The study aims to establish HPLC fingerprint and multi-index content determination method of Guanxin Qiwei tablets and provide scientific basis for its quality control. The fingerprints of 18 batches of Guanxin Qiwei tablets were established by Shim-pack GGIST HP C₁₈ chromatographic column, and analyzed comprehensively in combination with the Similarity Evaluation System of TCM Chromatographic Fingerprint (2012 edition). Cluster analysis (CA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used for stoichiometric study. HPLC-MS/MS method was established for simultaneous determination of 9 components. A total of 22 common peaks were identified in 18 batches of Guanxin Qiwei tablets fingerprint, and the similarity was 0.952-0.998, 9 common peaks were identified. They were No. 1 gallic acid, No. 3 protocatechuic acid, No. 8 ellagic acid, No. 9 salvianolic acid B, No. 12 luteolin, No. 13 apigenin, No. 19 dehydrodiisoeugenol, No. 20 cryptotanshinone and No. 21 tanshinone ⅡA. CA and PCA analysis grouped 18 batches of Guanxin Qiwei tablets into 3 categories: S1-S4 (manufacturer A) was grouped into one category, S5-S8 (manufacturer B) was grouped into one category, and S9-S18 (manufacturer C and D) was grouped into one category. Under OPLS-DA analysis mode, 14 quality differentiators were selected with the variable important projection (VIP) greater than 1 as the standard, and all of them had significant differences. The linear relationship of the 9 components was good in their respective ranges, and the linear correlation coefficient r was greater than or equal to 0.099 9. Precision RSDS were all lower than 3.00%. The stability and repeatability were good, RSD lower than 5.00%; The average recoveries were 96.58%-106.28%, RSD was 2.68%-6.45%. This method is efficient and stable, and can be used for quality control of Guanxin Qiwei tablets.

This study investigated the material basis of Huoluoxiaolingdan in treating diabetic peripheral neuropathy (DPN) through ultra performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF-MS/MS) and network pharmacology. UPLC-Q-TOF-MS/MS combined with PeakView^TM 1.2 software and Molecule Profiler^TM software were used to analyze the the chemical components of Huoluoxiaolingdan and blood-absorbed ingredients in normal rats and rats with DPN induced by high fat diet combined with low dose streptozotocin injection. Swiss Target Prediction database, GeneCards and other databases were used to search the corresponding targets of active ingredients and disease targets. The intersection targets were obtained using Venny 2.1 platform, which were then imported into the STRING platform and Cytoscape 3.10.1 software to construct the protein-protein interaction network and the "component-target" network relationship diagram, and the core components and core targets were analyzed. GO and KEGG pathway enrichment analysis of key targets were performed. All experiments were approved by the experimental Animal Ethics Committee from Nanjing University of Chinese Medicine (No. 202310A023). A total of 83 chemical components were identified, including 52 terpenoids such as tanshinone Ⅱ_A, 11 phthalides such as Z-ligustilide, 15 organic acids such as ferulic acid, 4 coumarins and 1 phenol. Additionally, 15 prototype components and 29 metabolites were identified in normal rats' plasma, and 17 prototype components and 32 metabolites were identified in DPN rats' plasma. Network pharmacology results show that 5 core components such as 3-acetyl-11-keto-β-boswellic acid and 11-keto-β-boswellic acid may act through 27 core targets such as TNF and IL6 to regulate AGE-RAGE and PI3K/Akt and other signaling pathways so as to play a therapeutic role in treatment of DPN. The study efficiently analyzed the constituents in vitro and blood-absorbed ingredients of Huoluoxiaolingdan and the cracking regularity of the main compounds, and the core components of its treatment of DPN were analyzed in combination with network pharmacology, which can provide reference for further research of the pharmacodynamic substantial basis and mechanism of Huoluoxiaolingdan in the treatment of DPN.

The study of micromechanical behavior during tablet pressing is often limited to phenomenological studies, accurate calibration of the discrete element model parameters of binary particles is a prerequisite for conducting modeling research on tablet compression. In this study, we take pregelatinized starch and microcrystalline cellulose as the research objects, and apply the Edinburgh elasto-plastic adhesion (EEPA) contact model to establish a discrete elemental simulation model for binary material pressing. Taking tablet force-hardness and force-volume reduction as response values, the optimal values of the discrete meta-parameters that significantly affect tablet pressing are obtained by applying Plackett-Burman design, Latin hypercubic sampling, Kriging model, and Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ) calibration. The results obtained the optimum combination of discrete element method (DEM) parameters for pregelatinized starch, Poisson's ratio 0.257, shear modulus 1×10⁹ Pa, granule-particle static friction coefficient 0.165, unit normal stiffness 2.419 2×10⁹ N·m^-3, unit tangential stiffness 7.954 6×10⁹ N·m^-3, and strength of adhesive force -0.009 155 8 N. For microcrystalline cellulose, Poisson's ratio 0.381, shear modulus 1.04×10⁹ Pa, particle-particle static friction coefficient 0.719, unit normal stiffness 3.171 5×10⁹ N·m^-3, unit tangential stiffness 6.746 2×10⁹ N·m^-3, and strength of adhesion -0.038 7 N. For optimum combinations of the DEM parameters for the binary blend of excipients, particle-particle collision recovery coefficient 0.1, unit normal stiffness 9.947 1×10⁹ N·m^-3, unit tangential stiffness 1.994 5×10⁹ N·m^-3, and adhesion force strength -0.060 35. The simulation results under the optimal parameter combination are similar to the experimental results, indicating that the calibrated parameters can be used for discrete element simulation research and provide theoretical basis and data support for the subsequent intelligent and continuous production of tablets.

In this study, licorice-derived vesicle-like particles (LVLPs) were used as carriers, and licochalcone-A (LCA), a signature active ingredient of the same source, was used as a model drug to construct a drug-loaded LVLP@LCA nanodelivery system, and to characterize and evaluate its in vitro properties and anti-inflammatory activity. Licochalcone-A (LCA), a signature active ingredient of traditional Chinese medicine from the same source, was used as a model drug to construct a drug-loaded exocyst-like nano-delivery system, LVLP@LCA, and its in vitro properties and anti-inflammatory activities were characterized and evaluated. The LVLP@LCA nanodelivery system was prepared by extracting the exocyst-like nanoparticles by gradient centrifugation and loading the anti-inflammatory drug LCA by ultrasonication. The LVLP@LCA nanoparticles were prepared with a particle size of about 160 nm and a tea saucershaped bilayer structure, with a high encapsulation rate and drug loading capacity. The in vitro results showed that LVLP@LCA further enhanced the ability of LCA to inhibit the proliferation of inflammatory cells and reduce the levels of ROS and NO in inflammatory cells. Meanwhile, ELISA and qRT-PCR results showed that LVLP@LCA significantly reduced the secretion and mRNA expression of IL-6, IL-1β, TNF-α, CCL5, CCL17 and other related inflammatory factors and chemokines. It was demonstrated by Western blot that LVLP@LCA reduced the expression of inflammation-inducing factor interleukin 6 (IL-6) through the JAK/STAT pathway, and then inhibited the activation of inflammatory response. The present study provides a theoretical basis for the comprehensive anti-inflammatory effect of LVLP@LCA and a new way of thinking for the application of Glycyrrhiza glabra as a traditional Chinese medicine against atopic dermatitis.

JAZ proteins, as inhibitors in the jasmonic acid (JA) signaling pathway, play a crucial role in regulating plant growth and development, as well as the biosynthesis of secondary metabolites in plants. To explore the functions of the JAZ gene family in Tripterygium wilfordii, our study systematically identified the members of the JAZ gene family in T. wilfordii. We analyzed their physicochemical properties, chromosome localization, phylogenetic tree, and protein conserved motifs. Additionally, we investigated the expression patterns of TwJAZs in different tissues, constructed a gene regulatory network map, and ultimately cloned the full-length sequences of 18 JAZ genes. The results showed that the 18 TwJAZs were unevenly distributed across 12 chromosomes, encoding amino acid numbers ranging from 122 to 525, with molecular weights of 13.87 to 54.73 kDa, and isoelectric points ranging from 6.83 to 10.27. Subcellular localization prediction indicated that 13 TwJAZs were localized in the nucleus, while 5 TwJAZs were located in the cytoplasm and chloroplasts. The phylogenetic tree analysis revealed that the JAZ family proteins of T. wilfordii could be divided into five subfamilies, with members of the same subfamily sharing similar conserved motifs. Expression pattern analysis demonstrated that TwJAZs were predominantly expressed in flowers, leaves, and peeled stems, with most TwJAZs showing the highest expression levels after 4 hours of methyl jasmonate (MeJA) induction. The transcription factor regulatory network shows that TwJAZs are strongly correlated with transcription factor families such as AP2/ERF-ERF, NAC, and bHLH. This study comprehensively identified all the JAZ gene family sequences in T. wilfordii, initially clarifying the structural and functional characteristics of the TwJAZs, and laying an important foundation for further research on the functions and regulatory mechanisms of TwJAZs.

Based on the genome and transcriptome data of Salvia miltiorrhiza, a cytochrome P450 gene annotated as SmCYP72A395, which was highly expressed in the periderm of S. miltiorrhiza root was cloned. The total length of the cDNA sequence of SmCYP72A395 was 1 578 base pairs, encoding 525 amino acids. The predicted molecular weight of the protein was 59.9 kDa. The physicochemical properties, subcellular localization, protein structure, and conserved domains were predicted by online bioinformatic tools. The theoretical isoelectric point of SmCYP72A395 was 8.68, with a transmembrane domain in the protein. This gene was highly expressed in the flower, leaf, and root periderm tissues of S. miltiorrhiza. To further identify the biological function of SmCYP72A395, the transgenic hairy roots with SmCYP72A395 overexpressed (SmCYP72A395-OE) and RNA interference (SmCYP72A395-RNAi) were constructed, and the content of tanshinone compounds was detected by UPLC between these transgenic lines and control line (haboring the vector plasmid in the transgenic line). Compared with the control line of transgenic hairy roots, the content of dihydrotanshinone Ⅰ, cryptotanshinone, tanshinone Ⅰ and tanshinone ⅡA in the SmCYP72A395-OE lines was significantly less than those in the control line. On the contrary, the content of dihydrotanshinone Ⅰ, cryptotanshinone, and tanshinone Ⅰ was higher in the SmCYP72A395-RNAi lines than those in the control line. These results demonstrated that SmCYP72A395 played a negative role in the regulation of tanshinone accumulation in S. miltiorrhiza. This study lays the foundation for further elucidating the biosynthesis and regulatory pathways of tanshinone compounds in S. miltiorrhiza.

Autophagy is an important physiological process that can degrade cellular components and maintain cellular homeostasis. In the process of cancer development, autophagy plays a dual role in promoting or inhibiting autophagy, and targeting autophagy is considered to be an important means of cancer treatment. According to Chinese medicine theory, autophagy has the function of regulating the balance of Yin and Yang, and the balance of good and evil in the organism, and based on the theory of "supporting the positive and dispelling the evil", the use of active ingredients of traditional Chinese medicine (TCM) to target autophagy has been proven to be effective in the treatment of cancer. In addition, autophagic cell death, as a type Ⅱ programmed cell death, is often accompanied by autophagic features, and the regulation of autophagic cell death is an important way for autophagy to achieve anti-tumor effects. In recent years, more and more studies have found that the active ingredients of TCM have good effects in cancer treatment, among which, targeting autophagic cell death is an important way for TCM active ingredients to achieve anti-tumor effects. This paper outlines the understanding of cancer and autophagy in Chinese medicine theory, and summarizes the current Chinese medicine small molecule compounds targeting autophagic cell death and their mechanisms of action based on the classification of natural medicines. Finally, the development of Chinese medicine-derived compounds targeting autophagic cell death for the treatment of diseases is summarized and prospected, which hopefully can provide clues for subsequent exploration and research.

Artificial intelligence (AI) technology is increasingly applied across various fields, particularly in handling and analyzing large volumes of data, providing breakthroughs for numerous scientific studies. In Chinese medicine research, AI demonstrates significant advantages by enhancing the systematic, efficient, and accurate nature of studies through its exceptional learning and data processing capabilities. As a discipline with a long-standing history and rich theoretical framework, Chinese medicine research requires the integration of complex information, for which AI provides crucial support. AI technologies, especially machine learning and deep learning, can decipher complex biological and chemical data, advancing new discoveries in Chinese medicine pharmacology. Researchers can systematically analyze the multi-target mechanisms of Chinese medicine components and optimize formulation efficacy through these technologies. The combination of AI with multi-omics data and its application in cell phenotype analysis aids in accurately identifying drug targets and exploring new mechanisms. Additionally, AI-integrated network pharmacology combines experimental, computational, and clinical data to analyze multi-target drug mechanisms, enhancing the efficacy of TCM formule. AI accelerates the target identification of active compounds as well as dissecting the pharmacological effects. The development of large language models also plays a crucial role in constructing Chinese medicine knowledge graphs and literature analysis, extracting valuable information from extensive literature using natural language processing to build a systematic knowledge structure. The introduction of AI technology has propelled the modernization of Chinese medicine research and has a pivotal role in the development of internationalization and precision medicine. AI not only enhances the overall level of Chinese medicine research but also provides a solid foundation for interdisciplinary collaboration and innovation. With the continuous advancement of AI technology, Chinese medicine is anticipated to have a greater influence and role globally. This process is not only a significant marker of the modernization of Chinese medicine but also a reflection of the integration of science and traditional wisdom, which will undoubtedly drive progress and development in the entire medical field.

Colorectal cancer is a major cancer threatening the life and health of people worldwide. With the transformation of modern medical models, treatment strategies represented by traditional Chinese medicine (TCM) with multiple targets have become a new research direction in the treatment of colorectal cancer. In the study of TCM, in addition to deconstructing the components and targets of TCM based on reductionism, more attention should be paid to the holistic concept in the basic theories of TCM, analyzing and understanding the mechanism of action of TCM treatment from a holistic perspective. TCM compound prescriptions, as a collection of single herbs, are composed of various monomers. Viewing TCM from different levels and considering different herbs and monomers as a whole helps us better understand TCM. At the same time, TCM has the characteristic of multiple targets. In addition to directly acting on tumor cells themselves, it can also affect the intestinal flora to improve the tumor microenvironment, treating tumors in an all-round and multi-dimensional way, regulating the physical functions of tumor patients from a holistic perspective, and comprehensively improving the health status of the individual. This review aims to systematically elaborate on the efficacy and multi-target mechanism of TCM in the treatment of colorectal cancer from three levels: TCM compound prescriptions, single herbs, and TCM monomers, based on clinical trials and preclinical research results. Meanwhile, this article will combine systems biology with the holistic view of TCM to conduct an in-depth analysis of related research on TCM treatment of colorectal cancer.

Prenylated aromatic natural products (PANPs) are widely distributed in nature. PANPs exhibit a great structural diversity due to their various core scaffolds (coumarin, lignan, benzoic acid/benzyl alcohol, flavonoid, xanthone, anthraquinone, and aromatic alkaloid, etc.) and the distinct types and substitution sites of isoprenoid moieties which may possess either linear or cyclic structures. The structural diversity of PANPs endow them with various bioactivities including anti-bacterial, anti-oxidation, anti-cancer, anti-inflammatory and analgesic effects, which makes them a group of highly promising molecules for drug development. Notably, isoprenoid moieties are often the indispensable pharmacophores in these active PANPs. Aromatic prenyltransferases (aPTs) are responsible for prenylation in the biosynthesis of PANPs. aPTs can be divided into three classes according to their evolutionary relationships and structural features, i.e. membrane-bound aPTs (UbiA type), soluble aPTs with a PT barrel structure (ABBA type and DMATS type) and terpene synthase-like aPTs. Herein, we summarize 94 aPTs belonging to the different classes which were characterized in the past ten years, in particular introduce their substrate selectivity/tolerance, regioselectivity, evolutionary relationships and structural features. This would provide cues for discovery and engineering of new aPTs, and modification and bio-production of active PANPs.