Exploring the mechanism of action of licorice in the treatment of COVID-19 through bioinformatics analysis and molecular dynamics simulation.

Purpose: The rapid worldwide spread of Corona Virus Disease 2019 (COVID-19) has become not only a global challenge, but also a lack of effective clinical treatments. Studies have shown that licorice can significantly improve clinical symptoms such as fever, dry cough and shortness of breath in COVID-19 patients with no significant adverse effects. However, there is still a lack of in-depth analysis of the specific active ingredients of licorice in the treatment of COVID-19 and its mechanism of action. Therefore, we used molecular docking and molecular dynamics to explore the mechanism of action of licorice in the treatment of COVID-19. Methods: We used bioinformatics to screen active pharmaceutical ingredients and potential targets, the disease-core gene target-drug network was established and molecular docking was used for verification. Molecular dynamics simulations were carried out to verify that active ingredients were stably combined with protein targets. The supercomputer platform was used to measure and analyze stability of protein targets at the residue level, solvent accessible surface area, number of hydrogen bonds, radius of gyration and binding free energy. Results: Licorice had 255 gene targets, COVID-19 had 4,628 gene targets, the intersection gene targets were 101. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene ontology (GO) analysis showed that licorice played an important role mainly through the signaling pathways of inflammatory factors and oxidative stress. Molecular docking showed that Glycyrol, Phaseol and Glyasperin F in licorice may playe a role in treating COVID-19 by acting on STAT3, IL2RA, MMP1, and CXCL8. Molecular dynamics were used to demonstrate and analyze the binding stability of active ingredients to protein targets. Conclusion: This study found that Phaseol in licorice may reduce inflammatory cell activation and inflammatory response by inhibiting the activation of CXCL8 and IL2RA; Glycyrol may regulate cell proliferation and survival by acting on STAT3. Glyasperin F may regulate cell growth by inhibiting the activation of MMP1, thus reducing tissue damage and cell death caused by excessive inflammatory response and promoting the growth of new tissues. Therefore, licorice is proposed as an effective candidate for the treatment of COVID-19 through STAT3, IL2RA, MMP1, and CXCL8.

Molecular docking and molecular dynamics study Lianhua Qingwen granules (LHQW) treats COVID-19 by inhibiting inflammatory response and regulating cell survival.

Purpose: 2019 Coronavirus disease (COVID-19) is endangering health of populations worldwide. Latest research has proved that Lianhua Qingwen granules (LHQW) can reduce tissue damage caused by inflammatory reactions and relieve patients' clinical symptoms. However, the mechanism of LHQW treats COVID-19 is currently lacking. Therefore, we employed computer simulations to investigate the mechanism of LHQW treats COVID-19 by modulating inflammatory response. Methods: We employed bioinformatics to screen active ingredients in LHQW and intersection gene targets. PPI, GO and KEGG was used to analyze relationship of intersection gene targets. Molecular dynamics simulations validated the binding stability of active ingredients and target proteins. Binding free energy, radius of gyration and the solvent accessible surface area were analyzed by supercomputer platform. Results: COVID-19 had 4628 gene targets, LHQW had 1409 gene targets, intersection gene targets were 415. Bioinformatics analysis showed that intersection targets were closely related to inflammation and immunomodulatory. Molecular docking suggested that active ingredients (including: licopyranocoumarin, Glycyrol and 3-3-Oxopropanoic acid) in LHQW played a role in treating COVID-19 by acting on CSF2, CXCL8, CCR5, NLRP3, IFNG and TNF. Molecular dynamics was used to prove the binding stability of active ingredients and protein targets. Conclusion: The mechanism of active ingredients in LHQW treats COVID-19 was investigated by computer simulations. We found that active ingredients in LHQW not only reduce cell damage and tissue destruction by inhibiting the inflammatory response through CSF2, CXCL8, CCR5 and IFNG, but also regulate cell survival and growth through NLRP3 and TNF thereby reducing apoptosis.

Mechanism of N-0385 blocking SARS-CoV-2 to treat COVID-19 based on molecular docking and molecular dynamics.

Purpose: 2019 Coronavirus disease (COVID-19) has caused millions of confirmed cases and deaths worldwide. TMPRSS2-mediated hydrolysis and maturation of spike protein is essential for SARS-CoV-2 infection in vivo. The latest research found that a TMPRSS2 inhibitor called N-0385 could effectively prevent the infection of the SARS-CoV-2 and its variants. However, it is not clear about the mechanism of N-0385 treatment COVID-19. Therefore, this study used computer simulations to investigate the mechanism of N-0385 treatment COVID-19 by impeding SARS-CoV-2 infection. Methods: The GeneCards database was used to search disease gene targets, core targets were analyzed by PPI, GO and KEGG. Molecular docking and molecular dynamics were used to validate and analyze the binding stability of small molecule N-0385 to target proteins. The supercomputer platform was used to simulate and analyze the number of hydrogen bonds, binding free energy, stability of protein targets at the residue level, radius of gyration and solvent accessible surface area. Results: There were 4,600 COVID-19 gene targets from GeneCards database. PPI, GO and KEGG analysis indicated that signaling pathways of immune response and inflammation played crucial roles in COVID-19. Molecular docking showed that N-0385 could block SARS-CoV-2 infection and treat COVID-19 by acting on ACE2, TMPRSS2 and NLRP3. Molecular dynamics was used to demonstrate that the small molecule N-0385 could form very stable bindings with TMPRSS2 and TLR7. Conclusion: The mechanism of N-0385 treatment COVID-19 was investigated by molecular docking and molecular dynamics simulation. We speculated that N-0385 may not only inhibit SARS-CoV-2 invasion directly by acting on TMPRSS2, ACE2 and DPP4, but also inhibit the immune recognition process and inflammatory response by regulating TLR7, NLRP3 and IL-10 to prevent SARS-CoV-2 invasion. Therefore, these results suggested that N-0385 may act through multiple targets to reduce SARS-CoV-2 infection and damage caused by inflammatory responses.

Mechanism of N-0385 blocking SARS-CoV-2 to treat COVID-19 based on molecular docking and molecular dynamics

Purpose 2019 Coronavirus disease (COVID-19) has caused millions of confirmed cases and deaths worldwide. TMPRSS2-mediated hydrolysis and maturation of spike protein is essential for SARS-CoV-2 infection in vivo. The latest research found that a TMPRSS2 inhibitor called N-0385 could effectively prevent the infection of the SARS-CoV-2 and its variants. However, it is not clear about the mechanism of N-0385 treatment COVID-19. Therefore, this study used computer simulations to investigate the mechanism of N-0385 treatment COVID-19 by impeding SARS-CoV-2 infection. Methods The GeneCards database was used to search disease gene targets, core targets were analyzed by PPI, GO and KEGG. Molecular docking and molecular dynamics were used to validate and analyze the binding stability of small molecule N-0385 to target proteins. The supercomputer platform was used to simulate and analyze the number of hydrogen bonds, binding free energy, stability of protein targets at the residue level, radius of gyration and solvent accessible surface area. Results There were 4,600 COVID-19 gene targets from GeneCards database. PPI, GO and KEGG analysis indicated that signaling pathways of immune response and inflammation played crucial roles in COVID-19. Molecular docking showed that N-0385 could block SARS-CoV-2 infection and treat COVID-19 by acting on ACE2, TMPRSS2 and NLRP3. Molecular dynamics was used to demonstrate that the small molecule N-0385 could form very stable bindings with TMPRSS2 and TLR7. Conclusion The mechanism of N-0385 treatment COVID-19 was investigated by molecular docking and molecular dynamics simulation. We speculated that N-0385 may not only inhibit SARS-CoV-2 invasion directly by acting on TMPRSS2, ACE2 and DPP4, but also inhibit the immune recognition process and inflammatory response by regulating TLR7, NLRP3 and IL-10 to prevent SARS-CoV-2 invasion. Therefore, these results suggested that N-0385 may act through multiple targets to reduce SARS-CoV-2 infection and damage caused by inflammatory responses.

An allocation model for emergency medical services based on integrated healthcare during an epidemic

Enhanced virus control and patient treatment outcomes during an epidemic requires flexible and efficient medical services. This research explores an epidemic medical service allocation model from an integrated healthcare perspective, aiming to enhance the overall regional emergency medical service capability based on collaborative medical treatment. The study is based on COVID-19 medical services and its main treatment stages, and resource allocation models are constructed for the allocation of multiple medical services. The model addresses the dispersed medical service resources and demands in a certain region, and realizes the division of labor and resource sharing among medical institutions from the perspectives of distance, cost, and fairness with the advantage of integrated healthcare. We design examples in the context of COVID-19 epidemic and verify the validity and applicability of the model under different phases. This paper provides reference to the research and practice of achieving collaborative medical treatment between multiple medical institutions.

Exploring the mechanism of action of licorice in the treatment of COVID-19 through bioinformatics analysis and molecular dynamics simulation

The mechanisms analysis of licorice in the treatment of COVID-19.

Exploring the mechanism of action of Xuanfei Baidu granule (XFBD) in the treatment of COVID-19 based on molecular docking and molecular dynamics.

Purpose: The Corona Virus Disease 2019 (COVID-19) pandemic has become a challenge of world. The latest research has proved that Xuanfei Baidu granule (XFBD) significantly improved patient's clinical symptoms, the compound drug improves immunity by increasing the number of white blood cells and lymphocytes, and exerts anti-inflammatory effects. However, the analysis of the effective monomer components of XFBD and its mechanism of action in the treatment of COVID-19 is currently lacking. Therefore, this study used computer simulation to study the effective monomer components of XFBD and its therapeutic mechanism. Methods: We screened out the key active ingredients in XFBD through TCMSP database. Besides GeneCards database was used to search disease gene targets and screen intersection gene targets. The intersection gene targets were analyzed by GO and KEGG. The disease-core gene target-drug network was analyzed and molecular docking was used for verification. Molecular dynamics simulation verification was carried out to combine the active ingredient and the target with a stable combination. The supercomputer platform was used to measure and analyze the number of hydrogen bonds, the binding free energy, the stability of protein target at the residue level, the solvent accessible surface area, and the radius of gyration. Results: XFBD had 1308 gene targets, COVID-19 had 4600 gene targets, the intersection gene targets were 548. GO and KEGG analysis showed that XFBD played a vital role by the signaling pathways of immune response and inflammation. Molecular docking showed that I-SPD, Pachypodol and Vestitol in XFBD played a role in treating COVID-19 by acting on NLRP3, CSF2, and relieve the clinical symptoms of SARS-CoV-2 infection. Molecular dynamics was used to prove the binding stability of active ingredients and protein targets, CSF2/I-SPD combination has the strongest binding energy. Conclusion: For the first time, it was found that the important active chemical components in XFBD, such as I-SPD, Pachypodol and Vestitol, reduce inflammatory response and apoptosis by inhibiting the activation of NLRP3, and reduce the production of inflammatory factors and chemotaxis of inflammatory cells by inhibiting the activation of CSF2. Therefore, XFBD can effectively alleviate the clinical symptoms of COVID-19 through NLRP3 and CSF2.

Which Matters More in Fighting COVID-19-Government Policy or Community Participation?

Objective: As a heavily populated megacity, Shanghai faces major epidemic risks. However, Shanghai's control of COVID-19 has been successful owing to both the strict government policy and wide community participation. Here, we investigated the impact of these stakeholders and examined who played a major role across different epidemic stages. Design: We extended the classic susceptible-exposed-infectious-recovered (SEIR) model considering the heterogeneous contact structure in four social sceneries, i.e., school, workplace, public entertainment venues, and neighborhood community, which could reflect the impact of lockdown policy and wide participation of residents happened at the community level. Result: The simulation results showed that without lockdown policy and only with community participation, the daily new confirmed cases would gradually increase to more than 7,000 [292/1,000,000] at the end of Sep. However, without community participation and only with a lockdown policy, the daily new confirmed cases sharply decreased to 30 [1.2/1,000,000] at the end of the 1st month and remained low for several months. However, when a lockdown policy was gradually lifted, the new confirmed cases increased exponentially, eventually reaching more than 17,000 [708/1,000,000]. Therefore, a government lockdown policy was necessary for the rapid control of COVID-19 during the outbreak stage while community participation is more important in keeping the number of new confirmed cases low during the reopening stage. Conclusion: Government lockdown policy and community participation play different roles in the control of COVID-19 at different stages of the epidemic: although the government played a leading role in setting up policies, the broader participation of community fever clinics (CFCs) and the general public were especially crucial in winning the battle against COVID-19 in the long run.

Asymmetric causality of economic policy uncertainty and oil volatility index on time-varying nexus of the clean energy, carbon and green bond

Vigorously developing the clean energy industry, improving the carbon allowance trading scheme, and issuing green bonds can effectively reduce emissions. To this end, this study aims to investigate the time-varying connections among clean energy, carbon, and green bonds through the DCC-MIDAS model, thus providing a bird's-eye view of their dynamic nexus. A non-parametric causality-in-quantile method is also employed to adequately capture the asymmetric causation of economic policy uncertainty (EPU) and the oil volatility index (OVX) on cross-asset correlations under different market conditions. The primary results imply complicated links among these three assets, with alternating positive and negative trends throughout the sample period. Notably, turbulence in financial markets can exacerbate network connectivity, particularly during the COVID-19 pandemic. Moreover, EPU and OVX can serve as strong predictors across various distributions of cross-market connections, which indicates that co-movement between assets is vulnerable to exogenous risks, especially under normal market conditions. Our findings have broader implications for market participants and policymakers.

Research on the mechanism of berberine in the treatment of COVID-19 pneumonia pulmonary fibrosis using network pharmacology and molecular docking.

Purpose Pulmonary fibrosis caused by COVID-19 pneumonia is a serious complication of COVID-19 infection, there is a lack of effective treatment methods clinically. This article explored the mechanism of action of berberine in the treatment of COVID-19 (Corona Virus Disease 2019, COVID-19) pneumonia pulmonary fibrosis with the help of the network pharmacology and molecular docking. Methods We predicted the role of berberine protein targets with the Pharmmapper database and the 3D structure of berberine in the Pubchem database. And GeneCards database was used in order to search disease target genes and screen common target genes. Then we used STRING web to construct PPI interaction network of common target protein. The common target genes were analyzed by GO and KEGG by DAVID database. The disease-core target gene-drug network was established and molecular docking was used for prediction. We also analyzed the binding free energy and simulates molecular dynamics of complexes. Results Berberine had 250 gene targets, COVID-19 pneumonia pulmonary fibrosis had 191 gene targets, the intersection of which was 23 in common gene targets. Molecular docking showed that berberine was associated with CCl2, IL-6, STAT3 and TNF-α. GO and KEGG analysis reveals that berberine mainly plays a vital role by the signaling pathways of influenza, inflammation and immune response. Conclusion Berberine acts on TNF-α, STAT3, IL-6, CCL2 and other targets to inhibit inflammation and the activation of fibrocytes to achieve the purpose of treating COVID-19 pneumonia pulmonary fibrosis.

Understanding the antecedents of mobile social media acceptance during the public health crisis maintenance stage

Mobile social media experienced explosive growth during the COVID-19 pandemic. To understand the underlying causes of users' acceptance towards mobile social media, this study draws upon the uses and gratifications theory, media dependency theory, and related literature of individuals' perceived appraisal (perceived trust, perceived benefits, and perceived risk) to explore the determinants that influenced mobile social media acceptance during the public health crisis maintenance stage. Data were obtained from 724 mobile social media users in China through an online paid questionnaire survey platform. The results revealed that perceived trust and perceived benefits positively affected information seeking and information sharing, which jointly influenced an individual's intention to use mobile social media during the public health crisis maintenance stage. Social media dependency also positively affected mobile social media users' usage intentions. However, perceived risk negatively influenced information seeking and information sharing. The results of this study offer valuable theoretical and practical implications for crisis communication researchers, emergency management practitioners, and mobile social media platforms.

Novel coronavirus pneumonia lesion segmentation in CT images (preprint)

Background: The 2019 novel coronavirus disease (COVID-19) has been spread widely in the world, causing a huge threat to people's living environment. Objective: Under computed tomography (CT) imaging, the structure features of COVID-19 lesions are complicated and varied greatly in different cases. To accurately locate COVID-19 lesions and assist doctors to make the best diagnosis and treatment plan, a deep-supervised ensemble learning network is presented for COVID-19 lesion segmentation in CT images. Methods: Considering the fact that a large number of COVID-19 CT images and the corresponding lesion annotations are difficult to obtained, a transfer learning strategy is employed to make up for the shortcoming and alleviate the overfitting problem. Based on the reality that traditional single deep learning framework is difficult to extract COVID-19 lesion features effectively, which may cause some lesions to be undetected. To overcome the problem, a deep-supervised ensemble learning network is presented to combine with local and global features for COVID-19 lesion segmentation. Results: The performance of the proposed method was validated in experiments with a publicly available dataset. Compared with manual annotations, the proposed method acquired a high intersection over union (IoU) of 0.7279. Conclusion: A deep-supervised ensemble learning network was presented for coronavirus pneumonia lesion segmentation in CT images. The effectiveness of the proposed method was verified by visual inspection and quantitative evaluation. Experimental results shown that the proposed mehtod has a perfect performance in COVID-19 lesion segmentation.

Establishment of epidemic early warning index system and optimization of infectious disease model: Analysis on monitoring data of public health emergencies.

The ability to mitigate the damages caused by emergencies is an important symbol of the modernization of an emergency capability. When responding to emergencies, government agencies and decision makers need more information sources to estimate the possible evolution of the disaster in a more efficient manner. In this paper, an optimization model for predicting the dynamic evolution of COVID-19 is presented by combining the propagation algorithm of system dynamics with the warning indicators. By adding new parameters and taking the country as the research object, the epidemic situation in countries such as China, Japan, Korea, the United States and the United Kingdom was simulated and predicted, the impact of prevention and control measures such as effective contact coefficient on the epidemic situation was analyzed, and the effective contact coefficient of the country was analyzed. The paper strives to provide early warning of emergencies scientifically and effectively through the combination of these two technologies, and put forward feasible references for the implementation of various countermeasures. Judging from the conclusion, this study reaffirmed the importance of responding quickly to public health emergencies and formulating prevention and control policies to reduce population exposure and prevent the spread of the pandemic.

Possible posttraumatic stress disorder in Chinese frontline healthcare workers who survived COVID-19 6 months after the COVID-19 outbreak: prevalence, correlates, and symptoms.

Suffering from COVID-19 and witnessing the suffering and deaths of patients with COVID-19 may place frontline healthcare workers (HCWs) at particularly high risk for posttraumatic stress disorder (PTSD); however, few data are available on the clinical characteristics of PTSD among frontline HCWs who survived COVID-19 ("surviving HCWs" hereafter). The present study examined the prevalence, correlates, and clinical symptoms of possible PTSD in surviving HCWs 6 months after the COVID-19 outbreak in China. A total of 291 surviving HCWs and 42 age- and gender-matched COVID-19-free frontline HCWs (control group) were recruited and administered the Chinese Essen Trauma Inventory, which was used to assess the presence of possible PTSD according to DSM-IV-TR criteria. Survivors' clinical data and characteristics of exposure to COVID-19 were collected via self-report questionnaires. Surviving HCWs had significantly higher rates of possible PTSD than controls (19.9% vs. 4.8%, P = 0.017). Correlates of PTSD in survivors were ICU admission (OR = 8.73, P = 0.003), >10 respiratory symptoms during the most symptomatic period of COVID-19 (OR = 3.08, P = 0.006), the residual symptom of dizziness (OR = 2.43, P = 0.013), the residual symptom of difficult breathing (OR = 2.23, P = 0.027), life in danger due to COVID-19 (OR = 16.59, P = 0.006), and exposure to other traumatic events (OR = 2.94, P = 0.035). Less commonly seen PTSD symptoms in survivors were having nightmares about the event (34.5%), suddenly feeling like they were living through the event suddenly (25.9%), being unable to remember an important part of the event (32.8%), and overalertness (31.0%). Nearly one-fifth of the surviving HCWs had possible PTSD 6 months after the COVID-19 outbreak. Mental health services for this vulnerable population should include periodic screening for PTSD, expanded social support, and, when necessary, psychotherapy and psychopharmacological treatment.

Early Immune Responses and Prognostic Factors in Children with COVID-19: A Single-center Retrospective Analysis (preprint)

Background Early diagnostic indicators and the identification of possible progression to severe or critical COVID-19 in children  are unknown. To investigate the immune characteristics of early SARS-CoV-2 infection in children and possible key prognostic factors for early identification of critical COVID-19, a retrospective study including 121 children with COVID-19 was conducted.  Peripheral blood lymphocyte subset counts, T cell-derived cytokine concentrations, inflammatory factor concentrations, and routine blood counts were analyzed statistically at the initial presentation.  Results The T lymphocyte subset and natural killer cell counts decreased with increasing disease severity. Group III (critical cases) had a higher Th/Tc ratio than groups I and II (common and severe cases); group I had a higher B cell count than groups II and III. IL-6, IL-10, IFN-γ, SAA, and procalcitonin levels increased with disease severity. Hemoglobin concentration, and RBC and eosinophil counts decreased with disease severity. Groups II and III had significantly lower lymphocyte counts than group I. T, Th, Tc, IL-6, IL-10, RBC, and hemoglobin had relatively high contribution and area under the curve values.  Conclusions Decreased T, Th, Tc, RBC, hemoglobin and increased IL-6 and IL-10 in early SARS-CoV-2 infection in children are valuable indices for early diagnosis of disease severity.  The significantly reduced Th and Tc cells and significantly increased IL-6, IL-10, ferritin, procalcitonin, and SAA at this stage in children with critical COVID-19 may be closely associated with the systemic cytokine storm caused by immune dysregulation. 

A New System for Surveillance and Digital Contact Tracing for COVID-19: Spatiotemporal Reporting Over Network and GPS.

The current pandemic of the coronavirus disease (COVID-19) has highlighted the importance of rapid control of the transmission of infectious diseases. This is particularly important for COVID-19, where many individuals are asymptomatic or have only mild symptoms but can still spread the disease. Current systems for controlling transmission rely on patients to report their symptoms to medical professionals and be able to recall and trace all their contacts from the previous few days. This is unrealistic in the modern world. However, existing smartphone-based GPS and social media technology may provide a suitable alternative. We, therefore, developed a mini-program within the app WeChat. This analyzes data from all users and traces close contacts of all patients. This permits early tracing and quarantine of potential sources of infection. Data from the mini-program can also be merged with other data to predict epidemic trends, calculate individual and population risks, and provide recommendations for individual and population protection action. It may also improve our understanding of how the disease spreads. However, there are a number of unresolved questions about the use of smartphone data for health surveillance, including how to protect individual privacy and provide safeguards against data breaches.

From SARS to COVID-19: What we have learned about children infected with COVID-19.

INTRODUCTION: Coronaviruses, both SARS-CoV and SARS-CoV-2, first appeared in China. They have certain biological, epidemiological and pathological similarities. To date, research has shown that their genes exhibit 79% of identical sequences and the receptor-binding domain structure is also very similar. There has been extensive research performed on SARS; however, the understanding of the pathophysiological impact of coronavirus disease 2019 (COVID-19) is still limited. METHODS: This review drew upon the lessons learnt from SARS, in terms of epidemiology, clinical characteristics and pathogenesis, to further understand the features of COVID-19. RESULTS: By comparing these two diseases, it found that COVID-19 has quicker and wider transmission, obvious family agglomeration, and higher morbidity and mortality. Newborns, asymptomatic children and normal chest imaging cases emerged in COVID-19 literature. Children starting with gastrointestinal symptoms may progress to severe conditions and newborns whose mothers are infected with COVID-19 could have severe complications. The laboratory test data showed that the percentage of neutrophils and the level of LDH is higher, and the number of CD4+ and CD8+T-cells is decreased in children's COVID-19 cases. CONCLUSION: Based on these early observations, as pediatricians, this review put forward some thoughts on children's COVID-19 and gave some recommendations to contain the disease.

Updated diagnosis, treatment and prevention of COVID-19 in children: experts' consensus statement (condensed version of the second edition).

In the early February, 2020, we called up an experts' committee with more than 30 Chinese experts from 11 national medical academic organizations to formulate the first edition of consensus statement on diagnosis, treatment and prevention of coronavirus disease 2019 (COVID-19) in children, which has been published in this journal. With accumulated experiences in the diagnosis and treatment of COVID-19 in children, we have updated the consensus statement and released the second edition recently. The current version in English is a condensed version of the second edition of consensus statement on diagnosis, treatment and prevention of COVID-19 in children. In the current version, diagnosis and treatement criteria have been optimized, and early identification of severe and critical cases is highlighted. The early warning indicators for severe pediatric cases have been summarized which is utmost important for clinical practice. This version of experts consensus will be valuable for better prevention, diagnosis and treatment of COVID-19 in children worldwide.