Efficacy of nasal irrigation and oral rinse with sodium bicarbonate solution on virus clearance for COVID-19 patients.

Background: Recent studies have shown that the infectivity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is reduced under alkaline conditions. The purpose of this study is to assess the effect of nasal irrigation and oral rinse with sodium bicarbonate solution on virus clearance among COVID-19 patients. Materials and methods: COVID-19 patients were recruited and randomly divided into two group, i.e., the experimental group and the control group. The experimental group received regular care plus nasal irrigation and oral rinse with 5% sodium bicarbonate solution, while the control group only received regular care. Nasopharyngeal and oropharyngeal swab samples were collected daily for reverse transcription-polymerase chain reaction (RT-PCR) assays. The negative conversion time and hospitalization time of the patients were recorded, and the results were statistically analyzed. Results: A total of 55 COVID-19 patients with mild or moderate symptoms were included in our study. There was no significant difference in gender, age and health status between the two groups. The average negative conversion time was 1.63 days after treatment with sodium bicarbonate, and the average hospitalization time of the control group and the experimental group were 12.53 and 7.7 days, respectively. Conclusions: Nasal irrigation and oral rinse with 5% sodium bicarbonate solution is effective in virus clearance for COVID-19 patients.

Computational exploration of natural peptides targeting ACE2.

Interaction between the SARS-COV-2 (2019 novel coronavirus) spike protein and ACE2 receptors expressed on cellular surfaces initialises viral attachment and consequent infection. Blocking this interaction shows promise for blocking or ameliorating the virus' pathological effects on the body. By contrast to work focusing on the coronavirus, which has significant potential diversity through possible accumulation of mutations during transmission, targeting the conserved ACE2 protein expressed on human cells offers an attractive alternative route to developing pharmacological prophylactics against viral invasion. In this study, we screened a virtual database of natural peptides in silico, with ACE2 as the target, and performed structural analyses of the interface region in the SARS-COV-2 RBD/ACE2 complex. These analyses have identified 15 potentially effective compounds. Analyses of ACE2/polypeptide interactions suggest that these peptides can block viral invasion of cells by stably binding in the ACE2 active site pocket. Molecular simulation results for Complestatin and Valinomycin indicate that they may share this mechanism. The discovery of this probable binding mechanism provides a frame of reference for further optimization, and design of high affinity ACE2 inhibitors that could serve as leads for production of drugs with preventive and therapeutic effects against SARS-COV-2. Communicated by Ramaswamy H. Sarma.

Modeling the trend of coronavirus disease 2019 and restoration of operational capability of metropolitan medical service in China: a machine learning and mathematical model-based analysis.

Background: To contain the outbreak of coronavirus disease 2019 (COVID-19) in China, many unprecedented intervention measures are adopted by the government. However, these measures may interfere in the normal medical service. We sought to model the trend of COVID-19 and estimate the restoration of operational capability of metropolitan medical service in China. Methods: Real-time data of COVID-19 and population mobility data were extracted from open sources. SEIR (Susceptible, Exposed, Infectious, Recovered) and neural network models (NNs) were built to model disease trends in Wuhan, Beijing, Shanghai and Guangzhou. Combined with public transportation data, Autoregressive Integrated Moving Average (ARIMA) model was used to estimate the accumulated demands for nonlocal hospitalization during the epidemic period in Beijing, Shanghai and Guangzhou. Results: The number of infected people and deaths would increase by 45% and 567% respectively, given that the government only has implemented traffic control in Wuhan without additional medical professionals. The epidemic of Wuhan (measured by cumulative confirmed cases) was predicted to reach turning point at the end of March and end in later April, 2020. The outbreak in Beijing, Shanghai and Guangzhou was predicted to end at the end of March and the medical service could be fully back to normal in middle of April. During the epidemic, the number of nonlocal inpatient hospitalizations decreased by 69.86%, 57.41% and 66.85% in Beijing, Shanghai and Guangzhou respectively. After the end of epidemic, medical centers located in these metropolises may face 58,799 (95% CI 48926-67,232) additional hospitalization needs in the first month. Conclusion: The COVID-19 epidemic in China has been effectively contained and medical service across the country is expected to return to normal in April. However, the huge unmet medical needs for other diseases could result in massive migration of patients and their families, bringing tremendous challenges for medical service in major metropolis and disease control for the potential asymptomatic virus carrier.