The global depression population is showing a significant increase. Hemerocallis fulva L. is a common Traditional Chinese Medicine (TCM). Its flower buds are known to have ability to clear away heat and dampness, detoxify, and relieve depression. Ancient TCM literature shows that its roots have a beneficial effect in calming the spirit and even the temper in order to reduce the feeling of melancholy. Therefore, it is inferred that the root of Hemerocallis fulva L. can be used as a therapeutic medicine for depression. This study aims to uncover the pharmacological mechanism of the antidepressant effect of Hemerocallis Radix (HR) through network pharmacology method. During the analysis, 11 active components were obtained and screened using ADME—absorption, distribution, metabolism, and excretion— method. Furthermore, 267 HR targets and 740 depressive disorder (DD) targets were gathered from various databases. Then protein–protein interaction (PPI) network of HR and DD targets were constructed and cluster analysis was applied to further explore the connection between the targets. In addition, gene ontology (GO) enrichment and pathway analysis was applied to further verify that the biological process related to the target protein is associated with the occurrence of depression disorder. In conclusion, the most important bioactive components—anthraquinone, kaempferol, and vanillic acid—can alleviate depression symptoms by regulating MAOA, MAOB, and ESR1. The proposed network pharmacology strategy provides an integrating method to explore the therapeutic mechanism of multi-component drugs on a systematic level.

Chitosan, a naturally derived polymer, has been shown to possess antimicrobial and anti-inflammatory properties; however, little is known about the effect of chitosan on the immune responses and glutamic oxaloacetic transaminase (GOT), glutamic pyruvic transaminase (GPT) and lactate dehydrogenase (LDH) activities in normal mice. The aim of the present study was to investigate whether chitosan has an effect on the immune responses and GOT, GPT and LDH activities in mice in vivo. BALB/c mice were divided into four groups. The negative control group was treated with a normal diet; the positive control group was treated with a normal diet plus orally administered acetic acid and two treatment groups were treated with a normal diet plus orally administered chitosan in acetic acid at doses of 5 and 20 mg/kg, respectively, every other day for 24 days. Mice were weighed during the treatment, and following the treatment, blood was collected, and liver and spleen samples were isolated and weighted. The blood samples were used for measurement of white blood cell markers, and the spleen samples were used for analysis of phagocytosis, natural killer (NK) cell activity and cell proliferation using flow cytometry. The results indicated that chitosan did not markedly affect the body, liver and spleen weights at either dose. Chitosan increased the percentages of CD3 (T-cell marker), CD19 (B-cell marker), CD11b (monocytes) and Mac-3 (macrophages) when compared with the control group. However, chitosan did not affect the phagocytic activity of macrophages in peripheral blood mononuclear cells, although it decreased it in the peritoneal cavity. Treatment with 20 mg/kg chitosan led to a reduction in the cytotoxic activity of NK cells at an effector to target ratio of 25:1. Chitosan did not significantly promote B-cell proliferation in lipopolysaccharide-pretreated cells, but significantly decreased T-cell proliferation in concanavalin A-pretreated cells, and decreased the activity of GOT and GPT compared with that in the acetic acid-treated group,. In addition, it significantly increased LDH activity, to a level similar to that in normal mice, indicating that chitosan can protect against liver injury.

Chitosan and Agaricus blazei Murill (ABM) extracts possess antitumor activities. The aim of the present study was to investigate whether chitosan, ABM extract or the two in combination were effective against tumors in tumor‑bearing mice. The mice were subcutaneously injected with SK-Hep 1 cells and were then were divided into the following six groups: Group 1, control group; group 2, chitosan 5 mg/kg/day; group 3, chitosan 20 mg/kg/day; group 4, ABM (246 mg/kg/day) and chitosan (5 mg/kg/day) combined; group 5, ABM (984 mg/kg/day) and chitosan (20 mg/kg/day) combined; and group 6, ABM (984 mg/kg/day). The mice were treated with the different concentrations of chitosan, ABM or combinations of the two for 6 weeks. The levels of glutamic oxaloacetic transaminase (GOT), glutamic pyruvic transaminase (GPT) and vascular endothelial growth factor (VEGF), and tissue histopathological features were examined in the surviving animals. Based on the results of the investigation, the treatments performed in groups 2, 3 and 4 were identified as being capable of reducing the weights of the tumors, however, group 4, which was treated with chitosan (5 mg/kg/day) in combination with ABM (246 mg/kg/day) was able to reduce the levels of GOT and VEGF. As a result, treatment with chitosan in combination with ABM may offer potential in cancer therapy and requires further investigation.

Background and objective: Based on comprehensive network-pharmacology and molecular docking analysis, this study was intended to unveil the multiple mechanisms of Si-Ni-San (SNS) in treating anxious insomnia. Methods: The compounds of SNS were meticulously analyzed, selected and standardized with references to their pharmacological attributes. The components included chaihu (Bupleurum chinense DC.), baishao (Paeonia lactiflora Pall.), zhishi (Citrus aurantium L.) and gancao (Glycyrrhiza uralensis Fisch. ex DC.). We used the Traditional Chinese Medicine System Pharmacology (TCMSP) Database, Traditional Chinese Medicines Integrated Database (TCMID), GeneCards database, therapeutic target database (TTD) and comparative toxicogenomic database (CTD) to construct the components-compounds-targets networks and used Cytoscape 3.9.1 software to visualize the outcome. Afterwards, the STRING database and Cytoscape 3.9.1 software were utilized to construct and visualize the protein-protein interaction (PPI) network analysis. In addition, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were also conducted through the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The molecular docking program was carried out using AutoDock 4.2 software to understand interactions between target receptors and compound ligands selected for study. Results: We thoroughly sorted and filtered 31 pharmacologically active compounds from SNS. Subsequently, several potential target genes were predicted, of which there were 59 target genes distinctly associated with anxious insomnia. The PPI analysis indicated that the core target proteins included AKT1, IL6, TNF, SLC6A4, MAOA and GABRA2. The results of our study indicated that SNS potentially remediates anxious insomnia by reducing inflammation, neurodegeneration, and cell apoptosis of neurons. In addition, GO and KEGG enrichment analysis results indicated that SNS could modulate multiple aspects of anxious insomnia through mechanisms related to pathways of neuroactive ligand-receptor interaction. These pathways include various kinds of synaptic transmission pathways, and anti-inflammatory activity associated with response pathways. When we compared the components-compounds-targets networks and the compounds-targets-synaptic pathways networks, the five active compounds, including beta-Sitosterol, Kaempferol, Tetramethoxyluteolin, Isorhamnetin and Shinpterocarpin, were selected to conduct molecular docking experiments. Eleven target proteins, (AKT1, SLC6A4, ADRB2, MAOA, ACHE, ESR1, CYP3A4, CHRNA7, GABRA2, HTR2A and NOS3), which also play significant roles in regulating serotonergic, cholinergic, dopaminergic and GABAergic systems in the PPI network, were selected to act as receptors in molecular docking trials. The results showed that docking pairs isorhamnetin-AKT1, isorhamnetin-SLC6A4, β-sitosterol-MAOA, β- sitosterol-ACHE, isorhamnetin-CHRNA7 and shinpterocarpin-GABRA2 provided the most stable conformations of ligand-receptor binding between key compounds and core target proteins in the SNS. Conclusion: In the study, we offer a computational result, revealing that SNS may alleviate sleep disorders associated with anxiety through a “multi-compounds, multi-targets, and multi-pathways” mechanism. The network-pharmacology and molecular docking outcomes could theoretically confirm the anti-anxiety and anti-insomnia effects of SNS. Although this research is purely statistical and systematic without empirical validation, it serves as a stepping stone and cornerstone for subsequent experimental investigations.