Wen Li

The incidence of depression is increasing year by year and has become a major problem threatening global public health. However, the limited efficacy of existing antidepressant drugs, accompanied by significant side effects and dependence, has prompted researchers to search for safer and more effective drugs. Recent studies have shown that neuroinflammation plays a key role in the pathological mechanisms of depression, suggesting that anti-inflammatory drugs may have potential for treating depression. Glabridin, the main active ingredient in Glycyrrhiza glabra, has significant anti-inflammatory and neuroprotective effects, but its antidepressant effects and mechanisms have not been fully elucidated. In the present study, we used a combination of network pharmacological prediction and in vivo experiments to investigate the ameliorative effect of glabridin on chronic unpredictable mild stress (CUMS)-induced depressive-like behaviours in mice and the possible molecular mechanisms. The experimental results showed that glabridin significantly ameliorated the symptoms of pleasure deficit and behavioral despair in CUMS mice, as evidenced by an increase in sucrose preference and a significant reduction in tail-hanging immobility time and forced swimming immobility time. In addition, glabridin effectively alleviated CUMS-induced neuronal damage in the hippocampal region and significantly reduced the expression of inflammatory factors, such as IL-1β, IL-6, and IL-18, suggesting that it could reduce the neuroinflammatory response. Network pharmacological analysis revealed that MAPK and NF-κB signaling pathways may be the key pathways for the antidepressant effect of glabridin. Further Western blot validation showed that glabridin inhibited the activation of the P38MAPK/NF-κB pathway in the hippocampus and reduced the phosphorylation level of related proteins. Overall, we provide evidence suggesting that the antidepressant mechanism of glabridin may be closely associated with multiple pathways, including downregulation of MAPK/NF-κB pathway activity, inhibition of inflammatory factor expression, and neurotransmitter regulation. This study offers new insights into the therapeutic potential of glabridin for treating depression.

Hop has been widely utilized in both food production and traditional medicine owing to their distinctive flavor and various pharmacological effects. In recent years, the increasing demand for hop has led to their cultivation in many regions across China. However, hops require specific ecological conditions, including climate, soil, precipitation, and temperature, which significantly affect their distribution and growth. To facilitate the standardization and scientific cultivation of hops, it is essential to clarify the distribution of their ecological suitability. In this study, we collected data from 95 hops distribution locations and 115 ecological factors to determine the areas suitable for hops cultivation using the Maximum Entropy (MaxEnt) model and Geographic Information System (GIS). The highly suitable areas are primarily located in the northwestern part of the Xinjiang Uygur Autonomous Region, the eastern part of Gansu Province, Shaanxi Province, the southwestern part of Shanxi Province, and parts of Ningxia Hui Autonomous Region and Yunnan Province. These findings provide valuable guidance for the scientific cultivation of hops, ensuring the efficient use of ecological resources and promoting sustainable cultivation practices.

Drug repositioning is gaining attention as a method for developing new drugs due to its low cost, short cycle time, and high success rate. One important approach is to explore new uses for already marketed drugs. In this study, we utilized the strategy of drug repositioning, focusing on the Dan-Lou tablet. We predicted the efficacy of Dan-Lou tablet against non-small cell lung cancer based on gene expression similarity and verified it by in vitro experiments. Next, we performed further analysis and validation using network pharmacology, molecular docking and molecular dynamics. Based on the results, it was concluded that Dan-Lou tablet mainly acted through nine compounds, Quercetin, Luteolin, Scoparone, Isorhamnetin, Eugenol, Genistein, Coumestrol, Hederagenin, Succinic Acid, and mainly targeted CCL2, FEN1, TPI1, RMI2 by six pathways. This discovery not only provides a new idea for the development of Dan-Lou tablet but also provides useful predictive information for clinical treatment. The method we adopted has great development prospects as a way to predict the efficacy of new drugs and their main mechanisms of action, and it has a positive impact on the research and development of new drugs using drug repositioning and the modernization of traditional Chinese medicine.

Codonopsis Radix (CR) is an edible food and traditional Chinese herb medicine in China. Various varieties of Codonopsis Radix have different tastes. To make the flavor of processed food stable, two kinds of electronic sensory devices, electronic nose and electronic tongue, were used to establish a discrimination model to identify the botanical origin of each sample. The optimal model built on the 88 batches of samples was selected from the models trained with all combination of two pretreatment methods and three classification methods. A comparison were performed on the models trained on the data collected by electronic nose and electronic tongue. The results showed that the model trained on the fused dataset outperformed the models trained separately on the electronic nose data and electronic tongue data. The two preprocessing approaches could improve the prediction performance of all classification methods. Classification and Regression Tree approach performed better than Partial Least Square Discriminant Analysis and Linear Discriminant Analysis in terms of accuracy. But Classification and Regression Tree tends to assign the samples of minority class to the majority class. Meanwhile, Partial Least Square Discriminant Analysis keeps a good balance between the identification requirements of all the two groups of samples. Taking all the results above, the model built using the Partial Least Square Discriminant Analysis method on the fused data after z-score was used to identify the botanical origin of Codonopsis Radix.