bluuebunny/crossref_metadata_2025_split huggingface dataset:
The influence of human genetic variation on Epstein-Barr virus sequence diversity
Authors: Rüeger Sina , Hammer Christian , Loetscher Alexis , McLaren Paul J , Lawless Dylan , Naret Olivier , Depledge Daniel P. , Morfopoulou Sofia , Breuer Judith , Zdobnov Evgeny , Fellay Jacques ,   Swiss HIV Cohort Study
Published: December 2020

AbstractEpstein-Barr virus (EBV) is one of the most common viruses latently infecting humans. Little is known about the impact of human genetic variation on the large inter-individual differences observed in response to EBV infection. To search for a potential imprint of host genomic variation on the EBV sequence, we jointly analyzed paired viral and human genomic data from 268 HIV-coinfected individuals with CD4+ T cell count <200/mm3 and elevated EBV viremia. We hypothesized that the reactivated virus circulating in these patients could carry sequence variants acquired during primary EBV infection, thereby providing a snapshot of early adaptation to the pressure exerted on EBV by the individual immune response. We searched for associations between host and pathogen genetic variants, taking into account human and EBV population structure. Our analyses revealed significant associations between human and EBV sequence variation. Three polymorphic regions in the human genome were found to be associated with EBV variation: one at the amino acid level (BRLF1:p.Lys316Glu); and two at the gene level (burden testing of rare variants in BALF5 and BBRF1). Our findings confirm that jointly analyzing host and pathogen genomes can identify sites of genomic interactions, which could help dissect pathogenic mechanisms and suggest new therapeutic avenues.
Can serum biomarkers predict the outcome of systemic therapy for atopic dermatitis?
Authors: Hurault Guillem , Roekevisch Evelien , Schram Mandy E. , Szegedi Krisztina , Kezic Sanja , Middelkamp-Hup Maritza A. , Spuls Phyllis I. , Tanaka Reiko J. 
Published: December 2020

SUMMARYBackgroundAtopic dermatitis (AD or eczema) is a most common chronic skin disease. Designing personalised treatment strategies for AD based on patient stratification, rather than the “one-size-fits-all” treatments, is of high clinical relevance. It has been hypothesised that the measurement of biomarkers could help predict therapeutic response for individual patients.ObjectiveWe aim to assess whether biomarkers can predict the outcome of systemic therapy.MethodsWe developed a statistical machine learning predictive model using the data of an already published longitudinal study of 42 patients who received systemic therapy. The data contained 26 serum cytokines measured before the therapy. The model described the dynamics of the latent disease severity and measurement errors to predict AD severity scores (EASI, (o)SCORAD and POEM) two-weeks ahead. We conducted feature selection to identify the most important biomarkers for predicting the AD severity scores.ResultsWe validated our model and confirmed that it outperformed standard time-series forecasting models. Adding biomarkers did not improve predictive performance. Our estimates of the minimum detectable change for the AD severity scores were larger than already published estimates of the minimal clinically important difference.ConclusionsBiomarkers had a negligible and non-significant effect for predicting the future AD severity scores and the outcome of the systemic therapy. Instead, a historical record of severity scores provides rich and insightful dynamical information required for prediction of therapeutic responses.
Childhood growth and development and DNA methylation age in mid-life
Authors: Maddock Jane , Castillo-Fernandez Juan , Wong Andrew , Ploubidis George B , Kuh Diana , Bell Jordana T , Hardy Rebecca 
Published: December 2020

ABSTRACTBackgroundIn the first study of its kind, we examine the association between growth and development in early life and DNAm age biomarkers in mid-life.MethodsParticipants were from the Medical Research Council National Survey of Health and Development(n=1,376). Four DNAm age acceleration(AgeAccel) biomarkers were measured when participants were aged 53y:AgeAccelHannum, AgeAccelHorvath, AgeAccelLevine and AgeAccelGrim. Exposure variables included relative weight gain (standardised residuals from models of current weight z-score on current height, and previous weight and height z-scores) and linear growth (standardised residuals from models of current height z-score on previous height and weight z-scores) during infancy (0-2y, weight gain only), early childhood(2-4y), middle childhood(4-7y) and late childhood to adolescence(7- 15y), age at menarche and pubertal stage for men at 14-15y. The relationship between relative weight gain and linear growth and AgeAccel was investigated using conditional growth models. We replicated analyses from the late childhood to adolescence period and pubertal timing among 240 participants from The National Child and Development Study(NCDS).ResultsA 1 SD increase in relative weight gain in late childhood to adolescence was associated with 0.50y(95% CI:0.20,0.79) higher AgeAccelGrim. This was replicated in NCDS (0.57y(95%CI:-0.01, 1.16). A I SD increase in linear growth during early childhood was associated with lower AgeAccelLevine(−0.39y [95% CI:-0.74,-0.04) however we did not have the data to replicate this finding in NCDS. There was no strong evidence that relative weight gain and linear growth in childhood was associated with any other AgeAccel biomarker. There was no relationship between pubertal timing in men and AgeAccel biomarkers. Women who reached menarche ≥12y had 1.20y(95% CI:0.15,2.24) higher AgeAccelGrim on average than women who reached menarche <12y; however this was not replicated in NCDS.ConclusionsOur findings generally do not support an association between growth and AgeAccel biomarkers in mid-life. However, rapid weight gain during pubertal development, which we found to be related to older AgeAccelGrim and had previously been related to higher cardiovascular disease risk, warrants further investigation.
Causative Organisms, Antibiotic Sensitivity Patterns and Risk Factors Associated with Neonatal Sepsis at Moi Teaching and Referral Hospital, Kenya
Authors: Ateka Benard Mageto , Songok Julia , Nyandiko Winstone 
Published: December 2020

ABSTRACTBackgroundNeonatal bacterial infections have been associated with rising antimicrobial resistance levels. This has led to increasing neonatal morbidity and mortality in poorly resourced health facilities located in low income countries. Local studies on neonatal antibiotic sensitivity patterns and its associated risk factors could inform empirical antibiotic therapy and hospital infection control strategies.PurposeThe study aimed at determining the causative organisms, antibiotic sensitivity patterns and risk factors associated with neonatal sepsis at a tertiary teaching hospital in Western Kenya.Materials and MethodsCross-sectional study among neonates suspected to have sepsis and undergoing treatment at Moi Teaching and Referral Hospital (MTRH’s) newborn unit (NBU) between September 2017 and July 2018. Blood culture tests isolated bacteria and determined their antimicrobial sensitivity. Neonatal and maternal characteristics were obtained through medical chart reviews. Descriptive statistics, Pearson chi-square test of association and odds ratios were adopted.ResultsThe study enrolled 141 neonates, majority (57.4%) of whom were female. The median gestational age and birth weight were 37 (IQR: 22-45) weeks and 2400g (IQR: 800 - 4700) respectively. Of the 151 bacterial isolates identified, 46.4% were Klebsiella spp. followed by Coagulate negative staphylococcus (CoNS) at 27.8%. Klebsiella spp. was sensitive to meropenem, amikacin and cefepime but resistant to ceftriaxone, gentamycin and cefotaxime. However, CoNS was sensitive to vancomycin and penicillin. Both the neonatal and maternal risk factors assessed were not associated with neonatal sepsis.ConclusionThe main bacterial causes of neonatal sepsis were Klebsiella spp. and CoNS which were both sensitivity to meropenem and amikacin.
Electrocorticography and stereo EEG provide distinct measures of brain connectivity: Implications for network models
Authors: Bernabei John M. , Arnold T. Campbell , Shah Preya , Revell Andrew , Ong Ian Z. , Kini Lohith G. , Stein Joel M. , Shinohara Russell T. , Lucas Timothy H. , Davis Kathryn A. , Bassett Danielle S. , Litt Brian 
Published: December 2020

AbstractBrain network models derived from graph theory have the potential to guide functional neurosurgery, and to improve rates of post-operative seizure freedom for patients with epilepsy. A barrier to applying these models clinically is that intracranial EEG electrode implantation strategies vary by center, region and country, from cortical grid & strip electrodes (ECoG), to purely stereotactic depth electrodes (SEEG), to a mixture of both. To determine whether models derived from one type of study are broadly applicable to others, we investigate the differences in brain networks mapped by ECoG and SEEG in a cohort of patients who underwent surgery for temporal lobe epilepsy and achieved a favorable outcome. We show that networks derived from ECoG and SEEG define distinct relationships between resected and spared tissue, which may be driven by sampling bias of temporal depth electrodes in patients with predominantly cortical grids. We propose a method of correcting for the effect of internodal distance that is specific to electrode type and explore how additional methods for spatially correcting for sampling bias affect network models. Ultimately, we find that smaller surgical targets tend to have lower connectivity with respect to the surrounding network, challenging notions that abnormal connectivity in the epileptogenic zone is typically high. Our findings suggest that effectively applying computational models to localize epileptic networks requires accounting for the effects of spatial sampling, particularly when analyzing both ECoG and SEEG recordings in the same cohort, and that future network studies of epilepsy surgery should also account for differences in focality between resection and ablation. We propose that these findings are broadly relevant to intracranial EEG network modeling in epilepsy and an important step in translating them clinically into patient care.Author summaryBernabei et al. report that electrocorticography and stereo EEG provide different quantifications of epileptogenic zone connectivity due to differences in electrode type and implant patterns. After correcting for sampling differences between modalities, they find that more focal forms of epilepsy surgery target regions of weaker connectivity compared to the remaining epileptic network.
Determinants of COVID-19 Incidence and Mortality in the US: Spatial Analysis
Authors: Kathe Niranjan J. , Wani Rajvi J. 
Published: December 2020

ABSTRACTOBJECTIVESThe US continues to account for the highest proportion of the global Coronavirus Disease-2019 (COVID-19) cases and deaths. Currently, it is important to contextualize the spread and success of mitigation efforts. The objective of this study was to assess the ecological determinants (policy, health behaviors, socio-economic, physical environment, and clinical care) of COVID-19 incidence and mortality in the US.METHODSData from the New York Times’ COVID-19 repository (01/21/2020-10/27/2020), 2020 County Health Rankings, 2016 County Presidential Election Returns, and 2018-2019 Area Health Resource File were used. County-level logged incidence and mortality rate/million were modeled using the Spatial Autoregressive Combined model and spatial lag model.RESULTSCounties with higher proportions of racial minorities (African American β= 0.007, Native Americans β= 0.008, Hispanics β= 0.015), non-English speakers (β= 0.010), population density ([logged] β= 0.028), and air pollution (β= 0.062) were significantly associated with high COVID-19 incidence rates. Subsequently, counties with higher Republican voters (β= 0.017), excessive drinkers (β= 0.107), children in single-parent households (β= 0.018), uninsured adults (β= 0.038), racial minorities (African American β= 0.032, Native Americans β= 0.034, Hispanics β= 0.037), females (β= 0.101), and population density ([logged] β= 0.270), air pollution (β= 0.130), and non-Whites/Whites’ residential segregation (β= 0.014) were significantly associated with high COVID-19 mortality rates. Additionally, longer state-level restrictions were associated with lower COVID-19 incidence and mortality rates.CONCLUSIONSThe spatial models identified longer state-level restrictions, population density, air pollution, uninsured rate, and race/ethnicity as important determinants of the geographic disparities in COVID-19 incidence and mortality.
The impact of seasonal respiratory virus transmission on syndromic surveillance for COVID-19 in Ontario, Canada
Authors: Maharaj Arjuna , Parker Jennifer , Hopkins Jessica P. , Gournis Effie , Bogoch Isaac I. , Rader Benjamin , Astley Christina M. , Ivers Noah , Hawkins Jared B. , Tuite Ashleigh R. , Fisman David N. , Brownstein John S. , Lapointe-Shaw Lauren 
Published: December 2020

ABSTRACTBackgroundSyndromic surveillance systems for COVID-19 are being increasingly used to track and predict outbreaks of confirmed cases. Seasonal circulating respiratory viruses share syndromic overlap with COVID-19, and it is unknown how they will impact the performance of syndromic surveillance tools. Here we investigated the role of non-SARS-CoV-2 respiratory virus test positivity on COVID-19 two independent syndromic surveillance systems in Ontario, Canada.MethodsWe compared the weekly number of reported COVID-19 cases reported in the province of Ontario against two syndromic surveillance metrics: 1) the proportion of respondents with a self-reported COVID-like illness (CLI) from COVID Near You (CNY) and 2) the proportion of emergency department visits for upper respiratory conditions from the Acute Care Enhanced Surveillance (ACES) system. Separately, we plotted the percent positivity for other seasonal respiratory viruses over the same time period and reported Pearson’s correlation coefficients before and after the uncoupling of syndromic tools to COVID-19 cases.ResultsThere were strong positive correlations of both CLI and ED visits for upper respiratory causes with COVID-19 cases up to and including a rise in entero/rhinovirus (r = 0.86 and 0.87, respectively). There was a strong negative correlation of both CLI and ED visits for upper respiratory causes with COVID-19 cases (r = −0.85 and −0.91, respectively) during a fall in entero/rhinovirus.InterpretationTwo methods of syndromic surveillance showed strong positive correlations with COVID-19 confirmed case counts before and during a rise in circulating entero/rhinovirus. However, as positivity for enterovirus/rhinovirus fell in late September 2020, syndromic signals became uncoupled from COVID-19 cases and instead tracked the fall in entero/rhinovirus. This finding provides proof-of-principle that regional transmission of seasonal respiratory viruses may complicate the interpretation of COVID-19 surveillance data. It is imperative that surveillance systems incorporate other respiratory virus testing data in order to more accurately track and forecast COVID-19 disease activity.
Modelling the Test, Trace and Quarantine Strategy to Control the COVID-19 Epidemic in the State of São Paulo, Brazil
Authors: Amaku Marcos , Covas Dimas Tadeu , Coutinho Francisco Antonio Bezerra , Azevedo Neto Raymundo Soares , Struchiner Claudio , Wilder-Smith Annelies , Massad Eduardo 
Published: December 2020

AbstractTesting for detecting the infection by SARS-CoV-2 is the bridge between the lockdown and the opening of society. In this paper we modelled and simulated a test-trace-and-quarantine strategy to control the COVID-19 outbreak in the State of São Paulo, Brasil. The State of São Paulo failed to adopt an effective social distancing strategy, reaching at most 59% in late March and started to relax the measures in late June, dropping to 41% in 08 August. Therefore, São Paulo relies heavily on a massive testing strategy in the attempt to control the epidemic.Two alternative strategies combined with economic evaluations were simulated. One strategy included indiscriminately testing the entire population of the State, reaching more than 40 million people at a maximum cost of 2.25 billion USD, that would reduce the total number of cases by the end of 2020 by 90%. The second strategy investigated testing only symptomatic cases and their immediate contacts – this strategy reached a maximum cost of 150 million USD but also reduced the number of cases by 90%.The conclusion is that if the State of São Paulo had decided to adopt the simulated strategy on April the 1st, it would have been possible to reduce the total number of cases by 90% at a cost of 2.25 billion US dollars for the indiscriminate strategy but at a much smaller cost of 125 million US dollars for the selective testing of symptomatic cases and their contacts.
Mapping each pre-existing condition’s association to short-term and long-term COVID-19 complications
Authors: Venkatakrishnan AJ , Pawlowski Colin , Zemmour David , Hughes Travis , Anand Akash , Berner Gabriela , Kayal Nikhil , Puranik Arjun , Conrad Ian , Bade Sairam , Barve Rakesh , Sinha Purushottam , O’Horo John C. , Badley Andrew D. , Soundararajan Venky 
Published: December 2020

AbstractUnderstanding the relationships between pre-existing conditions and complications of COVID-19 infection is critical to identifying which patients will develop severe disease. Here, we leverage 1.1 million clinical notes from 1,903 hospitalized COVID-19 patients and deep neural network models to characterize associations between 21 pre-existing conditions and the development of 20 complications (e.g. respiratory, cardiovascular, renal, and hematologic) of COVID-19 infection throughout the course of infection (i.e. 0-30 days, 31-60 days, and 61-90 days). Pleural effusion was the most frequent complication of early COVID-19 infection (23% of 383 complications) followed by cardiac arrhythmia (12% of 383 complications). Notably, hypertension was the most significant risk factor associated with 10 different complications including acute respiratory distress syndrome, cardiac arrhythmia and anemia. Furthermore, novel associations between cancer (risk ratio: 3, p=0.02) or immunosuppression (risk ratio: 4.3, p=0.04) with early-onset heart failure have also been identified. Onset of new complications after 30 days is rare and most commonly involves pleural effusion (31-60 days: 24% of 45 patients, 61-90 days: 25% of 36 patients). Overall, the associations between pre-COVID conditions and COVID-associated complications presented here may form the basis for the development of risk assessment scores to guide clinical care pathways.
Anemia is a risk factor for rehospitalization after SARS-CoV-2 clearance
Authors: Lenehan Patrick , Ramudu Eshwan , Venkatakrishnan AJ , Berner Gabriela , McMurry Reid , O’Horo John C. , Badley Andrew D. , Morice William , Halamka John , Soundararajan Venky 
Published: December 2020

SummaryBackgroundAs the number of new and recovering COVID-19 cases continues to rise, it has become evident that patients can experience symptoms and complications after viral clearance. Clinical biomarkers characterizing patients who are likely to experience these prolonged effects are unknown.MethodsWe conducted a retrospective study to compare longitudinal lab test measurements (hemoglobin, hematocrit, estimated glomerular filtration rate, serum creatinine, and blood urea nitrogen) in patients rehospitalized after PCR-confirmed SARS-CoV-2 clearance (n=104) versus patients not rehospitalized after viral clearance (n=278).FindingsCompared to patients who were not rehospitalized after PCR-confirmed viral clearance, those who were rehospitalized had lower median hemoglobin levels in the year prior to COVID-19 diagnosis (cohen’s D = -0.50; p=1.2×10−3) and during the active infection window (cohen’s D = -0.71; p=4.6×10−8). Patients hospitalized after viral clearance were also more likely to be diagnosed with moderate or severe anemia during the active infection window (OR = 2.18; p = 4.99×10−9).ConclusionsThe occurrence of moderate or severe anemia in hospitalized COVID-19 patients is strongly associated with rehospitalization after viral clearance. Whether interventions to mitigate anemia can improve long term outcomes of COVID-19 patients should be further investigated.FundingThis study was funded by nference.
A Systematic Review and Meta-Analysis of Studies Examining the Relationship Between Reported Racism and Health and Wellbeing for Children and Adolescents
Authors: Priest Naomi , Doery Kate , Truong Mandy , Guo Shuaijun , Trenerry Brigid , Karlsen Saffron , Kelly Yvonne , Paradies Yin 
Published: December 2020

ABSTRACTIntroductionThere is a growing body of research showing associations between experiences of racism and poor health and wellbeing outcomes for children and adolescents. The aim of this review protocol is to update the first systematic review conducted by Priest et al. 2013, including a meta-analysis of findings. Based on previous empirical data, it is anticipated that child and adolescent health will be negatively impacted by racism. This review will provide updated evidence of effect sizes across outcomes and identify moderators and mediators of relationships.Methods and analysisThis systematic review and meta-analysis will include studies that explore associations between experiences of racism and racial dissemination with health outcomes of children and adolescents aged 0- 24 years of age from any racial/ethnic/cultural group. Outcome measures include general health and wellbeing, physical health, mental health, healthcare utilisation and health behaviours. Exposure measures include self- reported and proxy reported personal experiences of racism and reported experiences of vicarious racism. The authors will conduct a comprehensive search of studies from the earliest time available to September 2020. All relevant studies will be screened with data extraction, quality appraisal and publication bias conducted independently by at least two authors.Ethics and DisseminationThis review will provide evidence for future research within the field and help to support policy and practice development. Results from this systematic review and meta-analysis will be widely disseminated to both academic and non-academic audiences.Ethics approval is not required as this is a review of existing empirical findings.Article Summary-This is an updated systematic review which aims to update the findings from the first international review conducted by Priest et al. 2013. However, it is the first meta-analysis to be conducted exploring the relationship between racism and health in child and adolescent from all ethnic/racial/cultural backgrounds.-This systematic review will show the health effects of racial discrimination on child and adolescent health, the key pathways by which racial discrimination influences these outcomes and identify potential moderators and mediators.-Findings from this systematic review and meta-analysis will be used to provide recommendations for future research and inform the development of effective evidence-based strategies for addressing racism and ameliorating its harmful effects.-This systematic review has a bias towards papers published in English as this review will only search studies published in English, meaning that studies not-published in English will not be included in this review. By doing so this review may not include all findings of all relevant studies.