Showing papers by "Georgia State University published in 2021"
TL;DR: This paper endeavor to present an overview of the bibliometric methodology, with a particular focus on its different techniques, while offering step-by-step guidelines that can be relied upon to rigorously perform bibliomet analysis with confidence.
1,756 citations
Daniel J. Klionsky1, Amal Kamal Abdel-Aziz2, Sara Abdelfatah3, Mahmoud Abdellatif4 +2980 more•Institutions (777)
TL;DR: In this article, the authors present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes.
Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.
1,129 citations
TL;DR: A large international community sample was recruited to complete measures of self-perceived risk of contracting COVID-19, fear of the virus, moral foundations, political orientation, and behavior change in response to the pandemic, and the only predictor of positive behavior change was fear of COVID -19, with no effect of politically relevant variables.
Abstract: In the current context of the global pandemic of coronavirus disease-2019 (COVID-19), health professionals are working with social scientists to inform government policy on how to slow the spread of the virus. An increasing amount of social scientific research has looked at the role of public message framing, for instance, but few studies have thus far examined the role of individual differences in emotional and personality-based variables in predicting virus-mitigating behaviors. In this study, we recruited a large international community sample (N = 324) to complete measures of self-perceived risk of contracting COVID-19, fear of the virus, moral foundations, political orientation, and behavior change in response to the pandemic. Consistently, the only predictor of positive behavior change (e.g., social distancing, improved hand hygiene) was fear of COVID-19, with no effect of politically relevant variables. We discuss these data in relation to the potentially functional nature of fear in global health crises.
913 citations
TL;DR: Treatment of SARS-CoV-2-infected ferrets with a nucleoside analogue (MK-4482/EIDD-2801) reduced the viral load in the upper respiratory tract and suppressed the spread of the virus to untreated ferrets.
Abstract: The coronavirus disease 2019 (COVID-19) pandemic is having a catastrophic impact on human health1. Widespread community transmission has triggered stringent distancing measures with severe socio-economic consequences. Gaining control of the pandemic will depend on the interruption of transmission chains until vaccine-induced or naturally acquired protective herd immunity arises. However, approved antiviral treatments such as remdesivir and reconvalescent serum cannot be delivered orally2,3, making them poorly suitable for transmission control. We previously reported the development of an orally efficacious ribonucleoside analogue inhibitor of influenza viruses, MK-4482/EIDD-2801 (refs. 4,5), that was repurposed for use against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is currently in phase II/III clinical trials (NCT04405570 and NCT04405739). Here, we explored the efficacy of therapeutically administered MK-4482/EIDD-2801 to mitigate SARS-CoV-2 infection and block transmission in the ferret model, given that ferrets and related members of the weasel genus transmit the virus efficiently with minimal clinical signs6-9, which resembles the spread in the human young-adult population. We demonstrate high SARS-CoV-2 burden in nasal tissues and secretions, which coincided with efficient transmission through direct contact. Therapeutic treatment of infected animals with MK-4482/EIDD-2801 twice a day significantly reduced the SARS-CoV-2 load in the upper respiratory tract and completely suppressed spread to untreated contact animals. This study identified oral MK-4482/EIDD-2801 as a promising antiviral countermeasure to break SARS-CoV-2 community transmission chains.
299 citations
TL;DR: During the early phase of the outbreak in the United States, older adults perceived the risks of COVID-19 to be higher than did younger adults, but older men were comparatively less worried about CO VID-19 than their younger counterparts.
Abstract: OBJECTIVES: The case fatality rate of COVID-19 is higher amongst older adults than younger adults and is also higher amongst men than women. However, worry, which is a key motivator of behavioral health changes, occurs less frequently for older than younger adults, and less frequently for men than women. Building on this, we tested whether older adults - and particularly older men -- would report the least amount of COVID-19 worry and also fewer COVID-19 behavior changes. METHODS: From March 23-31, 2020, we administered an online questionnaire assessing COVID-19 perceptions, worries, and behavior changes. Participants were a convenience sample of United States residents, who were community-dwelling younger adults (18-35) or older adults (65 to 81). Analyses included 146 younger adults (68 men, 78 women) and 156 older adults (82 men, 74 women). Participants was predominately White, living in suburban/urban areas, and had completed some college. RESULTS: During the early phase of the outbreak in the United States, older adults perceived the risks of COVID-19 to be higher than did younger adults. Despite this, older men were comparatively less worried about COVID-19 than their younger counterparts. Compared to the other participants, older men had also implemented the fewest behavior changes. DISCUSSION: Interventions are needed to increase COVID-19 behavior changes in older men. These results also highlight the importance of understanding emotional-responses to COVID-19, as these are predictive of their behavioral responses.
219 citations
TL;DR: For over half a century, male rodents have been the default model organism in preclinical neuroscience research, a convention that has likely contributed to higher rates of misdiagnosis and adverse side effects from drug treatment in women as mentioned in this paper.
Abstract: For over half a century, male rodents have been the default model organism in preclinical neuroscience research, a convention that has likely contributed to higher rates of misdiagnosis and adverse side effects from drug treatment in women. Studying both sexes could help to rectify these public health problems, but incentive structures in publishing and career advancement deter many researchers from doing so. Moreover, funding agency directives to include male and female animals and human participants in grant proposals lack mechanisms to hold recipients accountable. In this Perspective, we highlight areas of behavioral, cellular and systems neuroscience in which fundamental sex differences have been identified, demonstrating that truly rigorous science must include males and females. We call for a cultural and structural change in how we conduct research and evaluate scientific progress, realigning our professional reward systems and experimental standards to produce a more equitable, representative and therefore translational body of knowledge.
194 citations
TL;DR: The updated taxonomy of Negarnaviricota is presented, as now accepted by the ICTV, after the phylum was amended and emended in March 2020.
Abstract: In March 2020, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. At the genus rank, 20 new genera were added, two were deleted, one was moved, and three were renamed. At the species rank, 160 species were added, four were deleted, ten were moved and renamed, and 30 species were renamed. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.
168 citations
Stony Brook University1, University of Minnesota2, University of Notre Dame3, University of North Texas4, Fordham University5, Macquarie University6, University of North Carolina at Chapel Hill7, Georgia State University8, Oklahoma State University–Stillwater9, State University of New York System10, Emory University11, Rosalind Franklin University of Medicine and Science12, University of Pittsburgh13
TL;DR: The Hierarchical Taxonomy of Psychopathology (HiTOP) consortium proposed a model based on structural evidence to address problems of diagnostic heterogeneity, comorbidity, and unreliability.
Abstract: Traditional diagnostic systems went beyond empirical evidence on the structure of mental health Consequently, these diagnoses do not depict psychopathology accurately, and their validity in research and utility in clinicalpractice are therefore limited The Hierarchical Taxonomy of Psychopathology (HiTOP) consortium proposed a model based on structural evidence It addresses problems of diagnostic heterogeneity, comorbidity, and unreliability We review the HiTOP model, supporting evidence, and conceptualization of psychopathology in this hierarchical dimensional framework The system is not yet comprehensive, and we describe the processes for improving and expanding it We summarize data on the ability of HiTOP to predict and explain etiology (genetic, environmental, and neurobiological), risk factors, outcomes, and treatment response We describe progress in the development of HiTOP-based measures and in clinical implementation of the system Finally, we review outstanding challenges and the research agenda HiTOP is of practical utility already, and its ongoing development will produce a transformative map of psychopathology
149 citations
TL;DR: The Bio3D‐eddm package supports both experimental and theoretical simulation‐generated structures, is integrated with other methods for dissecting sequence‐structure–function relationships, and can be used in a highly automated and reproducible manner.
Abstract: Bio3D is a family of R packages for the analysis of biomolecular sequence, structure, and dynamics. Major functionality includes biomolecular database searching and retrieval, sequence and structure conservation analysis, ensemble normal mode analysis, protein structure and correlation network analysis, principal component, and related multivariate analysis methods. Here, we review recent package developments, including a new underlying segregation into separate packages for distinct analysis, and introduce a new method for structure analysis named ensemble difference distance matrix analysis (eDDM). The eDDM approach calculates and compares atomic distance matrices across large sets of homologous atomic structures to help identify the residue wise determinants underlying specific functional processes. An eDDM workflow is detailed along with an example application to a large protein family. As a new member of the Bio3D family, the Bio3D-eddm package supports both experimental and theoretical simulation-generated structures, is integrated with other methods for dissecting sequence-structure-function relationships, and can be used in a highly automated and reproducible manner. Bio3D is distributed as an integrated set of platform independent open source R packages available from: http://thegrantlab.org/bio3d/.
133 citations
TL;DR: In this paper, the optimal allocation of a limited vaccine supply in the United States across groups differentiated by age and essential worker status was investigated, where younger essential workers are prioritized to control spread or seniors to directly control mortality.
Abstract: COVID-19 vaccines have been authorized in multiple countries, and more are under rapid development. Careful design of a vaccine prioritization strategy across sociodemographic groups is a crucial public policy challenge given that 1) vaccine supply will be constrained for the first several months of the vaccination campaign, 2) there are stark differences in transmission and severity of impacts from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) across groups, and 3) SARS-CoV-2 differs markedly from previous pandemic viruses. We assess the optimal allocation of a limited vaccine supply in the United States across groups differentiated by age and essential worker status, which constrains opportunities for social distancing. We model transmission dynamics using a compartmental model parameterized to capture current understanding of the epidemiological characteristics of COVID-19, including key sources of group heterogeneity (susceptibility, severity, and contact rates). We investigate three alternative policy objectives (minimizing infections, years of life lost, or deaths) and model a dynamic strategy that evolves with the population epidemiological status. We find that this temporal flexibility contributes substantially to public health goals. Older essential workers are typically targeted first. However, depending on the objective, younger essential workers are prioritized to control spread or seniors to directly control mortality. When the objective is minimizing deaths, relative to an untargeted approach, prioritization averts deaths on a range between 20,000 (when nonpharmaceutical interventions are strong) and 300,000 (when these interventions are weak). We illustrate how optimal prioritization is sensitive to several factors, most notably, vaccine effectiveness and supply, rate of transmission, and the magnitude of initial infections.
129 citations
TL;DR: In this paper, the authors used bibliometric analysis and systematic review to analyze electronic word-of-mouth (eWOM) research and found that the contributors to the field have preferred mixed research designs with more focus on theory building.
TL;DR: A comprehensive survey of GANs in privacy and security can be found in this paper, where the authors classified the existing works into proper categories based on privacy-and security functions, and conducted a comprehensive analysis of their advantages and drawbacks.
Abstract: Generative Adversarial Networks (GANs) have promoted a variety of applications in computer vision and natural language processing, among others, due to its generative model’s compelling ability to generate realistic examples plausibly drawn from an existing distribution of samples. GAN not only provides impressive performance on data generation-based tasks but also stimulates fertilization for privacy and security oriented research because of its game theoretic optimization strategy. Unfortunately, there are no comprehensive surveys on GAN in privacy and security, which motivates this survey to summarize systematically. The existing works are classified into proper categories based on privacy and security functions, and this survey conducts a comprehensive analysis of their advantages and drawbacks. Considering that GAN in privacy and security is still at a very initial stage and has imposed unique challenges that are yet to be well addressed, this article also sheds light on some potential privacy and security applications with GAN and elaborates on some future research directions.
TL;DR: A reinforcement learning (RL)-based intelligent central server with the capability of recognizing heterogeneity is implemented, which can help lead the trend toward better performance for majority of clients.
Abstract: The ubiquity of devices in Internet of Things (IoT) has opened up a large source for IoT data. Machine learning (ML) models with big IoT data is beneficial to our daily life in monitoring air condition, pollution, climate change, etc. However, centralized conventional ML models rely on all clients’ data at a central server, which seriously threatens user privacy. Federated learning (FL) emerges as a promising solution aiming to protect user privacy by enabling model training on a large corpus of decentralized data. The recent studies indicate FL suffers from the heterogeneity issue as it treats all clients’ data equally, that is, FL might sacrifice the performance of the majority of clients to accommodate the performance of the minority of clients with low usability data. In order to overcome this issue, a reinforcement learning (RL)-based intelligent central server with the capability of recognizing heterogeneity is implemented, which can help lead the trend toward better performance for majority of clients. To be specific, an FL central server analyses the benefits of different collaboration by capturing the intricate patterns in heterogeneous clients based on rating feedback and then updates clients’ weights iteratively, until it establishes a coalition of clients with quasioptimal performance. The experimental results on three real data sets under various heterogeneity levels demonstrate the superior performance of the proposed solution.
TL;DR: In this article, the authors used T1-weighted magnetic resonance images to determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.
Abstract: Importance Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood.
Objective To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia.
Design, Setting, and Participants Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244.
Main Outcomes and Measures Interregional profiles of group difference in cortical thickness between cases and controls.
Results A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders.
Conclusions and Relevance In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
TL;DR: In this article, the authors analyzed publicly available HIV surveillance data and census data to describe: current HIV prevalence and new HIV diagnoses by region, race or ethnicity, and age, trends in HIV diagnoses over time by HIV acquisition risk and age; and the distribution of HIV prevalence by geographical area.
TL;DR: In this paper, the authors used RNA-encoded Cas13a for mitigating influenza virus A and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in mice and hamsters, respectively.
Abstract: Cas13a has been used to target RNA viruses in cell culture, but efficacy has not been demonstrated in animal models. In this study, we used messenger RNA (mRNA)-encoded Cas13a for mitigating influenza virus A and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in mice and hamsters, respectively. We designed CRISPR RNAs (crRNAs) specific for PB1 and highly conserved regions of PB2 of influenza virus, and against the replicase and nucleocapsid genes of SARS-CoV-2, and selected the crRNAs that reduced viral RNA levels most efficiently in cell culture. We delivered polymer-formulated Cas13a mRNA and the validated guides to the respiratory tract using a nebulizer. In mice, Cas13a degraded influenza RNA in lung tissue efficiently when delivered after infection, whereas in hamsters, Cas13a delivery reduced SARS-CoV-2 replication and reduced symptoms. Our findings suggest that Cas13a-mediated targeting of pathogenic viruses can mitigate respiratory infections.
Max Planck Society1, Doncaster R.F.C.2, University of Nice Sophia Antipolis3, University of Padua4, Areva5, Institut national de la recherche agronomique6, Polytechnic University of Catalonia7, French Institute for Research in Computer Science and Automation8, Delft University of Technology9, Beihang University10, Seoul National University11, Eindhoven University of Technology12, University of Ljubljana13, Technische Universität München14, Georgia State University15, Commissariat à l'énergie atomique et aux énergies alternatives16, École Polytechnique Fédérale de Lausanne17, University of Alberta18
TL;DR: JOREK as mentioned in this paper is a massively parallel fully implicit non-linear extended magneto-hydrodynamic (MHD) code for realistic tokamak X-point plasmas.
Abstract: JOREK is a massively parallel fully implicit non-linear extended magneto-hydrodynamic (MHD) code for realistic tokamak X-point plasmas. It has become a widely used versatile simulation code for studying large-scale plasma instabilities and their control and is continuously developed in an international community with strong involvements in the European fusion research programme and ITER organization. This article gives a comprehensive overview of the physics models implemented, numerical methods applied for solving the equations and physics studies performed with the code. A dedicated section highlights some of the verification work done for the code. A hierarchy of different physics models is available including a free boundary and resistive wall extension and hybrid kinetic-fluid models. The code allows for flux-surface aligned iso-parametric finite element grids in single and double X-point plasmas which can be extended to the true physical walls and uses a robust fully implicit time stepping. Particular focus is laid on plasma edge and scrape-off layer (SOL) physics as well as disruption related phenomena. Among the key results obtained with JOREK regarding plasma edge and SOL, are deep insights into the dynamics of edge localized modes (ELMs), ELM cycles, and ELM control by resonant magnetic perturbations, pellet injection, as well as by vertical magnetic kicks. Also ELM free regimes, detachment physics, the generation and transport of impurities during an ELM, and electrostatic turbulence in the pedestal region are investigated. Regarding disruptions, the focus is on the dynamics of the thermal quench (TQ) and current quench triggered by massive gas injection and shattered pellet injection, runaway electron (RE) dynamics as well as the RE interaction with MHD modes, and vertical displacement events. Also the seeding and suppression of tearing modes (TMs), the dynamics of naturally occurring TQs triggered by locked modes, and radiative collapses are being studied.
TL;DR: A collaborative city digital twin based on FL, a novel paradigm that allowing multiple city DT to share the local strategy and status in a timely manner, and eventually establish a `global view' for city crisis management is proposed.
Chinese Academy of Sciences1, Fudan University2, National University of Singapore3, Dalian Polytechnic University4, Zhejiang University5, Peking University6, Radboud University Nijmegen7, Washington University in St. Louis8, University of Helsinki9, Shihezi University10, Hong Kong Baptist University11, Michigan State University12, Aberystwyth University13, Georgia State University14
TL;DR: A comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics and chemistry, is presented in this article.
Abstract: Artificial Intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day to day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes performs a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The goal of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.
TL;DR: In this paper, the mortality effects of temperature vary across U.S. climate regions to assess local and national damages from projected climate change using 22 years of Medicare data, and they find that the mortality effect of temperature varies across different regions of the country.
Abstract: We estimate how the mortality effects of temperature vary across U.S. climate regions to assess local and national damages from projected climate change. Using 22 years of Medicare data, we find th...
Centre national de la recherche scientifique1, Katholieke Universiteit Leuven2, Georgia State University3, Heidelberg University4, University of Lausanne5, German Cancer Research Center6, University of Freiburg7, Harvard University8, Chinese Academy of Sciences9, University of Geneva10, French Institute of Health and Medical Research11, National Institutes of Health12, University of Strasbourg13
TL;DR: In this paper, a morphologically distinct subpopulation of astrocytes expressed OT receptors and mediates anxiolytic and positive reinforcement effects of OT in the central amygdala of mice and rats.
Abstract: Oxytocin (OT) orchestrates social and emotional behaviors through modulation of neural circuits. In the central amygdala, the release of OT modulates inhibitory circuits and, thereby, suppresses fear responses and decreases anxiety levels. Using astrocyte-specific gain and loss of function and pharmacological approaches, we demonstrate that a morphologically distinct subpopulation of astrocytes expresses OT receptors and mediates anxiolytic and positive reinforcement effects of OT in the central amygdala of mice and rats. The involvement of astrocytes in OT signaling challenges the long-held dogma that OT acts exclusively on neurons and highlights astrocytes as essential components for modulation of emotional states under normal and chronic pain conditions.
TL;DR: In this paper, the complementary strengths of RDoC and Hierarchical Taxonomy of Psychopathology (HiTOP) can be leveraged to accelerate progress in the way psychopathology is studied, classified, and treated.
TL;DR: In this article, the authors developed and validated a measure for COVID-19 as traumatic stress, which consisted of three dimensions: threat/fear of infection and death, economic hardship, and disturbed r...
Abstract: The goal was to develop and validate a measure for COVID-19 as traumatic stress. The scale consisted of three dimensions: “threat/fear of infection and death,” “economic hardship,” and “disturbed r...
TL;DR: This work uses node2vec technique to automatically learn a richer representation of protein-protein interaction (PPI) network topologies than a score function, and shows that the PPI network embedding contributes most to the improvement.
Abstract: Computational methods including centrality and machine learning-based methods have been proposed to identify essential proteins for understanding the minimum requirements of the survival and evolution of a cell. In centrality methods, researchers are required to design a score function which is based on prior knowledge, yet is usually not sufficient to capture the complexity of biological information. In machine learning-based methods, some selected biological features cannot represent the complete properties of biological information as they lack a computational framework to automatically select features. To tackle these problems, we propose a deep learning framework to automatically learn biological features without prior knowledge. We use node2vec technique to automatically learn a richer representation of protein-protein interaction (PPI) network topologies than a score function. Bidirectional long short term memory cells are applied to capture non-local relationships in gene expression data. For subcellular localization information, we exploit a high dimensional indicator vector to characterize their feature. To evaluate the performance of our method, we tested it on PPI network of S. cerevisiae. Our experimental results demonstrate that the performance of our method is better than traditional centrality methods and is superior to existing machine learning-based methods. To explore which of the three types of biological information is the most vital element, we conduct an ablation study by removing each component in turn. Our results show that the PPI network embedding contributes most to the improvement. In addition, gene expression profiles and subcellular localization information are also helpful to improve the performance in identification of essential proteins.
TL;DR: This paper investigates the joint problem of sensing task assignment and schedule with considering multi-dimensional task diversity, including partial fulfillment, bilaterally-multi-schedule, attribute diversity, and price diversity and rigorously proves that all the four auction schemes are computationally-efficient, individually-rational, and incentive-compatible.
Abstract: To promote development of Mobile Crowdsensing Systems (MCSs), numerous auction schemes have been proposed to motivate mobile users’ participation. But, task diversity of MCSs has not been fully explored by most existing works. To further exploit task diversity and improve performance of MCSs, in this paper, we investigate the joint problem of sensing task assignment and schedule with considering multi-dimensional task diversity, including partial fulfillment, bilaterally-multi-schedule, attribute diversity, and price diversity. First, task owner-centric auction model is formulated and two distributed auction schemes (CPAS and TPAS) are proposed such that each task owner can locally process auction procedure. Then, mobile user-centric auction model is established and two distributed auction schemes (VPAS and DPAS) are developed to facilitate local auction implementation. These four auction schemes differ in their approaches to determine winners and compute payments. We further rigorously prove that all the four auction schemes (CPAS, TPAS, VPAS, and DPAS) are computationally-efficient, individually-rational, and incentive-compatible and that both CPAS and TPAS are budget-feasible. Finally, we comprehensively evaluate the effectiveness of CPAS, TPAS, VPAS, and DPAS via comparing with the state-of-the-art in real-data experiments.
TL;DR: In this article, the authors synthesize the literature on broader health and social impacts on people with disabilities arising from lockdown-related measures, and identify the primary and two central themes were identified: (1) Disrupted access to healthcare (other than for COVID-19); (2) Reduced physical activity leading to health and functional decline; (3) From physical distance and inactivity to social isolation and loneliness; (4) Disruption of personal assistance and community support networks; (5) Children with disabilities disproportionally affected by school closures; (6) Psychological consequences of
Abstract: People with disabilities may be disproportionally affected by the COVID-19 pandemic. We synthesize the literature on broader health and social impacts on people with disabilities arising from lockdown-related measures. Methods: Scoping review with thematic analysis. Up to mid-September 2020, seven scientific databases and three pre-print servers were searched to identify empirical or perspective papers addressing lockdown-related disparities experienced by people with disabilities. Snowballing searches and experts’ consultation also occurred. Two independent reviewers took eligibility decisions and performed data extractions. Results: Out of 1026 unique references, 85 addressed lockdown-related disparities experienced by people with disabilities. Ten primary and two central themes were identified: (1) Disrupted access to healthcare (other than for COVID-19); (2) Reduced physical activity leading to health and functional decline; (3) From physical distance and inactivity to social isolation and loneliness; (4) Disruption of personal assistance and community support networks; (5) Children with disabilities disproportionally affected by school closures; (6) Psychological consequences of disrupted routines, activities, and support; (7) Family and informal caregiver burden and stress; (8) Risks of maltreatment, violence, and self-harm; (9) Reduced employment and/or income exacerbating disparities; and (10) Digital divide in access to health, education, and support services. Lack of disability-inclusive response and emergency preparedness and structural, pre-pandemic disparities were the central themes. Conclusions: Lockdown-related measures to contain the COVID-19 pandemic can disproportionally affect people with disabilities with broader impact on their health and social grounds. Lack of disability-inclusive response and emergency preparedness and pre-pandemic disparities created structural disadvantages, exacerbated during the pandemic. Both structural disparities and their pandemic ramifications require the development and implementation of disability-inclusive public health and policy measures.
TL;DR: In this paper, the authors classified counties in the USA into five groups by level of social vulnerability, using the Social Vulnerability Index (a widely used measure of social disadvantage) developed by the US Centers for Disease Control and Prevention.
Abstract: Background Given the effect of chronic diseases on risk of severe COVID-19 infection, the present pandemic may have a particularly profound impact on socially disadvantaged counties. Methods Counties in the USA were categorised into five groups by level of social vulnerability, using the Social Vulnerability Index (a widely used measure of social disadvantage) developed by the US Centers for Disease Control and Prevention. The incidence and mortality from COVID-19, and the prevalence of major chronic conditions were calculated relative to the least vulnerable quintile using Poisson regression models. Results Among 3141 counties, there were 5 010 496 cases and 161 058 deaths from COVID-19 by 10 August 2020. Relative to the least vulnerable quintile, counties in the most vulnerable quintile had twice the rates of COVID-19 cases and deaths (rate ratios 2.11 (95% CI 1.97 to 2.26) and 2.42 (95% CI 2.22 to 2.64), respectively). Similarly, the prevalence of major chronic conditions was 24%–41% higher in the most vulnerable counties. Geographical clustering of counties with high COVID-19 mortality, high chronic disease prevalence and high social vulnerability was found, especially in southern USA. Conclusion Some counties are experiencing a confluence of epidemics from COVID-19 and chronic diseases in the context of social disadvantage. Such counties are likely to require enhanced public health and social support.
TL;DR: In this paper, the authors used a publicly available real-time daily series of age-stratified COVID-19 cases and deaths reported by the Ministry of Health in Chile from the beginning of the epidemic in March through August 31, 2020.
Abstract: Early severity estimates of coronavirus disease 2019 (COVID-19) are critically needed to assess the potential impact of the ongoing pandemic in different demographic groups. Here we estimate the real-time delay-adjusted case fatality rate across nine age groups by gender in Chile, the country with the highest testing rate for COVID-19 in Latin America. We used a publicly available real-time daily series of age-stratified COVID-19 cases and deaths reported by the Ministry of Health in Chile from the beginning of the epidemic in March through August 31, 2020. We used a robust likelihood function and a delay distribution to estimate real-time delay-adjusted case-fatality risk and estimate model parameters using a Monte Carlo Markov Chain in a Bayesian framework. As of August 31, 2020, our estimates of the time-delay adjusted case fatality rate (CFR) for men and women are 4.16% [95% Credible Interval (CrI): 4.09–4.24%] and 3.26% (95% CrI: 3.19–3.34%), respectively, while the overall estimate is 3.72% (95% CrI: 3.67–3.78%). Seniors aged 80 years and over have an adjusted CFR of 56.82% (95% CrI: 55.25–58.34%) for men and 41.10% (95% CrI: 40.02–42.26%) for women. Results showed a peak in estimated CFR during the June peak of the epidemic. The peak possibly reflects insufficient laboratory capacity, as illustrated by high test positivity rates (33% positive 7-day average nationally in June), which may have resulted in lower reporting rates. Severity estimates from COVID-19 in Chile suggest that male seniors, especially among those aged ≥ 70 years, are being disproportionately affected by the pandemic, a finding consistent with other regions. The ongoing pandemic is imposing a high death toll in South America, and Chile has one of the highest reported mortality rates globally thus far. These real-time estimates may help inform public health officials' decisions in the region and underscore the need to implement more effective measures to ameliorate fatality.
TL;DR: Regression analysis reveals that article attributes such as article order, methodology, presence of authors from Europe, number of references, number-of- keywords, and abstract length have a significant association with the citations.
TL;DR: This article conceptualizes technology renewal as an inherently paradoxical digital transformation process that requires organizations to simultaneously remove their technological foundation and build on the practices that depend on it to implement a new technological foundation.
Abstract: To realize their strategic goals and maintain a competitive advantage in the digital era, organizations must periodically renew their digital platforms and infrastructures. However, knowledge about ...