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Objective: To investigate epidemiological features of skin damage among front-line healthcare workers fighting against COVID-19 pandemic. Method(s): A self-designed questionnaire was released on an online survey website "wenjuan.com", and sent to the front-line medical staff caring for patients with confirmed COVID-19 in 6 infectious disease wards of the General Hospital of Central Theater Command of PLA via WeChat from March 10th to 20th, 2020. Then, the questionnaires were collected, a database was established, and statistical analysis was performed on the incidence, types and epidemiological characteristics of skin damage among the medical staff. Result(s): A total of about 550 medical staff were surveyed, 404 questionnaires were collected, of which 391 were valid, and 303 cases had skin damage. The survey showed that females, hand cleaning frequency > 10 times per day, wearing three-level protective equipment for more than 6 hours per week were risk factors for skin damage, and frequent use of a hand cream could reduce skin problems. Among the respondents, the incidence of skin damage was significantly higher in the females (79.81%, 249/312) than in the males (38.35%, 54/79;chi2 = 4.741, P = 0.029), and higher in the groups with hand cleaning frequency of 10-20 times per day (79.73%, 118/148) and > 20 times per day (85.71%, 84/98) than in the group with hand cleaning frequency of 1-10 times per day (69.66%, 101/145;chi2 = 9.330, P = 0.009). The incidence of skin damage was significantly lower in the group wearing protective equipment for 1-5 hours per week (64.04%, 73/114) than in the groups wearing protective equipment for 6-10 hours per week (81.48%, 66/81), 11-15 hours per week (95.24%, 20/21), 16-20 hours per week (81.82%, 36/44), 21-25 hours per week (86.49%, 32/37), and > 25 hours per week (80.85%, 76/94;chi2 = 19.164, P = 0.002). Among the 391 respondents, the skin damage related to disinfection and protective equipment mainly manifested as dry skin (72.89%), desquamation (56.78%), skin pressure injury (54.48%), skin maceration (45.01%), and sensitive skin (33.50%);acne (27.11%) was the related skin disease with the highest incidence, followed by facial dermatitis (23.27%), eczematous dermatitis (21.48%), folliculitis (18.92%), dermatomycosis (11.00%), urticaria (9.21%), etc. Conclusion(s): There was a high incidence of skin damage related to protective equipment among the front-line healthcare workers fighting against COVID-19, and strengthening skin protection could markedly reduce the incidence of skin damage.Copyright © 2020 by the Chinese Medical Association.
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These five poems have been selected from Ho Fuk Yan's 2021 poetry anthology Love in the Time of Coronavirus. They were written in 2020, along with the development of the pandemic that started to affect everyone in the world. It is noteworthy that the poet does not simply want to record the current events, but rather aims to achieve a balance between what happens in reality and what happens in our consciousness. In other words, to record the pandemic and beyond. © 2023 Taylor & Francis Group, LLC.
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To understand the influence of coronavirus disease control policies on changes in characteristics of particulate matter smaller than 2.5 μm (PM2.5), concentrations of various PM2.5 components in Jinan city before and after implementation of the epidemic control measures during the 2020 Spring Festival were studied using online monitoring data. Standardized multiple linear regression was used to analyze the contribution of meteorological factors to the variations in concentrations of PM2.5 components. After the epidemic control measures were implemented, the concentrations of PM2.5 components in the area decreased significantly, and the rate at which the daily average concentration was exceeded decreased by 24.8%. The concentrations of all PM2.5 components decreased to various degrees, with those of trace elements (TE), elemental carbon (EC), and nitrate (NO3−) having decreased significantly by 50.3%, 46.8%, and 31.5%, respectively. In terms of component proportions, those of TE and EC decreased after the epidemic control measures were initiated whereas those of ammonium (NH4+), organic matter (OM), sulfate (SO4 2− ), and mineral dust increased;the proportion of NO3 − changed slightly, and the total proportion of secondary ions SO4 2−, NO3−, and NH4 + increased by 14.3%. Comparison of the proportions of PM2.5 components showed that after the epidemic control measures were implemented, the proportions of NO3 − and EC in PM2.5 that cause a light pollution level decreased whereas those of OM, SO4 2−, and NH4 + increased. This indicated that people traveled less, motor vehicle emissions decreased, work at construction sites stopped, and NO3 − proportion was greatly reduced while epidemic control measures were in place. However, afterward, decrease in concentrations of PM2.5 components and increase in secondary transformation of volatile organic compounds led to an increase in OM concentration. Compared with those before the epidemic control measures were implemented, the NO2/SO2 and NO3– /SO4 2− ratios fell significantly, and their average values decreased by 30.0% and 14.0%, respectively, indicating that the contribution of mobile sources (e.g., automobile exhaust) to pollution had decreased during the epidemic control period. Under the influence of the control measures, the OC concentration also decreased for excellent, good, and mild pollution levels;however, the secondary organic carbon concentration increased, indicating that secondary conversions did not decrease under the epidemic control conditions. Standardized multiple linear regression analyses of meteorological factors showed that changes in the height of the boundary layer contributed the most (46.5%) to changes in concentrations of PM2.5 components before the epidemic control measures were implemented;afterward, humidity was the primary factor governing the increase in these concentrations. © 2022, The Science Press. All rights reserved.
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To examine the bus travel behaviour of the elderly in the context of the COVID-19 pandemic, this study analysed the mechanisms influencing the elderly's risk perceptions regarding behavioural intention towards bus travel whilst focusing on the normalisation stage of pandemic prevention and control. Based on the theory of planned behaviour, a structural equation model of the elderly's bus travel intention was constructed. The interactions among six factors-including attitudes, subjective norms, perceived behavioural control, cognitive risk perception, affective risk perception and the behavioural intention of the elderly's bus travel-were quantitatively analysed. Valid sample data were used for empirical research. The results of this study show that perceived behavioural control, attitudes and subjective norms have a significant positive impact on the behavioural intentions of the elderly's bus travel during the normalisation stage of pandemic prevention and control, with perceived behavioural control being the most influential factor. Moreover, perceived behavioural control also has a significant positive impact on attitudes, which indirectly influences behavioural intention. Cognitive risk perception has a direct and significant negative impact on attitudes, perceived behavioural control and subjective norms;however, affective risk perception only has a significant negative impact on subjective norms. Additionally, there is a positive correlation between the two, with both indirectly and negatively influencing the behavioural intentions of the elderly's bus travel. This study can provide a basis for the formulation and improvement of pandemic prevention measures for bus travel during the normalisation stage of pandemic prevention and control to safeguard the elderly's bus travel rights.
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SARS-CoV-2 continues to accumulate mutations to evade immunity, leading to breakthrough infections after vaccination. How researchers can anticipate the evolutionary trajectory of the virus in advance in the design of next-generation vaccines requires investigation. Here, we performed a comprehensive study of 11,650,487 SARS-CoV-2 sequences, which revealed that the SARS-CoV-2 spike (S) protein evolved not randomly but into directional paths of either high infectivity plus low immune resistance or low infectivity plus high immune resistance. The viral infectivity and immune resistance of variants are generally incompatible, except for limited variants such as Beta and Kappa. The Omicron variant has the highest immune resistance but showed high infectivity in only one of the tested cell lines. To provide cross-clade immunity against variants that undergo diverse evolutionary pathways, we designed a new pan-vaccine antigen (Span). Span was designed by analyzing the homology of 2675 SARS-CoV-2 S protein sequences from the NCBI database before the Delta variant emerged. The refined Span protein harbors high-frequency residues at given positions that reflect cross-clade generality in sequence evolution. Compared with a prototype wild-type (Swt) vaccine, which, when administered to mice, induced serum with decreased neutralization activity against emerging variants, Span vaccination of mice elicited broad immunity to a wide range of variants, including those that emerged after our design. Moreover, vaccinating mice with a heterologous Span booster conferred complete protection against lethal infection with the Omicron variant. Our results highlight the importance and feasibility of a universal vaccine to fight against SARS-CoV-2 antigenic drift.
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Covid-19 has become a world pandemic for years. With the appearance of mutations, immune escape has become a problem, reducing the effectiveness of vaccines and antibodies. To reveal the mechanism of immune escape, we analyze the geometrical properties of the receptor-binding domain in the SARS-CoV-2 spike protein, which plays a vital role in the immune reaction. Several important variants are taken as examples, and the wild type model is prepared as a reference. The computational method is applied to simulate the behaviors of the models, and alpha shape algorithm is employed to extract geometrical data of the protein surface. Average moving distance of the surface atoms is used to quantify their activity. Our results show that the mutations changed the properties of the protein. The variants have different distributions of active sites, which may change the specific antigenicity and influence the binding abilities of drugs and antibodies. This study explains the mechanism of immune escape of SARS-CoV-2, and provides a geometrical method to find potential new target sites for the design of drugs and vaccines. © 2022 IEEE.
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Vaccination is a major achievement that has become an effective prevention strategy against infectious diseases and active control of emerging pathogens worldwide. In response to the coronavirus disease 2019 (COVID-19) pandemic, several diverse vaccines against severe acute respiratory syndrome coronavirus 2 have been developed and deployed for use in a large number of individuals, and have been reported to protect against symptomatic COVID-19 cases and deaths. However, the application of vaccines has a series of limitations, including protective failure for variants of concern, unavailability of individuals due to immune deficiency, and the disappearance of immune protection for increasing infections in vaccinated individuals. These aspects raise the question of how to modulate the immune system that contributes to the COVID-19 vaccine protective effects. Herbal medicines are widely used for their immune regulatory abilities in clinics. More attractively, herbal medicines have been well accepted for their positive role in the COVID-19 prevention and suppression through regulation of the immune system. This review presents a brief overview of the strategy of COVID-19 vaccination and the response of the immune system to vaccines, the regulatory effects and mechanisms of herbal medicine in immune-related macrophages, natural killer cells, dendritic cells, and lymphocytes T and B cells, and how they help vaccines work. Later in the article, the potential role and application of herbal medicines in the most recent COVID-19 vaccination are discussed. This article provides new insights into herbal medicines as promising alternative supplements that may benefit from COVID-19 vaccination.Graphical :: http://links.lww.com/AHM/A31.
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The emerging Corona virus Disease 2019 (COVID-19) pandemic poses a massive crisis to global public health. World Health Organization (WHO) declared the global pandemic of COVID-19 on March 11, 2020. The progress of 2019- nCoV vaccines cover nearly all forms of current vaccine research, including inactivated vaccine, recombinant protein vaccine, viral vector-based vaccine, nucleic-acid vaccine and live attenuated vaccine, as well as the vaccine design based on novel concepts such as reverse vaccinology and vaccinomics. This article reviews the COVID-19 vaccines in development and clinical trials as well as the challenge in vaccine development. Copyright © 2021 Changchun Institute of Biological Products. All rights reserved.
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Aim Human TMPRSS2 is a transmembrane serine protease.In this paper, the structure and function of the protein were systematically analyzed by bioinformatics, the codon was optimized and the pro- karvotie expression vector was constructed to explore the molecular mechanism of SARS-CoV-2 infecting host cells.Methods The recombinant expression vector pET-22b-TMPRSS2 was generated by molecular cloning technology.The homology, functional sites, subcellular localization, three-dimensional structure and evolutionary characteristics of TMPRSS2 protein were systematically analyzed by using analytical tools such as Protparam, NetPhos3.1, Blast, Clustal X2 and MEGA7.0.Results The prokarvotic expression plas- mid was constructed correctly;TMPRSS2 belongs to medium molecular weight protein, which is composed of 492 amino acid residues.The theoretical isoelectric point is 8.12, the molecular extinction coefficient is 118 145 L * mol~1 * cm"1 , and the half-life is 30 h;TMPRSS2 has 15 potential glycosylation sites and 49 possible phosphorylation sites.It is a transmembrane hydrophilie protein without signal sequenee.In addition, the protein has 13 potential B-cell epitopes and 7 T-eell epitopes.Seeondarv structure analysis showed that random coil accounted for the highest proportion of TMPRSS2 protein ( 0.453 3) , followed by extended strand (0.252 0).Sequence comparison and evolutionary analysis showed that the highest sequence consistency and closest genetic relationship with human TMPRSS2 was Pan troglodytes, followed by gorilla.Conclusions Human-derived TMPRSS2 protein is ev- olutionarilv conserved and functionally important.Hie results of this study can help to reveal the structure and mechanism of action of TMPRSS2 protein, provide ideas for the diagnosis and treatment of COYID-19, and accelerate the research and development process of new drugs targeting TMPRSS2 protein. Copyright © 2022 Publication Centre of Anhui Medical University. All rights reserved.
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For rapid discovery of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro) inhibitors from a natural product library, a novel colorimetric screening assay was developed. According to the colorimetric principle, the synthetic peptide TSAVLQ-para-nitroanilide (pNA) was used as the Mpro hydrolysis substrate. Subsequently, the working concentration of pNA substrate, Mpro working concentration, hydrolysis time and DMSO tolerance were optimized for the development of a simple and robust colorimetric screening assay. Through these systematic optimizations, we selected 0.4 mumol.L-1 Mpro and 100 mumol.L-1 pNA substrate as the optimal working concentrations in this colorimetric screening assay, and a high Z' factor of 0.9 was achieved. Using this screening assay, natural product ginkgolic acid C13: 0 (GA13: 0) was identified as a novel competitive Mpro inhibitor in vitro. Taken together, we have successfully developed a simple and optimized colorimetric screening assay, which will be vital for the discovery of novel SARS-CoV-2 Mpro inhibitors. Copyright © 2022, Chinese Pharmaceutical Association. All rights reserved.
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Background: Lung protective ventilation plays a crucial role in the management of patients with COVID-19 ARDS treated with VV-ECMO. We hypothesized that increasingly protective ventilator settings may be associated with improved lung recovery by reducing ventilator induced lung injury. Method(s): We performed a retrospective cohort study of all patients treated with VV-ECMO for COVID-19 at NYU Langone Medical Center from March 2020 to June 2020. Ventilator data including tidal volume (cc/ kg predicted body weight), peak airway pressure, PEEP, Driving pressure (DP), Respiratory Rate, FiO2, lung compliance, and mechanical power were obtained. Pulmonary function test (PFT) results, 6-minute walk test results, and quantitative chest CT scores were obtained from the first outpatient follow up assessment. Bivariate and multivariate analysis correlating ventilator data with lung function and CT outcomes was performed. Result(s): 30 COVID-19 patients were treated with VV-ECMO during the study period, of which 26 survived without lung transplantation and 12 completed follow up assessment at a median of 106 days post ECMO decannulation. Multivariate LASSO regression model results;FEV1: DP (beta=-5.535), Respiratory Rate (beta=-0.370), compliance (beta=0.467), FVC: DP (beta=-4.08), compliance (beta=0.875), preECMO tidal volume (beta=-0.0008), TLC: DP (beta=-4.518), ECMO sweep (beta=-0.598), DLCO: peak airway presure (beta=-1.836), 6MWT distance: compliance (beta=1.436), Chest CT total opacity score: DP(beta=-0.60), preECMO tidal volume(beta=-0.0033). Conclusion(s): Driving pressure and peak airway pressure during VV-ECMO had the strongest associations with improved short-term follow up lung volumes, DLCO, and chest CT outcomes in VV-ECMO treated COVID-19 survivors.
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As of November 2021, there were 21 million confirmed active cases of COVID-19, including 77,016 patients in serious or critical condition (virusncov.com). However, there are no effective oral drugs for the treatment of severe COVID 19 patients. We here discuss the mechanism of action for Proxalutaminde to treat mild, moderate and severe COVID-19 Patients. Cellular entry and infection of SARS-CoV-2 virus are mediated by two key proteins in host cells, angiotensin converting enzyme 2 (ACE2), a host transmembrane protein, providing the binding sites for SARS-CoV-2 on the host cell surface, and transmembrane protease serine 2 protein (TMPRSS2), priming the S protein of SARS-Cov-2 to facilitate the viral entry into the host cells. Both ACE2 and TMPRSS2 proteins are regulated by androgen receptor (AR) signaling. Previously, Proxalutamide has been reported to downregulate the expression of ACE2 and TMPRSS2 in cells derived from prostate, lung cancer and normal lung epithelial cells. In this study, we demonstrate that Proxalutamide inhibited the infection of SARS-COV-2 wild type, alpha and delta variants, with IC50s of 69, 48 and 39 nM, respectively. Moreover, Proxalutamide reduced SARS-COV-2 viral load in outpatients with COVID-19 (82% viral RT-PCR negative rate in active group vs. 31% in placebo group after treatment for 7 days (p-value<0.0001). Severe COVID-19 disease leads to cytokine storm resulting in pulmonary inflammation and extensive damage in lung and other organs. Anti-inflammatory drugs, including Baricitinib and dexamethasone, have shown limited clinical benefit for hospitalized COVID-19 patients. Therefore, more effective drugs are in urgent need for patients suffering from severe COVID-19. Recently, Proxalutamide has been reported to reduce the mortality rate (HR=0.16) and lung injury (by 57%, active drug vs placebo groups) in hospitalized patients with COVID-19 in an IIT phase III study. We presented here the mechanism of action of Proxalutamide for targeting cytokine storm in severe COVID-19 patients. Proxalutamide was demonstrated to activate nuclear factor erythroid 2-related factor 2 (Nrf2) in macrophages, which stimulates the antioxidant response element (ARE) for reducing cytokine storm-induced organ damage in COVID-19. In addition, Proxalutamide inhibited TNF alpha and IL-6 expression and blocked INF gamma signaling by downregulating STAT1 expression in immune cells. Importantly, Proxalutamide reduced inflammatory cells in lungs in a Poly (I:C), pseudoviral induced-lung injury animal models. Further, Proxalutamide decreased C-reactive protein, D-Dimer and improved lymphocyte count, biomarkers for COVID-19 progression in clinical studies. Together, these results provide a strong rationale for the treatment of severe COVID-19 patients with Proxalutamide.
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The pandemic of coronavirus disease 2019 (COVID-19) is rapidly spreading all over the world. In order to reduce the workload of doctors, chest X-ray (CXR) and chest computed tomography (CT) scans are playing a major role in the detection and following-up of COVID-19 symptoms. Artificial intelligence (AI) technology based on machine learning and deep learning has significantly upgraded recently medical image screening tools, therefore, medical specialists can make clinical decisions more efficiently on COVID-19 infection cases, providing the best protection to patients as soon as possible. This paper tries to cover the latest progress of automated medical imaging diagnosis techniques involved with COVID-19, including image acquisition, segmentation, diagnosis, and follow-up. This paper focuses on the combination of X-ray, CT scan with AI, especially the deep-learning technique, all of which can be widely used in the frontline hospitals to fight against COVID-19. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.
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Background: Symptoms reduction is a crucial outcome to be considered when testing novel treatments for COVID-19. The goal was to assess the impact of casirivimab+imdevimab (cas+imd) dose/exposure on the trajectory and resolution time of symptoms in outpatients with COVID-19. Methods: Analysis used data from the COV-2067 trial (NCT04425629). Cas+imd was administered intravenously (total dose 1.2 to 8 g). Symptoms data were collected using SE-C19, a patient-reported survey developed de novo to assess the symptomatic course of COVID-19. Based on patients' responses on SE-C19, a Rasch analysis was used to derive a latent score to infer their overall underlying symptom severity. A direct response model was fitted to the latent score-time data to quantify the effects of dose/exposure, demographic and clinical characteristics on latent symptom trajectory. Symptoms resolution time was defined as time from randomization to the 1st day during which the patient scored "no symptom". Several parametric models were tested as structural model, assuming a known distribution, eg, exponential or Weibull, for time to symptoms resolution data. Risk variables (eg, binary treatment or categorical dose levels, exposure metrics, baseline demographic, clinical, and biological characteristics) were tested as covariates using a proportional hazard model. Results: Results from the direct response model suggest that each dose, as compared to placebo, remarkably reduced IT50 (time taken to achieve half of the maximal response of reducing symptom) by ∼40%. By excluding data from placebo arm, none of the tested doses or predicted exposures, were significant covariates on any of the model parameters. Results from the parametric regression analysis further confirmed that cas+imd (HR=1.25) is a major factor shortening the symptoms resolution time in a dose-and exposure-independent manner. Males (HR=1.13) have a shorter symptoms resolution time. Older age (HR=0.991), higher BMI (HR=0.988), and more severe baseline symptoms (HR=0.783 for moderate and 0.589 for severe) significantly contribute to longer symptoms resolution time. Conclusion: Treatment with cas+imd (1.2 g or above), rapidly resolved symptoms in outpatients in a dose-and exposure-independent manner as indicated by a direct response model using derived latent score and further confirmed by a survival analysis using time to symptoms resolution. In addition, symptom severity, age, BMI, sex were major risk factors affecting the symptoms resolution time.
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Background: Casirivimab+imdevimab (hereinafter referred to as drug) remains vital in reducing hospitalization/death by 70% when administered early in the course of the infection. Our aim was to illustrate the mechanism of drug action in vivo and determine the magnitude of antiviral efficacy of various dose regimens given to outpatients with COVID-19, evaluating the presence of SARS-CoV-2 sero-antibody and ≥1 high-risk factor for developing severe COVID-19 illness as predictors of viral kinetics. Methods: Analysis data came from 2 clinical studies in SARS-CoV-2 infected outpatients with no or ≥1 risk factor for severe COVID-19 (NCT04425629 and NCT04666441), who received single dose of placebo or drug IV (300mg to 8g) or SC (600mg to 1.2g), had assessed viral load in nasopharyngeal swab and drug concentrations in serum (N=4500). The median number of viral load assessments per patient was 5 (range 1-8) within up to 14 days of follow-up time. Drug concentrations were predicted using the individual pharmacokinetic parameters yielded by a population model. The median patient age was 42 years, with similar proportion of males and females. The median viral load at baseline was 6.79 log10 copies/mL, and the median time of symptom onset was 3 days before study baseline. A standard target cell-limited model was used to estimate the time of infection and reconstruct viral kinetic profiles. Various relationships between exposure and resulting antiviral response were evaluated, where the drug could block de novo infection, increase the elimination rate of infected cells, or reduce viral production from infected cells. Results: The results support that the main mechanism of drug action is blocking de novo infection with an estimated decrease in the infectivity rate of 96.6%, for all dose regimens evaluated herein. High-risk factor for severe COVID-19 and baseline sero-antibody-positive/other status were associated with a 4.71% decrease and a 4.96% increase in the elimination rate of infected cells, respectively. The estimated median and 95th percentile of time to viral clearance (ie, viral count reaches below assay quantification limit) were 1.4 and 3.4 days shorter in drug vs placebo (median 10.6 vs 12.0 days, and 95th percentile 15.2 vs 18.6 days). Conclusion: All IV and SC casirivimab+imdevimab dose regimens evaluated herein showed similar near-maximal antiviral activity by blocking de novo infection;hence, shortening the time to virus clearance.
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The Corona Virus Disease 2019 (COVID-19) epidemic is a sudden public health crisis, known as an "International Emergency of Public Health Event". This study uses the bottom-up characteristics of multi-agents to construct multi-agent simulation models for COVID-19 prevention and control. The development trend of the epidemic situation under the condition that the government adopts different prevention and control measures is studied, and on this basis, the influence of temperature on the spread of the virus is discussed. The simulation results show that the multi-agent modeling method can effectively capture the emergence of complex systems. The evaluation of the effects of single measures and multiple interventions will help determine key prevention and control strategies and provide important experience and scientific basis for future epidemic prevention and control. © 2022 IEEE.
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The emerging Corona virus Disease 2019 (COVID-19) pandemic poses a massive crisis to global public health. World Health Organization (WHO) declared the global pandemic of COVID-19 on March 11, 2020. The progress of 2019- nCoV vaccines cover nearly all forms of current vaccine research, including inactivated vaccine, recombinant protein vaccine, viral vector-based vaccine, nucleic-acid vaccine and live attenuated vaccine, as well as the vaccine design based on novel concepts such as reverse vaccinology and vaccinomics. This article reviews the COVID-19 vaccines in de¬velopment and clinical trials as well as the challenge in vaccine development.
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Jiedu Huoxue Decoction (JHD), a recommended traditional prescription for patients with severe COVID-19, has appeared in the treatment protocols in China. Based on bioinformatics and computational chemistry methods, including molecular docking, molecular dynamics (MD) simulation, and Molecular Mechanics Generalized Born Surface Area (MM/GBSA) calculation, we aimed to reveal the mechanism of JHD in treating severe COVID-19. The compounds in JHD were obtained and screened on TCMSP, SwissADME, and ADMETLab platforms. The compound targets were obtained from TCMSP and STITCH, while COVID-19 targets were obtained from Genecards and NCBI. The protein-protein interaction network was constructed by using STRING. Gene Ontology (GO) and KEGG enrichment were performed with ClueGO and R language. AutoDock vina was employed for molecular docking. 100 ns MD simulation of the optimal docking complex was carried out with AmberTools 20. A total of 84 compounds and 29 potential targets of JHD for COVID-19 were collected. The key phytochemicals included quercetin, luteolin, β-sitosterol, puerarin, stigmasterol, kaempferol, and wogonin, which could regulate the immune system. The hub genes included IL6, IL10, VEGFA, IL1B, CCL2, HMOX1, DPP4, and ACE2. ACE2 and DPP4 were related to SARS-CoV-2 entering cells. GO and KEGG analysis showed that JHD could intervene in cytokine storm and endothelial proliferation and migration related to thrombosis. The molecular docking, 100 ns MD simulation, and MM/GBSA calculation confirmed that targets enriched in the COVID-19 pathway had high affinities with related compounds, and the conformations of the puerarin-ACE2, quercetin-EGFR, luteolin-EGFR, and quercetin-IL1B complexes were stable. In a word, JHD could treat COVID-19 by intervening in cytokine storm, thrombosis, and the entry of SARS-CoV-2, while regulating the immune system. These mechanisms were consistent with JHD's therapeutic concept of “detoxification” and “promoting blood circulation and removing blood stasis” in treating COVID-19. The research provides a theoretical basis for the development and application of JHD. © The Author(s) 2022.
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Multi-Agent System (MAS) is an important branch of artificial intelligence research. This study uses the bottom-up characteristics of multi-agents to construct multi-agent simulation models for Corona Virus Disease 2019 (COVID-19) virus prevention and control based on different age groups. The development of the epidemic and the infection of residents of all ages under different prevention and control measures issued by the government were studied. The simulation results proved that the multi-agent modeling method could effectively capture the emergence of complex systems. Its experimental conclusions provided a basis for predicting the development of the epidemic and provide scientific support for government decision-making. © 2021 IEEE.