Objective To construct an intelligent agent for the diagnosis and treatment of Alzheimer’s disease (AD) based on knowledge of renowned veteran traditional Chinese medicine (TCM) physicians’ knowledge by adopting artificial intelligence techniques including chain-of-thought reasoning, retrieval-augmented generation (RAG), and prompt engineering, so as to support clinical decision-making with expert TCM experience. Methods Relevant literature and monographs regarding AD treatment by prestigious TCM physicians were retrieved, and a total of 16 renowned veteran TCM physicians, including Tian Jinzhou, Zhou Zhongying, and Shen Baofan, were selected. Their medical records, clinical experience, and academic theories were systematically mined to establish a knowledge base of renowned veteran TCM physicians. To address inconsistencies in syndrome differentiation approaches among different physicians, a syndrome-element classification method was adopted to standardize syndrome differentiation.Based on a large language model and the constructed knowledge base, an intelligent agent for the diagnosis and treatment of AD was developed on the Dify 1.9.2 platform, incorporating both an agent-based individual decision-making scheme and an agent-based group decision-making scheme. Symptom clusters extracted from 108 real-world medical records were used as inputs to the agent, which generated syndrome differentiation results and recommended prescriptions, thereby creating an evaluation dataset. A total of 30 cases were randomly selected for a single-blind expert questionnaire evaluation. Experts evaluated the rationality of syndrome differentiation and prescription recommendations generated by three approaches: the original medical records, the agent-based individual decision-making scheme, and the agent-based group decision-making scheme. Results The agent-based group decision-making scheme achieved the highest estimated marginal mean score (3.93 ± 0.14), outperforming both the agent-based individual decision-making scheme (3.47 ± 0.14) and the original medical records (3.16 ± 0.14). The agent-based individual decision-making scheme also outperformed the original medical records. Conclusion By integrating large language model technology with a syndrome-element classification method, this study incorporated the syndrome differentiation experience of multiple renowned veteran TCM physicians and developed an intelligent agent for the diagnosis and treatment of AD that embodies their collective expertise. The agent-based group decision-making scheme achieved higher scores in expert evaluations, suggesting that this approach can leverage the advantages of collaborative decision-making among multiple renowned physicians. The development of this intelligent agent provides a reusable methodological framework and implementation pathway for applying renowned physicians’ knowledge to support clinical decision-making, and offers a model for developing disease-specific intelligent agents that leverage the advantages of group decision-making, thereby laying the foundation for a subsequent prospective validation platform.

Objective An evidence assessment was conducted on five commonly used traditional Chinese patent medicines for the treatment of knee osteoarthritis (KOA), using the integrated evidence chain-based efficacy evaluation of traditional Chinese medicine (Eff-iEC) method and the grading of recommendations assessment,development and evaluation (GRADE) system. Methods The internationally recognized GRADE system and Eff-iEC method, which aligns with the characteristics of TCM, were applied in parallel to evaluate the evidence for five high-frequency recommended CPMs from clinical guidelines and expert consensuses. Simultaneously, a Meta-analysis was performed to evaluate their clinical efficacy and safety, using the clinical effective rate as a core indicator for evidence determination. Results GRADE assessment showed that, due to limitations in randomized controlled trials (RCTs) such as blinding and publication bias, among the five Chinese patent medicines, Jintiange Capsules and Biqi Capsules were rated as Grade C (low-quality evidence), while the rest were rated as Grade B (moderate-quality evidence). In contrast, the Eff-iEC method provided different evidence stratification: Jintiange Capsules (AA+B+), Zhuangguguanjie Capsules (BAA), and Biqi Capsules (AA+B+) were identified as high-level evidence. Wangbi Tablets/Capsules (BA+B+), Xianling Gubao Capsules (BA+B+) were identified as moderatelevel evidence. The Meta-analysis showed that CPMs combined with conventional Western medical therapy significantly improved the overall clinical effective rate (RR range 1.15—1.26, all P < 0.05). Notably, Wangbi Tablets/Capsules (RR = 0.41), Xianling Gubao Capsules (RR = 0.57), significantly reduced the risk of adverse reactions, demonstrating efficacy enhancement and toxicity reduction effects. Conclusion The Eff-iEC system and GRADE each have their own advantages in evidence evaluation. The Eff-iEC evaluation system can more comprehensively assess the efficacy evidence of traditional Chinese medicine compared to the GRADE system, avoiding underestimation of value due to flaws in trial design. However, high-quality RCTs are still needed in the future to further strengthen the certainty of the evidence.

Objective CiteSpace and VOSviewer softwares were used to conduct a visualized analysis of the current status of research on Gentiana worldwide, so as to predict its future research hotspots and developmental trends based on bibliometric methods. Methods Relevant literatures on Gentiana from January 1, 2005 to December 31, 2025 were retrieved from the China National Knowledge Infrastructure (CNKI) and Web of Science (WOS) Core Collection databases. After manually excluding duplicate and ineligible literatures and standardizing keywords, Excel, VOSviewer and CiteSpace were used to perform visualized analyses on the annual publication volume, publication journals, institutions, authors, countries and keywords of Chinese and English literatures in the field of Gentiana, respectively. Results A total of 7 449 eligible literature were retrieved, including 6 121 Chinese literature and 1 328 English literature. The annual publication volume of Chinese literature showed a fluctuating trend, while that of English literature presented a rapid upward trend. The Chinese and English journals publishing the most Gentiana-related studies were Chinese Traditional and Herbal Drugs (114 publications) and Journal of Ethnopharmacology (44 publications), respectively. The authors with the highest publication outputs were Wang Yuanzhong (61 publications) and Zhang Ji (27 publications). The institutions with the largest number of Chinese and English publications were Heilongjiang University of Chinese Medicine (118 publications) and Chinese Academy of Sciences (110 publications), respectively. The top three countries in terms of the number of articles published were China (709 publications), India (111 publications), and Japan (105 publications). The keyword analysis revealed that the current research hotspots mainly focused on the analysis of compound formulations, clinical applications, species identification, chemical composition, pharmacological effects, and mechanisms of action related to the Gentiana genus. In addition, traditional Chinese medicine preparations containing Gentiana have also been used to treat symptoms such as coughing and wheezing in patients during the COVID-19 pandemic. Conclusion Research on the Gentiana genus both domestically and internationally is currently showing an overall upward trend. In recent years, studies are gradually shifting from the single analysis of chemical components and pharmacological effects to the exploration of “multi-components and multi-targets” synergistic mechanisms. This research is deeply integrating modern technological methods such as genomics, molecular docking, and network pharmacology, providing important directions for the analysis of the efficacy mechanisms and innovative applications of Gentiana-related species. Future research in this field can also promote the precision and multi-layered development of Gentiana studies by strengthening international collaboration and deepening the integration of modern technologies.

Objective To clone the leucoanthocyanidin reductase gene SsLAR2 from Spatholobi Caulis (dried rattan stem of Spatholobus suberectus), and conduct bioinformatics and function verification, in order to elucidate the role of SsLAR2 gene in the biosynthesis of catechin. Methods SsLAR2 was amplified from the cDNA of Spatholobi Caulisvia RT-PCR and conducted systematic bioinformatics analysis. The SsLAR2 overexpression vector was constructed and genetically transformed into Nicotiana benthamiana. The total flavonoid content, catechin content, and the expression levels of key enzyme genes in the catechin synthesis pathway were determined in the transgenic plants. Results The full length of SsLAR2 gene was 1 092 bp in length, encoding 363 amino acids. The molecular weight of SsLAR2 protein was 40 513.75, and the isoelectric point was 5.75. The SsLAR2 protein was a hydrophilic protein with a transmembrane region, showing high homology with LAR proteins from various plants such as Cajanus cajan, Gastrolobium bilobum and Abrus precatorius. The promoter sequence of SsLAR2 contained photoresponsive elements, as well as responsive elements for multiple plant hormones such as methyl jasmonate, gibberellin, and salicylic acid. Gene functional analysis revealed that overexpression of SsLAR2 significantly increased the total flavonoid and catechin contents, as well as the expression levels of key enzyme genes in the catechin biosynthetic pathway in the transgenic plants. Conclusion Heterologous expression of SsLAR2 can promote catechin biosynthesis in plants. This gene provides important genetic materials and a theoretical basis for in-depth dissection of the regulatory mechanisms underlying catechin biosynthesis and targeted molecular breeding of Spatholobi Caulis.

Objective To establish the HPLC fingerprint of Heleocharis dulcis and simultaneously determine the contents of chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin, and to evaluate the quality of H. dulcis from different regions by chemical pattern recognition method, so that a reference can be provided for quality control of H. dulcis. Methods The fingerprint of H. dulcis was established on a ZORBAX SB C₁₈ (250 mm × 4.6 mm, 5 μm) column using acetonitrile-0.1% phosphoric acid solution as the mobile phase with gradient elution. the “Chinese medicine chromatographic fingerprint pattern similarity evaluation system”(2012.130723 edition) was used for similarity evaluation, SPSS27.0 and SIMCA14.1software was performed for hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were utilized to evaluate the quality of H. dulcis from diverse origins. The five chemical constituents were identified and content determined by comparison with the reference substance, and the results were synthesized using chemical pattern recognition and entropy weighted TOPSIS method. Results A total of 15 common peaks were matched to 26 batches of H. dulcis HPLC fingerprints, and five components including chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin were identified. The similarity of fingerprints was between 0.865 and 0.995. The 26 batches of H. dulcis were clustered into two classes by HCA. PCA analysis yielded a cumulative variance contribution of 83.283% for the three primary constituents. Four components, including luteolin and chlorogenic acid, were screened by OPLS-DA as the indicator components for the quality difference of H. dulcis from different regions. The mass fractions of chlorogenic acid, caffeic acid, ferulic acid, luteolin and jaceosidin in 26 batches of H.dulcis were 5.43—60.65 , 0.44—2.27, 1.65—6.46, 2.58—59.94 and 0.31—24.40 μg/g, successively. Both PCA and entropy weighted TOPSIS results indicated that samples from Hubei Province exhibited the best quality. Conclusion The established HPLC fingerprinting method is characterised by its stability, reliability, and reproducibility. which can be used for the quality evaluation of H. dulcis in combination with chemical pattern recognition, and provides a reference for the quality control and resource development of H. dulcis.

Objective To evaluate the quality difference evaluation of Hedychium flavum from different origins based on multi-index content determination, using principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (PLS-DA) and CRITIC-TOPSIS methods, so as to provide a basis for further development and utilization. Methods HPLC was used with BetaMax Neutral C₁₈ column, acetonitrile -0.4%phosphoric acid solution as mobile phase with gradient elution, detection wavelength of 320, 230, 360 and 210 nm. A total of 17 batches of H. flavum from different origins were collected. The contents of 13 chemical constituents including protocatechuic acid, trans-4-hydroxycinnamic acid, coniferaldehyde, isocoronarin D, coronarin D, coronarin A, coronarin E, quercetin, kaempferol, isorhamnetin, daucosterol, stigmasterol, β-sitosterol were detected, while extractives and total ash were examined. The 17 batches of H. flavum were grouped using PCA and PLS-DA methods, and quality differential markers were screened out. The weights of each index was calculated using the CRITIC method, and a comprehensive quality evaluation model for H. flavum was constructed using the TOPSIS method. Results The contents of the above 13 indexes among 17 batches of H. flavum were 0.121—0.295, 0.044—0.091, 0.036—0.104, 0.400—1.071, 0.300—0.515, 0.902—1.677, 0.089—0.153, 0.473—0.916, 0.177—0.378, 0.136—0.249, 0.068—0.117, 0.223—0.453, 0.240—0.863 mg/g, while the ranges of extractives and total ash were 11.4%—21.5% and 3.1%—9.2 %, respectively. PCA results showed that the cumulative variance contribution rate of two principal components was 87.564%, and 17 batches of H. flavum were divided into three categories. Kaempferol, coronarin A, protocatechuic acid, extractives, β-sitosterol, isocoronarin D and quercetin were selected as quality differential markers by PLS-DA methods. The results of CRITIC-TOPSIS method showed that the comprehensive relative proximities of 17 batches of H. flavum samples was 0.421 6—0.618 1. The quality of samples from Guizhou and Sichuan provinces exhibited superior comprehensive quality. Conclusion The established multi-index quantitative combined with PCA, PLS-DA and CRITIC-TOPSIS method can comprehensively evaluate the quality difference of H. flavum from different habitats. The method is scientific, intuitive, accurate and reliable, which can provide a theoretical and technical reference for the quality difference evaluation of H. flavum.

Fresh traditional Chinese medicine (Fresh herbs) has the unique advantage of being effective due to its freshness, with the core being the complete retention of active ingredients and high physiological activity. However, the clinical promotion of fresh drugs is restricted by the variability of their components during growth and after harvest, the lagging preservation technology and the lack of standards. This article systematically reviews the historical evolution of the application of fresh herbs and explains the material basis for efficacy due to freshness, summarizes the dynamic changes of the active ingredients of fresh herbs, such as spatio-temporal accumulation before harvest, physical escape, enzymatic oxidation and hydrolytic polymerization after harvest, and proposes a classification processing and precise storage strategy centered on retaining dominant active ingredients. It aims to reveal the scientific connotation of efficacy due to freshness of fresh herbs, and provide theoretical basis and ideas for the protection of active ingredients, quality improvement and modern application of fresh herbs.

Traditional Chinese medicine (TCM) has a long history of treating human diseases with proven efficacy. However, due to the inherent complexity of TCM, significant challenges remain in scientifically elucidating its chemical composition, processing mechanisms, pharmacological and toxicological effects, and related mechanisms. Currently, commonly used qualitative and quantitative analytical instruments, such as ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS), have made substantial contributions to the scientific interpretation of the complex chemical components and pharmacological mechanisms of TCM. Nevertheless, these methods often fail to provide information on the spatial distribution and localization of target chemical components. Mass spectrometry imaging (MSI) is an emerging molecular visualization technique. It not only possesses the qualitative identification capabilities of mass spectrometry but also enables the intuitive visualization of the spatial distribution of various chemical components within a sample, allowing simultaneous qualitative, quantitative, and spatial analyses. Currently, MSI has achieved a series of research outcomes in the field of TCM research. Firstiy, several commonly used MSI techniques are introduced. It then focuses on reviewing the research progress of MSI in the field of TCM analysis in recent years. Furthermore, it summarizes the technical bottlenecks encountered in MSI applications and corresponding solutions. Finally, it discusses the future development trends of this technology in TCM research, aiming to provide reference for enhancing the application of MSI in field of TCM analysis.

The blood-brain barrier is the core bottleneck for drug delivery to the central nervous system. Bingpian (Borneolum Syntheticum), as a traditional “guide” drug, can reversibly modulate blood-brain barrier permeability, thereby providing a unique natural efficacy-enhancing tool for brain-targeted delivery. Therefore, integrating Borneolum Syntheticum into the construction strategies of modern drug delivery systems is a powerful approach to achieve synergistic enhancement. By retrieving relevant literature on Borneolum Syntheticum-mediated brain-targeted drug delivery systems published since 2018 from CNKI and PubMed databases, focusing on the construction strategies of such drug delivery systems, this study summarized them into three categories: physical loading, chemical conjugation, and biological fusion. The design principles, carrier characteristics, and representative systems of each strategy are elaborated in detail. The influence rules between construction strategies and key properties of drug delivery systems, including stability, release capacity, blood-brain barrier crossing ability, and delivery efficacy, are deeply analyzed. Finally, the core decision-making principle of “treatment needs-strategy matching-process evaluation” is distilled, providing scientific basis and strategic references for the design, performance optimization, and clinical translation of such systems.

The theory of five flavors serves as a core component of medicinal property system in traditional Chinese medicine (TCM). The “flavor-effect” association is closely linked with the functional substances through the medicinal properties such as “pungent dispersion and sour astringency”, thereby providing a critical bridge for screening, mechanistic interpretation, and modern research on effective components. This paper systematically outlines the developmental trajectory of five-flavor theory and constructs a “taste-component-meridian tropism-effect” research framework. By analyzing characteristic components of five flavors and their multi-target regulatory effects on visceral functions, it reveals the molecular basis underlying the traditional efficacy of TCM. Furthermore, a flavor theory-guided strategy for studying effective components is proposed, integrating interdisciplinary technologies such as electronic tongue/nose bionic sensing, chromatography-mass spectrometry, network pharmacology, and artificial intelligence to establish a systematic pathway from material analysis to mechanistic verification. This framework deeply integrates traditional TCM theory with modern scientific techniques, strengthening the guiding role of five-flavor theory in discovering effective components and enhancing scientific rigor and reproducibility of mechanistic explanations for TCM actions. It aims to deeply reveal the scientific connotations and integrated action rules of the effective components in TCM, expand the research ideas of effective components, and contribute to the modernization research of TCM.