基于指纹图谱及网络药理学的白芍质量标志物(Q-marker)预测分析

目的基于指纹图谱和网络药理学方法,分析预测当归四逆汤中单味药白芍潜在的质量标志物(Q-marker)。方法建立白芍水煎液和当归四逆汤指纹图谱,明确成分传递规律;进一步通过网络药理学方法,构建"成分-靶点-通路"网络,预测白芍的Q-marker。结果建立了15批白芍水煎液和15批当归四逆汤指纹图谱,并各指认其中5个色谱峰,分别为没食子酸、芍药内酯苷、芍药苷、1,2,3,4,6-O-五没食子酰葡萄糖和苯甲酰芍药苷;经网络药理学分析,筛选出潜在的2个活性成分、8个核心靶点、13条关键通路,表明白芍主要通过这些成分、靶点、通路发挥作用,初步预测芍药苷、芍药内酯苷为白芍潜在的Q-marker。结论研究分析预测的Q-marker,为白芍质量的全面控制提供参考,同时也为白芍功效关联物质的研究及作用机制的阐释奠定基础。     

基于网络药理学吴茱萸致肝毒性机制研究

目的筛选吴茱萸主要肝毒性成分,预测毒性成分作用靶点,探讨其多成分-多靶点-多通路的肝毒性作用机制。方法依据TCMSP数据库、PubChem数据库Pharmmapper服务器、UniprotKB数据库筛选吴茱萸的活性成分,并预测肝毒性作用靶点。借助Cytoscape软件构建吴茱萸毒性成分-作用靶点网络,通过KOBAS3.0数据库对靶点基因功能及代谢通路进行分析。结果网络分析结果表明吴茱萸中筛选得到14-甲酰基二氢吴茱萸次碱、芳樟醇、1-甲基-2-戊烷基-4(1H)喹诺酮、辛弗林、柠檬烯等147个潜在毒性成分,涉及靶点F2、PIM1、MMP13、MAOB等49个,经建立网络连接,细胞代谢、催化活性、刺激反应等通路可能与肝毒性作用相关。结论应用网络药理学的方法,发现吴茱萸中的多种潜在毒性成分可能通过多个靶点与细胞代谢、催化活性等通路相互作用,从而可能产生肝毒性,为后续进一步深入验证吴茱萸肝毒性作用机制研究提供新线索。     

Biohorology and biomarkers of aging: Current state-of-the-art,challenges and opportunities

The aging process results in multiple traceable footprints, which can be quantified and used to estimate an organism's age. Examples of such aging biomarkers include epigenetic changes, telomere attrition, and alterations in gene expression and metabolite concentrations. More than a dozen aging clocks use molecular features to predict an organism's age, each of them utilizing different data types and training procedures. Here, we offer a detailed comparison of existing mouse and human aging clocks, discuss their technological limitations and the underlying machine learning algorithms. We also discuss promising future directions of research in biohorology — the science of measuring the passage of time in living systems. Overall, we expect deep learning, deep neural networks and generative approaches to be the next power tools in this timely and actively developing field.     

基于系统药理学和分子对接研究薤白治疗冠心病的作用机制

目的通过系统药理学和分子对接方法,对薤白治疗冠心病的作用机制进行研究。方法收集薤白的有效化合物;预测这些化合物对冠心病的作用靶点;对这些靶点进行PPI网络图的构建、GO富集分析和KEGG通路注释分析;将这些化合物与靶点进行分子对接。结果薤白共收集到11个有效化合物,作用于30个冠心病相关靶点。PPI网络图显示ALB、ACE、REN、MMP9、MAPK1、NOS3、F2、MMP2、SELE、PPARG为10个联系最多的靶点。GO富集分析显示出66个生物过程、22个分子功能、11个细胞成分,涉及雌激素反应、凝血、冠脉炎症、RAAS系统、抗氧化、稳定粥样斑块6个方面。KEGG通路注释分析显示出13条通路,其中6条通路与冠心病相关,分别是:Estrogen signaling pathway、PPAR signaling pathway、Complement and coagulation cascades、Renin-angiotensin system、HIF-1 signaling pathway and TNF signaling pathway。330组分子对接结果显示233组具有较好的结合活性。结论枳实薤白桂枝汤治疗冠心病具有多成分、多靶点的特点,可能通过抗凝血、稳斑块、抗氧化、抗炎症、降血脂、抑制RASS系统、增加NO保护、促进雌激素分泌8个方面发挥治疗冠心病的作用,且Estrogen signaling pathway是薤白作用冠心病的最主要通路。     

Bioinformatic identification of key candidate genes and pathways in axon regeneration after spinal cord injury in zebrafish

Zebrafish and human genomes are highly homologous;however,despite this genomic similarity,adult zebrafish can achieve neuronal proliferation,regeneration and functional restoration within 6–8 weeks after spinal cord injury,whereas humans cannot.To analyze differentially expressed zebrafish genes between axon-regenerated neurons and axon-non-regenerated neurons after spinal cord injury,and to explore the key genes and pathways of axonal regeneration after spinal cord injury,microarray GSE56842 was analyzed using the online tool,GEO2R,in the Gene Expression Omnibus database.Gene ontology and protein-protein interaction networks were used to analyze the identified differentially expressed genes.Finally,we screened for genes and pathways that may play a role in spinal cord injury repair in zebrafish and mammals.A total of 636 differentially expressed genes were obtained,including 255 up-regulated and 381 down-regulated differentially expressed genes in axon-regenerated neurons.Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment results were also obtained.A protein-protein interaction network contained 480 node genes and 1976 node connections.We also obtained the 10 hub genes with the highest correlation and the two modules with the highest score.The results showed that spectrin may promote axonal regeneration after spinal cord injury in zebrafish.Transforming growth factor beta signaling may inhibit repair after spinal cord injury in zebrafish.Focal adhesion or tight junctions may play an important role in the migration and proliferation of some cells,such as Schwann cells or neural progenitor cells,after spinal cord injury in zebrafish.Bioinformatic analysis identified key candidate genes and pathways in axonal regeneration after spinal cord injury in zebrafish,providing targets for treatment of spinal cord injury in mammals.     

基于网络药理学探讨大承气汤治疗急性胰腺炎的物质基础和分子机制

采用网络药理学方法预测大承气汤治疗急性胰腺炎的物质基础和分子机制。通过数据库检索并预测大承气汤化合物的作用靶点及急性胰腺炎的疾病基因;并对关键靶点和相关活性化学成分进行分子对接验证;利用DAVID"富集分析"得到大承气汤的活性成分在治疗急性胰腺炎过程中所涉及的功能及通路,最终构建"中药材-活性化学成分-靶点-通路"综合网络。在大承气汤中发现了108种活性化学成分可与28个疾病靶点相关联,分子对接结果显示关键靶点与其对应化合物均有较强的结合能力。经DAVID富集分析得到,生物学过程438条,分子功能31条,细胞组成17条,KEGG通路富集96条。大承气汤可能通过药物反应、脂多糖反应和反向调节凋亡等生物过程,抗炎、抗氧化活性、反向调节细胞凋亡以及调节胰腺分泌等方式来实现其药效作用,涉及IL-17,TNF,NF-κB等多条信号通路。该研究运用网络药理学的方法,揭示了大承气汤以多种成分协同作用于多靶点、多信号通路治疗急性胰腺炎的分子机制,为生物实验提供理论基础。     

Multi‐scale network regression for brain‐phenotype associations

Brain networks are increasingly characterized at different scales, including summary statistics, community connectivity, and individual edges. While research relating brain networks to behavioral measurements has yielded many insights into brain‐phenotype relationships, common analytical approaches only consider network information at a single scale. Here, we designed, implemented, and deployed Multi‐Scale Network Regression (MSNR), a penalized multivariate approach for modeling brain networks that explicitly respects both edge‐ and community‐level information by assuming a low rank and sparse structure, both encouraging less complex and more interpretable modeling. Capitalizing on a large neuroimaging cohort (n = 1, 051) , we demonstrate that MSNR recapitulates interpretable and statistically significant connectivity patterns associated with brain development, sex differences, and motion‐related artifacts. Compared to single‐scale methods, MSNR achieves a balance between prediction performance and model complexity, with improved interpretability. Together, by jointly exploiting both edge‐ and community‐level information, MSNR has the potential to yield novel insights into brain‐behavior relationships.