Exploration of molecular targets and mechanisms of Chinese medicinal formula Acacia Catechu -Scutellariae Radix in the treatment of COVID-19 by a systems pharmacology strategy.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In China, the Acacia catechu (AC)-Scutellariae Radix (SR) formula has been widely used for pulmonary infection in clinical practice for several centuries. However, the potential role and mechanisms of this formula against COVID-19 remains unclear. The present study was designed to dissect the active ingredients, molecular targets, and the therapeutic mechanisms of AC-SR formula in the treatment of COVID-19 based on a systems pharmacology strategy integrated by ADME screening, target prediction, network analysis, GO and KEGG enrichment analysis, molecular docking, and molecular dynamic (MD) simulations. Finally, Quercetin, Fisetin(1-), kaempferol, Wogonin, Beta-sitosterol, Baicalein, Skullcapflavone II, Stigmasterol were primarily screened to be the potentially effective active ingredients against COVID-19. The hub-proteins were TP53, JUN, ESR1, MAPK1, Akt1, HSP90AA1, TNF, IL-6, SRC, and RELA. The potential mechanisms of AC-SR formula in the treatment of COVID-19 were the TNF signaling pathway, PI3K-Akt signaling pathway and IL-17 signaling pathway, etc. Furthermore, virtual docking revealed that baicalein, (+)-catechin and fisetin(1-) exhibited high affinity to SARS-CoV-2 3CLpro, which has validated by the FRET-based enzymatic inhibitory assays with the IC50 of 11.3, 23.8, and 44.1 µM, respectively. And also, a concentration-dependent inhibition of baicalein, quercetin and (+)-catechin against SARS-CoV-2 ACE2 was observed with the IC50 of 138.2, 141.3, and 348.4 µM, respectively. These findings suggested AC-SR formula exerted therapeutic effects involving "multi-compounds and multi-targets." It might be working through directly inhibiting the virus, improving immune function, and reducing the inflammatory in response to anti-COVID-19. Ultimately, this study would provide new perspective for discovering potential drugs and mechanisms against COVID-19.

Improving Data Surveillance Resilience Beyond COVID-19: Experiences of Primary heAlth Care quAlity Cohort In ChinA (ACACIA) Using Unannounced Standardized Patients.

We analyzed COVID-19 influences on the design, implementation, and validity of assessing the quality of primary health care using unannounced standardized patients (USPs) in China. Because of the pandemic, we crowdsourced our funding, removed tuberculosis from the USP case roster, adjusted common cold and asthma cases, used hybrid online-offline training for USPs, shared USPs across provinces, and strengthened ethical considerations. With those changes, we were able to conduct fieldwork despite frequent COVID-19 interruptions. Furthermore, the USP assessment tool maintained high validity in the quality checklist (criteria), USP role fidelity, checklist completion, and physician detection of USPs. Our experiences suggest that the pandemic created not only barriers but also opportunities to innovate ways to build a resilient data collection system. To build data system reliance, we recommend harnessing the power of technology for a hybrid model of remote and in-person work, learning from the sharing economy to pool strengths and optimize resources, and dedicating individual and group leadership to problem-solving and results. (Am J Public Health. 2022;112(6):913-922. https://doi.org/10.2105/AJPH.2022.306779).