Diosmetin alleviates acute lung injury caused by lipopolysaccharide by targeting barrier function.

Acute lung injury (ALI) is an acute and devastating disease caused by systemic inflammation e.g. patients infected with bacteria and viruses such as SARS-CoV-2 have an unacceptably high mortality rate. It has been well documented that endothelial cell damage and repair play a central role in the pathogenesis of ALI because of its barrier function. Nevertheless, the leading compounds that effectively accelerate endothelial cell repair and improve barrier dysfunction in ALI are largely unknown. In the present study, we found that diosmetin had promising characteristics to inhibit the inflammatory response and accelerate the repair of endothelial cells. Our results indicated that diosmetin accelerated wound healing and barrier repair by improving the expression of the barrier-related proteins, including zonula occludens-l (ZO-1) and occludin, in human umbilical vein endothelial cells (HUVECs) treated with lipopolysaccharide (LPS). Meanwhile, diosmetin administration significantly inhibited inflammatory response by decreasing the content of TNFα and IL-6 in the serum, alleviated lung injury by reducing lung wet/dry (W/D) ratio and histologic score, improved endothelial hyperpermeability by decreasing protein levels and neutrophil infiltration in the bronchoalveolar lavage fluid (BALF) and increasing ZO-1 and occludin expression in the lung tissues of LPS-treated mice. Mechanistically, diosmetin also mediated the expression of Rho A and ROCK1/2 in HUVECs treated with LPS, and fasudil, a Rho A inhibitor remarkably inhibited the role of diosmetin in ZO-1 and occludin proteins. All these findings of this study revealed that diosmetin can be an effective protector of lung injury and the Rho A/ROCK1/2 signal pathway plays a pivotal role in diosmetin accelerating barrier repair in ALI.

Identification of the Hub Genes and the Signaling Pathways in Human iPSC-Cardiomyocytes Infected by SARS-CoV-2.

Severe Acute Respiratory Syndrome Coronavirus Type 2 (SARS-CoV-2) is an enveloped single-stranded RNA virus that can lead to respiratory symptoms and damage many organs such as heart, kidney, intestine, brain and liver. It has not been clearly documented whether myocardial injury is caused by direct infection of cardiomyocytes, lung injury, or other unknown mechanisms. The gene expression profile of GSE150392 was obtained from the Gene Expression Omnibus (GEO) database. The processing of high-throughput sequencing data and the screening of differentially expressed genes (DEGs) were implemented by R software. The R software was employed to analyze the Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The protein-protein interaction (PPI) network of the DEGs was constructed by the STRING website. The Cytoscape software was applied for the visualization of PPI network and the identification of hub genes. The statistical analysis was performed by the GraphPad Prism software to verify the hub genes. A total of 516 up-regulated genes and 191 down-regulated genes were screened out. The top 1 enrichment items of GO in biological process (BP), Cellular Component (CC), and Molecular Function (MF) were type I interferon signaling pathway, sarcomere, and receptor ligand activity, respectively. The top 10 enrichment pathways, including TNF signaling pathway, were identified by KEGG enrichment analysis. A PPI network was established, consisting of 613 nodes and 3,993 edges. The 12 hub genes were confirmed as statistically significant, which was verified by GSE151879 dataset. In conclusion, the hub genes of human iPSC-cardiomyocytes infected with SARS-CoV-2 were identified through bioinformatics analysis, which may be used as biomarkers for further research.

COVID-19 distributes socially in China: A Bayesian spatial analysis.

PURPOSE: The ongoing coronavirus disease 2019 (COVID-19) epidemic increasingly threatens the public health security worldwide. We aimed to identify high-risk areas of COVID-19 and understand how socioeconomic factors are associated with the spatial distribution of COVID-19 in China, which may help other countries control the epidemic. METHODS: We analyzed the data of COVID-19 cases from 30 provinces in mainland China (outside of Hubei) from 16 January 2020 to 31 March 2020, considering the data of demographic, economic, health, and transportation factors. Global autocorrelation analysis and Bayesian spatial models were used to present the spatial pattern of COVID-19 and explore the relationship between COVID-19 risk and various factors. RESULTS: Global Moran's I statistics of COVID-19 incidences was 0.31 (P<0.05). The areas with a high risk of COVID-19 were mainly located in the provinces around Hubei and the provinces with a high level of economic development. The relative risk of two socioeconomic factors, the per capita consumption expenditure of households and the proportion of the migrating population from Hubei, were 1.887 [95% confidence interval (CI): 1.469~2.399] and 1.099 (95% CI: 1.053~1.148), respectively. The two factors explained up to 78.2% out of 99.7% of structured spatial variations. CONCLUSION: Our results suggested that COVID-19 risk was positively associated with the level of economic development and population movements. Blocking population movement and reducing local exposures are effective in preventing the local transmission of COVID-19.

The construction and visualization of the transmission networks for COVID-19: A potential solution for contact tracing and assessments of epidemics.

The WHO has described coronavirus disease 2019 (COVID-19) as a pandemic due to the speed and scale of its transmission. Without effective interventions, the rapidly increasing number of COVID-19 cases would greatly increase the burden of clinical treatments. Identifying the transmission sources and pathways is of vital importance to block transmission and allocate limited public health resources. According to the relationships among cases, we constructed disease transmission network graphs for the COVID-19 epidemic through a visualization technique based on individual reports of epidemiological data. We proposed an analysis strategy of the transmission network with the epidemiological data in Tianjin and Chengdu. The transmission networks showed different transmission characteristics. In Tianjin, an imported case of COVID-19 can produce an average of 2.9 secondary infections and ultimately produce as many as 4 generations of infections, with a maximum of 6 cases being generated before the imported case is identified. In Chengdu, 45 noninformative cases and 24 cases with vague exposure information made accurate information about the transmission network difficult to provide. The proposed analysis framework of visualized transmission networks can trace the transmission source and contacts, assess the current situation of transmission and prevention, and provide evidence for the global response and control of the COVID-19 pandemic.

Research Progress of Mesenchymal Stem Cell Therapy for Severe COVID-19.

Corona virus disease 2019 (COVID-19) refers to a type of pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Sixty million confirmed cases have been reported worldwide until November 29, 2020. Unfortunately, the novel coronavirus is extremely contagious and the mortality rate of severe and critically ill patients is high. Thus, there is no definite and effective treatment in clinical practice except for antiviral therapy and supportive therapy. Mesenchymal stem cells (MSCs) are not only characterized by low immunogenicity and homing but also have anti-inflammatory and immunomodulation characteristics. Furthermore, they can inhibit the occurrence and development of a cytokine storm, inhibit lung injury, and exert antipulmonary fibrosis and antioxidative stress, therefore MSC therapy is expected to become one of the effective therapies to treat severe COVID-19. This article will review the possible mechanisms of MSCs in the treatment of severe COVID-19.

Synergistic Inhibition of SARS-CoV-2 Replication using Disulfiram/Ebselen and Remdesivir (preprint)

The SARS-CoV-2 replication and transcription complex (RTC) comprising nonstructural protein (nsp) 2-16 plays crucial roles in viral replication, reducing the efficacy of broad-spectrum nucleoside analog drugs such as remdesivir and in evading innate immune responses. Most studies target a specific viral component of the RTC such as the main protease or the RNA-dependent RNA polymerase. In contrast, our strategy is to target multiple conserved domains of the RTC to prevent SARS-CoV-2 genome replication and to create a high barrier to viral resistance and/or evasion of antiviral drugs. We show that clinically-safe Zn-ejector drugs, disulfiram/ebselen, can target conserved Zn2+-sites in SARS-CoV-2 nsp13 and nsp14 and inhibit nsp13 ATPase and nsp14 exoribonuclease activities. As the SARS-CoV-2 nsp14 domain targeted by disulfiram/ebselen is involved in RNA fidelity control, our strategy allows coupling of the Zn-ejector drug with a broad-spectrum nucleoside analog that would otherwise be excised by the nsp14 proofreading domain. As proof-of-concept, we show that disulfiram/ebselen, when combined with remdesivir, can synergistically inhibit SARS-CoV-2 replication in Vero E6 cells. We present a mechanism of action and the advantages of our multi-targeting strategy, which can be applied to any type of coronavirus with conserved Zn2+-sites.

Summary of the COVID-19 epidemic and estimating the effects of emergency responses in China.

Coronavirus disease-2019 (COVID-19) pandemic has affected millions of people since December 2019. Summarizing the development of COVID-19 and assessing the effects of control measures are very critical to China and other countries. A logistic growth curve model was employed to compare the development of COVID-19 before and after the emergency response took effect. We found that the number of confirmed cases peaked 9-14 days after the first detection of an imported case, but there was a peak lag in the province where the outbreak was concentrated. Results of the growth curves indicated that the fitted cumulative confirmed cases were close to the actual observed cases, and the R2 of all models was above 0.95. The average growth rate decreased by 44.42% nationally and by 32.5% outside Hubei Province. The average growth rate in the 12 high-risk areas decreased by 29.9%. The average growth rate of cumulative confirmed cases decreased by approximately 50% after the emergency response. Areas with frequent population migration have a high risk of outbreak. The emergency response taken by the Chinese government was able to effectively control the COVID-19 outbreak. Our study provides references for other countries and regions to control the COVID-19 outbreak.

The Recommendations for the Management of Chinese Children With Epilepsy During the COVID-19 Outbreak.

The coronavirus disease (COVID-19) is the most severe public health problem facing the world currently. Social distancing and avoidance of unnecessary movements are preventive strategies that are being advocated to prevent the spread of the causative virus [severe acute respiratory syndrome (SARS)-CoV2]. It is known that epileptic children need long term treatments (antiepileptic drugs and/or immunosuppressive agents) as well as close follow up due to the nature of the disease. In addition, it is clear that epilepsy can concur with other chronic illnesses which can lower body immunity. As a result, epileptic children have high risk of acquiring this novel disease due to weak/immature immune system. Of concern, the management of children with epilepsy has become more challenging during this outbreak due to the prevention measures that are being taken. Although children with controlled seizures can be managed at home, it is challenging for pediatricians when it comes to cases with uncontrolled seizures/severe cases. To this end, we provide recommendations for the management of epileptic children at home, outpatient and inpatient settings.