Combining network pharmacology and experimental verification to reveal the mechanism of Chaigui granules in the treatment of depression through PI3K/Akt/mTOR signaling pathways.

INTRODUCTION: Chaigui granules are a novel manufactured traditional Chinese antidepressant medicine, which is originated from the ancient classical prescription of Xiaoyaosan. It ameliorated depression-like behavior and concomitant symptoms in animal models. But its antidepressant mechanism is still unclear. Therefore, network pharmacology and molecular biology were used to explore underlying antidepressant mechanism in this study. METHODS: Firstly, network pharmacology was used to screen main active ingredients and potential targets in the treatment of depression with Chaigui granules, and to perform pathway enrichment analysis. Secondly, chronic and unpredictable mild stress-induced depression model rats were used, and behavioral tests were used to evaluate the antidepressant effect of Chaigui granules. Finally, the core targets and key pathways predicted by network pharmacology were validated by qRT-PCR and Western blot to determine the relevant gene and protein expression levels in rat hippocampus. RESULTS: The results of network pharmacology indicated that the PI3K/Akt signaling pathway may play a key role in antidepressant of Chaigui granules. The results of animal experiments showed that Chaigui granules significantly modulated behavioral indicators. Subsequently, the upregulation of relative mRNA levels of mTOR, Akt and PI3K and downregulation of GSK-3ß and FoxO3a were observed in rat hippocampus by molecular biology diagnosis. In addition, the decreased expression of Akt and mTOR in CUMS rats hippocampus was significantly reversed, and the expression levels of GSK-3ß and FoxO3a were upregulated. CONCLUSIONS: Based on the results of network pharmacology and animal experiment validation, Chaigui granules may reverse CUMS-induced depression-like behavior in rats through PI3K/Akt/mTOR signaling pathway.

Branched-Chain Amino Acids Catabolism Pathway Regulation Plays a Critical Role in the Improvement of Leukopenia Induced by Cyclophosphamide in 4T1 Tumor-Bearing Mice Treated With Lvjiaobuxue Granule.

Background: Cyclophosphamide is a common tumor chemotherapy drug used to treat various cancers. However, the resulting immunosuppression leads to leukopenia, which is a serious limiting factor in clinical application. Therefore, the introduction of immunomodulators as adjuvant therapy may help to reduce the hematological side effects of cyclophosphamide. Lvjiaobuxue granule has been widely used in the clinical treatment of gynecological diseases such as anemia and irregular menstruation. Recently, it has been found to increase the function of white blood cells, but its mechanism of action is still unclear. We aimed to reveal the mechanisms of Lvjiaobuxue granule against acute leukopenia by an integrated strategy combining metabolomics with network pharmacology. Methods: Subcutaneously inoculated 4T1 breast cancer cells to prepare tumor-bearing mice, intraperitoneal injection of cyclophosphamide to establish a 4T1 tumor-bearing mice leukopenia animal model, using pharmacodynamic indicators, metabolomics, network pharmacology and molecular biology and other technical methods. To comprehensively and systematically elucidate the effect and mechanism of Lvjiaobuxue granule in improving cyclophosphamide-induced leukopenia in 4T1 tumor-bearing mice. Results: Lvjiaobuxue granule can improve the blood routine parameters and organ index levels of the leukopenia model of 4T1 tumor-bearing mice. Metabolomics studies revealed that 15 endogenous metabolites in the spleen of mice were considered as potential biomarkers of Lvjiaobuxue granule for their protective effect. Metabonomics and network pharmacology integrated analysis indicated that Lvjiaobuxue granule exerted the leukocyte elevation activity by inhibiting the branched-chain amino acids (BCAAs) degradation pathway and increasing the levels of valine, leucine and isoleucine. The results of molecular biology also showed that Lvjiaobuxue granule can significantly regulate the key enzymes in the catabolism of BCAAs, which further illustrates the importance of BCAAs in improving leukopenia. Conclusion: Lvjiaobuxue granule exerts obvious pharmacological effects on the leukopenia model of 4T1 tumor-bearing mice induced by cyclophosphamide, which could be mediated by regulating the branched-chain amino acid degradation pathway and the levels of valine, leucine and isoleucine.

Chemical profiling of Callicarpa nudiflora and its effective compounds identification by compound-target network analysis.

Callicarpa nudiflora, belonging to the family Verbenaceae, is widely used to treat inflammation caused by bacterial infection.However, the underlying active substances of C. nudiflora against inflammation remains obscure. In this work, an ultra high-performance liquid chromatography (UHPLC) coupled with quadrupole time-of-flight mass spectrometry method was developed to characterize the ingredients in C. nudiflora, and a validated UHPLC coupled with triple quadrupole tandem mass spectrometry method was applied to quantify major components. As a result, a total of 96 chemical compounds were identified in C. nudiflora, and 26 compounds of them were further quantified in 34 batches of C. nudiflora. Based on the identified components from C. nudiflora, a compound-target network for the anti-inflammation effect was constructed by reverse docking target prediction, disease associated genes screening in DisGeNET and the protein-protein interaction from STRING. The compound-target network showed that C. nudiflora might exert anti-inflammation effect on the target of complement 3 and 5 in the pathway of cells and molecules involved in local acute inflammatory response, and 16 effective candidate compounds were found such as catalpol, acteoside, rutin, etc. This study provided an opportunity to deepen the understanding of the chemical composition and the potential anti-inflammatory mechanism of C. nudiflora.

[Research progress in pathogenesis of hemolytic anemia and its treatment with traditional Chinese medicine].

Hemolytic anemia is a common clinical disease with diverse pathogenesis. In recent years, the incidence of hemolytic anemia is increasing dramatically. The present clinical treatment of immunosuppressive agents or splenectomy is effective to some extent; however, the accompanied clinical adverse reactions are also significant. Traditional Chinese medicine (TCM) has beneficial therapeutic effect on hemolytic anemia, with the obvious advantages including curative effect, less adverse reactions, and low price. The pathogenesis of hemolytic anemia as well as the pharmacological effects and mechanisms of the compound, single herb, and monomer composition of TCM in the treatment of hemolytic anemia were reviewed, aiming to provide the basis for the clinical treatment of hemolytic anemia and the modern research on the mechanism of TCM.

[Application of near infrared spectroscopy combined with particle swarm optimization based least square support vactor machine to rapid quantitative analysis of Corni Fructus].

A novel method was developed for the rapid determination of multi-indicators in corni fructus by means of near infrared (NIR) spectroscopy. Particle swarm optimization (PSO) based least squares support vector machine was investigated to increase the levels of quality control. The calibration models of moisture, extractum, morroniside and loganin were established using the PSO-LS-SVM algorithm. The performance of PSO-LS-SVM models was compared with partial least squares regression (PLSR) and back propagation artificial neural network (BP-ANN). The calibration and validation results of PSO-LS-SVM were superior to both PLS and BP-ANN. For PSO-LS-SVM models, the correlation coefficients (r) of calibrations were all above 0.942. The optimal prediction results were also achieved by PSO-LS-SVM models with the RMSEP (root mean square error of prediction) and RSEP (relative standard errors of prediction) less than 1.176 and 15.5% respectively. The results suggest that PSO-LS-SVM algorithm has a good model performance and high prediction accuracy. NIR has a potential value for rapid determination of multi-indicators in Corni Fructus.