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                <text>Utility Evaluation of Porcine Enteroids as PDCoV Infection Model in vitro</text>
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                <text>Hao Luo, Jingyou Zheng, Yunlu Chen, Tingjun Wang, Zhen-Ning Zhang, Ying Shan, Jidong Xu, Min Yue, Weihuan Fang, Xiaoliang Li</text>
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                <text>Porcine deltacoronavirus (PDCoV) is a novel emerging enteric coronavirus found in pigs. Intestinal enteroids, which partially recreate the structure and function of intestinal villi-crypts, have many physiological similarities to the intestinal tissues in vivo. Enteroids exhibit advantages in studying the interactions between intestines and enteric pathogens. To create a novel infection model for PDCoV, we developed an in vitro system to generate porcine intestinal enteroids from crypts of duodenum, jejunum, and ileum of pigs. Enterocytes, enteroendocrine cells, Paneth cells, stem cells, proliferating cells, and goblet cells were found in the differentiated enteroids. Replication of PDCoV was detected in the cultured enteroids by immunofluorescence and quantitative RT-PCR. Double immunofluorescence labeling demonstrated that PDCoV was present in Sox9-positive intestinal cells and Villin1-positive enterocytes. There were multiple cellular responses shown as changes of transcription of genes related to mucosal immunity, antiviral genes, and marker genes of stem cells and other cells in the enteroids infected with PDCoV. We conclude that the 2-D enteroids derived from porcine jejunum can be used as an in vitro multicellular model for the investigation of pathogenesis and host immune responses to porcine enteric pathogens, such as PDCoV.</text>
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                <text>DOI: 10.3389/fmicb.2020.00821</text>
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                <text>Frontiers in Microbiology</text>
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                <text>Elena Ciaglia, Carmine Vecchione, Annibale  Alessandro Puca</text>
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                <text>DOI: 10.3389/fped.2020.00206</text>
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                <text>Frontiers in Pediatrics</text>
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                <text>DOI: 10.3389/fmed.2020.00146</text>
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                <text>Mauricio Roberto da Silva, Giovani de Lorenzi Pires, Rogerio Santos Pereira</text>
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                <text>Diante da crise estrutural do capitalismo e da pandemia provocada pela disseminação do coronavirus, o editorial acrescenta que a saída necroliberal imposta pelo capitalismo monopolista ao Brasil, desde o golpe de 2016, tem ainda a presença nefasta de um presidente da república que demonstra não apenas não estar preparado para o cargo como tem praticado crimes de lesa-humanidade nesse episódio do isolamento social requerido pela ciência para o enfrentamento da COVID-19.</text>
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                <text>DOI: 10.5007/2175-8042.2020e72755</text>
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                <text>Motrivivência</text>
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                <text>Min Ah Park, Alex R Cook, Jue Tao Lim, Yinxiaohe Sun, Borame L. Dickens</text>
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                <text>As the novel coronavirus (SARS-CoV-2) continues to spread rapidly across the globe, we aimed to identify and summarize the existing evidence on epidemiological characteristics of SARS-CoV-2 and the effectiveness of control measures to inform policymakers and leaders in formulating management guidelines, and to provide directions for future research. We conducted a systematic review of the published literature and preprints on the coronavirus disease (COVID-19) outbreak following predefined eligibility criteria. Of 317 research articles generated from our initial search on PubMed and preprint archives on 21 February 2020, 41 met our inclusion criteria and were included in the review. Current evidence suggests that it takes about 3-7 days for the epidemic to double in size. Of 21 estimates for the basic reproduction number ranging from 1.9 to 6.5, 13 were between 2.0 and 3.0. The incubation period was estimated to be 4-6 days, whereas the serial interval was estimated to be 4-8 days. Though the true case fatality risk is yet unknown, current model-based estimates ranged from 0.3% to 1.4% for outside China. There is an urgent need for rigorous research focusing on the mitigation efforts to minimize the impact on society.</text>
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                <text>DOI: 10.3390/jcm9040967</text>
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                <text>Journal of Clinical Medicine</text>
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            <description>A name given to the resource</description>
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                <text>Mesenchymal Stromal Cell Secretome for Severe COVID-19 Infections: Premises for the Therapeutic Use</text>
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                <text>Elia Bari, Ilaria Ferrarotti, Laura Saracino, Sara Perteghella, Maria Luisa Torre, Angelo Guido Corsico</text>
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            <description>An account of the resource</description>
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                <text>From the end of 2019, the world population has been faced the spread of the novel coronavirus SARS-CoV-2 responsible for COVID-19 infection. In approximately 14% of the patients affected by the novel coronavirus, the infection progresses with the development of pneumonia that requires mechanical ventilation. At the moment, there is no specific antiviral treatment recommended for the COVID-19 pandemic and the therapeutic strategies to deal with the infection are only supportive. In our opinion, mesenchymal stem cell secretome could offer a new therapeutic approach in treating COVID-19 pneumonia, due to the broad pharmacological effects it shows, including anti-inflammatory, immunomodulatory, regenerative, pro-angiogenic and anti-fibrotic properties.</text>
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                <text>2020</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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                <text>SARS-CoV-2, COVID-19, acute respiratory distress syndrome, mesenchymal stem cells, extracellular vesicles, Microvesicles</text>
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            <description>An unambiguous reference to the resource within a given context</description>
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                <text>DOI: 10.3390/cells9040924</text>
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            <description>A related resource from which the described resource is derived</description>
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                <text>Cells</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="15838">
                <text>MDPI AG</text>
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                <text>Biology (General)</text>
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            <description>A language of the resource</description>
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                <text>EN</text>
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              <name>Title</name>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>Quarantine Vehicle Scheduling for Transferring High-Risk Individuals in Epidemic Areas</text>
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            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
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                <text>Minxia Zhang, Hong-Fan Yan, Jiayu Wu, Yujun Zheng</text>
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            <description>An account of the resource</description>
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                <text>In a large-scale epidemic outbreak, there can be many high-risk individuals to be transferred for medical isolation in epidemic areas. Typically, the individuals are scattered across different locations, and available quarantine vehicles are limited. Therefore, it is challenging to efficiently schedule the vehicles to transfer the individuals to isolated regions to control the spread of the epidemic. In this paper, we formulate such a quarantine vehicle scheduling problem for high-risk individual transfer, which is more difficult than most well-known vehicle routing problems. To efficiently solve this problem, we propose a hybrid algorithm based on the water wave optimization (WWO) metaheuristic and neighborhood search. The metaheuristic uses a small population to rapidly explore the solution space, and the neighborhood search uses a gradual strategy to improve the solution accuracy. Computational results demonstrate that the proposed algorithm significantly outperforms several existing algorithms and obtains high-quality solutions on real-world problem instances for high-risk individual transfer in Hangzhou, China, during the peak period of the novel coronavirus pneumonia (COVID-19).</text>
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                <text>2020</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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                <text>Public health emergencies, epidemics, medical isolation, vehicle scheduling, optimization, water wave optimization (WWO)</text>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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              <elementText elementTextId="15846">
                <text>DOI: 10.3390/ijerph17072275</text>
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            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="15847">
                <text>International Journal of Environmental Research and Public Health</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="15848">
                <text>MDPI AG</text>
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            </elementTextContainer>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Medicine</text>
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            <description>A language of the resource</description>
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                <text>EN</text>
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              <name>Title</name>
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                  <text>Coronavirus</text>
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              <name>Description</name>
              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
      <description>A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text.</description>
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                <text>COVID-19 Trend Estimation in the Elderly Italian Region of Sardinia</text>
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                <text>Mariangela Valentina Puci, Federica Loi, Ottavia  Eleonora Ferraro, Stefano Cappai, Sandro Rolesu, Cristina Montomoli</text>
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            <name>Description</name>
            <description>An account of the resource</description>
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                <text>December 2019 saw a novel coronavirus (COVID-19) from China quickly spread globally. Currently, COVID-19, defined as the new pandemic by the World Health Organization (WHO), has reached over 750,000 confirmed cases worldwide. The virus began to spread in Italy from the 22nd February, and the number of related cases is still increasing. Furthermore, given that a relevant proportion of infected people need hospitalization in Intensive Care Units, this may be a crucial issue for National Healthcare System's capacity. WHO underlines the importance of specific disease regional estimates. Because of this, Italy aimed to put in place proportioned and controlled measures, and to guarantee adequate funding to both increase the number of ICU beds and increase production of personal protective equipment. Our aim is to investigate the current COVID-19 epidemiological context in Sardinia region (Italy) and to estimate the transmission parameters using a stochastic model to establish the number of infected, recovered, and deceased people expected. Based on available data from official Italian and regional sources, we describe the distribution of infected cases during the period between 2nd and 15th March 2020. To better reflect the actual spread of COVID-19 in Sardinia based on data from 15th March (first Sardinian declared outbreak), two Susceptible-Infectious-Recovered-Dead (SIRD) models have been developed, describing the best and worst scenarios. We believe that our findings represent a valid contribution to better understand the epidemiological context of COVID-19 in Sardinia. Our analysis can help health authorities and policymakers to address the right interventions to deal with the rapidly expanding health emergency.</text>
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                <text>2020</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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                <text>COVID-19, coronavirus, public health emergency, Pandemic, SIRD-model</text>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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                <text>DOI: 10.3389/fpubh.2020.00153</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="15857">
                <text>Frontiers in Public Health</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="15858">
                <text>Frontiers Media S.A.</text>
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            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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                <text>Public aspects of medicine</text>
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            <name>Language</name>
            <description>A language of the resource</description>
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                <text>EN</text>
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              <name>Title</name>
              <description>A name given to the resource</description>
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                  <text>Coronavirus</text>
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              <name>Description</name>
              <description>An account of the resource</description>
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                  <text>Dominio científico: Coronavirus</text>
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      <name>Text</name>
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          <element elementId="50">
            <name>Title</name>
            <description>A name given to the resource</description>
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                <text>3-D Printed Protective Equipment During COVID-19 Pandemic</text>
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            <name>Creator</name>
            <description>An entity primarily responsible for making the resource</description>
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                <text>Christian Wesemann, Stefano Pieralli, Tobias Fretwurst, Julian Nold, Katja Nelson, Rainer Schmelzeisen, Elmar Hellwig, Benedikt Christopher Spies</text>
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            <description>An account of the resource</description>
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                <text>While the number of coronavirus cases from 2019 continues to grow, hospitals are reporting shortages of personal protective equipment (PPE) for frontline healthcare workers. Furthermore, PPE for the eyes and mouth, such as face shields, allow for additional protection when working with aerosols. 3-D printing enables the easy and rapid production of lightweight plastic frameworks based on open-source data. The practicality and clinical suitability of four face shields printed using a fused deposition modeling printer were examined. The weight, printing time, and required tools for assembly were evaluated. To assess the clinical suitability, each face shield was worn for one hour by 10 clinicians and rated using a visual analogue scale. The filament weight (21–42 g) and printing time (1:40–3:17 h) differed significantly between the four frames. Likewise, the fit, wearing comfort, space for additional PPE, and protection varied between the designs. For clinical suitability, a chosen design should allow sufficient space for goggles and N95 respirators as well as maximum coverage of the facial area. Consequently, two datasets are recommended. For the final selection of the ideal dataset to be used for printing, scalability and economic efficiency need to be carefully balanced with an acceptable degree of protection.</text>
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            <name>Date</name>
            <description>A point or period of time associated with an event in the lifecycle of the resource</description>
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              <elementText elementTextId="15864">
                <text>2020</text>
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            <name>Subject</name>
            <description>The topic of the resource</description>
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              <elementText elementTextId="15865">
                <text>3D printing, COVID-19, personal protective equipment, Face shield</text>
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            <name>Identifier</name>
            <description>An unambiguous reference to the resource within a given context</description>
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              <elementText elementTextId="15866">
                <text>DOI: 10.3390/ma13081997</text>
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            <name>Source</name>
            <description>A related resource from which the described resource is derived</description>
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              <elementText elementTextId="15867">
                <text>Materials</text>
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            <name>Publisher</name>
            <description>An entity responsible for making the resource available</description>
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              <elementText elementTextId="15868">
                <text>MDPI AG</text>
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            <name>Coverage</name>
            <description>The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant</description>
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              <elementText elementTextId="15869">
                <text>Technology, Engineering (General). Civil engineering (General), Electrical engineering. Electronics. Nuclear engineering, Microscopy, Descriptive and experimental mechanics</text>
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            <name>Language</name>
            <description>A language of the resource</description>
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                <text>EN</text>
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                <text>EN</text>
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