Exploring potential mechanisms of Suhexiang Pill against COVID-19 based on network pharmacology and molecular docking.

BACKGROUND: The traditional Chinese medicine prescription Suhexiang Pill (SHXP), a classic prescription for the treatment of plague, has been recommended in the 2019 Guideline for coronavirus disease 2019 (COVID-19) diagnosis and treatment of a severe type of COVID-19. However, the bioactive compounds and underlying mechanisms of SHXP for COVID-19 prevention and treatment have not yet been elucidated. This study investigates the mechanisms of SHXP in the treatment of COVID-19 based on network pharmacology and molecular docking. METHODS: First, the bioactive ingredients and corresponding target genes of the SHXP were screened from the traditional Chinese medicine systems pharmacology database and analysis platform database. Then, we compiled COVID-19 disease targets from the GeneCards gene database and literature search. Subsequently, we constructed the core compound-target network, the protein-protein interaction network of the intersection of compound targets and disease targets, the drug-core compound-hub gene-pathway network, module analysis, and hub gene search by the Cytoscape software. The Metascape database and R language software were applied to analyze gene ontology biological processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. Finally, AutoDock software was used for molecular docking of hub genes and core compounds. RESULTS: A total of 326 compounds, 2450 target genes of SHXP, and 251 genes related to COVID-19 were collected, among which there were 6 hub genes of SHXP associated with the treatment of COVID-19, namely interleukin 6, interleukin 10, vascular endothelial growth factor A, signal transducer and activator of transcription 3 (STAT3), tumor necrosis factor (TNF), and epidermal growth factor. Functional enrichment analysis suggested that the effect of SHXP against COVID-19 is mediated by synergistic regulation of several biological signaling pathways, including Janus kinase/ STAT3, phosphatidylinositol 3-kinase (PI3K)-protein kinase B (Akt), T cell receptor, TNF, Nuclear factor kappa-B, Toll-like receptor, interleukin 17, Chemokine, and hypoxia-inducible factor 1 signaling pathways. SHXP may play a vital role in the treatment of COVID-19 by suppressing the inflammatory storm, regulating immune function, and resisting viral invasion. Furthermore, the molecular docking results showed an excellent binding affinity between the core compounds and the hub genes. CONCLUSION: This study preliminarily predicted the potential therapeutic targets, signaling pathways, and molecular mechanisms of SHXP in the treatment of severe COVID-19, which include the moderate immune system, relieves the "cytokine storm," and anti-viral entry into cells.

Validation of the soft-embalmed Thiel cadaver as a high-fidelity simulator of pressure during targeted nerve injection.

INTRODUCTION: Although administration of regional anesthesia nerve blocks has increased during the COVID-19 pandemic, training opportunities in regional anesthesia have reduced. Simulation training may enhance skills, but simulators must be accurate enough for trainees to engage in a realistic way-for example, detection of excessive injection pressure. The soft-embalmed Thiel cadaver is a life-like, durable simulator that is used for dedicated practice and mastery learning training in regional anesthesia. We hypothesized that injection opening pressure in perineural tissue, at epineurium and in subepineurium were similar to opening pressures measured in experimental animals, fresh frozen cadavers, glycol soft-fix cadavers and patients. METHODS: We systematically reviewed historical data, then conducted three validation studies delivering a 0.5 mL hydrolocation bolus of embalming fluid and recording injection pressure. First, we delivered the bolus at 12 mL/min at epimysium, perineural tissue, epineurium and in subepineurium at 48 peripheral nerve sites on three cadavers. Second, we delivered the bolus at using three infusion rates: 1 mL/min, 6 mL/min and 12 mL/min on epineurium at 70 peripheral nerve sites on five cadavers. Third, we repeated three injections (12 mL/min) at 24 epineural sites over the median and sciatic nerves of three cadavers. RESULTS: Mean (95%) injection pressure was greater at epineurium compared with subepineurium (geometric ratio 1.2 (95% CI: 0.9 to 1.6)), p=0.04, and perineural tissue (geometric ratio 5.1 (95% CI: 3.7 to 7.0)), p<0.0001. Mean (95%) injection pressure was greater at 12 mL/min compared with 1 mL/min (geometric ratio 1.6 (95% CI: 1.2 to 2.1), p=0.005). Pressure measurements were similar in study 3 (p>0.05 for all comparisons). DISCUSSION: We conclude that the soft-embalmed Thiel cadaver is a realistic simulator of injection opening pressure.

Dissecting the novel mechanism of reduning injection in treating Coronavirus Disease 2019 (COVID-19) based on network pharmacology and experimental verification.

ETHNOPHARMACOLOGICAL RELEVANCE: Reduning injection (RDNI) is a patented Traditional Chinese medicine that contains three Chinese herbal medicines, respectively are the dry aboveground part of Artemisia annua L., the flower of Lonicera japonica Thunb., and the fruit Gardenia jasminoides J.Ellis. RDNI has been recommended for treating Coronavirus Disease 2019 (COVID-19) in the "New Coronavirus Pneumonia Diagnosis and Treatment Plan". AIM OF THE STUDY: To elucidate and verify the underlying mechanisms of RDNI for the treatment of COVID-19. METHODS: This study firstly performed anti-SARS-CoV-2 experiments in Vero E6 cells. Then, network pharmacology combined with molecular docking was adopted to explore the potential mechanisms of RDNI in the treatment for COVID-19. After that, western blot and a cytokine chip were used to validate the predictive results. RESULTS: We concluded that half toxic concentration of drug CC50 (dilution ratio) = 1:1280, CC50 = 2.031 mg crude drugs/mL (0.047 mg solid content/mL) and half effective concentration of drug (EC50) (diluted multiples) = 1:25140.3, EC50 = 103.420 µg crude drugs/mL (2.405 µg solid content/mL). We found that RDNI can mainly regulate targets like carbonic anhydrases (CAs), matrix metallopeptidases (MMPs) and pathways like PI3K/AKT, MAPK, Forkhead box O s and T cell receptor signaling pathways to reduce lung damage. We verified that RDNI could effectively inhibit the overexpression of MAPKs, PKC and p65 nuclear factor-κB. The injection could also affect cytokine levels, reduce inflammation and display antipyretic activity. CONCLUSION: RDNI can regulate ACE2, Mpro and PLP in COVID-19. The underlying mechanisms of RDNI in the treatment for COVID-19 may be related to the modulation of the cytokine levels and inflammation and its antipyretic activity by regulating the expression of MAPKs, PKC and p65 nuclear factor NF-κB.

Impact of Systematic Factors on the Outbreak Outcomes of the Novel COVID-19 Disease in China: Factor Analysis Study.

BACKGROUND: The novel COVID-19 disease has spread worldwide, resulting in a new pandemic. The Chinese government implemented strong intervention measures in the early stage of the epidemic, including strict travel bans and social distancing policies. Prioritizing the analysis of different contributing factors to outbreak outcomes is important for the precise prevention and control of infectious diseases. We proposed a novel framework for resolving this issue and applied it to data from China. OBJECTIVE: This study aimed to systematically identify national-level and city-level contributing factors to the control of COVID-19 in China. METHODS: Daily COVID-19 case data and related multidimensional data, including travel-related, medical, socioeconomic, environmental, and influenza-like illness factors, from 343 cities in China were collected. A correlation analysis and interpretable machine learning algorithm were used to evaluate the quantitative contribution of factors to new cases and COVID-19 growth rates during the epidemic period (ie, January 17 to February 29, 2020). RESULTS: Many factors correlated with the spread of COVID-19 in China. Travel-related population movement was the main contributing factor for new cases and COVID-19 growth rates in China, and its contributions were as high as 77% and 41%, respectively. There was a clear lag effect for travel-related factors (previous vs current week: new cases, 45% vs 32%; COVID-19 growth rates, 21% vs 20%). Travel from non-Wuhan regions was the single factor with the most significant impact on COVID-19 growth rates (contribution: new cases, 12%; COVID-19 growth rate, 26%), and its contribution could not be ignored. City flow, a measure of outbreak control strength, contributed 16% and 7% to new cases and COVID-19 growth rates, respectively. Socioeconomic factors also played important roles in COVID-19 growth rates in China (contribution, 28%). Other factors, including medical, environmental, and influenza-like illness factors, also contributed to new cases and COVID-19 growth rates in China. Based on our analysis of individual cities, compared to Beijing, population flow from Wuhan and internal flow within Wenzhou were driving factors for increasing the number of new cases in Wenzhou. For Chongqing, the main contributing factor for new cases was population flow from Hubei, beyond Wuhan. The high COVID-19 growth rates in Wenzhou were driven by population-related factors. CONCLUSIONS: Many factors contributed to the COVID-19 outbreak outcomes in China. The differential effects of various factors, including specific city-level factors, emphasize the importance of precise, targeted strategies for controlling the COVID-19 outbreak and future infectious disease outbreaks.