Systematic investigation on the anti-rheumatoid arthritis material basis and mechanism of Juan Bi Tang. Part 1: Integrating metabolic profiles and network pharmacology

Juan Bi Tang, a traditional Chinese medicine, for alleviating pain related to arteriovenous fistula in maintenance hemodialysis patients: An interventional pilot study with brief review

Myofascial pain around an arteriovenous fistula (AVF) during hemodialysis (HD) can affect a patient compliance with HD and quality of life. Prolonged use of analgesics is often associated with increased adverse events. Juan Bi Tang (JBT) is an ancient decoction of Chinese traditional medicinal plants commonly used to treat spasms and pain in the shoulder and upper arm, and it is popularly believed to have favorable outcomes in Asian populations. This interventional prospective pilot study was worked to demonstrate the potential of JBT for fistula-associated myofascial pain in HD patients and to prepare for future randomized controlled trials. Eligible patients were enrolled in this study and took JBT to treat fistula-associated myofascial pain for 4 weeks. Pain scores on a visual analogue scale (VAS) were reported at baseline, after a 4-week intervention, and 2 weeks after completion of treatment. The Kidney Disease Quality of Life 36-Item Short Form and a safety laboratory monitor were statistically compared between different time points. A total of 20 patients were selected as eligible participants and completed the intervention and questionnaires. The mean VAS score was significantly reduced after JBT treatment (P < .01). Participants reported improved physical (P < .01) and mental health (P < .05) after treatment. However, only improvements in mental health were preserved 2 weeks after the end of treatment (P < .05). In this study, complementary JBT for HD patients with fistula-related myofascial pain was viable and well tolerated, and it demonstrated the expected effects on pain control.

Integration of Deep Learning and Sequential Metabolism to Rapidly Screen Dipeptidyl Peptidase (DPP)-IV Inhibitors from Gardenia jasminoides Ellis

Traditional Chinese medicine (TCM) possesses unique advantages in the management of blood glucose and lipids. However, there is still a significant gap in the exploration of its pharmacologically active components. Integrated strategies encompassing deep-learning prediction models and active validation based on absorbable ingredients can greatly improve the identification rate and screening efficiency in TCM. In this study, the affinity prediction of 11,549 compounds from the traditional Chinese medicine system's pharmacology database (TCMSP) with dipeptidyl peptidase-IV (DPP-IV) based on a deep-learning model was firstly conducted. With the results, Gardenia jasminoides Ellis (GJE), a food medicine with homologous properties, was selected as a model drug. The absorbed components of GJE were subsequently identified through in vivo intestinal perfusion and oral administration. As a result, a total of 38 prototypical absorbed components of GJE were identified. These components were analyzed to determine their absorption patterns after intestinal, hepatic, and systemic metabolism. Virtual docking and DPP-IV enzyme activity experiments were further conducted to validate the inhibitory effects and potential binding sites of the common constituents of deep learning and sequential metabolism. The results showed a significant DPP-IV inhibitory activity (IC50 53 ± 0.63 μg/mL) of the iridoid glycosides' potent fractions, which is a novel finding. Genipin 1-gentiobioside was screened as a promising new DPP-IV inhibitor in GJE. These findings highlight the potential of this innovative approach for the rapid screening of active ingredients in TCM and provide insights into the molecular mechanisms underlying the anti-diabetic activity of GJE.

Study of Xuanhuang Pill in protecting against alcohol liver disease using ultra-performance liquid chromatography/time-of-flight mass spectrometry and network pharmacology

Introduction

Xuanhuang Pill (XHP) is a traditional Chinese medicine oral formula composed of 10 herbs. This study aims to verify the hepatoprotective activity of XHP and explain its possible mechanism.

Methods

The hepatoprotective activity of XHP was evaluated by constructing a mouse model of alcoholic liver disease, and the mechanism of XHP was preliminarily explained by utilizing ultra-performance liquid chromatography/time-of-flight mass spectrometry (UPLC-QTOF/MS), proteomics and network pharmacology.

Results

The current study demonstrated that treatment with XHP ameliorated acute alcohol-induced liver injury in mice by significantly reducing alanine aminotransferase (ALT) and aspartate aminotransferase (AST) levels and triglycerides (TGs) and malondialdehyde (MDA) content. Remarkably, treatment also increased superoxide dismutase (SOD) activity and glutathione (GSH) content. UPLC-QTOF/MS, 199 compounds were identified as within the make-up of the XHP. Network pharmacology analysis showed that 103 targets regulated by 163 chemical components may play an important role in the protective liver effect mediated by XHP. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis suggest that the HIF-1, FoxO, PI3K-Akt, insulin, and thyroid hormone signaling pathways are key modulators of XHP’s effects. Finally, eight key targets including Mapk1, Mapk3, Akt1, Map2k1, Pik3ca, Pik3cg, Raf1, and Prkca were verified by molecular docking and proteomics analysis, which provide insight into the hepatoprotective effect observed with XHP treatment.

Conclusion

In summary, these results improved upon knowledge of the chemical composition and the potential mechanisms of hepatoprotective action of oral XHP treatment, providing foundational support for this formulation as a viable therapeutic option for alcoholic liver disease.

Integrated Strategy From In Vitro, In Situ, In Vivo to In Silico for Predicting Active Constituents and Exploring Molecular Mechanisms of Tongfengding Capsule for Treating Gout by Inhibiting Inflammatory Responses

The study of screening active constituents from traditional Chinese medicine (TCM) is important for explicating the mechanism of action of TCM and further evaluating the safety and efficacy effectively. However, detecting and identifying the active constituents from complicated biological samples still remain a challenge. Here, a practical, quick, and novel integrated strategy from in vitro, in situ, in vivo to in silico for rapidly screening the active constituents was developed. Firstly, the chemical profile of TCM in vitro was identified using UPLC-Q Exactive-Orbitrap HRMS. Secondly, the in situ intestinal perfusion with venous sampling (IPVS) method was used to investigate the intestinal absorption components. Thirdly, after intragastric administration of the TCM extract, the in vivo absorbed prototype components were detected and identified. Finally, the target network pharmacology approach was applied to explore the potential targets and possible mechanisms of the absorbed components from TCM. The reliability and availability of this approach was demonstrated using Tongfengding capsule (TFDC) as an example of herbal medicine. A total of 141 compounds were detected and identified in TFDC, and among them, 64 components were absorbed into the plasma. Then, a total of 35 absorbed bioactive components and 50 related targets shared commonly by compounds and gout were integrated via target network pharmacology analysis. Ultimately, the effects of the absorbed components on metabolism pathways were verified by experiments. These results demonstrated that this original method may provide a practical tool for screening bioactive compounds from TCM treating particular diseases. Furthermore, it also can clarify the potential mechanism of action of TCM and rationalize the application of TFDC as an effective herbal therapy for gout.