Objective To investigate the relationship of the1675A/G polymorphism of AT2 gene with the therapeutic effect of indapamide sustained release tablets in female patients with primary hypertension.Methods Two hundred and twenty female patients with primary hypertension were treated with Indapamide Sustained Release Tablets ( 1.5 mg · qd) for 8 weeks.The blood samples from the patients were collect to determine AT2 gene polymorphism by PCR combined with HRM and sequencing.Results Two hundred and five patients completed the test.In female patients,the therapeutic efficacy of indapamide sustained telease tablets among different AT2R genotypes( AA:70.6％,AG:71.6％,GG:71.4％ ) showed no significant difference ( x2=2.53,P=0.49 ),neither do the decline of BP after therapy ( F=0.39 and 0.19 respecrively,P ＞ 0.05).Conclusion The AT2 genotype was assumed to be not correlated to the blood pressure lowering response to Indapamide Sustained Release Tablets in female primary hypertension patients.

GEP (Gene expression programming) is a new genetic algorithm, and it has been proved to be excellent in function finding. In this paper, for the purpose of setting up a diagnostic model, GEP is used to deal with the data of heart disease. Eight variables, Sex, Chest pain, Blood pressure, Angina, Peak, Slope, Colored vessels and Thal, are picked out of thirteen variables to form a classified function. This function is used to predict a forecasting set of 100 samples, and the accuracy is 87%. Other algorithms such as SVM (Support vector machine) are applied to the same data and the forecasting results show that GEP is better than other algorithms.
Algorithms ; Artificial Intelligence ; Computational Biology ; methods ; Data Mining ; Diagnosis, Computer-Assisted ; instrumentation ; methods ; Gene Expression Profiling ; methods ; Gene Regulatory Networks ; genetics ; Heart Diseases ; diagnosis ; Humans ; Models, Cardiovascular

Complex systems exist widely,including medicines from natural products,functional foods,and bio-logical samples.The biological activity of complex systems is often the result of the synergistic effect of multiple components.In the quality evaluation of complex samples,multicomponent quantitative analysis(MCQA)is usually needed.To overcome the difficulty in obtaining standard products,scholars have proposed achieving MCQA through the"single standard to determine multiple components(SSDMC)"approach.This method has been used in the determination of multicomponent content in natural source drugs and the analysis of impurities in chemical drugs and has been included in the Chinese Pharmacopoeia.Depending on a convenient(ultra)high-performance liquid chromatography method,how can the repeatability and robustness of the MCQA method be improved?How can the chromatography conditions be optimized to improve the number of quantitative components?How can computer software technology be introduced to improve the efficiency of multicomponent analysis(MCA)?These are the key problems that remain to be solved in practical MCQA.First,this review article summarizes the calculation methods of relative correction factors in the SSDMC approach in the past five years,as well as the method robustness and accuracy evaluation.Second,it also summarizes methods to improve peak capacity and quantitative accuracy in MCA,including column selection and two-dimensional chromatographic analysis technology.Finally,computer software technologies for predict-ing chromatographic conditions and analytical parameters are introduced,which provides an idea for intelligent method development in MCA.This paper aims to provide methodological ideas for the improvement of complex system analysis,especially MCQA.

Objective:To analyze the changes of fasting plasma glucose(FPG)level before and after menopause.Methods:Kailuan health checkup cohort was used to extract data of women aged≥18 years who participated in the first physical examination of Kailuan physical examination cohort and had menopausal age at the end of the seventh physical examination. A total of 3 749 women with 22 057 physical examination records were included in the analysis. Natural logarithmic transformation was applied to FPG, and a segmented linear mixed-effects model was used to analyze the changes in ln-transformed FPG before and after menopause. Additionally, an interaction analysis was performed to assess the multiplicative effect of baseline age and baseline body mass index(BMI)on ln-transformed FPG concerning pre- and post-menopausal periods.Results:The average age of the first physical examination for women in this study was (45.63±4.52)years, the median menopausal age was 51(50~53)years, and the median number of physical examinations was 6(5~7)times. The results of the piecewise linear mixed effect model showed that lnFPG increased from 1 year before menopause, with an average annual increase of 0.021 mmol/L, and continued to increase from menopause to 5 years after menopause, with an average annual increase of 0.007 mmol/L. LnFPG tended to be stable after 5 years of menopause. Baseline age could affect the changes of lnFPG before and after menopause, and there was a negative multiplicative interaction between baseline age ≥45 years and the time period from 6 years to 1 year before menopause( P=0.032). Women with baseline age ≥45 years had a higher average annual increase in lnFPG from 1 year before menopause to 5 years after menopause than women with baseline age <45 years( P<0.05). On lnFPG, there was a positive multiplicative interaction between baseline BMI and time segments around menopause. Compared to women with BMI <24.0 kg/m 2, obese women displayed more annual increase in lnFPG from 6 years to 1 year before menopause as well as from menopause to 5 years after menopause( P<0.05). Conclusions:Menopause has an adverse impact on FPG, with the most significant changes occurring within the period of one year before menopause and up to five years after menopause. Age and BMI significantly influence the changes in FPG before and after menopause.

ObjectiveTo investigate the influence of concentration ratio（CR） between the internal reference and target components on the quantitative accuracy of quantitative analysis of multi-components by single marker（QAMS） by taking ginsenosides as an example. MethodUltra performance liquid chromatography（UPLC） was employed， the contents of nine components in Ginseng Radix et Rhizoma（ginsenosides Rg₁， Re， Rf， Rh₁， Rb₁， Rc， Rb₂， Rb₃， Rd） were determined by external standard method（ES）. Using ginsenoside Rg₁ as the internal reference， the contents of the remaining 8 ginsenosides were determined by QAMS， and the quantitative results were compared with those of ES to evaluate the quantitative accuracy of the established QAMS. According to the contents of these 9 ginsenosides， the simulated sample solutions with different CRs of ginsenoside Rg₁ to ginsenosides Rf， Rb₂， Rd were prepared with the reference substance（CR=100∶1， 10∶1， 5∶1， 2∶1， 1∶1， 0.5∶1， 0.25∶1）， in order to validate the effect of the CRs between the internal reference and other components on the quantitative accuracy of the QAMS. ResultThe results of ginsenosides Re， Rf， Rb₁， Rc， Rb₂ calculated by the two methods were the same with the relative standard deviation（RSD）<3%， however， the results of ginsenosides Rh₁， Rb₃ and Rd calculated by the two methods were different with RSDs of 7.06%-9.61%. According to the result of the simulated sample solution， the difference between the calculated results of ES and QAMS was large when the CR between the internal reference（ginsenoside Rg₁） and other components was 5 or 10 or even higher. ConclusionThe quantitative error of QAMS will increase when the CR between the quantitative component and the internal reference is too large， so it is suggested that when establishing the QAMS， the components with close concentration to the internal reference should be selected for quantification.

ObjectiveIn this study， the two different origins of Lycii Cortex in the 2020 edition of Chinese Pharmacopoeia were determined to analyze their chemical consistency by comparing their main chemical composition. MethodThirty representative batches of Lycii Cortex were collected， content determination and fingerprint analysis methods were established by ultra performance liquid chromatography-photodiode array detector （UPLC-PDA） combining with multivariate statistical analysis to evaluate the similarities and differences between two origins of Lycii Cortex. Respectively by the mobile phase of acetonitrile （A）-0.15% trifluoroacetic acid aqueous solution （B） and the mobile phase of acetonitrile （A）-0.1% formic acid aqueous solution （B） for gradient elution （0-4 min， 5%-12%A； 4-8 min， 12%A； 8-12 min， 12%-14%A； 12-15 min， 14%-30%A； 15-17 min， 30%-40%A； 17-18 min， 40%-90%A）， and the detection wavelength was set at 280 nm. ResultThis established content determination and fingerprint methods had good precision， stability and repeatability. The similarities of 30 batches of Lycii Cortex were above 0.90 by comparing with the control fingerprint， and the eight common peaks in fingerprints of Lycii Cortex from Lycium barbarum and L. chinense were all phenolic amides， which were kukoamine B， N-（4，9，13-triazatridecan-1-yl）-3，4-dihydroxybenzenepropanamide， feruloylputrescine， N₁，N₅-bis （dihydrocaffeoyl） spermidine or N₅，N₁₀-bis （dihydrocaffeoyl） spermidine， N₅-caffeoyl-N₁₀-dihydrocaffeoylspermidine， N₅-dihydrocaffeoyl-N₁₀-caffeoylspermidine， N₁，N₅-bis （caffeoyl） spermidine and lyciumin A. Among them， the content ranges of kukoamine B in Lycii Cortex from L. chinense and L. barbarum were 1.22%-8.18%， 2.52%-12.24%， respectively. ConclusionThe established UPLC analysis method can be used for the content determination and fingerprint analysis of Lycii Cortex. This study indicates that chemical contour of Lycii Cortex from L. barbarum and L. chinense are similar， there are no significant differences in kukoamine B content， and they have consistency in the chemical composition.

ObjectiveTo establish an ultra-high performance liquid chromatography-tandem triple quadrupole mass spectrometry（UHPLC-QqQ-MS） for determination of the active ingredients in Erdongtang， and to predict the targets and pathways of anti-insulin resistance action of this formula. MethodThe analysis was performed on an ACQUITY UPLC BEH C₁₈ column（2.1 mm×100 mm， 1.7 μm） with the mobile phase of 0.1% formic acid aqueous solution（A）-acetonitrile（B） for gradient elution（0-3 min， 90%-87%A； 3-6 min， 87%-86%A； 6-9 min， 86%-83%A； 9-11 min， 83%-75%A； 11-18 min， 75%-70%A； 18-19 min， 70%-52%A； 19-22 min， 52%A； 22-25 min， 52%-5%A； 25-27 min， 5%-90%A； 27-30 min， 90%A）. The contents of active ingredients in Erdongtang was detected by electrospray ionization（ESI） and multiple reaction monitoring（MRM） mode under positive and negative ion modes. On this basis， network pharmacology was applied to predict the targets and pathways of Erdongtang exerting anti-insulin resistance effect. ResultThe 20 active ingredients in Erdongtang showed good linear relationships within a certain mass concentration range， and the precision， stability， repeatability and recovery rate were good. The results of determination showed that the ingredients with high content in 15 batches of samples were baicalein（1 259.39-1 635.78 mg·L^-1）， baicalin（1 078.37-1 411.52 mg·L^-1）， the ingredients with medium content were mangiferin（148.59-217.04 mg·L^-1）， timosaponin BⅡ（245.10-604.89 mg·L^-1）， quercetin-3-O-glucuronide（89.30-423.26 mg·L^-1）， rutin（46.91-1 553.61 mg·L^-1）， glycyrrhizic acid（55.97-391.47 mg·L^-1）， neomangiferin（37.45-127.03 mg·L^-1）， nuciferine（0.89-63.48 mg·L^-1）， hyperoside（6.96-136.78 mg·L^-1）， liquiritin（30.89-122.78 mg·L^-1）， liquiritigenin（26.64-110.67 mg·L^-1）， protodioscin（58.57-284.26 mg·L^-1）， the ingredients with low content were wogonin（7.16-20.74 mg·L^-1）， pseudoprotodioscin（5.49-22.96 mg·L^-1）， ginsenoside Rb₁（7.31-23.87 mg·L^-1）， ginsenoside Rg₁（10.78-28.33 mg·L^-1）， ginsenoside Re（7.78-24.76 mg·L^-1）， ophiopogonin D（2.08-4.29 mg·L^-1）， methylophiopogonanone A（0.74-1.67 mg·L^-1）. The results of network pharmacology indicated that the mechanism of anti-insulin resistance exerted by Erdongtang might be related to the phosphatidylinositol 3-kinase/protein kinase B（PI3K/Akt） signaling pathway. ConclusionThe established UHPLC-QqQ-MS has the advantages of simple sample processing， strong exclusivity and high sensitivity， and can simultaneously determine the contents of the main ingredients from seven herbs in Erdongtang， which can lay the foundation for the development of Erdongtang compound preparations. The results of the network pharmacology can provide a reference for the mechanism study of Erdongtang in the treatment of type 2 diabetes mellitus.

ObjectiveTo establish fingerprint profiles and a quantitative determination method for Lycii Cortex， providing a scientific basis for the formulation of quality standards for Lycii Cortex and its roasted products. MethodsHigh performance liquid chromatography（HPLC） was developed for the quantitative method for determining kukoamine B in Lycii Cortex and its roasted products on an Alphasil XD-C₁₈ CH column（4.6 mm×250 mm， 5 μm）. HPLC fingerprint profiles were established for 10 batches of Lycii Cortex and its roasted products， and ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry（UPLC-Q-TOF-MS） was used to identify the common peaks based on reference standards， literature and MS information. Quality evaluation indicators included yield of decoction pieces， appearance properties， content of kukoamine B， and fingerprint profiles. The temperature and time of the roasting process were investigated to select the optimal preparation process， which was then verified. Additionally， chemical pattern recognition was combined to assess the differences in the chemical composition of Lycii Cortex before and after roasting， as well as among samples from different origins. ResultsQuantitative analysis indicated that the contents of kukoamine B in Lycii Cortex and its roasted products were 0.35%-5.51% and 0.24%-4.15%， respectively. The transfer rate of kukoamine B was 58.6%-78.9% after roasting. The fingerprint profile analysis demonstrated that the method established in this study effectively separated kukoamine B from other components in the samples and distinctly differentiated it from its impurity peak， cis-N-caffeoylputrescine. The HPLC fingerprint profiles of Lycii Cortex and its roasted products showed high similarity（all above 0.95）， with 7 common peaks identified and five common components， including kukoamine B， cis-N-caffeoylputrescine， N-coumaroyl tyramine， feruloyltyramine， and glucosyringic acid， confirmed. Process optimization confirmed that baking at 110 ℃ for 20 min was a stable and feasible method for roasting Lycii Cortex. Principal component analysis and cluster analysis showed that there was little difference in the chemical composition between raw and roasted Lycii Cortex， but the quality of Lycii Cortex from different origins differed greatly. ConclusionThis study successfully established the fingerprint profiles and a quantitative method for the effective component kukoamine B in Lycii Cortex and roasted Lycii Cortex. The qualitative and quantitative analyses clarified that the impact of the roasting process on the chemical composition of Lycii Cortex was less significant than the variations due to its geographical origin. The findings of this study offer a reference for the development of quality evaluation methods and the establishment of quality standards for Lycii Cortex and its processed products.

The development of famous classical formula compound preparations has been a research hotspot in recent years， carrying great expectations from the government， academia and industry. During the process of its research and development， it reflects many problems related to traditional Chinese medicine （TCM） industry and deserves deep consideration by the academic community. Based on the current status of development of famous classical formulas， this paper summarizes the key problems and made an in-depth analysis. The results show that three key issues should be paid attention. The first is the weakness of basic research in TCM， which affect the healthy development of TCM. The second is the understanding of development of famous classical formula compound preparations is not in-depth， and the formulation of relevant policies needs to be more reasonable. Thirdly， the expectation for the development of famous classical formula compound preparations is too high， which affects the research and development process of the compound preparations. It is hoped that the TCM industry can take this opportunity to face the problems， propose solutions， and form new breakthroughs to promote the development and progress of TCM.

Pharmaceutical analysis is a discipline based on chemical, physical, biological, and information technologies. At present, biotechnological analysis is a short branch in pharmaceutical analysis; however, bioanalysis is the basis and an important part of medicine. Biotechnological approaches can provide information on biological activity and even clinical efficacy and safety, which are important characteristics of drug quality. Because of their advantages in reflecting the overall biological effects or functions of drugs and providing visual and intuitive results, some biotechnological analysis methods have been gradually applied to pharmaceutical analysis from raw material to manufacturing and final product analysis, including DNA super-barcoding, DNA-based rapid detection, multiplex ligation-dependent probe amplification, hyperspectral imaging combined with artificial intelligence, 3D biologically printed organoids, omics-based artificial intelligence, microfluidic chips, organ-on-a-chip, signal transduction pathway-related reporter gene assays, and the zebrafish thrombosis model. The applications of these emerging biotechniques in pharmaceutical analysis have been discussed in this review.