bluuebunny/crossref_metadata_2025_split huggingface dataset:
Changing Dynamics of COVID-19 in the U.S. with the Emergence of the Delta Variant: Projections of the COVID-19 Simulator
Authors: Chhatwal Jagpreet , Xiao Yingying , Mueller Peter , Adee Madeline , Dalgic Ozden O , Ladd Mary Ann , Ayer Turgay , Linas Benjamin P 
Published: August 2021

SUMMARYWith the recent emergence of the B.1.617.2 (Delta) variant of SARS-CoV-2 in the U.S., many states are seeing rising cases and hospitalizations after a period of steady decline. As We used theCOVID-19 Simulator, an interactive online tool that utilizes a validated mathematical model, to simulate the trajectory of COVID-19 at the state level in the U.S. COVID-19 Simulator’s forecasts are updated weekly and included in the Centers for Disease Control and Prevention (CDC) ensemble model. We employed our model to analyze scenarios where the Delta variant becomes dominant in every state.The combination of high transmissibility of the Delta variant, low vaccination coverage in several regions, and more relaxed attitude towards social distancing is expected to result in as surge in COVID-19 deaths in at least 40 states. In several states – including Idaho, Maine, Montana, Nebraska, North Carolina, Oregon, Puerto Rico, Washington, and West Virginia – the projected daily deaths in 2021 could exceed the prior peak daily deaths under current social distancing behavior and vaccination rate. The number of COVID-19 deaths across the U.S. could exceed 1600 per day.Between August 1, 2021, and December 31, 2021, there could be additional 157,000 COVID-19 deaths across the U.S. Of note, our model projected approximately 20,700 COVID-19 deaths in Texas, 16,000 in California, 12,400 in Florida, 12,000 in North Carolina, and 9,300 in Georgia during this period. In contrast, the projected number of COVID-19 deaths would remain below 200 in New Jersey, Massachusetts, Connecticut, Vermont, and Rhode Island.We project COVID-19 deaths based on the current vaccination rates and social distancing behavior. Our hope is that the findings of this report serve a warning sign and people revert to wearing masks and maintain social distancing to reduce COVID-19 associated deaths in the U.S. Our projections are updated weekly by incorporating vaccination rates and social distancing measures in each state; the latest results can be found at theCOVID-19 Simulatorwebsite.
Epidemiological Study of COVID-19 Infections: Case of Ga East Municipal Hospital Treatment Centre - Kwabenya-Ghana
Authors: Oduro-Mensah Ebenezer , Asubonteng Delali , Crankson Shirley 
Published: August 2021

AbstractBackgroundThe COVID-19 pandemic still poses a considerable threat to global health, resulting in an unprecedented demand for regular research to continuously identify and update its risk profiles to ensure relevant interventions.ObjectivesThis study aimed to examine the epidemiological characteristics of the COVID-19 outbreak in Ghana and identify risk factors for severe COVID-19 disease.MethodThis was a cross-sectional study involving the data of patients with COVID-19 clinically managed at the Ga-East Municipal Hospital, the main COVID-19 treatment centre in Ghana, from 21st March to 21st June 2020. The data were retrieved from the electronic medical records and folders of the patients. It included sociodemographic characteristics, COVID-19 disease severity, and treatment outcomes. Binomial logistic regression was used to identify risk factors of severe COVID-19 illness.ResultAmong the 360 COVID-19 cases in this study, 55.3% were males, and 44.7% were females. Their mean age was 39.9±16.7years. Most of them were Ghanaians (92.8%) and employed (72.5%). The majority (93%) presented with mild disease, and hypertension (19.2%) was the most common comorbidity. The average length of hospital admission was 10.6±6.4day. Many of the cases recovered (98.6%), resulting in a case fatality of 1.4%. Finally, the logistic regression showed that increasing age (OR=1.12, p= 0.002) and diabetes mellitus (OR=19.85, p=0.007) are risk factors for severe COVID-19 disease.ConclusionFindings from the study confirmed that increasing age and diabetes mellitus are risk factors for severe COVID-19 disease. Thus, Ghana could prioritise these identified populations when implementing interventions to reduce the COVID-19 disease burden.Strength and limitations of this studyThis study is one of the few studies exploring the risk factors for severe COVID-19 disease in Ghana; thus, it presents novel context-specific findings that could inform COVID-19 case management in Ghana.The study was limited in drawing a causal association between the explanatory and outcome variables due to the cross-sectional design.The study included only one COVID-19 treatment centre. Consequently, the findings may not be generalizable to the entire COVID-19 population in Ghana, even though the included centre is the main COVID-19 treatment centre.
Heterozygous PRKN mutations are common but do not increase the risk of Parkinson’s disease
Authors: Zhu William , Huang Xiaoping , Yoon Esther , Bandres-Ciga Sara , Blauwendraat Cornelis , Cade Joshua H. , Wu Beverly P. , Williams Victoria H. , Schindler Alice B. , Brooks Janet , Gibbs J Raphael , Hernandez Dena G , Ehrlich Debra , Singleton Andrew , Narendra Derek 
Published: August 2021

ABSTRACTPRKN mutations are the most common recessive cause of Parkinson’s disease (PD) and are a promising target for gene and cell replacement therapies. Identification of biallelic PRKN patients (PRKN-PD) at the population scale, however, remains a challenge, as roughly half are copy number variants (CNVs) and many single nucleotide polymorphisms (SNPs) are of unclear significance. Additionally, the true prevalence and disease risk associated with heterozygous PRKN mutations is unclear, as a comprehensive assessment of PRKN SNPs and CNVs has not been performed at a population scale. To address these challenges, we evaluated PRKN mutations in 2 cohorts analyzed with both a genotyping array and exome or genome sequencing: the NIH PD cohort, a deeply phenotyped cohort of PD patients, and the UK Biobank, a population scale cohort with nearly half a million participants. Genotyping array identified the majority of PRKN mutations and at least 1 mutation in most biallelic PRKN mutation carriers in both cohorts. Additionally, in the NIH-PD cohort, functional assays of patient fibroblasts resolved variants of unclear significance in biallelic carriers and ruled out cryptic loss of function variants in monoallelic carriers. In the UK Biobank, we identified 2,692 PRKN CNVs from genotyping array data from nearly half a million participants (the largest collection to date). Deletions or duplications involving exons 2 accounted for roughly half of all CNVs and the vast majority (88%) involved exons 2, 3, or 4. Combining estimates from whole exome sequencing (from ∼200,000 participants) and genotyping array data, we found a pathogenic PRKN mutation in 1.8% of participants and 2 mutations in ∼1/7,800 participants. Those with 1 PRKN pathogenic variant were as likely as non-carriers to have PD (OR = 0.91, CI= 0.58 – 1.38, p-value = 0.76) or a parent with PD (OR = 1.12, CI = 0.94 – 1.31, p-value = 0.19). Together our results demonstrate that heterozygous pathogenic PRKN mutations are common in the population but do not increase the risk of PD. Additionally, they suggest a cost-effective framework to screen for biallelic PRKN patients at the population scale for targeted studies.
Grandparent inference from genetic data: The potential for parentage-based tagging programs to identify offspring of hatchery strays
Authors: Delomas Thomas A. , Campbell Matthew 
Published: August 2021

AbstractFisheries managers routinely use hatcheries to increase angling opportunity. Many hatcheries operate as segregated programs where hatchery-origin fish are not intended to spawn with natural-origin conspecifics in order to prevent potential negative effects on the natural-origin population. Currently available techniques to monitor the frequency with which hatchery-origin strays successfully spawn in the wild rely on either genetic differentiation between the hatchery- and natural-origin fish or extensive sampling of fish on the spawning grounds. We present a method to infer grandparent-grandchild trios using only genotypes from two putative grandparents and one putative grandchild. We developed estimators of false positive and false negative error rates and showed that genetic panels containing 500 - 700 single nucleotide polymorphisms or 200 - 300 microhaplotypes are expected to allow application of this technique for monitoring segregated hatchery programs. We discuss the ease with which this technique can be implemented by pre-existing parentage-based tagging programs and provide an R package that applies the method.
The relationship between sleep disturbance and cognitive impairment in mood disorders: A systematic review
Authors: Pearson Oliver , Uglik-Marucha Nora , Miskowiak Kamilla W. , Cairney Scott A. , Rosenzweig Ivana , Young Allan H. , Stokes Paul R.A. 
Published: August 2021

AbstractBackgroundCognitive impairment experienced by people with bipolar disorders (BD) or major depressive disorder (MDD) is associated with impaired psychosocial function and poorer quality of life. Sleep disturbance is another core symptom of mood disorders which may be associated with, and perhaps worsen, cognitive impairments. The aim of this systematic review was to critically assess the relationship between sleep disturbance and cognitive impairment in mood disorders.MethodsIn this systematic review, relevant studies were identified using electronic database searches of PsychINFO, MEDLINE, Embase and Web of Science.FindingsFourteen studies were included; eight investigated people with BD, five investigated people with MDD, and one included both people with MDD and people with BD. One study was an intervention for sleep disturbance and the remaining thirteen studies used either a longitudinal or cross-sectional observational design. Ten studies reported a significant association between subjectively measured sleep disturbance and cognitive impairment in people with MDD or BD after adjusting for demographic and clinical covariates, whereas no such association was found in healthy participants. Two studies reported a significant association between objectively measured sleep abnormalities and cognitive impairment in mood disorders. One study of cognitive behavioural therapy for insomnia modified for BD (CBTI-BD) found an association between improvements in sleep and cognitive performance in BD.InterpretationThere is preliminary evidence to suggest a significant association between sleep disturbance and cognitive impairment in mood disorders. These findings suggest that identifying and treating sleep disturbance may be important when addressing cognitive impairment in mood disorders.
A causal association between schizophrenia and bipolar disorder on rheumatoid arthritis: A two-sample Mendelian randomization study
Authors: Koc Gonul Hazal , Ozel Fatih , Okay Kaan , Koc Dogukan , de Jong Pascal H.P. 
Published: August 2021

ABSTRACTBackgroundSchizophrenia (SCZ) and bipolar disorder (BD) are both associated with several autoimmune disorders including rheumatoid arthritis(RA). However, a causal association of SCZ and BD on RA is controversial and elusive. In the present study, we aimed to investigate the causal association of SCZ and BD with RA by using the Mendelian randomization (MR) approach.MethodsA two-sample MR (2SMR) study including the inverse-variance weighted(IVW), weighted median, simple mode, weighted mode and MR-Egger methods were performed. We used summary-level genome-wide association study(GWAS) data in which BD and SCZ are the exposure and RA the outcome. We used data from the Psychiatric Genomics Consortium(PGC) for BD(n= 41,917) and SCZ(n= 33,426) and RA GWAS dataset(n= 2,843) from the European ancestry for RA.ResultsWe found 48 and 52 independent single nucleotide polymorphisms (SNPs, r2 <0.001)) that were significant for respectively BD and SCZ (p <5×10-8). Subsequently, these SNPs were utilized as instrumental variables(IVs) in 2SMR analysis to explore the causality of BD and SCZ on RA. The two out of five MR methods showed a statistically significant inverse causal association between BD and RA: weighted median method(odds ratio (OR), 0.869, [95% CI, 0.764-0.989];P= 0.034) and inverse-variance weighted(IVW) method (OR, 0.810, [95% CI, 0.689-0.953];P= 0.011). However, we did not find any significant association of SCZ with RA (OR, 1.008, [95% CI, 0.931-1.092];P= 0.829, using the IVW method).ConclusionsThese results provide support for an inverse causal association between BD and RA. Further investigation is needed to explain the underlying protective mechanisms in the development of RA.Key messagesMendelian randomization can offer strong insight into the cause-effect relationships in rheumatology.Bipolar disorder had a protective effect on rheumatoid arthritis.There is no inverse causal association between schizophrenia and rheumatoid arthritis contrary to the findings from observational studies.
Efficacy of SARS-CoV-2 vaccine in thoracic cancer patients: a prospective study supporting a third dose in patients with minimal serologic response after two vaccine doses
Authors: Gounant Valérie , Ferré Valentine Marie , Soussi Ghassen , Charpentier Charlotte , Flament Héloïse , Fidouh Nadhira , Collin Gilles , Namour Céline , Assoun Sandra , Bizot Alexandra , Brouk Zohra , Vicaut Eric , Teixeira Luis , Descamps Diane , Zalcman Gérard 
Published: August 2021

AbstractHypothesisCoronavirus disease 2019 (COVID-19) resulted in a 30% mortality rate in thoracic cancer patients. Given that cancer patients were excluded from serum anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) vaccine registration trials, it is still unknown whether they would develop a protective anti-spike antibody response following vaccination. This prospective vaccine monitoring study primarily aimed to assess humoral responses to SARS-CoV2 vaccine in thoracic cancer patients.MethodsSARS-CoV2-spike antibodies were measured using Abbot ARCHITECT SARS-CoV-2 IgG immunoassay, prior to first injection of BNT162b2 mRNA vaccine, as well as at Week 4, and two-to-sixteen weeks after second vaccine dose. The factors associated with antibody response were analyzed.ResultsOverall, 306 patients, with a median age of 67.0 years (IQR=58-74), were vaccinated. Of these, 283 patients received two vaccine doses at 28-day intervals. After 4.7-month median follow-up, seven patients (2.3%) contracted proven symptomatic SARS-CoV-2 infection, with rapid favorable evolution. Of 269 serological results available beyond Day 14 post-second vaccine dose, 17 (6.3%) were still negative (<50 AU/mL) (arbitrary units/mL), while 34 (11%)were <300 AU/mL (12.5thpercentile). In multivariate analysis, only age and chronic corticosteroid treatment were significantly associated with a lack of immunization. Thirty patients received a third vaccine dose, with only three patients showing persistent negative serology thereafter, whereas the others demonstrated clear seroconversion.ConclusionSARS-CoV2 vaccines were shown to be efficient in thoracic cancer patients, most of them being immunized after two doses. A third shot given to 1% of patients with persistent low antibody titers resulted in a 88% immunization rate.
Pandemic excess mortality in Spain, Sweden, and Switzerland during the COVID-19 pandemic in 2020 was at its highest since 1918
Authors: Staub Kaspar , Panczak Radoslaw , Matthes Katarina L. , Floris Joël , Berlin Claudia , Junker Christoph , Weitkunat Rolf , Mamelund Svenn-Erik , Egger Matthias , Zwahlen Marcel , Riou Julien 
Published: August 2021

AbstractEstimating excess mortality allows quantification of overall pandemic impact. For recent decades, mortality data are easily accessible for most industrialized countries, but only a few countries have continuous data available for longer periods. Since Spain, Sweden, and Switzerland were militarily neutral and not involved in combat during both world wars, these countries have monthly all-cause mortality statistics available for over 100 years with no interruptions. We show that during the COVID-19 pandemic in 2020, Spain, Sweden and Switzerland recorded the highest aggregated monthly excess mortality (17%, 9% and 14%) since the 1918 influenza pandemic (53%, 33% and 49%), when compared to respective expected values. For Sweden and Switzerland, the highest monthly spikes in 2020 almost reached those of January 1890. These findings emphasize the historical dimensions of the ongoing pandemic and support the notion of a pandemic disaster memory gap.One-Sentence SummaryDuring the COVID-19 pandemic in 2020, Spain, Sweden, and Switzerland recorded their highest monthly excess and all-cause mortality levels since the 1918 influenza pandemic, emphasizing the historical dimension of the ongoing pandemic.
Clinical course impacts early kinetics and long-term magnitude and amplitude of SARS-CoV-2 neutralizing antibodies beyond one year after infection
Authors: Pradenas Edwards , Trinité Benjamin , Urrea Víctor , Marfil Silvia , Tarrés-Freixas Ferran , Ortiz Raquel , Rovirosa Carla , Rodon Jordi , Vergara-Alert Júlia , Segalés Joaquim , Guallar Victor , Valencia Alfonso , Izquierdo-Useros Nuria , Noguera-Julian Marc , Carrillo Jorge , Paredes Roger , Mateu Lourdes , Chamorro Anna , Toledo Ruth , Massanella Marta , Clotet Bonaventura , Blanco Julià 
Published: August 2021

AbstractBackgroundUnderstanding the determinants of long-term immune responses to SARS-CoV-2 and the concurrent impact of vaccination and emerging variants of concern will guide optimal strategies to achieve global protection against the COVID-19 pandemic.MethodsA prospective cohort of 332 COVID-19 patients was followed beyond one year. Plasma neutralizing activity was evaluated using HIV-based reporter pseudoviruses expressing different SARS-CoV-2 spikes and was longitudinally analyzed using mixed-effects models.FindingsLong-term neutralizing activity was stable beyond one year after infection in mild/asymptomatic and hospitalized participants. However, longitudinal models suggest that hospitalized individuals generate both short- and long-lived memory B cells, while outpatient responses were dominated by long-lived B cells. In both groups, vaccination boosted responses to natural infection, although viral variants, mainly B.1.351, reduced the efficacy of neutralization. Importantly, despite showing higher neutralization titers, hospitalized patients showed lower cross-neutralization of B.1.351 variant compared to outpatients. Multivariate analysis identified severity of primary infection as the factor that independently determines both the magnitude and the inferior cross-neutralization activity of long-term neutralizing responses.ConclusionsNeutralizing response induced by SARS-CoV-2 is heterogeneous in magnitude but stable beyond one year after infection. Vaccination boosts these long-lasting natural neutralizing responses, counteracting the significant resistance to neutralization of new viral variants. Severity of primary infection determines higher magnitude but poorer quality of long-term neutralizing responses.
Seroprevalence of anti-SARS-CoV-2 antibodies six months into the vaccination campaign in Geneva, Switzerland
Authors: Stringhini Silvia , Zaballa María-Eugenia , Pullen Nick , Perez-Saez Javier , de Mestral Carlos , Loizeau Andrea , Lamour Julien , Pennacchio Francesco , Wisniak Ania , Dumont Roxane , Baysson Hélène , Richard Viviane , Lorthe Elsa , Semaani Claire , Balavoine Jean-François , Pittet Didier , Vuilleumier Nicolas , Chappuis François , Kherad Omar , Azman Andrew S. , Posfay-Barbe Klara , Kaiser Laurent , Guessous Idris ,   the Specchio-COVID19 study group
Published: August 2021

AbstractBackgroundUp-to-date seroprevalence estimates are critical to describe the SARS-CoV-2 immune landscape in the population and guide public health measures. We aimed to estimate the seroprevalence of anti-SARS-CoV-2 antibodies 15 months into the COVID-19 pandemic and six months into the vaccination campaign.MethodsWe conducted a population-based cross-sectional serosurvey between June 1 and July 7, 2021, recruiting participants from age- and sex-stratified random samples of the general population. We tested participants for anti-SARS-CoV-2 antibodies targeting the spike (S) or nucleocapsid (N) proteins (Roche Elecsys immunoassays). We estimated the anti-SARS-CoV-2 antibodies seroprevalence following vaccination and/or infection (anti-S antibodies), or infection only (anti-N antibodies).ResultsWe included 3355 individuals, of which 1814 (54.1%) were women, 697 (20.8%) were aged <18 years and 449 (13.4%) were aged ≥65 years, 2161 (64.4%) tested positive for anti-S antibodies, and 906 (27.0%) tested positive for anti-N antibodies. The total seroprevalence of anti-SARS-CoV-2 antibodies was 66.1% (95% credible interval, 64.1-68.0). We estimated that 29.9% (28.0-31.9) of the population developed antibodies after infection; the rest having developed antibodies only via vaccination. Seroprevalence estimates were similar across sexes, but differed markedly across age groups, being lowest among children aged 0-5 years (20.8% [15.5-26.7]) and highest among older adults aged ≥75 years (93.1% [89.6-96.0]). Seroprevalence of antibodies developed via infection and/or vaccination was higher among participants with a higher educational level.ConclusionsMost adults have developed anti-SARS-CoV-2 antibodies, while most teenagers and children remain vulnerable to infection. As the SARS-CoV-2 Delta variant spreads and vaccination rates stagnate, efforts are needed to address vaccine hesitancy, particularly among younger individuals and socioeconomically disadvantaged groups, and to minimize spread among children.
Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks
Authors: Tran Thanh T. , Pham Hieu H. , Nguyen Thang V. , Le Tung T. , Nguyen Hieu T. , Nguyen Ha Q. 
Published: August 2021

AbstractChest radiograph (CXR) interpretation is critical for the diagnosis of various thoracic diseases in pediatric patients. This task, however, is error-prone and requires a high level of understanding of radiologic expertise. Recently, deep convolutional neural networks (D-CNNs) have shown remarkable performance in interpreting CXR in adults. However, there is a lack of evidence indicating that D-CNNs can recognize accurately multiple lung pathologies from pediatric CXR scans. In particular, the development of diagnostic models for the detection of pediatric chest diseases faces significant challenges such as (i) lack of physician-annotated datasets and (ii) class imbalance problems. In this paper, we retrospectively collect a large dataset of 5,017 pediatric CXR scans, for which each is manually labeled by an experienced radiologist for the presence of 10 common pathologies. A D-CNN model is then trained on 3,550 annotated scans to classify multiple pediatric lung pathologies automatically. To address the highclass imbalance issue, we propose to modify and apply “Distribution-Balanced loss” for training D-CNNs which reshapes the standard Binary-Cross Entropy loss (BCE) to efficiently learn harder samples by down-weighting the loss assigned to the majority classes. On an independent test set of 777 studies, the proposed approach yields an area under the receiver operating characteristic (AUC) of 0.709 (95% CI, 0.690–0.729). The sensitivity, specificity, and F1-score at the cutoff value are 0.722 (0.694–0.750), 0.579 (0.563–0.595), and 0.389 (0.373–0.405), respectively. These results significantly outperform previous state-of-the-art methods on most of the target diseases. Moreover, our ablation studies validate the effectiveness of the proposed loss function compared to other standard losses, e.g., BCE and Focal Loss, for this learning task. Overall, we demonstrate the potential of D-CNNs in interpreting pediatric CXRs.