Understanding natural and traditional medicine can lead to world-changing drug discoveries. Despite the therapeutic effectiveness of individual herbs, traditional Chinese medicine (TCM) lacks a scientific foundation and is often considered a myth. In this study, we establish a network medicine framework and reveal the general TCM treatment principle as the topological relationship between disease symptoms and TCM herb targets on the human protein interactome. We find that proteins associated with a symptom form a network module, and the network proximity of an herb’s targets to a symptom module is predictive of the herb’s effectiveness in treating the symptom. These findings are validated using patient data from a hospital. We highlight the translational value of our framework by predicting herb-symptom treatments with therapeutic potential. Our network medicine framework reveals the scientific foundation of TCM and establishes a paradigm for understanding the molecular basis of natural medicine and predicting disease treatments.

Objective: To conduct a randomized controlled clinical trial to evaluate the clinical efficacy and prognostic value of Jinhua Qinggan granules in patients with confirmed and suspected coronavirus disease 2019 (COVID-19).Methods: A total of 123 suspected and confirmed COVID-19 patients participated in this clinical trial and were randomly divided into Jinhua and Western medicine groups. For 14 days, the Jinhua group was treated with Jinhua Qinggan granules and antiviral drugs, and the Western medicine group was treated with antiviral drugs alone. We collected information on clinical symptoms, disease aggravation rates, and negative conversion rates of nucleic acids in patients, and observed the effects of anti-infective drugs.Results: There was no significant difference in symptom improvement rates between the two groups, both confirmed and suspected patients (P > 0.05). Both treatments relieved symptoms such as fever, fatigue, and diarrhea. However, the Jinhua treatment was superior in relieving fever and poor appetite. Anti-infective drug use rates were significantly lower in the Jinhua group than in the control group.Conclusion: Jinhua Qinggan granules combined with Western medicine could relieve the clinical symptoms of fever and poor appetite in COVID-19 patients, reduce the use of antibiotics to a certain extent.Clinical Trial Registration: The registration number at China Clinical Trial Registry is ChiCTR2000029601.

Objective: The objective of this study was to identify the biological correlation between the tongue coating color and oral and gut micro-characteristics in metabolic-associated fatty liver disease (MAFLD) patients.Method: The characteristics of the tongue coating were examined using an automatic tongue diagnosis system. Tongue coating and stool samples were collected from 38 MAFLD patients, and 16S rDNA full-length assembly sequencing technology (16S-FAST) was used for bioinformatic analysis.Results: Twenty-two and 16 subjects were included in two distinct clusters according to the white/yellow color of the tongue coating, which was assessed by the L*a*b* values of the image. Upon analyzing the microorganisms in the tongue coating, 66 and 62 pathognomonic bacterial genera were found in the White and Yellow Coating Groups, respectively. The abundance of Stomatobaculumis positively correlated with the a* values of the tongue coating in the White Coating Group, while Fusobacterium, Leptotrichia, and Tannerella abundance was significantly correlated with the b* values in the Yellow Coating Group. Function prediction mainly showed the involvement of protein families related to BRITE hierarchies and metabolism. The MHR (MONO%/high-density lipoprotein cholesterol) of the Yellow Coating Group was higher than that of the White Coating Group.Conclusion: In MAFLD patients, lower a* values and higher b* values are indicators of a yellow tongue coating. There were also significant differences in the flora of different tongue coatings, with corresponding changes in the intestinal flora, indicating a correlation between carbohydrate metabolism disorders and inflammation in the oral microbiome.