Showing papers by "Georgia State University published in 2020"
TL;DR: On 5 February 2020, in Yokohama, Japan, a cruise ship hosting 3,711 people underwent a 2-week quarantine after a former passenger was found with COVID-19 post-disembarking, and the delay-adjusted asymptomatic proportion of infections, along with the infections’ timeline were derived.
Abstract: On 5 February 2020, in Yokohama, Japan, a cruise ship hosting 3,711 people underwent a 2-week quarantine after a former passenger was found with COVID-19 post-disembarking. As at 20 February, 634 persons on board tested positive for the causative virus. We conducted statistical modelling to derive the delay-adjusted asymptomatic proportion of infections, along with the infections' timeline. The estimated asymptomatic proportion was 17.9% (95% credible interval (CrI): 15.5-20.2%). Most infections occurred before the quarantine start.
2,195 citations
TL;DR: The COVID-19 outbreak is a sharp reminder that pandemics, like other rarely occurring catastrophes, have happened in the past and will continue to happen in the future.
1,094 citations
Tulane University1, Cedars-Sinai Medical Center2, National Institutes of Health3, University of Arizona4, Karolinska Institutet5, Brigham and Women's Hospital6, Georgia State University7, University of Colorado Denver8, Washington University in St. Louis9, Johns Hopkins University10, University of Modena and Reggio Emilia11, University of Illinois at Chicago12, University of Texas Health Science Center at Houston13, Charité14, University of Zurich15, Georgetown University16, Duke University17, Veterans Health Administration18
TL;DR: Clinicians and researchers are guided to consider sex and gender in their approach to diagnosis, prevention, and treatment of diseases as a necessary and fundamental step towards precision medicine, which will benefit men's and women's health.
781 citations
TL;DR: The potential danger of exponential spread in the absence of interventions is illustrated, providing relevant information to strategies for restarting economic activity.
Abstract: State and local governments imposed social distancing measures in March and April 2020 to contain the spread of the novel coronavirus disease (COVID-19). These measures included bans on large socia...
689 citations
University of Duisburg-Essen1, University of Düsseldorf2, Harvard University3, University of Warsaw4, University of Melbourne5, St. Vincent's Institute of Medical Research6, Johns Hopkins University7, Swiss Institute of Bioinformatics8, Western General Hospital9, The Turing Institute10, University of British Columbia11, BC Cancer Agency12, ETH Zurich13, Delft University of Technology14, Leiden University Medical Center15, Broad Institute16, Georgia State University17, Karlsruhe Institute of Technology18, Heidelberg Institute for Theoretical Studies19, Centrum Wiskunde & Informatica20, Utrecht University21, University of Amsterdam22, Imperial College London23, Radboud University Nijmegen24, University Medical Center Groningen25, Wageningen University and Research Centre26, University of Connecticut27, University of Cambridge28, Wellcome Trust Sanger Institute29, European Bioinformatics Institute30, Saarland University31, Max Planck Society32, Zuse Institute Berlin33, German Cancer Research Center34, Leiden University35, I.M. Sechenov First Moscow State Medical University36, Princeton University37, Memorial Sloan Kettering Cancer Center38
TL;DR: This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years in single-cell data science.
Abstract: The recent boom in microfluidics and combinatorial indexing strategies, combined with low sequencing costs, has empowered single-cell sequencing technology. Thousands-or even millions-of cells analyzed in a single experiment amount to a data revolution in single-cell biology and pose unique data science problems. Here, we outline eleven challenges that will be central to bringing this emerging field of single-cell data science forward. For each challenge, we highlight motivating research questions, review prior work, and formulate open problems. This compendium is for established researchers, newcomers, and students alike, highlighting interesting and rewarding problems for the coming years.
677 citations
TL;DR: The results indicate early sustained transmission of COVID-19 in South Korea and support the implementation of social distancing measures to rapidly control the outbreak.
611 citations
TL;DR: The findings suggest that the containment strategies implemented in China are successfully reducing transmission and that the epidemic growth has slowed in recent days.
578 citations
TL;DR: This review presents some of the problems and current treatment options contributing to the poor outcomes for patients with liver cancer and suggests use of natural compounds and/or nanotechnology may provide patients with better outcomes with lower systemic toxicity and fewer side effects.
577 citations
TL;DR: The authors identified shared biology and host-directed drug targets to prioritize therapeutics with potential for rapid deployment against current and future coronavirus outbreaks, and found that individuals with genotypes corresponding to higher soluble IL17RA levels in plasma are at decreased risk of COVID-19 hospitalization.
Abstract: The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a grave threat to public health and the global economy. SARS-CoV-2 is closely related to the more lethal but less transmissible coronaviruses SARS-CoV-1 and Middle East respiratory syndrome coronavirus (MERS-CoV). Here, we have carried out comparative viral-human protein-protein interaction and viral protein localization analyses for all three viruses. Subsequent functional genetic screening identified host factors that functionally impinge on coronavirus proliferation, including Tom70, a mitochondrial chaperone protein that interacts with both SARS-CoV-1 and SARS-CoV-2 ORF9b, an interaction we structurally characterized using cryo-electron microscopy. Combining genetically validated host factors with both COVID-19 patient genetic data and medical billing records identified molecular mechanisms and potential drug treatments that merit further molecular and clinical study.
491 citations
TL;DR: Physical distancing interventions were associated with reductions in the incidence of covid-19 globally and might support policy decisions as countries prepare to impose or lift physical distancing measures in current or future epidemic waves.
Abstract: Objective To evaluate the association between physical distancing interventions and incidence of coronavirus disease 2019 (covid-19) globally. Design Natural experiment using interrupted time series analysis, with results synthesised using meta-analysis. Setting 149 countries or regions, with data on daily reported cases of covid-19 from the European Centre for Disease Prevention and Control and data on the physical distancing policies from the Oxford covid-19 Government Response Tracker. Participants Individual countries or regions that implemented one of the five physical distancing interventions (closures of schools, workplaces, and public transport, restrictions on mass gatherings and public events, and restrictions on movement (lockdowns)) between 1 January and 30 May 2020. Main outcome measure Incidence rate ratios (IRRs) of covid-19 before and after implementation of physical distancing interventions, estimated using data to 30 May 2020 or 30 days post-intervention, whichever occurred first. IRRs were synthesised across countries using random effects meta-analysis. Results On average, implementation of any physical distancing intervention was associated with an overall reduction in covid-19 incidence of 13% (IRR 0.87, 95% confidence interval 0.85 to 0.89; n=149 countries). Closure of public transport was not associated with any additional reduction in covid-19 incidence when the other four physical distancing interventions were in place (pooled IRR with and without public transport closure was 0.85, 0.82 to 0.88; n=72, and 0.87, 0.84 to 0.91; n=32, respectively). Data from 11 countries also suggested similar overall effectiveness (pooled IRR 0.85, 0.81 to 0.89) when school closures, workplace closures, and restrictions on mass gatherings were in place. In terms of sequence of interventions, earlier implementation of lockdown was associated with a larger reduction in covid-19 incidence (pooled IRR 0.86, 0.84 to 0.89; n=105) compared with a delayed implementation of lockdown after other physical distancing interventions were in place (pooled IRR 0.90, 0.87 to 0.94; n=41). Conclusions Physical distancing interventions were associated with reductions in the incidence of covid-19 globally. No evidence was found of an additional effect of public transport closure when the other four physical distancing measures were in place. Earlier implementation of lockdown was associated with a larger reduction in the incidence of covid-19. These findings might support policy decisions as countries prepare to impose or lift physical distancing measures in current or future epidemic waves.
449 citations
TL;DR: This article proposes a novel mechanism for data uploading in smart cyber-physical systems, which considers both energy conservation and privacy preservation, and proposes a heuristic algorithm that achieves an energy-efficient scheme for data upload by introducing an acceptable number of extra contents.
Abstract: To provide fine-grained access to different dimensions of the physical world, the data uploading in smart cyber-physical systems suffers novel challenges on both energy conservation and privacy preservation. It is always critical for participants to consume as little energy as possible for data uploading. However, simply pursuing energy efficiency may lead to extreme disclosure of private information, especially when the uploaded contents from participants are more informative than ever. In this article, we propose a novel mechanism for data uploading in smart cyber-physical systems, which considers both energy conservation and privacy preservation. The mechanism preserves privacy by concealing abnormal behaviors of participants, while still achieves an energy-efficient scheme for data uploading by introducing an acceptable number of extra contents. To derive an optimal uploading scheme is proved to be NP-hard. Accordingly, we propose a heuristic algorithm and analyze its effectiveness. The evaluation results towards a real-world dataset demonstrate that the performance of the proposed algorithm is comparable with the optimal results.
Paul M. Thompson1, Neda Jahanshad1, Christopher R.K. Ching1, Lauren E. Salminen1 +210 more•Institutions (99)
TL;DR: This review summarizes the last decade of work by the ENIGMA Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease, and highlights the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings.
Abstract: This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
TL;DR: The Journal of Business Research (JBR) is a journal of international repute that publishes original, peer-reviewed, and empirical research in business and management as discussed by the authors, and key business decisions, processes, and activities within real business settings frequently feature in JBR articles.
University of Notre Dame1, Royal Institute of Technology2, Commonwealth Scientific and Industrial Research Organisation3, Massachusetts Institute of Technology4, Stanford University5, Georgia Institute of Technology6, Catalan Institute for Water Research7, University of Calabria8, University of Pisa9, Mario Negri Institute for Pharmacological Research10, Federal University of Bahia11, North Carolina State University12, Howard University13, Bangor University14, École Polytechnique Fédérale de Lausanne15, University of Arizona16, Southern Nevada Water Authority17, University of Barcelona18, University of Yamanashi19, University of California, Santa Barbara20, Hokkaido University21, Indian Institute of Technology Gandhinagar22, Toyama Prefectural University23, Istituto Superiore di Sanità24, University of Naples Federico II25, University of Wisconsin–Milwaukee26, University of Washington27, University of Queensland28, University of North Carolina at Chapel Hill29, University of Antwerp30, Yale University31, Tufts University32, Michigan State University33, Spanish National Research Council34, University of Southern California35, Rice University36, Georgia State University37, University of Osnabrück38, University of Michigan39
TL;DR: Author(s): Bivins, Aaron; North, Devin; Ahmad, Arslan; Ahmed, Warish; Alm, Eric; Been, Frederic; Bhattacharya, Prosun; Bijlsma, Lubertus; Boehm, Alexandria B; Brown, Joe; Buttiglieri, Gianluigi; Calabro, Vincenza; Carducci, Annalaura; Castiglioni, Sara; Cetecioglu Guro
Abstract: Author(s): Bivins, Aaron; North, Devin; Ahmad, Arslan; Ahmed, Warish; Alm, Eric; Been, Frederic; Bhattacharya, Prosun; Bijlsma, Lubertus; Boehm, Alexandria B; Brown, Joe; Buttiglieri, Gianluigi; Calabro, Vincenza; Carducci, Annalaura; Castiglioni, Sara; Cetecioglu Gurol, Zeynep; Chakraborty, Sudip; Costa, Federico; Curcio, Stefano; de Los Reyes, Francis L; Delgado Vela, Jeseth; Farkas, Kata; Fernandez-Casi, Xavier; Gerba, Charles; Gerrity, Daniel; Girones, Rosina; Gonzalez, Raul; Haramoto, Eiji; Harris, Angela; Holden, Patricia A; Islam, Md Tahmidul; Jones, Davey L; Kasprzyk-Hordern, Barbara; Kitajima, Masaaki; Kotlarz, Nadine; Kumar, Manish; Kuroda, Keisuke; La Rosa, Giuseppina; Malpei, Francesca; Mautus, Mariana; McLellan, Sandra L; Medema, Gertjan; Meschke, John Scott; Mueller, Jochen; Newton, Ryan J; Nilsson, David; Noble, Rachel T; van Nuijs, Alexander; Peccia, Jordan; Perkins, T Alex; Pickering, Amy J; Rose, Joan; Sanchez, Gloria; Smith, Adam; Stadler, Lauren; Stauber, Christine; Thomas, Kevin; van der Voorn, Tom; Wigginton, Krista; Zhu, Kevin; Bibby, Kyle
TL;DR: This paper proposes a privacy-preserved data sharing framework for IIoTs, where multiple competing data consumers exist in different stages of the system, and provides for both algorithms a comprehensive consideration on privacy, data utility, bandwidth efficiency, payment, and rationality for data sharing.
Abstract: The effective physical data sharing has been facilitating the functionality of Industrial IoTs, which is believed to be one primary basis for Industry 4.0. These physical data, while providing pivotal information for multiple components of a production system, also bring in severe privacy issues for both workers and manufacturers, thus aggravating the challenges for data sharing. Current designs tend to simplify the behaviors of participants for better theoretical analysis, and they cannot properly handle the challenges in IIoTs where the behaviors are more complicated and correlated. Therefore, this paper proposes a privacy-preserved data sharing framework for IIoTs, where multiple competing data consumers exist in different stages of the system. The framework allows data contributors to share their contents upon requests. The uploaded contents will be perturbed to preserve the sensitive status of contributors. The differential privacy is adopted in the perturbation to guarantee the privacy preservation. Then the data collector will process and relay contents with subsequent data consumers. This data collector will gain both its own data utility and extra profits in data relay. Two algorithms are proposed for data sharing in different scenarios, based on whether the service provider will further process the contents to retain its exclusive utility. This work also provides for both algorithms a comprehensive consideration on privacy, data utility, bandwidth efficiency, payment, and rationality for data sharing. Finally, the evaluation on real-world datasets demonstrates the effectiveness of proposed methods, together with clues for data sharing towards Industry 4.0.
University of California, San Diego1, University of Arizona2, American Cancer Society3, Rutgers University4, Ohio State University5, George Washington University6, University of San Diego7, Memorial Hospital of South Bend8, Kaiser Permanente9, Georgia State University10, American Heart Association11
TL;DR: Recommendations for community action are presented to accompany the 4 recommendations for individual choices to reduce cancer risk, recognizing that a supportive social and physical environment is indispensable if individuals at all levels of society are to have genuine opportunities to choose healthy behaviors.
Abstract: The American Cancer Society (ACS) publishes the Diet and Physical Activity Guideline to serve as a foundation for its communication, policy, and community strategies and, ultimately, to affect dietary and physical activity patterns among Americans. This guideline is developed by a national panel of experts in cancer research, prevention, epidemiology, public health, and policy, and reflects the most current scientific evidence related to dietary and activity patterns and cancer risk. The ACS guideline focuses on recommendations for individual choices regarding diet and physical activity patterns, but those choices occur within a community context that either facilitates or creates barriers to healthy behaviors. Therefore, this committee presents recommendations for community action to accompany the 4 recommendations for individual choices to reduce cancer risk. These recommendations for community action recognize that a supportive social and physical environment is indispensable if individuals at all levels of society are to have genuine opportunities to choose healthy behaviors. This 2020 ACS guideline is consistent with guidelines from the American Heart Association and the American Diabetes Association for the prevention of coronary heart disease and diabetes as well as for general health promotion, as defined by the 2015 to 2020 Dietary Guidelines for Americans and the 2018 Physical Activity Guidelines for Americans.
TL;DR: Most recent estimates reached values largely below the epidemic threshold, indicating that a secondary outbreak of the novel coronavirus was unlikely to occur aboard the Diamond Princess Ship.
TL;DR: The authors investigates the main differences between prior financial-based crisis and the practices that managers can adopt to navigate and survive the current Coronavirus crisis from a social exchange theory (SET) view.
TL;DR: This paper converts the problem of finding the weak solution of PDEs into an operator norm minimization problem induced from the weak formulation, and parameterized as the primal and adversarial networks respectively, which are alternately updated to approximate the optimal network parameter setting.
TL;DR: Forecasts from each of the models suggest the outbreaks may be nearing extinction in both Guangdong and Zhejiang; however, the sub-epidemic model predictions also include the potential for further sustained transmission, particularly in Z hejiang.
Abstract: The ongoing COVID-19 epidemic continues to spread within and outside of China, despite several social distancing measures implemented by the Chinese government. Limited epidemiological data are available, and recent changes in case definition and reporting further complicate our understanding of the impact of the epidemic, particularly in the epidemic’s epicenter. Here we use previously validated phenomenological models to generate short-term forecasts of cumulative reported cases in Guangdong and Zhejiang, China. Using daily reported cumulative case data up until 13 February 2020 from the National Health Commission of China, we report 5- and 10-day ahead forecasts of cumulative case reports. Specifically, we generate forecasts using a generalized logistic growth model, the Richards growth model, and a sub-epidemic wave model, which have each been previously used to forecast outbreaks due to different infectious diseases. Forecasts from each of the models suggest the outbreaks may be nearing extinction in both Guangdong and Zhejiang; however, the sub-epidemic model predictions also include the potential for further sustained transmission, particularly in Zhejiang. Our 10-day forecasts across the three models predict an additional 65–81 cases (upper bounds: 169–507) in Guangdong and an additional 44–354 (upper bounds: 141–875) cases in Zhejiang by February 23, 2020. In the best-case scenario, current data suggest that transmission in both provinces is slowing down.
TL;DR: An international team of researchers has conducted a comprehensive review of the evolution spasers, from their first experimental demonstrations through to technological advances in the field and future research and new applications.
Abstract: Ten years ago, three teams experimentally demonstrated the first spasers, or plasmonic nanolasers, after the spaser concept was first proposed theoretically in 2003. An overview of the significant progress achieved over the last 10 years is presented here, together with the original context of and motivations for this research. After a general introduction, we first summarize the fundamental properties of spasers and discuss the major motivations that led to the first demonstrations of spasers and nanolasers. This is followed by an overview of crucial technological progress, including lasing threshold reduction, dynamic modulation, room-temperature operation, electrical injection, the control and improvement of spasers, the array operation of spasers, and selected applications of single-particle spasers. Research prospects are presented in relation to several directions of development, including further miniaturization, the relationship with Bose-Einstein condensation, novel spaser-based interconnects, and other features of spasers and plasmonic lasers that have yet to be realized or challenges that are still to be overcome.
TL;DR: The authors presented a large-scale curated dataset of over 152 million tweets, growing daily, related to COVID-19 chatter generated from January 1st to April 4th at the time of writing, allowing researchers to conduct a number of research projects relating to the emotional and mental responses to social distancing measures, the identification of sources of misinformation, and the stratified measurement of sentiment towards the pandemic in near real time.
Abstract: As the COVID-19 pandemic continues its march around the world, an unprecedented amount of open data is being generated for genetics and epidemiological research. The unparalleled rate at which many research groups around the world are releasing data and publications on the ongoing pandemic is allowing other scientists to learn from local experiences and data generated in the front lines of the COVID-19 pandemic. However, there is a need to integrate additional data sources that map and measure the role of social dynamics of such a unique world-wide event into biomedical, biological, and epidemiological analyses. For this purpose, we present a large-scale curated dataset of over 152 million tweets, growing daily, related to COVID-19 chatter generated from January 1st to April 4th at the time of writing. This open dataset will allow researchers to conduct a number of research projects relating to the emotional and mental responses to social distancing measures, the identification of sources of misinformation, and the stratified measurement of sentiment towards the pandemic in near real time.
TL;DR: The elevated death risk estimates are probably associated with a breakdown of the healthcare system, indicating that enhanced public health interventions, including social distancing and movement restrictions, should be implemented to bring the COVID-19 epidemic under control.
Abstract: Since December 2019, when the first case of coronavirus disease (COVID-19) was identified in the city of Wuhan in the Hubei Province of China, the epidemic has generated tens of thousands of cases throughout China. As of February 28, 2020, the cumulative number of reported deaths in China was 2,858. We estimated the time-delay adjusted risk for death from COVID-19 in Wuhan, as well as for China excluding Wuhan, to assess the severity of the epidemic in the country. Our estimates of the risk for death in Wuhan reached values as high as 12% in the epicenter of the epidemic and ≈1% in other, more mildly affected areas. The elevated death risk estimates are probably associated with a breakdown of the healthcare system, indicating that enhanced public health interventions, including social distancing and movement restrictions, should be implemented to bring the COVID-19 epidemic under control.
TL;DR: NeuroMark as discussed by the authors is a pipeline based on the priori-driven independent component analysis, which is capable of estimating brain functional network measures from functional MRI data that can be used to link brain network abnormalities among different datasets, studies, and disorders.
University of Tokyo1, University of Tsukuba2, Osaka University3, Hokkaido University4, Kanazawa Medical University5, Nagoya University6, Hiroshima University7, Yamaguchi University8, Saitama Medical University9, Hamamatsu University School of Medicine10, Showa University11, University of Toyama12, Kyoto University13, University of Tokushima14, Kyushu University15, National University of Ireland, Galway16, University of Southern California17, University of California, Irvine18, Georgia State University19
TL;DR: It is found that schizophrenia, bipolar disorder, and autism spectrum disorder share similar white matter microstructural differences in the body of the corpus callosum; schizophrenia and bipolar disorder featured comparable changes in the limbic system, such as the fornix and cingulum.
Abstract: Identifying both the commonalities and differences in brain structures among psychiatric disorders is important for understanding the pathophysiology. Recently, the ENIGMA-Schizophrenia DTI Working Group performed a large-scale meta-analysis and reported widespread white matter microstructural alterations in schizophrenia; however, no similar cross-disorder study has been carried out to date. Here, we conducted mega-analyses comparing white matter microstructural differences between healthy comparison subjects (HCS; N = 1506) and patients with schizophrenia (N = 696), bipolar disorder (N = 211), autism spectrum disorder (N = 126), or major depressive disorder (N = 398; total N = 2937 from 12 sites). In comparison with HCS, we found that schizophrenia, bipolar disorder, and autism spectrum disorder share similar white matter microstructural differences in the body of the corpus callosum; schizophrenia and bipolar disorder featured comparable changes in the limbic system, such as the fornix and cingulum. By comparison, alterations in tracts connecting neocortical areas, such as the uncinate fasciculus, were observed only in schizophrenia. No significant difference was found in major depressive disorder. In a direct comparison between schizophrenia and bipolar disorder, there were no significant differences. Significant differences between schizophrenia/bipolar disorder and major depressive disorder were found in the limbic system, which were similar to the differences in schizophrenia and bipolar disorder relative to HCS. While schizophrenia and bipolar disorder may have similar pathological characteristics, the biological characteristics of major depressive disorder may be close to those of HCS. Our findings provide insights into nosology and encourage further investigations of shared and unique pathophysiology of psychiatric disorders.
TL;DR: Parvocellular OT neurons receive particular inputs to control social behavior by coordinating the responses of the much larger population of magnocellular oxytocin neurons, which consequently show coordinated increases in their activity during social interactions between virgin female rats.
Abstract: Oxytocin (OT) is a great facilitator of social life but, although its effects on socially relevant brain regions have been extensively studied, OT neuron activity during actual social interactions remains unexplored. Most OT neurons are magnocellular neurons, which simultaneously project to the pituitary and forebrain regions involved in social behaviors. In the present study, we show that a much smaller population of OT neurons, parvocellular neurons that do not project to the pituitary but synapse onto magnocellular neurons, is preferentially activated by somatosensory stimuli. This activation is transmitted to the larger population of magnocellular neurons, which consequently show coordinated increases in their activity during social interactions between virgin female rats. Selectively activating these parvocellular neurons promotes social motivation, whereas inhibiting them reduces social interactions. Thus, parvocellular OT neurons receive particular inputs to control social behavior by coordinating the responses of the much larger population of magnocellular OT neurons. Charlet, Grinevich et al. show that social touch between female rats activates parvocellular oxytocin neurons; these neurons control social behavior by coordinating the responses of the much larger population of magnocellular oxytocin neurons.
TL;DR: In this paper, the authors studied the impact of distance learning on public health students taking courses in public health at the Georgia State University School of Public Health during the COVID-19 pandemic.
Abstract: On March 11, 2020, the World Health organization declared COVID-19 a global pandemic. Following the speed with which COVID-19 spread to all parts of the world, and to contain the spread of the disease, most governments around the world, including the US, authorized unprecedented social containment measures to stem the tide. These measures among others required social distancing and the temporary physical closure of educational institutions. The Georgia State University School of Public Health, like all other institutions of higher learning, had to create distance-learning opportunities to enable students to complete the 2019-2020 academic year. The unplanned, rapid, and uncertain duration of the approach presented challenges at all academic levels. Not much information on best practices was available to guide such abrupt transitions to college education. The purpose of the study was to collect data on how the transition to distance learning impacted undergraduate and graduate students taking courses in public health at GSU. The goal was to identify student academic challenges and the unforeseen benefits of distance learning, and to use that information to inform practices that can be implemented during crises that impact university education.
TL;DR: This article proposes an innovative hybrid blockchain crowdsourcing platform, named zkCrowd, which integrates with a hybrid blockchain structure, smart contract, dual ledgers, and dual consensus protocols to secure communications, verify transactions, and preserve privacy.
Abstract: Blockchain, a promising decentralized para-digm, can be exploited not only to overcome the shortcomings of the traditional crowdsourcing systems, but also to bring technical innovations, such as decentralization and accountability. Nevertheless, some critical inherent limitations of blockchain have been rarely addressed in the literature when it is incorporated into crowdsourcing, which may yield the performance bottleneck in the crowdsourcing systems. To further leverage the superiority of combining blockchain and crowdsourcing, in this article, we propose an innovative hybrid blockchain crowdsourcing platform, named zkCrowd. Our zkCrowd integrates with a hybrid blockchain structure, smart contract, dual ledgers, and dual consensus protocols to secure communications, verify transactions, and preserve privacy. Both the theoretical analysis and experiments are performed to evaluate the advantages of zkCrowd over the state of the art.
TL;DR: The results indicate that gut-derived bacterial SLs affect host lipid metabolism, and show that microbiome-derived SLs enter host circulation and alter ceramide production.
Abstract: Gut microbes are linked to host metabolism, but specific mechanisms remain to be uncovered. Ceramides, a type of sphingolipid (SL), have been implicated in the development of a range of metabolic disorders from insulin resistance (IR) to hepatic steatosis. SLs are obtained from the diet and generated by de novo synthesis in mammalian tissues. Another potential, but unexplored, source of mammalian SLs is production by Bacteroidetes, the dominant phylum of the gut microbiome. Genomes of Bacteroides spp. and their relatives encode serine palmitoyltransfease (SPT), allowing them to produce SLs. Here, we explore the contribution of SL-production by gut Bacteroides to host SL homeostasis. In human cell culture, bacterial SLs are processed by host SL-metabolic pathways. In mouse models, Bacteroides-derived lipids transfer to host epithelial tissue and the hepatic portal vein. Administration of B. thetaiotaomicron to mice, but not an SPT-deficient strain, reduces de novo SL production and increases liver ceramides. These results indicate that gut-derived bacterial SLs affect host lipid metabolism.