The Pivotal Role of SOD1 for Prediction of COVID-19 Progression Revealed by Proteomic and Bioinformatic Strategies (preprint)

Background: Severe acute respiratory distress syndrome-associated coronavirus-2 (SARS-CoV-2) is still threatening the whole human population worldwide. Patients infected with SARS-CoV-2 present diverse symptoms regarding to the severity of the disease. Determining the proteome changes associated with diverse symptoms and in different infection stages is beneficial for clinical diagnosis and management. Methods: We performed a TMT labeling proteomic study on the plasma of healthy controls and COVID-19 patients, including those with asymptomatic infection (NS), mild syndrome (MS), and severe syndrome in the early phase (SSEP) and later phase (SSLP). Bioinformatic and ELISA were used for the data analysis and identification. Findings: Hundreds of proteins were dysregulated in the plasma of COVID-19 patients including all the clinical symptoms. Bioinformatics analysis of the dysregulated proteins revealed that oxidative stress, complement activation and glycolysis-related proteins were affected after infection with SARS-CoV-2. ELISA analysis confirmed that SOD1, PRDX2 and LDHA levels were increased along with severe symptoms and did not change after recovery compared with those in healthy controls. Both GSEA and ROC analysis indicated that SOD1 could be a pivotal player in the progression of COVID-19. Interpretation: Our results indicated that plasma proteome changes differed based on symptoms and disease stages and SOD1 could be an important protein for indicating COVID-19 progression. These results may also provide new understanding for COVID-19 diagnosis and treatment. Funding: This project is supported by Shenzhen Bay Laboratory Opening Fund, Shenzhen Key Medical Discipline Construction Fund, Guangdong Natural Science Foundation, Sanming Project of Medicine in Shenzhen.Declaration of Interests: All the authors declared there are no conflicts of interest exist.Ethics Approval Statement: This research was approved by the ethics committee of the Shenzhen Center for Disease Control and Prevention [Approval number: 2020-025A].

A novel fermented Yi traditional medicine efficiently suppresses the replication of SARS-CoV-2 in vitro (preprint)

Currently, the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a worldwide epidemic, causing more than 80 million infections and more than 1.7 million deaths. The pandemic has led to the closure of enterprises and schools in many countries, resulting in serious disruption of the global economy and social activities. Remdesivir is currently approved by the FDA for the treatment of COVID-19, but the WHO declared that Remdesivir is almost ineffective against COVID-19. The research and development of vaccines has made great progress, but it will take at least several months for safe and effective vaccines to be widely used clinically. Clinical studies revealed that some Traditional Chinese Medicines, such as Lianhua Qingwen Capsule and Huoxiang Zhengqi Water, exhibited excellent therapeutic effect on COVID-19. However, until now, there is still no cure for COVID-19. Therefore, there is an urgent need to find medicines that can effectively fight against the SARS-CoV-2. In this study, JIE BEN No. 10 (JB10), a fermentation broth produced by Yi traditional medicine fermentation technology, was explored for its anti-coronavirus activity. The in vitro data showed that JB10 could significantly suppresses the replication of the SARS-CoV-2 with an EC50 of 769.1 times dilution and a selection index of 42.68. Further studies indicated that JB10 had significant anti-inflammatory and antioxidant activities. The analysis of active components suggested that JB10 contained a large amount of superoxide dismutase (SOD), flavones, polyphenols, crude polysaccharide, etc. which may explain the anti-coronavirus activity, anti-inflammatory and antioxidant effects. Our study provides a new potentially therapeutic strategy for COVID-19.

Prediction of the Epidemic of COVID-19 Based on Quarantined Surveillance in China (preprint)

Background and Objective: To predict the epidemic of COVID-19 based on quarantined surveillance from real world in China by modified SEIR model different from the previous simply mathematical model. Design and Methods: We forecasted the epidemic of COVID-19 based on current clinical and epidemiological data and built a modified SEIR model to consider both the infectivity during incubation period and the influence on the epidemic from strict quarantined measures. Results: The peak time of the curve for the infected newly diagnosed as COVID-19 should substantially present on Feb.5,2020(in non-Hubei areas) and Feb.19,2020(in Hubei. It is estimated that the peak of the curve of the cumulative confirmed cases will appear in non-Hubei areas on Mar.3,2020 and in Hubei province on Mar.10,2020,and the total number of the patients diagnosed as COVID-19 is 18,000 in non-Hubei areas and 78,000-96,000 in Hubei.The Chinese COVID-19 epidemic can be completely controlled in May,2020. Conclusions: COVID-19 is only a local outbreak in Hubei Province,China.It can be probably avoided the pandemic of global SARS-CoV-2 cases rise with the great efforts by Chinese government and its people.