[Exploration and example interpretation of real-world herbal prescription classification based on similarity matching algorithm].

In observational studies, herbal prescriptions are usually studied in the form of "similar prescriptions". At present, the classification of prescriptions is mainly based on clinical experience judgment, but there are some problems in manual judgment, such as lack of unified criteria, labor consumption, and difficulty in verification. In the construction of a database of integrated traditional Chinese and western medicine for the treatment of coronavirus disease 2019(COVID-19), our research group tried to classify real-world herbal prescriptions using a similarity matching algorithm. The main steps include 78 target prescriptions are determined in advance; four levels of importance labeling shall be carried out for the drugs of each target prescription; the combination, format conversion, and standardization of drug names of the prescriptions to be identified in the herbal medicine database; calculate the similarity between the prescriptions to be identified and each target prescription one by one; prescription discrimination is performed based on the preset criteria; remove the name of the prescriptions with "large prescriptions cover the small". Through the similarity matching algorithm, 87.49% of the real prescriptions in the herbal medicine database of this study can be identified, which preliminarily proves that this method can complete the classification of herbal prescriptions. However, this method does not consider the influence of herbal dosage on the results, and there is no recognized standard for the weight of drug importance and criteria, so there are some limitations, which need to be further explored and improved in future research.

Alterations in the gut microbiome and metabolome profiles of septic mice treated with Shen FuHuang formula.

Sepsis has a high mortality rate, and treating sepsis remains a significant challenge worldwide. In former studies, our group found that traditional Chinese medicine, Shen FuHuang formula (SFH), is a promising medicine in treating coronavirus disease 2019 (COVID-19) patients with the septic syndrome. However, the underlying mechanisms remain elusive. In the present study, we first investigated the therapeutic effects of SFH on septic mice. To investigate the mechanisms of SFH-treated sepsis, we identified the gut microbiome profile and exploited untargeted metabolomics analyses. The results demonstrated that SFH significantly enhanced the mice's 7-day survival rate and hindered the release of inflammatory mediators, i.e., TNF-α, IL-6, and IL-1ß. 16S rDNA sequencing further deciphered that SFH decreased the proportion of Campylobacterota and Proteobacteria at the phylum level. LEfSe analysis revealed that the treatment of SFH enriched Blautia while decreased Escherichia_Shigella. Furthermore, serum untargeted metabolomics analysis indicated that SFH could regulate the glucagon signaling pathway, PPAR signaling pathway, galactose metabolism, and pyrimidine metabolism. Finally, we found the relative abundance of Bacteroides, Lachnospiraceae_NK4A136_group, Escherichia_Shigella, Blautia, Ruminococcus, and Prevotella were closely related to the enrichment of the metabolic signaling pathways, including L-tryptophan, uracil, glucuronic acid, protocatechuic acid, and gamma-Glutamylcysteine. In conclusion, our study demonstrated that SFH alleviated sepsis by suppressing the inflammatory response and hence reduced mortality. The mechanism of SFH for treating sepsis may be ascribed to the enrichment of beneficial gut flora and modulation in glucagon signaling pathway, PPAR signaling pathway, galactose metabolism, and pyrimidine metabolism. To sum up, these findings provide a new scientific perspective for the clinical application of SFH in treating sepsis.

Qingfei Jiedu Granules fight influenza by regulating inflammation, immunity, metabolism, and gut microbiota.

Background and aim: Qingfei Jiedu Granules (QFJD) are a new Traditional Chinese Medicine (TCM) which has been clinically used against coronavirus pneumonia in China. In this study, the therapeutic effect and the underlying mechanisms of QFJD against influenza were investigated. Experimental procedure: Pneumonia mice were induced by influenza A virus. Survival rate, weight loss, lung index and lung pathology were measured to evaluate the therapeutic effect of QFJD. The expression of inflammatory factors and lymphocytes was used to assess anti-inflammatory and immunomodulatory effect of QFJD. Gut microbiome analysis was performed to decipher the potential effect of QFJD on intestinal microbiota. Metabolomics approach was conducted to explore the overall metabolic regulation of QFJD. Result and conclusion: QFJD shows a significant therapeutic effect on the treatment of influenza and the expression of many pro-inflammatory cytokines were obviously inhibited. QFJD also markedly modulates the level of T and B lymphocytes. The high-dose QFJD has shown similar therapeutic efficiency compared to positive drugs. QFJD profoundly enriched Verrucomicrobia and maintained the balance between Bacteroides and Firmicutes. QFJD associated with 12 signaling pathways in metabolomics study, 9 of which were the same as the model group and were closely related to citrate cycle and amino acid metabolism.To sum up, QFJD is a novel and promising drug against influenza. It can regulate inflammation, immunity, metabolism, and gut microbiota to fight influenza. Verrucomicrobia shows great potential to improve influenza infection and may be an important target.

Cangma Huadu granules, a new drug with great potential to treat coronavirus and influenza infections, exert its efficacy through anti-inflammatory and immune regulation.

ETHNOPHARMACOLOGICAL RELEVANCE: Coronavirus and influenza virus infection seriously threaten human health. Cangma Huadu Granules (CMHD) is an in-hospital preparation composed of eight traditional Chinese medicines (TCM), which has been clinically used against COVID-19 in China and may be a promising candidate for the treatment of influenza. However, the role of its treatment urgently needs to be studied. AIM OF THE STUDY: To evaluate the therapeutic effects of CMHD on pneumonia induced by coronavirus (HCoV-229E) and influenza A virus (H1N1/FM1) in mice and explore its mechanism of anti-infection. MATERIALS AND METHODS: Mice were infected with HCoV-229E or H1N1/FM1 virus through the nasal cavity. CMHD (12.1, 6.05 and 3.03 g/kg/d) or the positive control drugs were administered intragastrically. The lung index and histopathological changes were used to evaluate the therapeutic effect of CMHD. The expression of TNF-α, IL-1ß, IL-6 and IL-4 in Serum and the proportion of CD4+ and CD8+ T lymphocytes in peripheral blood were detected to evaluate the anti-inflammatory and immune regulation effects of CMHD, respectively. Furthermore, the levels of p-NF-κBp65/ NF-κB p65, which was the key targets of the NF-κB pathway was analyzed. RESULTS: In HCoV-229E-induced pneumonia, the lung index was markedly reduced, and lung pathology was improved in mice that treated with CMHD (12.1, 6.05 g/kg/d). Meanwhile, the expression of TNF-α, IL-6 were obviously inhibited, but the expression of IL-4 was significantly increased in CMHD groups. Compared with the model group, CMHD could also markedly upregulate the level of CD4+ and CD8+. Furthermore, CMHD has a markedly effect on inhibit the expression of p-NF-κB p65/NF-κB p65 in the lung. In H1N1-induced pneumonia, the lung index of mice in the CMHD (12.1 g/kg/d) treatment group was lower than that in the model group, and less inflammatory infiltration could be seen in the lung pathological. Moreover, CMHD could also obviously decrease the expression of TNF-α, IL-1ß, IL-6, but significantly increase the expression of IL-4. Except for that, CMHD could also markedly downregulate the level of CD4+ and upregulate the level of CD8+ compared with the model group. In addition, CMHD has a markedly effect on inhibit the expression of p-NF-κB p65/NF-κB p65 in the lung. CONCLUSION: CMHD can significantly combats viral infections caused by HCoV-229E and H1N1, and the mechanism may be related to its multiple functions of anti-inflammatory, immunity regulating and inhibiting NF-κB signal transduction pathway.

Efficacy and safety of Reduning injection in the treatment of COVID-19: a randomized, multicenter clinical study.

BACKGROUND: Reduning injection is a traditional Chinese medicine (TCM) with known efficacy against a variety of viral infections, but there is no data about its efficacy against coronavirus disease 2019 (COVID-19). METHODS: To explore the efficacy and safety of Reduning injection in the treatment of COVID-19, a randomized, open-labeled, multicenter, controlled trial was conducted from 12 general hospitals between 2020.02.06 and 2020.03.23. Patients with COVID-19 who met the diagnostic criteria of the "Diagnosis and Treatment Program for Novel Coronavirus Infection Pneumonia (Trial Fifth Edition)". Patients were randomized to routine treatment with or without Reduning injection (20 mL/day for 14 days) (ChiCTR2000029589). The primary endpoint was the rate of achieving clinical symptom recovery on day 14 of treatment. RESULTS: There were 77 and 80 participants in the Reduning and control groups. The symptom resolution rate at 14 days was higher in the Reduning injection than in controls [full-analysis set (FAS): 84.4% vs. 60.0%, P=0.0004]. Compared with controls, the Reduning group showed shorter median time to resolution of the clinical symptoms (143 vs. 313.5 h, P<0.001), shorter to nucleic acid test turning negative (146.5 vs. 255.5 h, P<0.001), shorter hospital stay (14.1 vs. 18.1 days, P<0.001), and shorter time to defervescence (29 vs. 71 h, P<0.001). There was no difference in AEs (3.9% vs. 8.8%, P=0.383). CONCLUSIONS: This preliminary trial suggests that Reduning injection might be effective and safe in patients with symptomatic COVID-19.

Systems Pharmacology and Verification of ShenFuHuang Formula in Zebrafish Model Reveal Multi-Scale Treatment Strategy for Septic Syndrome in COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19) has affected millions of people worldwide. Critically ill COVID-19 patients develop viral septic syndrome, including inflammatory damage, immune dysfunction, and coagulation disorder. In this study, we investigated ShenFuHuang formula (SFH), a traditional Chinese medicine, which has been widely used as complementary therapy for clinical treatment of COVID-19 in Wuhan, to understand its pharmacological properties. Results of systems pharmacology identified 49 active compounds of SFH and their 69 potential targets, including GSK3ß, ESR1, PPARG, PTGS2, AKR1B10, and MAPK14. Network analysis illustrated that the targets of SFH may be involved in viral disease, bacterial infection/mycosis, and metabolic disease. Moreover, signaling pathway analysis showed that Toll-like receptors, MAPK, PPAR, VEGF, NOD-like receptor, and NF-kappa B signaling pathways are highly connected with the potential targets of SFH. We further employed multiple zebrafish models to confirm the pharmacological effects of SFH. Results showed that SFH treatment significantly inhibited the inflammatory damage by reducing the generation of neutrophils in Poly (I:C)-induced viral infection model. Moreover, SFH treatment could improve the phagocytosis of macrophages and enhance the expression of immune genes in an immune deficiency model. Furthermore, SFH treatment exhibited promising anti-thrombosis effect in a thrombus model. This study provided additional evidence of SFH formula for treating COVID-19 patients with septic syndrome using multiple-scale estimation.

[Thoughts and suggestions on analysis of death cases report during COVID-19 epidemic].

It is an essential task to discuss the death cases for clinicians. During the emergent public events, the report and analysis of death cases is of far-reaching significance. The epidemic of coronavirus disease 2019(COVID-19) has brought huge losses to China, and the medical system has been sustaining tremendous pressure. The best weapon to defeat the epidemic is medical data and related scientific research, of which the systematic analysis and efficient use of death cases is a key step. Based on the incomplete record of death case report, the lack of humanistic perspective and patient report, every department and institution is facing great challenge in terms of data management. Given that the relevant systems need to be improved, and that the integration of standardized reports and clinical research is not mature,as well as other problems, we put forward several methodological suggestions: ① Establish national medical and health data center and improve relevant laws and regulations. ② Increase investment in medical data management and start data collection and analysis as early as possible during the epidemic. ③ Refine the content of death case report and promote the standardization of report. ④ Pay close attention to the report of death cases, review, summary and analysis. More importantly, we should continue to build and improve platforms and programs related to disease control, carry out epidemic-associated scientific research, enhance the managing efficiency of public health data, elevate the anti-risk capability of our medical system, and promote the steady progress of the health China strategy.