OBJECTIVE:To investigate the possible mechanism underlying the effect of the Lushi Runzao decoction(路氏润燥汤)on Sjogren's syndrome using network pharmacology and to verify the mechanisms via animal experiments.M...OBJECTIVE:To investigate the possible mechanism underlying the effect of the Lushi Runzao decoction(路氏润燥汤)on Sjogren's syndrome using network pharmacology and to verify the mechanisms via animal experiments.METHODS:Available biological data on each drug in the Lushi Runzao decoction were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform,and the target proteins of Sjogren's syndrome were retrieved from the GeneCards database.Information regarding Sjogren's syndrome and the targets of the drugs were compared to obtain overlapping elements.This information was imported into the STRING platform to obtain a proteinprotein interaction network diagram,following which a“component-target”network diagram was constructed using screened drug components and target information via Cytoscape software.The database for annotation,visualization,and integrated discovery was used for Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathways analyses.Pathway information predicted by network pharmacology was verified using animal experiments.RESULTS:The Lushi Runzao decoction ameliorated Sjogren's syndrome mainly by influencing tumor necrosis factor as well as certain cytokines and chemokines.The decoction also influenced the interleukin-17 and advanced glycosylation end products(AGE)-receptor for AGE signaling pathways.CONCLUSION:The Lushi Runzao decoction ameliorates Sjogren's syndrome via multiple targets and multiple signaling pathways.Network pharmacology is useful for making a comprehensive prediction regarding the efficacy of the Lushi Runzao decoction,and this information may be helpful in clinical research.展开更多
In this article, annual evapotranspiration(ET) and net primary productivity (NPP) of fourtypes of vegetation were estimated for the Lushi basin,a subbasin of the Yellow River in China. These fourvegetation types inclu...In this article, annual evapotranspiration(ET) and net primary productivity (NPP) of fourtypes of vegetation were estimated for the Lushi basin,a subbasin of the Yellow River in China. These fourvegetation types include: deciduous broadleaf forest,evergreen needle leaf forest, dwarf shrub and grass.Biome-BGC--a biogeochemical process model wasused to calculate annual ET and NPP for eachvegetation type in the study area from 1954 to 2000.Daily microclimate data of 47 years monitored byLushi meteorological station was extrapolated tocover the basin using MT-CLIM, a mountainmicroclimate simulator. The output files of MT-CLIM were used to feed Biome-BGC. We usedaverage ecophysiological values of each type ofvegetation supplied by Numerical TerradynamicSimulation Group (NTSG) in the University ofMontana as input ecophysiological constants file.The estimates of daily NPP in early July and annualET on these four biome groups were comparedrespectively with field measurements and other studies.Daily gross primary production (GPP) of evergreenneedle leaf forest measurements were very close tothe output of Biome-BGC, but measurements ofbroadleaf forest and dwarf shrub were much smallerthan the simulation result. Simulated annual ET andNPP had a significant correlation with precipitation,indicating precipitation is the major environmentalfactor affecting ET and NPP in the study area.Precipitation also is the key climatic factor for theinterannual ET and NPP variations.展开更多
基金the National Natural Science Foundation of China:Based on the Intestinal flora/SCFAs/FFA2 Approach to Explore the Mechanism of Lushi Runzao Decoction in Regulating Th17/Treg Immune Balance to treat Sjogren's Syndrome(No.82104837)。
文摘OBJECTIVE:To investigate the possible mechanism underlying the effect of the Lushi Runzao decoction(路氏润燥汤)on Sjogren's syndrome using network pharmacology and to verify the mechanisms via animal experiments.METHODS:Available biological data on each drug in the Lushi Runzao decoction were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform,and the target proteins of Sjogren's syndrome were retrieved from the GeneCards database.Information regarding Sjogren's syndrome and the targets of the drugs were compared to obtain overlapping elements.This information was imported into the STRING platform to obtain a proteinprotein interaction network diagram,following which a“component-target”network diagram was constructed using screened drug components and target information via Cytoscape software.The database for annotation,visualization,and integrated discovery was used for Gene Ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathways analyses.Pathway information predicted by network pharmacology was verified using animal experiments.RESULTS:The Lushi Runzao decoction ameliorated Sjogren's syndrome mainly by influencing tumor necrosis factor as well as certain cytokines and chemokines.The decoction also influenced the interleukin-17 and advanced glycosylation end products(AGE)-receptor for AGE signaling pathways.CONCLUSION:The Lushi Runzao decoction ameliorates Sjogren's syndrome via multiple targets and multiple signaling pathways.Network pharmacology is useful for making a comprehensive prediction regarding the efficacy of the Lushi Runzao decoction,and this information may be helpful in clinical research.
文摘In this article, annual evapotranspiration(ET) and net primary productivity (NPP) of fourtypes of vegetation were estimated for the Lushi basin,a subbasin of the Yellow River in China. These fourvegetation types include: deciduous broadleaf forest,evergreen needle leaf forest, dwarf shrub and grass.Biome-BGC--a biogeochemical process model wasused to calculate annual ET and NPP for eachvegetation type in the study area from 1954 to 2000.Daily microclimate data of 47 years monitored byLushi meteorological station was extrapolated tocover the basin using MT-CLIM, a mountainmicroclimate simulator. The output files of MT-CLIM were used to feed Biome-BGC. We usedaverage ecophysiological values of each type ofvegetation supplied by Numerical TerradynamicSimulation Group (NTSG) in the University ofMontana as input ecophysiological constants file.The estimates of daily NPP in early July and annualET on these four biome groups were comparedrespectively with field measurements and other studies.Daily gross primary production (GPP) of evergreenneedle leaf forest measurements were very close tothe output of Biome-BGC, but measurements ofbroadleaf forest and dwarf shrub were much smallerthan the simulation result. Simulated annual ET andNPP had a significant correlation with precipitation,indicating precipitation is the major environmentalfactor affecting ET and NPP in the study area.Precipitation also is the key climatic factor for theinterannual ET and NPP variations.
