Lonicerae Japonicae Flos is a significant food and traditional Chinese medicine,known as plant antibiotics.It has rich chemical constituents and significant pharmacological effects.The antitumor activity of Lonicerae ...Lonicerae Japonicae Flos is a significant food and traditional Chinese medicine,known as plant antibiotics.It has rich chemical constituents and significant pharmacological effects.The antitumor activity of Lonicerae Japonicae Flos has been clarified,but the study on its spectrum-effect relationship has not been reported.The compounds responsible for its antitumor activity are still unknown.In this study,processed products of Lonicerae Japonicae Flos at different temperatures were taken as experimental materials,and SMMC-7721,A549,andMGC80-3 cells were tested.The orthogonal partial least squares regressionmethod was used to analyze the common compounds in different processed products and the antitumor activity.The results show that processed products have a stronger inhibitory effect on A549 cells and MGC80-3 cells than SMMC-7721 cells.Compounds such as secologanic acid,isochlorogenic acid A,serotonin,and chlorogenic acid play an important role in their antitumor effects.展开更多
This study aimed to investigate microbial succession and metabolic dynamics during the traditional fermentation of Hongqu aged vinegar,and explore the core functional microbes closely related to the formation of flavo...This study aimed to investigate microbial succession and metabolic dynamics during the traditional fermentation of Hongqu aged vinegar,and explore the core functional microbes closely related to the formation of flavor components.Microbiome analysis demonstrated that Lactobacillus,Acetobacter,Bacillus,Enterobacter,Lactococcus,Leuconostoc and Weissella were the predominant bacterial genera,while Aspergillus piperis,Aspergillus oryzae,Monascus purpureus,Candida athensensis,C.xylopsoci,Penicillium ochrosalmoneum and Simplicillium aogashimaense were the predominant fungal species.Correlation analysis revealed that Acetobacter was positively correlated with the production of tetramethylpyrazine,acetoin and acetic acid,Lactococcus showed positive correlation with the production of 2-nonanone,2-heptanone,ethyl caprylate,ethyl caprate,1-hexanol,1-octanol and 1-octen-3-ol,C.xylopsoci and C.rugosa were positively associated with the production of diethyl malonate,2,3-butanediyl diacetate,acetoin,benzaldehyde and tetramethylpyrazine.Correspondingly,non-volatile metabolites were also detected through ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry.A variety of amino acids and functional dipeptides were identified during the traditional brewing of Hongqu aged vinegar.Correlation analysis revealed that Lactobacillus was significantly associated with DL-lactate,indolelactic acid,D-(+)-3-phenyllactic acid,pimelic acid,pregabalin and 3-aminobutanoic acid.This study is useful for understanding flavor formation mechanism and developing effective strategies for the suitable strains selection to improve the flavor quality of Hongqu aged vinegar.展开更多
The identification of timber properties is important for safe application.Near Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental attributes.However,in...The identification of timber properties is important for safe application.Near Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental attributes.However,in its application,weak signals are extracted from complex,overlapping and changing information.This study focused on the stability of NIR modeling.The Orthogonal Partial Least Squares(OPLS)and Successive Projections Algorithm(SPA)eliminates noise and extracts effective spectra,and an ensemble learning method MIX-PLS,is applied to establish the model.The elastic modulus of timber is taken as an example,and 201 wood samples of three species,Xylosmacongesta(Lour.)Merr.,Acer pictum subsp.mono,and Betula pendula,samples were divided into three groups to investigate modelling performance.The results show that OPLS can preprocess the near-infrared spectroscopy information according to the target object in the face of the system error and reduce errors to minimum.SPA finally selects 13 spectral bands,simplifies the NIR spectral data and improves model accuracy.The Pearson's correlation coefficient of Calibration(Rc)and the Pearson's correlation coefficient of Prediction(Rp)of Mix Partial Least Squares(MIX-PLS)were 0.95 and 0.90,and Root Mean Square Error of Calibration(RMSEC)and Root Mean Square Error of Prediction(RMSEP)are 2.075 and 6.001,respectively,which shows the model has good generalization abilities.展开更多
基金supported by the Scientific and Technological Research Project of Henan Province(grant no.242102310549)the Key Research and Development Programme of Henan Province(grant no.231111312700)+2 种基金the National Natural Science Foundation of China(grant no.82104329)theNational Key Research andDevelopment Programme of China(grant no.2017YFC1702800)the special funds for starting scientific research of Henan University of Chinese Medicine(grant no.00104311-2021-1-41).
文摘Lonicerae Japonicae Flos is a significant food and traditional Chinese medicine,known as plant antibiotics.It has rich chemical constituents and significant pharmacological effects.The antitumor activity of Lonicerae Japonicae Flos has been clarified,but the study on its spectrum-effect relationship has not been reported.The compounds responsible for its antitumor activity are still unknown.In this study,processed products of Lonicerae Japonicae Flos at different temperatures were taken as experimental materials,and SMMC-7721,A549,andMGC80-3 cells were tested.The orthogonal partial least squares regressionmethod was used to analyze the common compounds in different processed products and the antitumor activity.The results show that processed products have a stronger inhibitory effect on A549 cells and MGC80-3 cells than SMMC-7721 cells.Compounds such as secologanic acid,isochlorogenic acid A,serotonin,and chlorogenic acid play an important role in their antitumor effects.
基金funded by Outstanding Talent of“Qishan Scholar”of Fuzhou University of China(GXRC21049)the Open Project Program of the Beijing Laboratory of Food Quality and Safety,Beijing Technology and Business University(BTBU)(FQS-201802,FQS-202008).
文摘This study aimed to investigate microbial succession and metabolic dynamics during the traditional fermentation of Hongqu aged vinegar,and explore the core functional microbes closely related to the formation of flavor components.Microbiome analysis demonstrated that Lactobacillus,Acetobacter,Bacillus,Enterobacter,Lactococcus,Leuconostoc and Weissella were the predominant bacterial genera,while Aspergillus piperis,Aspergillus oryzae,Monascus purpureus,Candida athensensis,C.xylopsoci,Penicillium ochrosalmoneum and Simplicillium aogashimaense were the predominant fungal species.Correlation analysis revealed that Acetobacter was positively correlated with the production of tetramethylpyrazine,acetoin and acetic acid,Lactococcus showed positive correlation with the production of 2-nonanone,2-heptanone,ethyl caprylate,ethyl caprate,1-hexanol,1-octanol and 1-octen-3-ol,C.xylopsoci and C.rugosa were positively associated with the production of diethyl malonate,2,3-butanediyl diacetate,acetoin,benzaldehyde and tetramethylpyrazine.Correspondingly,non-volatile metabolites were also detected through ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry.A variety of amino acids and functional dipeptides were identified during the traditional brewing of Hongqu aged vinegar.Correlation analysis revealed that Lactobacillus was significantly associated with DL-lactate,indolelactic acid,D-(+)-3-phenyllactic acid,pimelic acid,pregabalin and 3-aminobutanoic acid.This study is useful for understanding flavor formation mechanism and developing effective strategies for the suitable strains selection to improve the flavor quality of Hongqu aged vinegar.
基金supported financially by the China State Forestry Administration“948”projects(2015-4-52)Heilongjiang Natural Science Foundation(C2017005)。
文摘The identification of timber properties is important for safe application.Near Infrared Spectroscopy(NIRS)technology is widely-used because of its simplicity,efficiency,and positive environmental attributes.However,in its application,weak signals are extracted from complex,overlapping and changing information.This study focused on the stability of NIR modeling.The Orthogonal Partial Least Squares(OPLS)and Successive Projections Algorithm(SPA)eliminates noise and extracts effective spectra,and an ensemble learning method MIX-PLS,is applied to establish the model.The elastic modulus of timber is taken as an example,and 201 wood samples of three species,Xylosmacongesta(Lour.)Merr.,Acer pictum subsp.mono,and Betula pendula,samples were divided into three groups to investigate modelling performance.The results show that OPLS can preprocess the near-infrared spectroscopy information according to the target object in the face of the system error and reduce errors to minimum.SPA finally selects 13 spectral bands,simplifies the NIR spectral data and improves model accuracy.The Pearson's correlation coefficient of Calibration(Rc)and the Pearson's correlation coefficient of Prediction(Rp)of Mix Partial Least Squares(MIX-PLS)were 0.95 and 0.90,and Root Mean Square Error of Calibration(RMSEC)and Root Mean Square Error of Prediction(RMSEP)are 2.075 and 6.001,respectively,which shows the model has good generalization abilities.
