bluuebunny/crossref_metadata_2025_split huggingface dataset:
Racial and Ethnic Disparities in Years of Potential Life Lost Attributable to COVID-19 in the United States: An Analysis of 45 States and the District of Columbia
Authors: Xu Jay J. , Chen Jarvis T. , Belin Thomas R. , Brookmeyer Ronald S. , Suchard Marc A. , Ramirez Christina M. 
Published: January 2021

AbstractThe coronavirus disease 2019 (COVID-19) epidemic in the United States has disproportionately impacted communities of color across the country. Focusing on COVID-19-attributable mortality, we expand upon a national comparative analysis of years of potential life lost (YPLL) attributable to COVID-19 by race/ethnicity (Bassett et al., 2020), estimating percentages of total YPLL for non-Hispanic Whites, non-Hispanic Blacks, Hispanics, non-Hispanic Asians, and non-Hispanic American Indian or Alaska Natives, contrasting them with their respective percent population shares, as well as age-adjusted YPLL rate ratios – anchoring comparisons to non-Hispanic Whites – in each of 45 states and the District of Columbia using data from the National Center for Health Statistics as of December 30, 2020. Using a novel Monte Carlo simulation procedure to quantify estimation uncertainty, our results reveal substantial racial/ethnic disparities in COVID-19-attributable YPLL across states, with a prevailing pattern of non-Hispanic Blacks and Hispanics experiencing disproportionately high and non-Hispanic Whites experiencing disproportionately low COVID-19-attributable YPLL. Furthermore, observed disparities are generally more pronounced when measuring mortality in terms of YPLL compared to death counts, reflecting the greater intensity of the disparities at younger ages. We also find substantial state-to-state variability in the magnitudes of the estimated racial/ethnic disparities, suggesting that they are driven in large part by social determinants of health whose degree of association with race/ethnicity varies by state.
R1441G but not G201S mutation enhances LRRK2 mediated Rab10 phosphorylation in human peripheral blood neutrophils
Authors: Fan Ying , Nirujogi Raja S. , Garrido Alicia , Martínez Javier Ruiz , Bergareche-Yarza Alberto , Mondragón Rezola Elisabet , Aragón Ana Vinagre , Croitoru Ioana , Pagola Ana Gorostidi , Markinez Laura Paternain , Alcalay Roy , Hickman Richard A. , Duering Jonas , Pratuseviciute Neringa , Padmanabhana Shalini , Valldeoriola Francesc , José Martí Maria , Tolosa Eduardo , Alessi Dario R , Sammler Esther 
Published: January 2021

AbstractGain-of kinase function variants in LRRK2 (leucine-rich repeat kinase 2) cause Parkinson’s disease (PD), albeit with incomplete and age-dependent penetrance, offering the prospect of disease-modifying treatment strategies via LRRK2 kinase inhibition. LRRK2 phosphorylates a subgroup of RabGTPases including Rab10 and pathogenic mutations enhance LRRK2-mediated phosphorylation of Rab10 at Thr73.In this study we analyse LRRK2 dependent Rab10Thr73 phosphorylation in human peripheral blood neutrophils isolated from 101 individuals using quantitative immunoblotting and mass spectrometry. Our cohort includes 42 LRRK2 mutation carriers (21 with the G2019S mutation that resides in the kinase domain and 21 with the R1441G mutation that lies within the ROC-COR domain), 27 patients with idiopathic PD, and 32 controls.We show that LRRK2 dependent Rab10 Thr73 phosphorylation is significantly elevated in all R1441G LRRKR2 mutation carriers irrespective of disease status. PD manifesting and non-manifesting G2019S mutation carriers as well as idiopathic PD samples did not display elevated Rab10 Thr73 phosphorylation. Furthermore, we analysed brain samples of 10 G2019S and 1 R1441H mutation carriers as well as 10 individuals with idiopathic PD and 10 controls. We find high variability for pRab10Thr73 phosphorylation amongst donors irrespective of genetic and disease state.We conclude that in vivo LRRK2 dependent pRab10Thr73 analysis in human peripheral blood neutrophils is a specific and robust biomarker for LRRK2 kinase activation for individuals with mutations such as R1441G that enhance pRab10Thr73 phosphorylation over 2-fold. We provide the first evidence that the LRRK2 R1441G mutation enhances LRRK2 kinase activity in a primary human cell.
SARS-CoV-2 Seroepidemiology in Children and Adolescents
Authors: Levorson Rebecca E , Christian Erica , Hunter Brett , Sayal Jasdeep , Sun Jiayang , Bruce Scott A , Garofalo Stephanie , Southerland Matthew , Ho Svetlana , Levy Shira , Defillipi Christopher , Peake Lilian , Place Frederick C , Hourigan Suchitra K 
Published: January 2021

AbstractObjectivesPediatric SARS-CoV-2 data remain limited and seropositivity rates in children were reported as <1% early in the pandemic. Seroepidemiologic evaluation of SARS-CoV-2 in children in a major metropolitan region of the United States was performed.MethodsChildren and adolescents ≤19 years were enrolled in a cross-sectional, observational study of SARS-CoV-2 seroprevalence from July-October 2020 in Northern Virginia, United States. Demographic, health, and COVID-19 exposure information was collected, and blood was analyzed for SARS-CoV-2 spike protein total antibody. Risk factors associated with SARS-CoV-2 seropositivity were analyzed. Orthogonal antibody testing was performed, and samples were evaluated for responses to different antigens.ResultsIn 1038 children, the anti-SARS-CoV-2 total antibody positivity rate was 8.5%. After multivariate logistic regression, significant risk factors included Hispanic ethnicity, public or absent insurance, a history of COVID-19 symptoms, exposure to person with COVID-19, a household member positive for SARS-CoV-2 and multi-family or apartment dwelling without a private entrance. 66% of seropositive children had no symptoms of COVID-19. Orthogonal antibody testing with a receptor binding domain specific antigen revealed a high concordance of 80.5%. Children also demonstrated a robust immune response to the nucleocapsid antigen.ConclusionsA much higher burden of SARS-CoV-2 infection, as determined by seropositivity, was found in children than previously reported; this was also higher compared to adults in the same region at a similar time. Contrary to prior reports, we determined children shoulder a significant burden of COVID-19 infection. The role of children’s disease transmission must be considered in COVID-19 mitigation strategies including vaccination.Article Summary8.5% of children had SARS-CoV-2 antibodies in Fall 2020, double the adult rate. The role of pediatric infection is important to consider in mitigation strategies.What’s Known on This SubjectSARS-CoV-2 pediatric seroepidemiologic data is limited. Reported viral rates underestimate the burden of infection in children due to mild or asymptomatic disease. Limited cohorts of children suggest low seropositivity rates compared to adults.What This Study AddsUS children in the largest SARS-CoV-2 seroepidemiology study to date had double the rate of antibodies compared to adults. Most children were asymptomatic. Risk factors include age, ethnicity and living conditions. Most children made antibodies to different antigens of SARS-CoV-2.
The Impact of Distractions on Intracortical Brain-Computer Interface Control of a Robotic Arm
Authors: Guthrie Michael D. , Herrera Angelica J. , Downey John E. , Brane Lucas J. , Boninger Michael L. , Collinger Jennifer L. 
Published: January 2021

AbstractThis was an investigational device observational trial with the objective to evaluate the impact of distractions on intracortical brain-computer interface (BCI) performance. Two individuals with tetraplegia had microelectrode arrays implanted into their motor cortex for trials of intracortical BCI safety and performance. The primary task was moving a robotic arm between two targets as quickly as possible, performed alone and with various secondary distraction conditions. Primary outcomes included targets acquired, path efficiency, and subjective difficulty. There was no difference in the number of targets acquired for either subject with or without distractions. Median path efficiency was similar across all conditions (range: 0.766-0.846) except the motor distraction for Subject P2, where the median path efficiency dropped to 0.675 (p = 0.033, Mann-Whitney U test). Both subjects rated the overall difficulty of the task with and without distractions as low. Overall, intracortical BCI performance was robust to various distractions.
Nationwide Seroprevalence of SARS-CoV-2 in Saudi Arabia
Authors: Alharbi Naif Khalaf , Alghnam Suliman , Algaissi Abdullah , Albalawi Hind , Alenazi Mohammed W. , Albargawi Areeb M. , Alharbi Abdullah G. , Alhazmi Abdulaziz , Qarni Ali Al , Alfarhan Ali , Zowawi Hossam M. , Alhatmi Hind , Alghamdi Jahad , Alroqi Fayhan , Arabi Yaseen M. , Hashem Anwar M. , Bosaeed Mohammed , Aldibasi Omar 
Published: January 2021

AbstractBackgroundEstimated seroprevalence of Coronavirus Infectious Disease 2019 (COVID-19), caused by the Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) is a critical evidence for a better evaluation of the virus spread and monitoring the progress of the COVID-19 pandemic in a population. In the Kingdom of Saudi Arabia (KSA), SARS-CoV-2 seroprevalence has been reported in specific regions, but an extensive nationwide study has not been reported. Here, we report a nationwide study to determine the prevalence of SARS-CoV-2 in the population of KSA during the pandemic, using serum samples from healthy blood donors, non-COVID patients and healthcare workers (HCWs) in six different regions of the kingdom, with addition samples from COVID-19 patients.MethodsA total of 11703 serum samples were collected from different regions of the KSA including; 5395 samples from residual healthy blood donors (D); 5877 samples from non-COVID patients collected through residual sera at clinical biochemistry labs from non-COVID patients (P); and 400 samples from consented HCWs. To determine the seroprevalence of SARS-CoV-2, all serum samples, in addition to positive control sera from RT-PCR confirmed COVID-19 patients, were subjected to in-house ELISA with a sample pooling strategy, which was further validated by testing individual samples that make up some of the pools, with a statistical estimation method to report seroprevalence estimatesResultsOverall (combining D and P groups) seroprevalence estimate was around 11% in Saudi Arabia; and was 5.1% (Riyadh), 1.5% (Jazan), 18.4% (Qassim), 20.8% (Hail), 14.7% (ER; Alahsa), and 18.8% in Makkah. Makkah samples were only D group and had a rate of 24.4% and 12.8% in the cities of Makkah and Jeddah, respectively. The seroprevalence in Saudi Arabia across the sampled areas would be 12 times the COVID-19 infection rate. Among HCWs, 7.5% (4.95-10.16 CI 95%) had reactive antibodies to SARS-CoV-2 without reporting any previously confirmed infection. This was higher in HCWs with hypertension. The study also presents the demographics and prevalence of co-morbidities in HCWs and subset of non-COVID-19 population.ConclusionOur study estimates the overall national serological prevalence of COVID-19 in Saudi Arabia to be 11%, with an apparent disparity between regions.
Health and Healthcare Variables Associated with Italy’s Excess Mortality during the First Wave of the COVID-19 pandemic: An Ecological Study
Authors: Buja Alessandra , Paganini Matteo , Fusinato Riccardo , Cocchio Silvia , Scioni Manuela , Rebba Vincenzo , Baldo Vincenzo , Boccuzzo Giovanna 
Published: January 2021

AbstractBackgroundHealthcare factors have strongly influenced the propagation of COVID-19. The present study aims to examine whether excess mortality during the first phase of the COVID-19 outbreak in Italy was associated with health, healthcare, demographic, and socioeconomic indicators measured at a provincial level.MethodsThe present ecological study concerns the raw number of deaths from Jan. 1 to Apr. 30, 2020 and the mean number of deaths in the same months of 2015 to 2019, per province. Information on socioeconomic factors and healthcare settings were extracted from the most recently updated databases on the ISTAT website. Two multilevel, multivariate models were constructed to test whether excess mortality was associated with the indicators across 107 provinces in Italy.ResultsOn linear multilevel, multivariate analysis, AIDS mortality rate (p-value <0.05) correlates positively with excess mortality, while a higher density of General Practitioners (number of GPs per 1,000 population) is associated with lower excess mortality (p-value <0.05). After controlling for the diffusion of COVID-19 in each province, the significance of GP density increases (p-value <0.001) and the rate of hospitalization in long-term care wards is positively associated (p-value <0.05) with excess mortality.ConclusionSome health and healthcare variables are strongly associated with excess mortality caused by COVID-19 in Italy and should be considered to implement mitigation policies and increase healthcare resilience.
A control framework to optimize public health policies in the course of the COVID-19 pandemic
Authors: Pataro Igor M L , Oliveira Juliane F , Morato Marcelo M , Amad Alan A S , Ramos Pablo I P , Pereira Felipe A C , Silva Mateus S , Jorge Daniel C P , Andrade Roberto F S , Barreto Maurício L , da Costa Marcus Americano 
Published: January 2021

The SARS-CoV-2 pandemic triggered substantial economic and social disruptions. Mitigation policies varied across countries based on resources, political conditions, and human behavior. In the absence of widespread vaccination able to induce herd immunity, strategies to coexist with the virus while minimizing risks of surges are paramount, which should work in parallel with reopening societies. To support these strategies, we present a predictive control system coupled with a nonlinear model able to optimize the level of policies to stop epidemic growth. We applied this system to study the unfolding of COVID-19 in Bahia, Brazil, also assessing the effects of varying population compliance. We show the importance of finely tuning the levels of enforced measures to achieve SARS-CoV-2 containment, with periodic interventions emerging as an optimal control strategy in the long-term.One-sentence summaryWe present an adaptive predictive control algorithm to provide optimal public health measures to slow the COVID-19 transmission rate.
Investigation of the Stress and Sleep Physiology Correlates of Next-Day Memory for Details of a Social Stressor Testing Environment
Authors: Bottary Ryan , Kark Sarah M. , Daley Ryan T. , Denis Dan , Cunningham Tony J. , Payne Jessica D. , Kensinger Elizabeth A. 
Published: January 2021

AbstractDespite evidence which demonstrates that psychosocial stress interacts with sleep to modulate memory, research that has examined next-day memory for the stressful environment itself has not accounted for post-stressor sleep. Here, participants completed the Trier Social Stress Test or a matched control task with psychophysiological monitoring and stress hormone assays. After a 24-hour delay that included overnight polysomnographically-recorded sleep, memory for objects in the testing room was assessed by having participants draw the testing room from the previous day from memory. As expected, stressed participants mounted greater psychophysiological and stress hormone responses to the stressor than participants in the control condition. However, there was only weak evidence that stress reactivity and post-encoding sleep interacted to modulate memory for testing room details. Instead, NREM sleep physiology on the night following testing room encoding was positively associated with memory for testing room details, though this association occurred in the control, but not stressed, participants.
Age-associated gut microbiota impairs hippocampus-dependent memory in a vagus-dependent manner
Authors: Rei Damien , Saha Soham , Haddad Marianne , Haider Rubio Anna , Perlaza Blanca Liliana , Ungeheuer Marie-Noelle , Sokol Harry , Lledo Pierre-Marie 
Published: January 2021

AbstractAging is known to be associated with hippocampus-dependent memory decline, but the underlying causes of the age-related memory impairment remain yet highly debated. Here we showed that fecal microbiota transplantation (FMT) from aged, but not young, animal donors in young mice is sufficient to trigger profound hippocampal alterations including astrogliosis, decreased adult neurogenesis, decreased novelty-induced neuronal activation and impairment in hippocampus-dependent memory. Furthermore, similar alterations were reported when mice were subjected to an FMT from aged human donors. To decipher the mechanisms involved in mediating these microbiota-induced effects on brain function, we mapped the vagus nerve (VN)-related neuronal activity patterns and report that aged-mice FM transplanted animals showed a reduction in neuronal activity in the ascending VN output brain structure, both in basal condition and following VN stimulation. Targeted pharmacogenetic manipulation of VN-ascending neurons demonstrated that the decrease in vagal activity is detrimental to hippocampal functions. In contrast, increasing vagal ascending activity alleviated the adverse effects of aged mice FMT on hippocampal functions, and had a pro-mnesic effect in aged mice. Thus, pharmacogenetic VN stimulation is a potential therapeutic strategy to lessen microbiota-dependent age-associated impairments in hippocampal functions.Graphical abstract
A systematic analysis of genetically regulated differences in gene expression and the role of co-expression networks across 16 psychiatric disorders and substance use phenotypes
Authors: Gerring Zachary F , Thorp Jackson G , Gamazon Eric R , Derks Eske M 
Published: January 2021

ABSTRACTGenome-wide association studies (GWASs) have identified thousands of risk loci for many psychiatric and substance use phenotypes, however the biological consequences of these loci remain largely unknown. We performed a transcriptome-wide association study of 10 psychiatric disorders and 6 substance use phenotypes (collectively termed “mental health phenotypes”) using expression quantitative trait loci data from 532 prefrontal cortex samples. We estimated the correlation due to predicted genetically regulated expression between pairs of mental health phenotypes, and compared the results with the genetic correlations. We identified 1,645 genes with at least one significant trait association, comprising 2,176 significant associations across the 16 mental health phenotypes of which 572 (26%) are novel. Overall, the transcriptomic correlations for phenotype pairs were significantly higher than the respective genetic correlations. For example, attention deficit hyperactivity disorder and autism spectrum disorder, both childhood developmental disorders, showed a much higher transcriptomic correlation (r=0.84) than genetic correlation (r=0.35). Finally, we tested the enrichment of phenotype-associated genes in gene co-expression networks built from prefrontal cortex. Phenotype-associated genes were enriched in multiple gene co-expression modules and the implicated modules contained genes involved in mRNA splicing and glutamatergic receptors, among others. Together, our results highlight the utility of gene expression data in the understanding of functional gene mechanisms underlying psychiatric disorders and substance use phenotypes.
SAILER: Scalable and Accurate Invariant Representation Learning for Single-Cell ATAC-Seq Processing and Integration
Authors: Cao Yingxin , Fu Laiyi , Wu Jie , Peng Qinke , Nie Qing , Zhang Jing , Xie Xiaohui 
Published: January 2021

AbstractMotivationSingle-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) provides new opportunities to dissect epigenomic heterogeneity and elucidate transcriptional regulatory mechanisms. However, computational modelling of scATAC-seq data is challenging due to its high dimension, extreme sparsity, complex dependencies, and high sensitivity to confounding factors from various sources.ResultsHere we propose a new deep generative model framework, named SAILER, for analysing scATAC-seq data. SAILER aims to learn a low-dimensional nonlinear latent representation of each cell that defines its intrinsic chromatin state, invariant to extrinsic confounding factors like read depth and batch effects. SAILER adopts the conventional encoder-decoder framework to learn the latent representation but imposes additional constraints to ensure the independence of the learned representations from the confounding factors. Experimental results on both simulated and real scATAC-seq datasets demonstrate that SAILER learns better and biologically more meaningful representations of cells than other methods. Its noise-free cell embeddings bring in significant benefits in downstream analyses: Clustering and imputation based on SAILER result in 6.9% and 18.5% improvements over existing methods, respectively. Moreover, because no matrix factorization is involved, SAILER can easily scale to process millions of cells. We implemented SAILER into a software package, freely available to all for large-scale scATAC-seq data analysis.AvailabilityThe software is publicly available athttps://github.com/uci-cbcl/SAILERContactjingz31@uci.eduandxhx@uci.edu
A Fast Lasso-Based Method for Inferring Pairwise Interactions
Authors: Elmes Kieran , Heywood Astra , Huang Zhiyi , Gavryushkin Alex 
Published: January 2021

AbstractLarge-scale genotype-phenotype screens provide a wealth of data for identifying molecular alternations associated with a phenotype. Epistatic effects play an important role in such association studies. For example, siRNA perturbation screens can be used to identify pairwise gene-silencing effects. In bacteria, epistasis has practical consequences in determining antimicrobial resistance as the genetic background of a strain plays an important role in determining resistance. Existing computational tools which account for epistasis do not scale to human exome-wide screens and struggle with genetically diverse bacterial species such asPseudomonas aeruginosa. Combining earlier work in interaction detection with recent advances in integer compression, we present a method for epistatic interaction detection on sparse (human) exome-scale data, and an R implementation in the packagePint. Our method takes advantage of sparsity in the input data and recent progress in integer compression to perform lasso-penalised linear regression on all pairwise combinations of the input, estimating up to 200 million potential effects, including epistatic interactions. Hence the human exome is within the reach of our method, assuming one parameter per gene and one parameter per epistatic effect for every pair of genes. We demonstratePinton both simulated and real data sets, including antibiotic resistance testing and siRNA perturbation screens.