[Rationality evaluation of Shuanghuanglian Injection combined with Ampicillin Sodium for Injection based on sequential analysis].

The lack of rationality evaluation method for drug combination has long restricted its clinical application. In view of this, this study took Shuanghuanglian Injection as model drug and established a "physical-chemical-biological" sequential analysis method, which is expected to provide clues for improving the safety and effectiveness of clinical drug combination. With the methods of insoluble particle testing, isothermal titration calorimetry(ITC), and real time cellular analysis(RTCA), the rationality of Shuanghuanglian Injection combined with Ampicillin Sodium for Injection was assessed. The results showed that the number of insoluble particles>10 µm in the solution of the combination met the standard of Chinese Pharmacopoeia, while the number of insoluble particles>25 µm did not meet the standard. ITC detection demonstrated that the change of Gibbs free energy(ΔG) was less than 0 during the fusion process, indicating that the process was spontaneous and enthalpy-driven reaction. Therefore, the interaction between the two was mainly chemical reaction, and the internal substances may change. RTCA found that Shuanghuanglian Injection alone and Ampicillin Sodium for Injection alone basically had no inhibitory effect on the growth of HEK293 T cells, while the combination of the two suppressed the growth of HEK293 T cells, suggesting that the combination was toxic to HEK293 T cells. This study showed that Shuanghuanglian Injection and Ampicillin Sodium for Injection reacted, yielding toxicity. This suggested that the two should not be combined for application. With the "physical-chemical-biological" sequential analysis, the molecular interaction of drugs was clarified. The method can be further applied for evaluating the rationality of other Chinese and western medicine injections.

[Exploration on rationality evaluation approach of drug combination medication based on sequential analysis and machine learning].

Drug combination is a common clinical phenomenon. However, the scientific implementation of drug combination is li-mited by the weak rational evaluation that reflects its clinical characteristics. In order to break through the limitations of existing evaluation tools, examining drug-to-drug and drug-to-target action characteristics is proposed from the physical, chemical and biological perspectives, combining clinical multicenter case resources, domestic and international drug interaction public facilities with the aim of discovering the common rules of drug combination. Machine learning technology is employed to build a system for evaluating and predicting the rationality of clinical drug combinations based on "drug characteristics-repository information-artificial intelligence" strategy, which will be debugged and validated in multi-center clinical practice, with a view to providing new ideas and technical references for the safety and efficacy of clinical drug use.

Berberine treatment-emergent mild diarrhea associated with gut microbiota dysbiosis.

Berberine (BBR) is a non-prescription drug to treat various bacteria-associated diarrheas. However, BBR has also been reported to cause diarrhea in clinic, with underlying mechanisms poorly understood. Because altered gut microbial ecology is a potential basis for diarrhea, this study was conducted to investigate the impact of BBR on gut microbiota of treatment-emergent diarrhea. BBR treatment (200 mg/kg, i.g.) in normal rats exhibited no significant changes in serum biochemical parameters but mild diarrhea occurred, accompanied with the decreased gastrointestinal transit time and increased fecal moisture, suggestive of the local effects of BBR in the intestine. Colon histology revealed the decreased abundance of mucus-filled goblet cells in BBR group. Although BBR-treated rats had the enlarged cecum with watery caecal digesta, short-chain fatty acids concentration was significantly lower than control group. Additionally, BBR caused gut microbiota dysbiosis by evaluating the decreased observed species number and Shannon index. BBR increased the relative abundances of families Porphyromonadaceae and Prevotellaceae as well as genera Parabacteroides, Prevotellaceae_UCG-001 and Prevotellaceae_NK3B31_group. Spearman's correlation analysis revealed family Prevotellaceae and genus Prevotellaceae_UCG-001 as the most prominent drivers of the BBR treatment-emergent diarrhea, correlating positively with fecal moisture but negatively with gastrointestinal transit time. This study therefore demonstrated that the treatment-emergent mild diarrhea of BBR was most likely due to the dysbiosis of the gut microbiota.

[Exploring research ideas of mechanism of dominant diseases in traditional Chinese medicine based on evidence-based medicine].

The prescription of clinical curative effect has promoted the formation and development of the dominant diseases in traditional Chinese medicine, but it has been controversial for a long time because its mechanism has not been effectively explained. Breaking the gap between animal/cell research and clinical research, and understanding the mechanism of dominant diseases in traditional Chinese medicine based on evidence-based medicine has become an important breakthrough in this scientific issue. Therefore, based on evidence-based medicine, we established the research concept that "originating from clinic, testing in experiment, returning to clinic". Taking the classic formula (Jinqi Jiangtang formula) treating diabetes as an example to find characteristic markers of diabetes supported by evidence-based medicine from clinic. We used the reverse analysis strategy of the response of characteristic markers to explore the intervention mechanism of Jinqi Jiangtang formula on characteristic markers. Then, we verified the key signaling molecules of the metabolic regulation of the Jinqi Jiangtang formula in clinic. The research ideas and key technologies for the mechanism of treatment of diabetes by Jinqi Jiangtang formula based on evidence-based medicine are formed, and it is expected to provide research reference for explaining the mechanism of dominant diseases in traditional Chinese medicine based on evidence-based medicine.