Network pharmacology-based predictions of active components and pharmacological mechanisms of Artemisia annua L. for the treatment of the novel Corona virus disease 2019 (COVID-19).

BACKGROUND: Novel Corona Virus Disease 2019 (COVID-19) is closely associated with cytokines storms. The Chinese medicinal herb Artemisia annua L. (A. annua) has been traditionally used to control many inflammatory diseases, such as malaria and rheumatoid arthritis. We performed network analysis and employed molecular docking and network analysis to elucidate active components or targets and the underlying mechanisms of A. annua for the treatment of COVID-19. METHODS: Active components of A. annua were identified through the TCMSP database according to their oral bioavailability (OB) and drug-likeness (DL). Moreover, target genes associated with COVID-19 were mined from GeneCards, OMIM, and TTD. A compound-target (C-T) network was constructed to predict the relationship of active components with the targets. A Compound-disease-target (C-D-T) network has been built to reveal the direct therapeutic target for COVID-19. Molecular docking, molecular dynamics simulation studies (MD), and MM-GBSA binding free energy calculations were used to the closest molecules and targets between A. annua and COVID-19. RESULTS: In our network, GO, and KEGG analysis indicated that A. annua acted in response to COVID-19 by regulating inflammatory response, proliferation, differentiation, and apoptosis. The molecular docking results manifested excellent results to verify the binding capacity between the hub components and hub targets in COVID-19. MD and MM-GBSA data showed quercetin to be the more effective candidate against the virus by target MAPK1, and kaempferol to be the other more effective candidate against the virus by target TP53. We identified A. annua's potentially active compounds and targets associated with them that act against COVID-19. CONCLUSIONS: These findings suggest that A. annua may prevent and inhibit the inflammatory processes related to COVID-19.

Application of refined management in prevention and control of the coronavirus disease 2019 epidemic in non-isolated areas of a general hospital.

OBJECTIVE: This article summarizes the experience in the prevention and control of coronavirus disease 2019(COVID-19) epidemic in non-isolated areas in a general hospital. METHODS: Based on refined management theory, we professionally developed the standards for prevention and control of COVID-19 in non-isolated areas, systematically implemented various prevention and control measures, performed gridding audits, effectively communicated among teams and between medical staff and patients assisted by information techniques, and reported results for quality improvement. RESULTS: There was no hospital-acquired COVID-19 infections among staff in the hospital. The rates of mask-wearing, epidemiological history screening, and the medical supplies disinfection were all 100% in the hospital. The accuracy rate of mask-wearing of patients and their families was 73.79% and the compliance rate of their hand hygiene was 40.78%. CONCLUSION: Refined management strategies for the prevention and control of COVID-19 infection in non-isolated areas of the general hospital are effective. The accuracy rate of mask-wearing and hand hygiene compliance of patients and their families need to be further improved.

Safety and efficacy of artemisinin-piperaquine for treatment of COVID-19: an open-label, non-randomised and controlled trial.

BACKGROUND: There are no effective therapies for patients with coronavirus disease-2019 (COVID-19). METHODS: Forty-one patients with confirmed COVID-19 were enrolled in the study and divided into two groups: artemisinin-piperaquine (AP) (n = 23) and control (n = 18). The primary outcome were the time taken to reach undetectable levels of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and the percentage of participants with undetectable SARS-CoV-2 on days 7, 10, 14, and 28. The computed tomography (CT) imaging changes within 10 days, corrected QT interval changes, adverse events, and abnormal laboratory parameters were the secondary outcomes. RESULTS: The mean time to reach undetectable viral RNA (mean ± standard deviation) was 10.6 ± 1.1 days (95% confidence interval [CI] 8.4-12.8) for the AP group and 19.3 ± 2.1 days (95% CI 15.1-23.5) for the control group. The percentages of patients with undetectable viral RNA on days 7, 10, 14, 21, and 28 were 26.1%, 43.5%, 78.3%, 100%, and 100%, respectively, in the AP group and 5.6%, 16.7%, 44.4%, 55.6%, and 72.2%, respectively, in the control group. The CT imaging within 10 days post-treatment showed no significant between-group differences (P > 0.05). Both groups had mild adverse events. CONCLUSIONS: In patients with mild-to-moderate COVID-19, the time to reach undetectable SARS-CoV-2 was significantly shorter in the AP group than that in the control group. However, physicians should consider QT interval changes before using AP.