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1.
China Journal of Chinese Materia Medica ; (24): 5522-5532, 2021.
Article in Chinese | WPRIM | ID: wpr-921734

ABSTRACT

Seabuckthorn contains flavonoids, tannins, terpenoids, polysaccharides, and vitamins, which have anti-inflammation,anti-oxidation, liver protection, anti-cardiovascular disease, anti-aging, immune enhancing, anti-tumor, and anti-bacterial activities.We reviewed the papers focusing on the chemical constituents, pharmacological activities, and utilization of seabuckthorn. The quality markers(Q-markers) of seabuckthorn were predicted and analyzed based on original plant phylogeny, chemical composition correlation, traditional medicinal properties, pharmacodynamic correlation, traditional and extended efficacy, pharmacokinetics, metabolic processes, and measurable components. With this review, we aim to provide theoretical reference for the quality control and quality standard establishment of seabuckthorn, so as to promote the rational exploitation and utilization of seabuckthorn resources, and improve the healthy and sustainable development of seabuckthorn industry.


Subject(s)
Anti-Inflammatory Agents , Biomarkers , Drugs, Chinese Herbal , Flavonoids , Hippophae
2.
China Journal of Chinese Materia Medica ; (24): 636-644, 2020.
Article in Chinese | WPRIM | ID: wpr-1008549

ABSTRACT

In this paper, ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry(UHPLC-Q-TOF-MS)-based metabolomics approach was used to explore the mechanism of Danggui Buxue Tang(DBT) in treating type 2 diabetes mellitus(T2 DM). T2 DM mice model was induced by high-sugar and high-fat fodder and streptozotocin(STZ). The routine indexes such as body weight, blood glucose, plasma insulin, IL-6 and related organ indexes were determined. The UHPLC-Q-TOF-MS technique was used to analyze the metabolism profile of serum samples between the control group and model group, and multiple statistical analysis methods including principal component analysis(PCA) and orthogonal partial least squares discriminant analysis(OPLS-DA) were used to screen and identify biomarkers. Metabolic profiling revealed 16 metabolites as the most potential biomarkers distinguishing mice in model group from those in control group. The metabolomics pathway analysis(MetPA) was used to investigate the underlying metabolic pathways. Seven major metabolic pathways such the valine, leucine and isoleucine biosynthesis, glycerophospholipid metabolism, primary bile acid biosynthesis, taurine and hypotaurine metabolism, phenylalanine metabolism, fatty acid metabolism and biosynthesis of unsaturated fatty acid. Eleven metabolites such as taurocholic acid and palmitic acid were down-regulated in T2 DM mice, and five metabolites such as L-leucine and leukotriene E4 were up-regulated. Moreover, the sixteen biomar-kers of each administration group had a trend of returning to mice in control group. The significantly-altered metabolite levels indicated that DBT can improve the progression of type 2 diabetes by increasing insulin sensitivity, regulating sugar and lipid metabolism disorders, and relieving inflammation.


Subject(s)
Animals , Mice , Biomarkers/metabolism , Chromatography, High Pressure Liquid , Diabetes Mellitus, Experimental/metabolism , Diabetes Mellitus, Type 2/metabolism , Drugs, Chinese Herbal/therapeutic use , Mass Spectrometry , Metabolomics
3.
Journal of Preventive Medicine ; (12): 130-133,138, 2018.
Article in Chinese | WPRIM | ID: wpr-792706

ABSTRACT

Objective To understand the temporal and spatial characteristics of air pollutants in Ningbo. Methods The air quality index (AQI) data of Ningbo in 2016 was used to study the temporal and spatial variations of air pollutants, including SO2, NO2, PM10, CO, O3-8H, PM2.5. Results AQIs in 310 days were less than or equal to 100, and AQIs in the other 56 days were greater than 100. The levels of NO2 and PM2.5 were higher than National Ambient Air Quality Standard Class II, and those of SO2, PM10, CO, O3-8H meted Class II. PM2.5 was the primary air pollutant in Ningbo. The seasonal variation of air pollutant concentration was obvious. The concentrations of SO2, NO2, PM10, CO, PM2.5 were high in January and December and low in July, August and September. The concentrations of O3-8H were high in May, and low in December. In terms of spatial heterogeneity, the concentrations of air pollutants were generally higher in north and lower in south, but the specific distributions of different pollutants were different. Conclusion Air pollution is still a critical issue in Ningbo. The concentrations of air pollutants in the north are generally higher than that in the south, and change with seasonal characteristics.

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