968 10 20655 https://www.socictopen.socict.org/files/original/5a7b8e66d280d96aa98fa2bab0c9cd27.pdf faca2c06d53a25e86e36d24093b3f625 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text 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. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Impact of Treatment Regimens on Antibody Response to the SARS-CoV-2 Coronavirus Creator An entity primarily responsible for making the resource Xinghuan Wang, Fuling Zhou, Xinghuan Wang, Yufeng Shang, Tao Liu, Tao Liu, Jingfeng Li, Natasha Mupeta Kaweme Description An account of the resource The coronavirus disease 2019 (COVID-19) is widely spread and remains a global pandemic. Limited evidence on the systematic evaluation of the impact of treatment regimens on antibody responses exists. Our study aimed to analyze the role of antibody response on prognosis and determine factors influencing the IgG antibodies’ seroconversion. A total of 1,111 patients with mild to moderate COVID-19 symptoms admitted to Leishenshan Hospital in Wuhan were retrospectively analyzed. A serologic SARS-CoV-2 IgM/IgG antibody test was performed on all the patients 21 days after the onset of symptoms. Patient clinical characteristics were compared. In the study, 42 patients progressed to critical illness, with 6 mortalities reported while 1,069 patients reported mild to moderate disease. Advanced age (P = 0.028), gasping (P < 0.001), dyspnea (P = 0.024), and IgG negativity (P = 0.006) were associated with progression to critical illness. The mortality rate in critically ill patients with IgG antibody was 6.45% (95% CI 1.12–22.84%) and 36.36% (95% CI 12.36–68.38%) in patients with no IgG antibody (P = 0.003). Symptomatic patients were more likely to develop IgG antibody responses than asymptomatic patients. Using univariable analysis, fever (P < 0.001), gasping (P = 0.048), cancer (P < 0.001), cephalosporin (P = 0.015), and chloroquine/hydroxychloroquine (P = 0.021) were associated with IgG response. In the multivariable analysis, fever, cancer, cephalosporins, and chloroquine/hydroxychloroquine correlated independently with IgG response. We determined that the absence of SARS-CoV-2 antibody IgG in the convalescent stage had a specific predictive role in critical illness progression. Importantly, risk factors affecting seropositivity were identified, and the effect of antimalarial drugs on antibody response was determined. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource cancer, covid-19, SARS-CoV-2, IgG, chloroquine/hydroxychloroquine Identifier An unambiguous reference to the resource within a given context 10.3389/fimmu.2021.580147 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Immunologic diseases. Allergy https://www.socictopen.socict.org/files/original/fd8f1f22e41b7cb5317f4d2f0bd7f7ec.pdf 1a7d5116e726bbb5c6ebbf29b94abf10 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text 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. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource [Consensus document on tracheotomy in patients with COVID 19]. Creator An entity primarily responsible for making the resource G Pérez Acosta, D González Romero, L Santana-Cabrera Date A point or period of time associated with an event in the lifecycle of the resource 2021 Identifier An unambiguous reference to the resource within a given context 10.1016/j.medin.2020.05.012 Source A related resource from which the described resource is derived Medicina intensiva https://www.socictopen.socict.org/files/original/3a7f2314510c36a17500deb4bb3d2c5e.pdf 058a081f39c5456cacdc9be3a9409e1a Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text 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. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Antibody Responses in COVID-19: A Review Creator An entity primarily responsible for making the resource María T. Rugeles, Paula A. Velilla, Mateo Chvatal-Medina, Yorjagis Mendez-Cortina, Pablo J. Patiño Description An account of the resource The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to spread worldwide as a severe pandemic. Although its seroprevalence is highly variable among territories, it has been reported at around 10%, but higher in health workers. Evidence regarding cross-neutralizing response between SARS-CoV and SARS-CoV-2 is still controversial. However, other previous coronaviruses may interfere with SARS-CoV-2 infection, since they are phylogenetically related and share the same target receptor. Further, the seroconversion of IgM and IgG occurs at around 12 days post onset of symptoms and most patients have neutralizing titers on days 14-20, with great titer variability. Neutralizing antibodies correlate positively with age, male sex, and severity of the disease. Moreover, the use of convalescent plasma has shown controversial results in terms of safety and efficacy, and due to the variable immune response among individuals, measuring antibody titers before transfusion is mostly required. Similarly, cellular immunity seems to be crucial in the resolution of the infection, as SARS-CoV-2-specific CD4+ and CD8+ T cells circulate to some extent in recovered patients. Of note, the duration of the antibody response has not been well established yet. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource seroprevalence, covid-19, kinetics, antibodies, SARS-CoV-2, therapeutics Identifier An unambiguous reference to the resource within a given context 10.3389/fimmu.2021.633184 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Immunologic diseases. Allergy https://www.socictopen.socict.org/files/original/f6d2af14e26fab462a9c8e5d39e4d39c.pdf 6f7f33ae56a7e35e90ec2c1defd46d31 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text 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. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource [Reply to «Consensus document on tracheotomy in patients with COVID-19»]. Creator An entity primarily responsible for making the resource M C Martín Delgado, M Bernal-Sprekelsen, R Villalonga Vadell Date A point or period of time associated with an event in the lifecycle of the resource 2021 Identifier An unambiguous reference to the resource within a given context 10.1016/j.medin.2020.06.021 Source A related resource from which the described resource is derived Medicina intensiva https://www.socictopen.socict.org/files/original/0fbb2e91667868ccb0ff1d7c5d001683.pdf 7fb1ebced845682895e701d4a66d33e7 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text 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. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Single-Cell RNA Sequencing Analysis of the Immunometabolic Rewiring and Immunopathogenesis of Coronavirus Disease 2019 Creator An entity primarily responsible for making the resource Furong Qi, Furong Qi, Wenbo Zhang, Jialu Huang, Lili Fu, Jinfang Zhao Description An account of the resource Although immune dysfunction is a key feature of coronavirus disease 2019 (COVID-19), the metabolism-related mechanisms remain elusive. Here, by reanalyzing single-cell RNA sequencing data, we delineated metabolic remodeling in peripheral blood mononuclear cells (PBMCs) to elucidate the metabolic mechanisms that may lead to the progression of severe COVID-19. After scoring the metabolism-related biological processes and signaling pathways, we found that mono-CD14+ cells expressed higher levels of glycolysis-related genes (PKM, LDHA and PKM) and PPP-related genes (PGD and TKT) in severe patients than in mild patients. These genes may contribute to the hyperinflammation in mono-CD14+ cells of patients with severe COVID-19. The mono-CD16+ cell population in COVID-19 patients showed reduced transcription levels of genes related to lysine degradation (NSD1, KMT2E, and SETD2) and elevated transcription levels of genes involved in OXPHOS (ATP6V1B2, ATP5A1, ATP5E, and ATP5B), which may inhibit M2-like polarization. Plasma cells also expressed higher levels of the OXPHOS gene ATP13A3 in COVID-19 patients, which was positively associated with antibody secretion and survival of PCs. Moreover, enhanced glycolysis or OXPHOS was positively associated with the differentiation of memory B cells into plasmablasts or plasma cells. This study comprehensively investigated the metabolic features of peripheral immune cells and revealed that metabolic changes exacerbated inflammation in monocytes and promoted antibody secretion and cell survival in PCs in COVID-19 patients, especially those with severe disease. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource inflammation, covid-19, peripheral blood mononuclear cells, metabolic changes, antibody secretion Identifier An unambiguous reference to the resource within a given context 10.3389/fimmu.2021.651656 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Immunologic diseases. Allergy https://www.socictopen.socict.org/files/original/e498d77e4e9ca489a984358151dd6d7f.pdf 6b2dea86c3781aad62cd17f7dda1eaa8 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text 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. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Leveraging Informatics and Technology to Support Public Health Response: Framework and Illustrations using COVID-19. Creator An entity primarily responsible for making the resource Jane L Snowdon, William Kassler, Hema Karunakaram, Brian E Dixon, Kyu Rhee Description An account of the resource To develop a conceptual model and novel, comprehensive framework that encompass the myriad ways informatics and technology can support public health response to a pandemic. The conceptual model and framework categorize informatics solutions that could be used by stakeholders (e.g., government, academic institutions, healthcare providers and payers, life science companies, employers, citizens) to address public health challenges across the prepare, respond, and recover phases of a pandemic, building on existing models for public health operations and response. Mapping existing solutions, technology assets, and ideas to the framework helped identify public health informatics solution requirements and gaps in responding to COVID-19 in areas such as applied science, epidemiology, communications, and business continuity. Two examples of technologies used in COVID-19 illustrate novel applications of informatics encompassed by the framework. First, we examine a hub from The Weather Channel, which provides COVID-19 data via interactive maps, trend graphs, and details on case data to individuals and businesses. Second, we examine IBM Watson Assistant for Citizens, an AI-powered virtual agent implemented by healthcare providers and payers, government agencies, and employers to provide information about COVID-19 via digital and telephone-based interaction. Early results from these novel informatics solutions have been positive, showing high levels of engagement and added value across stakeholders. The framework supports development, application, and evaluation of informatics approaches and technologies in support of public health preparedness, response, and recovery during a pandemic. Effective solutions are critical to success in recovery from COVID-19 and future pandemics. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource coronavirus, pandemics, artificial intelligence, information technology, public health informatics, clinical informatics Identifier An unambiguous reference to the resource within a given context 10.5210/ojphi.v13i1.11072 Source A related resource from which the described resource is derived Online journal of public health informatics https://www.socictopen.socict.org/files/original/abd8c1f5225aebc1d39fa76d5586bc3b.pdf e8bef52b6589d74b8c44edce1f9c3c8d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text 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. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Data Driven Approach for Prioritizing COVID-19 Vaccinations in the Midwestern United States. Creator An entity primarily responsible for making the resource Matthew Blaser, Michael D Cailas, John R Canar, Brian Cooper, Peter J Geraci, Kristin M Osiecki, Apostolis Sambanis, Greg Arling, Joel Flax-Hatch Description An account of the resource Considering the potential for widespread adoption of social vulnerability indices (SVI) to prioritize COVID-19 vaccinations, there is a need to carefully assess them, particularly for correspondence with outcomes (such as loss of life) in the context of the COVID-19 pandemic. The University of Illinois at Chicago School of Public Health Public Health GIS team developed a methodology for assessing and deriving vulnerability indices based on the premise that these indices are, in the final analysis, classifiers. Application of this methodology to several Midwestern states with a commonly used SVI indicates that by using only the SVI rankings there is a risk of assigning a high priority to locations with the lowest mortality rates and low priority to locations with the highest mortality rates. Based on the findings, we propose using a two-dimensional approach to rationalize the distribution of vaccinations. This approach has the potential to account for areas with high vulnerability characteristics as well as to incorporate the areas that were hard hit by the pandemic. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Identifier An unambiguous reference to the resource within a given context 10.5210/ojphi.v13i1.11621 Source A related resource from which the described resource is derived Online journal of public health informatics https://www.socictopen.socict.org/files/original/458bbd0c29523e361587cd2e975fec0a.pdf e52db17e81b3e9b24a7cecab5bf1053f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text 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. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Targeting protein-protein interaction interfaces in COVID-19 drug discovery. Creator An entity primarily responsible for making the resource Chung-ke Chang, Shan-Meng Lin, Shih-Chao Lin, Sin-Cih Sun, Hung-Yi Wu, Roshan Satange, Kylene Kehn-Hall, Ming-Hon Hou Description An account of the resource To date, the COVID-19 pandemic has claimed over 1 million human lives, infected another 50 million individuals and wreaked havoc on the global economy. The crisis has spurred the ongoing development of drugs targeting its etiological agent, the SARS-CoV-2. Targeting relevant protein-protein interaction interfaces (PPIIs) is a viable paradigm for the design of antiviral drugs and enriches the targetable chemical space by providing alternative targets for drug discovery. In this review, we will provide a comprehensive overview of the theory, methods and applications of PPII-targeted drug development towards COVID-19 based on recent literature. We will also highlight novel developments, such as the successful use of non-native protein-protein interactions as targets for antiviral drug screening. We hope that this review may serve as an entry point for those interested in applying PPIIs towards COVID-19 drug discovery and speed up drug development against the pandemic. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource covid-19, SARS-CoV-2, drug discovery, antiviral strategy, PPIIs Identifier An unambiguous reference to the resource within a given context 10.1016/j.csbj.2021.04.003 Source A related resource from which the described resource is derived Computational and structural biotechnology journal https://www.socictopen.socict.org/files/original/2727228338526a59d39d5165c9ecb305.pdf d60a0ca6be3c46edad5752bacb581e9a Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text 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. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Classification of COVID-19 Chest CT Images Based on Ensemble Deep Learning Creator An entity primarily responsible for making the resource Xiaoshuo Li, Wenjun Tan, Pan Liu, Qinghua Zhou, Jinzhu Yang Description An account of the resource Novel coronavirus pneumonia (NCP) has become a global pandemic disease, and computed tomography-based (CT) image analysis and recognition are one of the important tools for clinical diagnosis. In order to assist medical personnel to achieve an efficient and fast diagnosis of patients with new coronavirus pneumonia, this paper proposes an assisted diagnosis algorithm based on ensemble deep learning. The method combines the Stacked Generalization ensemble learning with the VGG16 deep learning to form a cascade classifier, and the information constituting the cascade classifier comes from multiple subsets of the training set, each of which is used to collect deviant information about the generalization behavior of the data set, such that this deviant information fills the cascade classifier. The algorithm was experimentally validated for classifying patients with novel coronavirus pneumonia, patients with common pneumonia (CP), and normal controls, and the algorithm achieved a prediction accuracy of 93.57%, sensitivity of 94.21%, specificity of 93.93%, precision of 89.40%, and F1-score of 91.74% for the three categories. The results show that the method proposed in this paper has good classification performance and can significantly improve the performance of deep neural networks for multicategory prediction tasks. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Identifier An unambiguous reference to the resource within a given context 10.1155/2021/5528441 Source A related resource from which the described resource is derived Biotemas Publisher An entity responsible for making the resource available Universidade Federal de Santa Catarina Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine (General), Medical technology https://www.socictopen.socict.org/files/original/d93c6f59412e3ed0208baae84d8ae2ba.pdf 7e0890d38c3a4a0817a2c8616b974567 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text 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. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Predictors of Covid-19 case fatality rate: An ecological study. Creator An entity primarily responsible for making the resource Reema Karasneh, Osama Y Alshogran, Shoroq M Altawalbeh, Sayer I Al-Azzam Description An account of the resource The outbreak of novel coronavirus (Covid-19) has a significant burden on global health and could be associated with significant mortality. Limited information exists about determinants of its fatality worldwide. Thus, this ecological study examined the association of various predictors with Covid-19 fatality. International data bases of Covid-19 statistics and health metrics available primarily at WHO were reviewed to collect information for 113 countries. The dependent variable was Covid-19 case fatality rate. Independent variables were demographic, social, clinical, economic, heath care and child health factors. Case fatality rate of Covid-19 varies across countries with an average of 4.2 ± 3.8%, and about half of countries had fatality rate >3.2% (median). Significant relationships were observed between Covid-19 fatality rate and socio-economic, clinical, and health variables at the unadjusted regression analysis. At the multivariate adjusted model, percentage of population with age>60 years was positively associated with Covid-19 fatality (B = 0.032, p = 0.005), while Polio-3 immunization at 1-year old was inversely related (B = -0.057, p = 0.017). This ecological investigation highlights the higher risk of death among elderly with Covid-19 pandemic and suggests that Polio-3 immunization coverage among 1-year-olds may be associated with better survival. Future research is warranted to validate these findings. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource covid-19, Fatality, Pandemic, global, Predictors, ecological study Identifier An unambiguous reference to the resource within a given context 10.1016/j.amsu.2021.102319 Source A related resource from which the described resource is derived Annals of medicine and surgery (2012)