinical swabs. Of the total 41 peptides captured by HRMS, 8 matched to nucleocapsid protein, 2 to ORF9b, 1 to spike glycoprotein and ORF3a, with remaining mapping to ORF1ab polyprotein. Additionally, host proteome analysis revealed several key host proteins to be uniquely expressed in COVID-19 patients. Pathway analysis of these proteins points towards modulation in immune response, especially involving neutrophil and IL-12 mediated signaling. Besides revealing the aspects of host-virus pathogenesis, our study opens new avenues to develop better diagnostic markers and therapeutics.
Dietary Practice and Associated Factors among Pregnant Women in Nono Woreda west shoa, Oromia, Ethiopia
Authors: Demissie Dereje Bayissa , Erena Tesfaye , Kolola Tufa 
Published: November 2020

AbstractBackgroundPregnancy is a unique and critical stage of life during which extensive anatomical, physiological, biochemical and several other related changes take place. The everyday vitality prerequisites for health women of typical weight who have a modestly dynamic way of life, increment during pregnancy and depend on the trimester of the baby. Maternal undernutrition is a serious developmental challenge contributing a large share to the global disease burden. It is a major reason for the increased risk of adverse pregnancy outcomes, poor infant survival, and elevated risks of chronic diseases at later stages of life. Ethiopia has an unacceptably high burden of malnutrition and its consequences, and yet little is known about the determinants and responses to undernutrition during pregnancyObjectivesTo assess the dietary practice and associated factors among pregnant women in Nono Woreda, West Shoa Zone, Ethiopia.MethodsA community-based cross-sectional study design with both quantitative and qualitative data collection was conducted. Simple random sampling was used to select 378 pregnant women. The data were collected using interviewer-administered questionnaire of Afan Oromo version. Data were entered using Epi info version 7 and analyzed by using Statistical Package for the Social Sciences (SPSS) software for Windows version 21. Multiple logistic regressions were run to assess factors that were associated with the dependent variable at P<0.05 and to control the confounders.ResultFinally, the result of the study has shown that 31% of the study participants had good dietary practices while the rest 69% of pregnant women had poor dietary practices. Concerning dietary knowledge about a balanced diet, 63.5% of the study participants had good dietary knowledge while 36.5% had poor dietary knowledge about a balanced diet. Marital status, breastfeeding, health-seeking behavior, food avoiding, and dietary knowledge were shown to have a significant association (P < 0.05) with dietary practices of pregnant women. The quantitative study revealed that marital status (AOR =95%CI, 7.983(1.387, 45.947, P<0.02).ConclusionA dietary practice of pregnant women in the study area was poor. Marital statuses, breastfeeding, health-seeking behavior, food avoiding and dietary knowledge of balance diet were independent predictors of women dietary practices. Therefore, Health professional, Zonal health office, regional Bureau and health planners would be better to increasing awareness to have good dietary practices those women married and supported by household head.
Time of quickening is associated with the placental site and BMI in nulliparous women
Authors: Jaafar Negin , Pedersen Lars Henning , Petersen Olav Bjørn , Hvidman Lone 
Published: November 2020

AbstractIntroductionQuickening, the first sensation of fetal movements, is an important milestone for pregnant women. Information on the expected gestational age at quickening may reduce anxiety and prevent delayed detection of intrauterine demise but the available data are from the 1980s before the emergence of modern ultrasound techniques.Materials and methodsProspective observational study on nulliparous women blinded for placental location in two hospitals in Denmark. The pregnant women were enrolled at the time of nuchal translucency scan, placental location was determined at time of second trimester scanning.. The women were blinded to placenta location before time of quickening. Time of quickening were reported by 122 women, 65 with an anterior and 57 with a posterior placenta. Thirteen women had a BMI >30 (10.7%).ResultsThe mean gestational age for quickening was 19 + 0 weeks for nulliparous women. The timing depended on placental site; women with an anterior placenta experienced quickening 6.4 days later than the women with a posterior placenta. BMI > 30 was associated with a later time of quickening.ConclusionsAnterior placental location is associated with delay in experience of fetal movements of 6.4 days and this may further be delayed in women with a BMI>30.
Accelerated Predictive Healthcare Analytics with Pumas, A High Performance Pharmaceutical Modeling and Simulation Platform
Authors: Rackauckas Chris , Ma Yingbo , Noack Andreas , Dixit Vaibhav , Mogensen Patrick Kofod , Elrod Chris , Tarek Mohammad , Byrne Simon , Maddhashiya Shubham , Calderón José Bayoán Santiago , Hatherly Michael , Nyberg Joakim , Gobburu Jogarao V.S. , Ivaturi Vijay 
Published: November 2020

ABSTRACTPharmacometric modeling establishes causal quantitative relationships between administered dose, tissue exposures, desired and undesired effects and patient’s risk factors. These models are employed to de-risk drug development and guide precision medicine decisions. However, pharmacometric tools have not been designed to handle today’s heterogeneous big data and complex models. We set out to design a platform that facilitates domain-specific modeling and its integration with modern analytics to foster innovation and readiness in healthcare.Pumas demonstrates estimation methodologies with dramatic performance advances. New ODE solver algorithms, such as coeficient-optimized higher order integrators and new automatic stiffness detecting algorithms which are robust to frequent discontinuities, give rise to a median 4x performance improvement across a wide range of stiff and non-stiff systems seen in pharmacometric applications. These methods combine with JIT compiler techniques, such as statically-sized optimizations and discrete sensitivity analysis via forward-mode automatic differentiation, to further enhance the accuracy and performance of the solving and parameter estimation process. We demonstrate that when all of these techniques are combined with a validated clinical trial dosing mechanism and non-compartmental analysis (NCA) suite, real applications like NLME fitting see a median 81x acceleration while retaining the same accuracy. Meanwhile in areas with less prior software optimization, like optimal experimental design, we see orders of magnitude performance enhancements over competitors. Further, Pumas combines these technical advances with several workflows that are automated and designed to boost productivity of the day-to-day user activity. Together we show a fast pharmacometric modeling framework for next-generation precision analytics.
Change of dominant strain during dual SARS-CoV-2 infection
Authors: Samoilov AE , Kaptelova VV , Bukharina AY , Shipulina OY , Korneenko EV , Lukyanov AV , Grishaeva AA , Ploskireva AA , Speranskaya AS , Akimkin VG 
Published: November 2020

SummaryBackgroundThe effect of SARS-CoV-2 mutations and viral load on the severity of COVID-19 is not well understood. The possibility of reinfection with SARS-CoV-2 has already been reported, but dual infection with SARS-CoV-2 is poorly described and is currently under discussion. We describe a study of two strains of SARS-CoV-2 detected in the same patient during the same disease presentation.MethodsTwo nasopharyngeal swabs were obtained eight days apart from the patient in their 90s, diagnosed with lobar pneumonia (J18.1). Both tests were positive for SARS-CoV-2 with high viral load (Ct = 13). We have performed high-throughput sequencing of SARS-CoV-2 genomes from both swabs.FindingsGenomic analysis of SARS-CoV-2 revealed the presence of two genetically distant strains in both swabs. Detected strains belong to different phylogenetic clades (GH and GR) and differ in the seven nucleotide positions. The relative abundance of strains was 70% (GH) and 30% (GR) in the first swab, and 3% (GH) and 97% (GR).InterpretationOur findings suggest that the patient was infected by two genetically distinct SARS-CoV-2 strains at the same time. One of the possible explanations is that the second infection occurred in the hospital. Change of the dominant strain ratio during disease manifestation could be explained by the advantage or higher virulence of the strain belonging to the clade GR.
Estimating pulse wave velocity from the radial pressure wave using machine learning algorithms
Authors: Jin Weiwei , Chowienczyk Philip , Alastruey Jordi 
Published: November 2020

AbstractOne of the European gold standard measurement of vascular ageing, a risk factor for cardiovascular disease, is the carotid-femoral pulse wave velocity (cfPWV), which requires an experienced operator to measure pulse waves at two sites. In this work, two machine learning pipelines were proposed to estimate cfPWV from the peripheral pulse wave measured at a single site, the radial pressure wave measured by applanation tonometry. The study populations were the Twins UK cohort containing 3,082 subjects aged from 18 to 110 years, and a database containing 4,374 virtual subjects aged from 25 to 75 years. The first pipeline uses Gaussian process regression to estimate cfPWV from features extracted from the radial pressure wave using pulse wave analysis. The mean difference and upper and lower limits of agreement (LOA) of the estimation on the 924 hold-out test subjects from the Twins UK cohort were 0.2 m/s, and 3.75 m/s & −3.34 m/s, respectively. The second pipeline uses a recurrent neural network (RNN) to estimate cfPWV from the entire radial pressure wave. The mean difference and upper and lower LOA of the estimation on the 924 hold-out test subjects from the Twins UK cohort were 0.05 m/s, and 3.21 m/s & −3.11m/s, respectively. The percentage error of the RNN estimates on the virtual subjects increased by less than 2% when adding 20% of random noise to the pressure waveform. These results show the possibility of assessing the vascular ageing using a single peripheral pulse wave (e.g. the radial pressure wave), instead of cfPWV. The proposed code for the machine learning pipelines is available from the following online depository (https://github.com/WeiweiJin/Estimate-Cardiovascular-Risk-from-Pulse-Wave-Signal).