The main chemical constituents of the genus Polygonum(Polygonaceae)are flavonoids,quinones,phenylpropanoids,and terpenoids,which show anticancer,antitumor,anti-oxidative,anti-inflammatory,analgesic,antibacterial,insec...The main chemical constituents of the genus Polygonum(Polygonaceae)are flavonoids,quinones,phenylpropanoids,and terpenoids,which show anticancer,antitumor,anti-oxidative,anti-inflammatory,analgesic,antibacterial,insecticidal,and other pharmacological effects.This paper summarizes research on the chemical constituents and pharmacological effects of compounds from the genus Polygonum in last15years.展开更多
Objective To identify the compounds withα-glucosidase inhibitory activity from Clerodendrum bungei Steud(Chou Mu Dan,臭牡丹)using HPLC-ESI-QTOF-MS/MS.Methods The ethanol extracts of Clerodendrum bungei Steud(Chou Mu ...Objective To identify the compounds withα-glucosidase inhibitory activity from Clerodendrum bungei Steud(Chou Mu Dan,臭牡丹)using HPLC-ESI-QTOF-MS/MS.Methods The ethanol extracts of Clerodendrum bungei Steud(Chou Mu Dan,臭牡丹)were partitioned with petroleum ether,ethyl acetate,n-butanol,and water.The assay forα-glucosidase inhibitory activity revealed strongα-glucosidase inhibitory activity in the ethyl acetate fraction,and the bioactive compounds present in this fraction were identified by the HPLCESI-QTOF-MS/MS method.Results A total of 29 compounds were determined,among the identified bioactive components;these included 12 phenylethanoid glycosides(compounds 5,6,17,20-22,24),7 flavonoids(compounds 10,19,23,25-28),5 phenolic acids(compounds 2-4,7,9),and 5 other compounds.Compounds 2-4,7,9-10,12-13,15,19,and 26,with a potentialα-glucosidase inhibitory activity,have been reported previously.Conclusions Our results show that the methodology used in this study is feasible,credible,and rapid in identifying known compounds and also for characterizing new natural glucosidase inhibitory candidates from Clerodendrum bungei Steud(Chou Mu Dan,臭牡丹).展开更多
Objective To establish early detection and diagnosis for bladder cancer.Methods In the current study,a metabolomics strategy was used to profile bladder cancer urine metabolites in mice and to further characterize the...Objective To establish early detection and diagnosis for bladder cancer.Methods In the current study,a metabolomics strategy was used to profile bladder cancer urine metabolites in mice and to further characterize the disease status at different stages.In addition,some chemometrics algorithms were adopted to analyze the metabolites fingerprints,including baseline removal and retention time shift,to overcome variations in the experimental process.After processing,metabolites were qualitatively and quantitatively analyzed in each sample at different stages.Finally,a random forest algorithm was used to discriminate the differences among different groups.Results Four potential biomarkers,including glyceric acid,(R*,R*)-2,3-Dihydroxybutanoic acid,N-(1-oxohexyl)-glycine and D-Turanose,were discovered by exploring the characteristics of different groups.Conclusion These results suggest that combining chemometrics with the metabolites profile is an effective approach to aid in clinical diagnosis.展开更多
基金support from the National Natural Science Foundation of China (No. 81374062 and No. 81673579)Hunan Province University Innovation Platform Open Fund (Project 13K077)
文摘The main chemical constituents of the genus Polygonum(Polygonaceae)are flavonoids,quinones,phenylpropanoids,and terpenoids,which show anticancer,antitumor,anti-oxidative,anti-inflammatory,analgesic,antibacterial,insecticidal,and other pharmacological effects.This paper summarizes research on the chemical constituents and pharmacological effects of compounds from the genus Polygonum in last15years.
基金the funding support from the China National Natural Science Foundation Funding Project(NO.81503452)Natural Science Foundation of Hunan Province,China(No.14JJ4066)
文摘Objective To identify the compounds withα-glucosidase inhibitory activity from Clerodendrum bungei Steud(Chou Mu Dan,臭牡丹)using HPLC-ESI-QTOF-MS/MS.Methods The ethanol extracts of Clerodendrum bungei Steud(Chou Mu Dan,臭牡丹)were partitioned with petroleum ether,ethyl acetate,n-butanol,and water.The assay forα-glucosidase inhibitory activity revealed strongα-glucosidase inhibitory activity in the ethyl acetate fraction,and the bioactive compounds present in this fraction were identified by the HPLCESI-QTOF-MS/MS method.Results A total of 29 compounds were determined,among the identified bioactive components;these included 12 phenylethanoid glycosides(compounds 5,6,17,20-22,24),7 flavonoids(compounds 10,19,23,25-28),5 phenolic acids(compounds 2-4,7,9),and 5 other compounds.Compounds 2-4,7,9-10,12-13,15,19,and 26,with a potentialα-glucosidase inhibitory activity,have been reported previously.Conclusions Our results show that the methodology used in this study is feasible,credible,and rapid in identifying known compounds and also for characterizing new natural glucosidase inhibitory candidates from Clerodendrum bungei Steud(Chou Mu Dan,臭牡丹).
基金funding support from the Natural Science Foundation of China (No. 81673585 and No. 81603400)Hunan Provincial Key Laboratory of Diagnostics in Chinese Medicine Open Fund (No. 2015ZYZD13 and No. 2015ZYZD10)+2 种基金Key research and development project of Hunan Province Science and Technology (No. 2016SK2048)Innovative Project for Post-graduate of Hunan University of Chinese Medicine (No. 2017CX05)the National Standard Project of Chinese Medicine (No. ZYBZH-Y-HUN-21)
文摘Objective To establish early detection and diagnosis for bladder cancer.Methods In the current study,a metabolomics strategy was used to profile bladder cancer urine metabolites in mice and to further characterize the disease status at different stages.In addition,some chemometrics algorithms were adopted to analyze the metabolites fingerprints,including baseline removal and retention time shift,to overcome variations in the experimental process.After processing,metabolites were qualitatively and quantitatively analyzed in each sample at different stages.Finally,a random forest algorithm was used to discriminate the differences among different groups.Results Four potential biomarkers,including glyceric acid,(R*,R*)-2,3-Dihydroxybutanoic acid,N-(1-oxohexyl)-glycine and D-Turanose,were discovered by exploring the characteristics of different groups.Conclusion These results suggest that combining chemometrics with the metabolites profile is an effective approach to aid in clinical diagnosis.
