Biomarkers based on multiplatform comprehensive analysis: A systematic analysis of Geng-Nian-Shu in perimenopausal syndrome

Although Geng-Nian-Shu has been shown to be clinically effective in perimenopausal syndrome, its active components and mechanism have not yet been elucidated. To demonstrate the mechanism-based biomarkers of Geng-Nian-Shu in treating perimenopausal syndrome, a total of 135 chemical constituents including 52 prototype blood constituents were identified via high-performance liquid chromatography-quadrupole-time of flight/mass spectrometry. Then, network pharmacology showed significant enrichment for the PhosphoInositide-3 Kinase/Akt pathway, suggesting that it may be the main regulatory pathway for the Geng-Nian-Shu treatment of the perimenopausal syndrome. Subsequently, multivariate analysis was performed between the Geng-Nian-Shu sham-treated and Geng-Nian-Shu ovariectomy-treated groups and further screened out 18 prototype blood constituents by correlation analysis with plasma estrogen levels to identify potential biomarkers associated with Geng-Nian-Shu treat the ovariectomy-induced perimenopausal syndrome. Finally, the results of pharmacological experimental verification and Pearson correlation analysis indicated that catalpol, ligustilide, paeoniflorin, and gallic acid were selected as biomarkers of Geng-Nian-Shu which were strongly and positively correlated with PhosphoInositide-3 Kinase/Akt signaling pathway. In this study, based on high-performance liquid chromatography-quadrupole-time of flight/mass spectrometry combined with pharmacodynamics, network pharmacology, pharmacology, and other disciplines, we explored the effects and mechanisms of Geng-Nian-Shu in the treatment of perimenopausal syndrome at multiple levels. Using multiplatform technology to investigate the role of Geng-Nian-Shu represents a new strategy for the selection and verification of biomarkers of Geng-Nian-Shu and provides a basis for further development and utilization of Geng-Nian-Shu.     

Rational Design of a Humanized Glucagon‐Like Peptide‐1 Receptor Agonist Antibody

Bovine antibody BLV1H12 possesses a unique “stalk–knob” architecture in its ultralong heavy chain CDR3, allowing substitutions of the “knob” domain with protein agonists to generate functional antibody chimeras. We have generated a humanized glucagon‐like peptide‐1 (GLP‐1) receptor agonist antibody by first introducing a coiled‐coil “stalk” into CDR3H of the antibody herceptin. Exendin‐4 (Ex‐4), a GLP‐1 receptor agonist, was then fused to the engineered stalk with flexible linkers, and a Factor Xa cleavage site was inserted immediately in front of Ex‐4 to allow release of the N‐terminus of the fused peptide. The resulting clipped herceptin–Ex‐4 fusion protein is more potent in vitro in activating GLP‐1 receptors than the Ex‐4 peptide. The clipped herceptin–Ex‐4 has an extended plasma half‐life of approximately four days and sustained control of blood glucose levels for more than a week in mice. This work provides a novel approach to the development of human or humanized agonist antibodies as therapeutics.     

丹荷颗粒治疗高脂血症质量标志物发现研究

为寻找丹荷颗粒治疗高脂血症的质量标志物,该研究基于丹荷颗粒体内成分分析结果,采用Cytoscape软件构建高脂血症-共有靶点-丹荷颗粒体内成分作用网络,利用DAVID及String数据库分别对共有靶点进行生物过程、通路富集及网络拓扑分析,明确丹荷颗粒降脂作用关键靶点及成分,再建立油酸诱导的HepG2细胞脂质堆积模型验证关键成分的降脂药效,最后结合相关成分在制剂中的含量、稳定性、特征性综合确定质量标志物。结果发现,丹荷颗粒体内成分作用于CES1、ADORA2A、ADORA1、APOB、LDLR、PPARA、PPARG、INSR、ESR2、ESR1共10个高脂血症疾病靶点,主要参与脂质代谢过程以及PPAR、cAMP信号通路,其中LDLR、PPARA、PPARG可能是关键靶点,而网络中与关键靶点直接作用的成分为白藜芦醇、柚皮素。白藜芦醇和柚皮素均可降低油酸诱导的HepG2细胞内脂滴数量,改善细胞脂质堆积严重程度,并显著降低细胞内甘油三酯含量,可能为关键成分;鉴于入体成分白藜芦醇和柚皮素来源于制剂中虎杖苷及柚皮苷,且制剂中虎杖苷及柚皮苷特征明显、含量丰富、稳定,故虎杖苷及柚皮苷可作为丹荷颗粒治疗高脂血症的质量标志物。该研究为丹荷颗粒质量标准的建立提供了合理的候选质控指标。     

Review: Separation and Pharmacology of Chiral Compounds in Traditional Chinese Medicine

More than 60% commonly used pharmaceutical active ingredients are chiral compounds. Developing more effective and safe chiral compounds has become a focus in the pharmaceutical industry. Chiral compounds widely exist in traditional Chinese medicine and include alkaloids, flavonoids, volatile oils, and amino acids. The characterization of chiral compounds used in traditional Chinese medicine remains limited. Here, the characterization of chiral compounds commonly used in traditional Chinese medicine is reviewed focusing upon their separation and pharmacology.     

Exploration of the mechanism of Zisheng Shenqi decoction against gout arthritis using network pharmacology

BackgroundIn this study, the network pharmacological methods were used to predict the target of effective components of compounds in Zisheng Shenqi Decoction (ZSD, or Nourishing Kidney Qi Decoction) in the treatment of gouty arthritis (GA).MethodThe main effective components and corresponding key targets of herbs in the ZSD were discerned through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis (TCMSP), Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine (BATMAN-TCM) database. UniProt database and Swiss Target Prediction (STP) database was used to rectify and unify the target names and supply the target information. The targets related to GA were obtained by using GeneCards database. After we discovered the potential common targets between ZSD and GA, the interaction network diagram of “ZSD-component-GA-target” was constructed by Cytoscape software (Version 3.7.1). Subsequently, the Protein-protein interaction (PPI) network of ZSD effective components-targets and GA-related targets was constructed by Search Tool for the Retrieval of Interacting Genes Database (STRING). Bioconductor package “org.Hs.eg.db” and “cluster profiler” package were installed in R software (Version 3.6.0) which used for Gene Ontology analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis.Results146 components and 613 targets of 11 herbal medicines in the ZSD were got from TCMSP database and BATMAN-TCM database. 987 targets of GA were obtained from GeneCards database. After intersected and removed duplications, 132 common targets between ZSD and GA were screened out by Cytoscape software (Version 3.7.1). These common targets derived from 81 effective components of 146 components, such as quercetin, stigmasterol and kaempferol. They were closely related to anti-inflammatory, analgesic and anti oxidative stress and the principal targets comprised of Purinergic receptor P2X, ligand-gated ion channel 7 (P2x7R), Nod-like receptor protein 3 (NLRP3) and IL-1β. GO enrichment analysis and KEGG pathway enrichment analysis by R software (Version 3.6.0) showed that the key target genes had close relationship with oxidative stress, reactive oxygen species (ROS) metabolic process and leukocyte migration in aspects of biological process, cell components and molecular function. It also indicated that ZSD could decrease inflammatory reaction, alleviate ROS accumulation and attenuate pain by regulating P2 × 7R and NOD like receptor signaling pathway of inflammatory reaction.ConclusionA total of 81 effective components and 132 common target genes between ZSD and GA were screened by network pharmacology. The PPI network, GO enrichment analysis and KEGG pathway enrichment analysis suggested that ZSD can exerte anti-inflammatory and analgesic effects on the treatment of GA by reducing decreasing inflammatory reaction, alleviating ROS accumulation, and attenuating pain. The possible molecular mechanism of it mainly involved multiple components, multiple targets and multiple signaling pathways, which provided a comprehensive understanding for further study. In general, the network pharmacological method applied in this study provides an alternative strategy for the mechanism of ZSD in the treatment of GA.     

Exploring the mechanism of Cremastra Appendiculata (SUANPANQI) against breast cancer by network pharmacology and molecular docking

BackgroundSUANPANQI, the pseudo phosphorous stem of Cremastra appendiculata, is one of the most well-known traditional Chinese medicine, which has been shown to inhibit tumorigenesis in various human cancers. However, the underlying mechanism of SUANPANQI treatment against breast cancer (BRCA) remains unclear. In this study. we aim to investigate the bioactive compounds and mechanisms of SUANPANQI in the treatment of BRCA based on network pharmacology and molecular docking.MethodsThe compounds were collected from previous research. SwissADME was used to screen bioactive compounds. The targets corresponding to SUANPANQI and BRCA were obtained using MalaCards and SwissTargetPrediction. SUANPANQI-related and BRCA-related targets were found and then overlapped to get intersections, which represented potential anti-BRCA targets of SUANPANQI. The Cytoscape software was used to construct bioactive compounds targeting the BRCA network. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of the targets was extracted from the metascape database, then conducted using the Cluster Profiler package in R software. Protein-Protein interaction (PPI) network was constructed using the STRING online database and analyzed using Cytoscape software. Pivotal genes were screened using the topological analysis, survival analysis, and pathological stage analysis. Molecular docking analysis was used to verify whether the bioactive compounds had a definite affinity with the pivotal targets.ResultsSixty-five bioactive compounds of SUANPANQI were involved with 225 predicted BRCA targets. Then, a compound-target network and a PPI network were constructed. The GO analysis and KEGG enrichment analysis suggested that SUANPANQI worked against BRCA via PI3K-Akt, Ras, FoxO, Rap1, and ErbB signaling pathways, etc. After topological analysis, survival analysis, and pathological stage analysis of the SUANPANQI potential targets against BRCA, 6 pivotal target genes (AR, HSP90AA1, MMP9, PGR, PTGS2, TNF) that were highly responsible for the therapeutic effects of SUANPANQI against BRCA were obtained. Molecular docking results showed that 6 bioactive compounds of SUANPANQI had strong binding efficiency with the 6 pivotal genes.ConclusionsThe present study clarifies the mechanism of SUANPANQI against BRCA through multiple targets and pathways, and provides evidence to support its clinical use.     

基于关联规则和技术功效矩阵的企业技术创新机会发现和辅助决策方法

为助力科技型创新企业准确且快速地从外部捕获创新技术机会, 提出一种企业技术机会发现和辅助决策方法. 首先, 挖掘领域内的技术热点、技术重点和有潜力的技术作为领域技术创新机会. 然后, 通过关联规则分析领域技术机会和企业已有技术之间的相关性, 进一步结合技术掌握度和新颖度, 识别更适合企业的技术创新机会. 最后, 创新性地采用Sen-BERT语言模型和K-means聚类方法构建技术功效矩阵, 辅助企业从功能需求的角度进行技术创新决策. 以电动汽车领域为例验证了该方法的可行性.     

Bergenia Genus: Traditional Uses,Phytochemistry and Pharmacology

Bergenia (Saxifragaceae) genus is native to central Asia and encompasses 32 known species. Among these, nine are of pharmacological relevance. In the Indian system of traditional medicine (Ayurveda), “Pashanabheda” (stone breaker) is an elite drug formulation obtained from the rhizomes of B. ligulata. Bergenia species also possess several other biological activities like diuretic, antidiabetic, antitussive, insecticidal, anti-inflammatory, antipyretic, anti-bradykinin, antiviral, antibacterial, antimalarial, hepatoprotective, antiulcer, anticancer, antioxidant, antiobesity, and adaptogenic. This review provides explicit information on the traditional uses, phytochemistry, and pharmacological significance of the genus Bergenia. The extant literature concerned was systematically collected from various databases, weblinks, blogs, books, and theses to select 174 references for detailed analysis. To date, 152 chemical constituents have been identified and characterized from the genus Bergenia that belong to the chemical classes of polyphenols, phenolic-glycosides, lactones, quinones, sterols, tannins, terpenes, and others. B. crassifolia alone possesses 104 bioactive compounds. Meticulous pharmacological and phytochemical studies on Bergenia species and its conservation could yield more reliable compounds and products of pharmacological significance for better healthcare.     

A network-based pharmacology study of active compounds and targets of Fritillaria thunbergii against influenza

Seasonal and pandemic influenza infections are serious threats to public health and the global economy. Since antigenic drift reduces the effectiveness of conventional therapies against the virus, herbal medicine has been proposed as an alternative. Fritillaria thunbergii (FT) have been traditionally used to treat airway inflammatory diseases such as coughs, bronchitis, pneumonia, and fever-based illnesses. Herein, we used a network pharmacology-based strategy to predict potential compounds from Fritillaria thunbergii (FT), target genes, and cellular pathways to better combat influenza and influenza-associated diseases. We identified five compounds, and 47 target genes using a compound-target network (C-T). Two compounds (beta-sitosterol and pelargonidin) and nine target genes (BCL2, CASP3, HSP90AA1, ICAM1, JUN, NOS2, PPARG, PTGS1, PTGS2) were identified using a compound-influenza disease target network (C-D). Protein-protein interaction (PPI) network was constructed and we identified eight proteins from nine target genes formed a network. The compound-disease-pathway network (C-D-P) revealed three classes of pathways linked to influenza: cancer, viral diseases, and inflammation. Taken together, our systems biology data from C-T, C-D, PPI and C-D-P networks predicted potent compounds from FT and new therapeutic targets and pathways involved in influenza.     

模糊综合评判法在创业机会评估中的应用研究

创业是极具风险的活动.在我国,创业企业的失败率是非常高的.创业机会稍纵即失,正确评价和把握创业机会,这对创业者和创业资本的提供者都十分重要.在Timmons的创业机会评价框架下,提出了创业机会综合评价的指标体系,建立了创业机会模糊综合评价模型,并给出算法,最后进行了实证分析.