Prevention effect of total ginsenosides and ginseng extract from Panax ginseng on cyclophosphamide-induced immunosuppression in mice.

Oral decoction is widely applied in traditional Chinese medicines. The polysaccharides of decoction promote the exposure of small molecules and increase their bioavailability. This study mainly compared the component and activities of total ginsenosides (TGS) and ginseng extract (GE) on immunosuppressed mice induced by cyclophosphamide. Thirty-two mice were randomly divided into control, model, TGS, and GE groups. The mice were orally administered for 28 days and then injected with cyclophosphamide on the last four days. The results of component analysis showed the total content of 12 ginsenosides in TGS (67.21%) was higher than GE (2.04%); the total content of 17 amino acids in TGS (1.41%) was lower than GE (5.36%); the total content of 10 monosaccharides was similar in TGS (74.12%) and GE (76.36%). The animal results showed that both TGS and GE protected the hematopoietic function of bone marrow by inhibiting cell apoptosis, and recovering the normal cell cycle of BM; maintained the dynamic balance between the Th1 and Th2 cells; also protected the spleen, thymus, and liver. Meanwhile, TGS and GE protected the intestinal bacteria of immunosuppressed mice by increasing the abundance of lactobacillus and decreasing the abundance of the odoribacter and clostridia_UCG-014. The prevention effect of GE was superior to TGS in some parameters. In conclusion, TGS and GE protected the immune function of immunosuppressed mice induced by cyclophosphamide. Meanwhile, GE showed higher bioavailability and bioactivity compared with TGS, because the synergistic effect of polysaccharides and ginsenosides plays an important role in protecting the immune function.

Divergence of Root Microbiota in Different Habitats based on Weighted Correlation Networks.

The root microbiome plays an important role in plant growth and environmental adaptation. Network analysis is an important tool for studying communities, which can effectively explore the interaction relationship or co-occurrence model of different microbial species in different environments. The purpose of this manuscript is to provide details on how to use the weighted correlation network algorithm to analyze different co-occurrence networks that may occur in microbial communities due to different ecological environments. All analysis of the experiment is performed in the WGCNA package. WGCNA is an R package for weighted correlation network analysis. The experimental data used to demonstrate these methods were microbial community data from the NCBI (National Center for Biotechnology Information) database for three niches of the rice (Oryza sativa) root system. We used the weighted correlation network algorithm to construct co-abundance networks of microbial community in each of the three niches. Then, differential co-abundance networks among endosphere, rhizoplane and rhizosphere soil were identified. In addition, the core genera in network were obtained by the "WGCNA" package, which plays an important regulated role in network functions. These methods enable researchers to analyze the response of microbial network to environmental disturbance and verify different microbial ecological response theories. The results of these methods show that the significant differential microbial networks identified in the endosphere, rhizoplane and rhizosphere soil of rice.