A combined method of high performance liquid chromatograph-elecrtrospray-ionization mass spectrometer（HPLC-ESI-MS/MS） coupled with a photodiode array detector（HPLC-DAD） and principal component analysis（PCA） was ...A combined method of high performance liquid chromatograph-elecrtrospray-ionization mass spectrometer（HPLC-ESI-MS/MS） coupled with a photodiode array detector（HPLC-DAD） and principal component analysis（PCA） was applied to the qualitative and quantitative analyses of alkaloids in Cortex Phellodendri（CP） samples, and to the differentiation of two species of CP, Cortex Phellodendri Chinensis（CPC） and Cortex Phellodendri Amurensis（CPA）. Twenty-two peaks appeared in the HPLC-MS base peak chromatogram of CP detected by the HPLC-ESI-MS/MS analysis, and the alkaloids were identified according to the MSn data, the known MS fragmentation rules and the literature data. Five alkaloids including berberine, palmatine, jatrorrhizine, phellodendrine and magnoflorine were simultaneously determinated by the HPLC-DAD. Berberine was the primary component in all CP samples, and the contents of berberine and palmatine were exploited to be two critical parameters for effective discrimination between the two species of CP. The average content of berberine in CPC（58.75 mg/g） was higher than that in CPA（9.16 mg/g）, while the content of palmatine was less, only 0.25 mg/g in CPC and 4.19 mg/g in CPA. With the use of PCA, samples datasets were separated successfully into two different clusters corresponding to the two species, and berberine, pahnatine, phellodendrine and magnoflorine contribute most to the above mentioned calssifying . The proposed method oroved to be a useful tool in the aualitv control of Chinese herbal medicines.展开更多
Tropical cyclone(TC)annual frequency forecasting is significant for disaster prevention and mitigation in Guangdong Province.Based on the NCEP-NCAR reanalysis and NOAA Extended Reconstructed global sea surface tempera...Tropical cyclone(TC)annual frequency forecasting is significant for disaster prevention and mitigation in Guangdong Province.Based on the NCEP-NCAR reanalysis and NOAA Extended Reconstructed global sea surface temperature(SST)V5 data in winter,the TC frequency climatic features and prediction models have been studied.During 1951-2019,353 TCs directly affected Guangdong with an annual average of about 5.1.TCs have experienced an abrupt change from abundance to deficiency in the mid to late 1980 with a slightly decreasing trend and a normal distribution.338 primary precursors are obtained from statistically significant correlation regions of SST,sea level pressure,1000hPa air temperature,850hPa specific humidity,500hPa geopotential height and zonal wind shear in winter.Then those 338 primary factors are reduced into 19 independent predictors by principal component analysis(PCA).Furthermore,the Multiple Linear Regression(MLR),the Gaussian Process Regression(GPR)and the Long Short-term Memory Networks and Fully Connected Layers(LSTM-FC)models are constructed relying on the above 19 factors.For three different kinds of test sets from 2010 to 2019,2011 to 2019 and 2010 to 2019,the root mean square errors(RMSEs)of MLR,GPR and LSTM-FC between prediction and observations fluctuate within the range of 1.05-2.45,1.00-1.93 and 0.71-0.95 as well as the average absolute errors(AAEs)0.88-1.0,0.75-1.36 and 0.50-0.70,respectively.As for the 2010-2019 experiment,the mean deviations of the three model outputs from the observation are 0.89,0.78 and 0.56,together with the average evaluation scores 82.22,84.44 and 88.89,separately.The prediction skill comparisons unveil that LSTM-FC model has a better performance than MLR and GPR.In conclusion,the deep learning model of LSTM-FC may shed light on improving the accuracy of short-term climate prediction about TC frequency.The current research can provide experience on the development of deep learning in this field and help to achieve further progress of TC disaster prevention and mitigation in Guangdong Province.展开更多
文摘目的探讨系统性红斑狼疮(systemic lupus erythematosus,SLE)患者血清上皮细胞黏附分子(epithelial cell adhesion molecule,EpCAM)和可溶性共刺激分子B7 H3(soluble costimulatory molecule B7-H3,sB7-H3)表达水平及其与疾病活动性的相关性。方法选取2020年6月~2022年5月汉中市中心医院血液风湿科收治的SLE患者135例作为SLE组,另选取同期健康体检者120例作为对照组。采用酶联免疫吸附法(ELISA)检测两组血清EpCAM和sB7-H3水平。依据SLE疾病活动指数(SLEDAI)评分将SLE组患者分为活动期组(n=75)和缓解期组(n=60)。采用Pearson相关性分析SLE组血清EpCAM与sB7-H3水平的相关性,Spearman相关性分析两者与SLEDAI评分的相关性。采用受试者工作特征(ROC)曲线评价血清EpCAM和sB7-H3区分SLE患者缓解期及活动期的价值。结果与对照组比较,SLE组患者血清EpCAM(11.38±3.32ng/ml vs 3.54±1.15ng/ml)水平升高,sB7-H3(12.18±3.54ng/ml vs 20.15±5.26ng/ml)水平降低,差异具有统计学意义(t=24.586,14.330,均P<0.05)。与缓解期组比较,活动期组患者血清EpCAM(13.50±3.89ng/ml vs 8.72±2.61ng/ml)水平升高,sB7-H3(9.79±2.84ng/ml vs 15.17±4.42ng/ml)水平降低,差异具有统计学意义(t=8.159,8.564,均P<0.05)。Pearson相关性分析显示,SLE组血清EpCAM与sB7-H3水平呈负相关(r=-0.607,P<0.05);Spearman相关性分析显示,SLE组血清EpCAM水平与SLEDAI评分呈正相关(r=0.475,P<0.05),sB7-H3水平与SLEDAI评分呈负相关(r=-0.664,P<0.05)。血清EpCAM,sB7-H3联合区分SLE患者缓解期及活动期ROC曲线下面积(AUC)显著大于EpCAM单独区分的AUC(Z=1.978,P=0.048)及sB7 H3单独区分的AUC(Z=2.277,P=0.023)。结论SLE患者血清EpCAM水平升高,sB7-H3水平降低,两者与患者疾病活动性关系密切。
基金Supported by the National Natural Science Foundation of China(No30725045)the Foundation of Eleventh Five-Year-Plan of China(No2008ZX09202-002)+1 种基金the Shanghai Leading Academic Discipline Project, China(NoB906)the Scientific Foundation of Shanghai City, China(No07DZ19702)
文摘A combined method of high performance liquid chromatograph-elecrtrospray-ionization mass spectrometer（HPLC-ESI-MS/MS） coupled with a photodiode array detector（HPLC-DAD） and principal component analysis（PCA） was applied to the qualitative and quantitative analyses of alkaloids in Cortex Phellodendri（CP） samples, and to the differentiation of two species of CP, Cortex Phellodendri Chinensis（CPC） and Cortex Phellodendri Amurensis（CPA）. Twenty-two peaks appeared in the HPLC-MS base peak chromatogram of CP detected by the HPLC-ESI-MS/MS analysis, and the alkaloids were identified according to the MSn data, the known MS fragmentation rules and the literature data. Five alkaloids including berberine, palmatine, jatrorrhizine, phellodendrine and magnoflorine were simultaneously determinated by the HPLC-DAD. Berberine was the primary component in all CP samples, and the contents of berberine and palmatine were exploited to be two critical parameters for effective discrimination between the two species of CP. The average content of berberine in CPC（58.75 mg/g） was higher than that in CPA（9.16 mg/g）, while the content of palmatine was less, only 0.25 mg/g in CPC and 4.19 mg/g in CPA. With the use of PCA, samples datasets were separated successfully into two different clusters corresponding to the two species, and berberine, pahnatine, phellodendrine and magnoflorine contribute most to the above mentioned calssifying . The proposed method oroved to be a useful tool in the aualitv control of Chinese herbal medicines.
基金National Key R&D Program of China(2017YFA0605004)Guangdong Major Project of Basic and Applied Basic Research(2020B0301030004)+4 种基金National Basic R&D Program of China(2018YFA0606203)Special Fund of China Meteorological Administration for Innovation and Development(CXFZ2021J026)Special Fund for Forecasters of China Meteorological Administration(CMAYBY2020-094)Graduate Independent Exploration and Innovation Project of Central South University(2021zzts0477)Science and Technology Planning Program of Guangdong Province(20180207)。
文摘Tropical cyclone(TC)annual frequency forecasting is significant for disaster prevention and mitigation in Guangdong Province.Based on the NCEP-NCAR reanalysis and NOAA Extended Reconstructed global sea surface temperature(SST)V5 data in winter,the TC frequency climatic features and prediction models have been studied.During 1951-2019,353 TCs directly affected Guangdong with an annual average of about 5.1.TCs have experienced an abrupt change from abundance to deficiency in the mid to late 1980 with a slightly decreasing trend and a normal distribution.338 primary precursors are obtained from statistically significant correlation regions of SST,sea level pressure,1000hPa air temperature,850hPa specific humidity,500hPa geopotential height and zonal wind shear in winter.Then those 338 primary factors are reduced into 19 independent predictors by principal component analysis(PCA).Furthermore,the Multiple Linear Regression(MLR),the Gaussian Process Regression(GPR)and the Long Short-term Memory Networks and Fully Connected Layers(LSTM-FC)models are constructed relying on the above 19 factors.For three different kinds of test sets from 2010 to 2019,2011 to 2019 and 2010 to 2019,the root mean square errors(RMSEs)of MLR,GPR and LSTM-FC between prediction and observations fluctuate within the range of 1.05-2.45,1.00-1.93 and 0.71-0.95 as well as the average absolute errors(AAEs)0.88-1.0,0.75-1.36 and 0.50-0.70,respectively.As for the 2010-2019 experiment,the mean deviations of the three model outputs from the observation are 0.89,0.78 and 0.56,together with the average evaluation scores 82.22,84.44 and 88.89,separately.The prediction skill comparisons unveil that LSTM-FC model has a better performance than MLR and GPR.In conclusion,the deep learning model of LSTM-FC may shed light on improving the accuracy of short-term climate prediction about TC frequency.The current research can provide experience on the development of deep learning in this field and help to achieve further progress of TC disaster prevention and mitigation in Guangdong Province.
