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In the contemporary world, the COVID-19 pandemic has seriously affected the health of people as well as economic development and social stability. Therefore, vaccination to prevent viral infection is an important scientific means to effectively control the epidemic. At present, many countries have developed more and more COVID-19 vaccines with different technology platforms at a record speed, and most of them have been approved for emergency use or be conditionally marketed. In this paper, we mainly reviewed and paid attention to the research progress and achievements related to 8 COVID-19 vaccine technology platforms, including inactivated vaccines, attenuated live vaccines, protein subunit vaccines, virus-like particle (VLP) vaccines, replicated virus vector-based vaccines, non-replicated virus vector-based vaccines, DNA vaccines, and mRNA vaccines. However, with the coming COVID-19 variants, the effectiveness and neutralization activity of the current vaccines, especially the omicron variant, are reduced. Therefore, for the improvement of vaccine effectiveness and safety, we can adopt measures such as developing and optimizing new vaccines such as immune adjuvants or nanoparticle vaccines, and changing inoculation methods such as mixed inoculation and changes in inoculation routes. Finally, we summarized a series of new problems and challenges arising from some COVID-19 vaccines and elaborated some views, hoping to provide some contributions for the development and design of effective strategies for future vaccine development to some extent. © 2023 SPIE.
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THE 19th International Workshop on Data Mining in Bioinformatics (BIOKDD 2020) was held virtually on August 24, 2020 due to the COVID-19 pandemic. BIOKDD 2020 featured the special theme of "Battling COVID-19" which particularly welcomed paper submissions and invited talks related to COVID-19 research. As a whole-day workshop, altogether 15 submissions were accepted among a total of 35 submissions, and they were divided into 4 sessions: (1) Bioinformatics, (2) Data Curation, (3) Deep Learning with Biomedical Data, and (4) Data Mining & Statistical Methods. There are also 7 invited talks by domain experts. This special section features the extended versions of 6 quality papers presented in BIOKDD 2020.
ABSTRACT
Vaccines are one of the biggest successes in modern history and are particularly important in light of the multiple ongoing epidemics. Recently, vaccines have protected peoples' health and lives around the world during the coronavirus disease 2019 pandemic. Different types of vaccines have their own characteristics and advantages and are used in the context of different epidemics. Responses to vaccination are also different, and can include adverse reactions and absent responses. These individual differences are thought to be influenced by host genes. In this review, we first discuss vaccine types and characteristics. Second, we discuss different responses to vaccination, primarily focusing on the association between genetic variation and inter-individual differences.
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Single-cell RNA-sequencing (scRNA-seq) is a rapidly increasing research area in biomedical signal processing. However, the high complexity of single-cell data makes efficient and accurate analysis difficult. To improve the performance of single-cell RNA data processing, two single-cell features calculation method and corresponding dual-input neural network structures are proposed. In this feature extraction and fusion scheme, the features at the cluster level are extracted by hierarchical clustering and differential gene analysis, and the features at the cell level are extracted by the calculation of gene frequency and cross cell frequency. Our experiments on COVID-19 data demonstrate that the combined use of these two feature achieves great results and high robustness for classification tasks. © 2021 Journal of Beijing Institute of Technology
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Studies have shown that COVID-19 patients infected with SARS-CoV-2 have severe pulmonary inflammation and cytokine storm, so the treatment of cytokine storm is an important part of rescuing critically ill patients with COVID-19. As an important cause of death, the preclinical study of cytokine storm is essential, and related experiments in vivo and in vitro are also the only way to develop new drugs for COVID-19 in the future. This paper reviews the in vitro and in vivo experimental methods of cytokine storm research articles at home and abroad in recent years, including the establishment of animal models, cell evaluation methods, pharmacodynamic evaluation indicators, etc., in order to provide reference and guidance for the experimental design methods of cytokine storm. © 2021 Publication Centre of Anhui Medical University. All rights reserved.
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In response to the impact of the Novel coronavirus infection in 2020, State Grid Corporation has introduced 12 important measures to fully promote enterprises to resume work and production. The evaluation method based on the ratio of user's current daily electricity consumption to the average electricity consumption of December 2019 is straightforward and effective, but difficult to scientifically defining the judgment threshold. In view of the problem of lacking rationality in the evaluation of resumption of work and production, this project deeply analyzes the current enterprise resumption index, then further proposes a K-means clustering analysis method. By extracting power consumption data of enterprises, characteristic indexes reflecting their production shutdown, resumption and peak periods are established. K-means clustering algorithm is applied to cluster characteristic samples, accurately analyzing the resumption situation of enterprises consequently, which helps improve the accuracy of the evaluation on resumption of work and production and achieve significant management, economic and social benefits.
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It is known to all that Coronavirus disease 2019 (COVID-19) is an infectious disease, which has spread to more than 180 countries and territories around the world since the end of 2019.lt is clear that this disease results in a moment of panic. However, some people used the data of Tieba to analyze public opinion and describe the intensity of people's emotions, but Tieba is not representative. Because whether it is in terms of popularity, number of users or age spread, the data of Weibo is more representative compared to Tieba. Therefore, this article carries out the public opinion analysis by using Python crawler to obtain data on the topic of COVID-19 in Weibo. The methods we use include word frequency analysis tools, plug-ins in the ROST content mining system, and analysis interfaces in the Baidu Brain Al open platform. The purpose of this article is to analyze the mental health level of the public, such as nervousness, fear, panic, and anxiety. By experimental results on the relevant Weibo in February and March, we find that positive emotions stood at 14.64%,neutral emotion blog posts still accounted for 66.64% and negative emotions accounted for 18.72%.In the negative segment, the general negative emotions accounted for 12.485%,the moderate negative emotions accounted for 4.9%,and the users showed a high degree of negative emotions accounted for 0.455%.And then we roughly give the relevant strategies and suggestions for some groups which have the intense negative emotions. The limitation is that we can't give them some specific suggestions for different users for the time being, which needs further research in the future. © 2020 IEEE.
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With the spread of the new coronavirus pneumonia in China, medical researchers at home and abroad have carried out clinical studies in order to find the best way to combat the epidemic. The quality control measures are the key to ensure the scientificity of results. An overview of a multi-center randomized controlled double-blind clinical study was presented which was on the efficacy and safety of terazavirin in the treatment of COVID-19. It has pointed out that the difficulty of quality control in this study lies in obtaining the first-line data for the research assistant due to the isolation, and the delay of quality control only through the verification of EDC data. And these problems could be solved by using "core data targeting" quality control form. The features of this form include the concise content directly aiming at the main chart data in the research report for quality control, focusing on the implementation of the core elements of the programme and function of reminding and helping research assistants understand the capabilities of the project.
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Background: Under the increasingly severe situation of COVID-19 pandemic, Hebei Province has received a large number of individuals returned from abroad.Therefore, on the occasion of returning to work, production and school, it is imperative to effectively strengthen SARS-CoV-2 screening and management of overseas imported cases and to take actions to cut off the transmission channels to prevent the spread of SARS-CoV-2 from this group.Objective: To study the clinical characteristics of overseas imported and local COVID-19 cases in Hebei Province, to provide a reference for developing targeted programs to prevent the recurrence of the pandemic.Methods: 28 patients with COVID-19(7 overseas imported and 21 local )who were admitted to Shijiazhuang Fifth Hospital from January 21 to April 5, 2020 were selected.The epidemiological characteristics, clinical manifestations, laboratory and imaging examinations of them were summarized and analyzed.Results (1)The imported group included 5 men and 2 women, mostly were young adults〔4(57.1%)were 19-29 years〕, with an average age of (23.6±11.1) years.The local group included 14 men and 7 women, mostly were middle-aged and elderly adults〔19(90.5%)aged 30-72 years〕, with an average age of(43.6±19.7) years, mainly were infected with COVID-19 after family gatherings.(2)Among the imported cases, 1 had fever, 1 had diarrhea, and 5 had no clinical symptoms;6(85.7%)had common type COVID-19, 1(14.3%)had severe type, no mild and critically severe types.Among the local cases, 15 had fever, 9 had cough, 5 had sore throat, 3 had fatigue, 2 had muscle pain, and 1 had diarrhea;1(4.8%) had mild type COVID-19, 15(71.4%)had common type, 4(19.0%)had severe type, and 1(4.8%)had critically severe type.(3)The imported cases showed lower average cycle threshold(Ct) value of SARS-CoV-2 N gene(t=14.430, P<0.001) than the local cases.Moreover, the average Ct value of SARS-CoV-2 N gene and ORF1ab gene was also lower in the imported cases(t=17.856, P<0.001).The prevalence of reduced CD4+ T lymphocytes was above 50.0% in both groups compared with the normal reference range value.The prevalence of reduced lymphocyte count and CD3+ T lymphocytes, and elevated C-reactive protein, aspartate aminotransferase, alanine aminotransferase and lactate dehydrogenase was higher than 40.0% in the imported cases.The prevalence of elevated C-reactive protein and lactate dehydrogenase was higher than 40.0% in the local cases.(4)The lung CT examination of two groups indicated that the lesions were mainly distributed in bilateral lung lobes, followed by unilateral unilobe, and then unilateral multiple lobes.Ground-glass opacity was the main image finding in the imported group, while ground-glass opacity and consolidation opacity were the main image findings in the local group.Conclusion: In Hebei Province, the imported COVID-19 cases showed milder symptoms, lower Ct values of SARS-CoV-2 N gene and ORF1ab gene and higher SARS-CoV-2 viral nucleic acids from nasopharyngeal swabs, which indicate that the virus from imported cases may be more contagious.Therefore, it is necessary to strengthen isolation, screening and early diagnosis of imported cases, so as to prevent the spread of disease as much as possible. Copyright © 2020 by the Chinese General Practice.
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Objective: To investigate the correlation between concomitant diabetes mellitus and clinical features in patients with COVID-19. Methods: Fifty patients with COVID-19 admitted to the Sixth People's Hospital of Shenyang were divided into 2 groups with and without diabetes mellitus. Indexes such as hospitalization days, duration of positive virus-PCR result, secondary infection, duration of fever, rate of liver dysfunction, and rate of cardiac injury were compared between 2 groups. Results: The average hospitalization durations of diabetes group and control group were(24.0±6.8) and(18.4±5.9) days, respectively, and the duration of positive virus-PCR testing results were(16.0±4.5) and(12.3±4.4) days respectively, suggesting longer hospital stay and longer time for virus clearance in the diabetes group than those in the control group(both P<0.05). The rates of secondary infection, severe subtype, liver dysfunction and cardiac injury in the diabetes group increased, though without significant difference(P>0.05). Conclusion: Prolonged duration of positive virus-PCR result and average days of hospitalization in patients with COVID-19 may be associated with diabetes mellitus. Copyright © 2020 by the Chinese Medical Association.
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Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2), has been spreading rapidly internationally. On the one hand, there is a certain correlation between the basic cardiovascular disease and the severity of COVID-19;on the other hand, the patients with severe and critical COVID-19 often have cardiovascular system-related clinical manifestations. This article reviews the interaction between COVID-19 and cardiovascular system, and the cardiovascular problems that may be encountered in the diagnosis and treatment of COVID-19. © 2020, Editorial Department of Journal of Shanghai Second Medical University. All right reserved.