Mechanistic insights into the use of rhubarb in diabetic kidney disease treatment using network pharmacology.

ABSTRACT: In this study, we predicted the core active compounds of rhubarb used in the treatment of diabetic kidney disease (DKD) and the related core gene targets and pathways using network pharmacological approaches.The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was used to identify active compounds of rhubarb. PharmMapper was used to predict the gene targets of active compounds, which were subsequently provided a standard nomenclature using the UniProt database. In addition, DKD-related target genes were predicted using GeneCards, Online Mendelian Inheritance in Man, and Therapeutic Target Database. The genes that were targeted both by rhubarb active compounds and implicated in DKD (hereafter referred to as overlapping target genes) were identified using Venny 2.1. A drug-target-disease network diagram was obtained using Cytoscape and a protein-protein interaction network diagram was constructed using the STRING database. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses of overlapping target proteins were performed using the Database for Annotation, Visualization and Integrated Discovery Bioinformatics Resources 6.8.Eighteen core active compounds of rhubarb were extracted, and 136 target genes of rhubarb were identified. Some of the active compounds revealed by the network pharmacological analysis were catechin, aloe-emodin, rhein, and emodin; certain core target proteins suggested by the protein-protein interaction network analysis were AKT1, PIK3R1, and SRC. The overlapping target genes were primarily involved in apoptosis and proteolysis, with the PI3K/Akt signaling pathway identified as significantly enriched.Network pharmacological strategies were used to identify core active compounds of rhubarb and their related pathways. We believe that our study will provide potential and effective novel targets to identify active compounds of rhubarb for treating DKD.

Ebullition Controls on CH4 Emissions in an Urban, Eutrophic River: A Potential Time-Scale Bias in Determining the Aquatic CH4 Flux.

Rivers and streams contribute significant quantities of methane (CH4) to the atmosphere. However, there is a lack of CH4 flux and ebullitive (bubble) emission data from urban rivers, which might lead to large underestimations of global aquatic CH4 emissions. Here, we conducted high-frequency surveys using the boundary layer model (BLM) supplemented with floating chambers (FCs) and bubble traps to investigate the seasonal and diurnal variability in CH4 emissions in a eutrophic urban river and to evaluate whether the contribution of bubbles is important. We found that ebullition contributed nearly 99% of CH4 emissions and varied on hourly to seasonal time scales, ranging from 0.83 to 230 mmol m-2 d-1, although diffusive emissions and CH4 concentrations in bubbles did not exhibit temporal variability. Ebullitive CH4 emissions presented high temperature sensitivity (r = 0.6 and p < 0.01) in this urban river, and eutrophication might have triggered this high temperature sensitivity. The ebullitive CH4 flux is more likely to be underestimated at low temperatures because capturing the bubble flux is more difficult, given the low frequency of ebullition events. This study suggests that future ebullition measurements on longer time scales are needed to accurately quantify the CH4 budgets of eutrophic urban rivers.