The Pharmacovigilance Guidelines for Clinical Application of Oral Chinese Patent Medicines （hereinafter referred to as the Guidelines） is first specialized in the field of drug safety for oral Chinese patent medicines （OCPMs） in China. Rooted in China's healthcare context， the Guidelines address the unique usage patterns and risk characteristics of OCPMs， filling a regulatory gap in the pharmacovigilance framework specific to this category. To facilitate accurate understanding and effective implementation of the Guidelines， and to promote the standardized development of pharmacovigilance practices for OCPMs， this study offered a systematic interpretation based on its three core components. In the domain of risk monitoring and reporting， the paper analyzed the rationale for multi-source information integration and clarified the criteria for identifying key products and target populations for intensive monitoring. Regarding risk assessment， the Guidelines were examined from three dimensions of formulation components， medication behaviors， and population to address complex safety issues arising from medicinal constituents， irrational use， and individual susceptibility. In the area of risk control， the analysis focused on context-based interventions and dynamic closed-loop management strategies， exploring practical pathways to shift from passive response to proactive risk mitigation. Furthermore， this paper evaluated the applied value of the Guidelines and identified implementation challenges， such as insufficient capacity at the primary-care level and limited digital infrastructure. In response， the study proposed optimization strategies including establishing a dynamic updating mechanism， strengthening training at the grassroots level， and incorporating artificial intelligence to enhance pharmacovigilance capacity. This interpretation aims to provide actionable insights for marketing authorization holders （including manufacturers）， pharmaceutical distributors， healthcare institutions， and research organizations， ultimately supporting the establishment and refinement of a full lifecycle pharmacovigilance system for OCPMs.

Objective: To characterize perioperative dynamic changes in immune-cell phenotypes and inflammatory cytokines in patients undergoing CPB (cardiopulmonary bypass) cardiac surgery, and to explore their associations with postoperative outcomes. Methods: In this prospective cohort study, 120 adult patients who underwent elective cardiac surgery under CPB at West China Hospital from May 2022 to March 2023 were enrolled. Perioperative immune-cell phenotypes and concentrations of 40 inflammation-related cytokines were measured. The primary outcomes were the sequential organ failure assessment (SOFA) score at 24 h after surgery and ΔSOFA (the peak SOFA score within 48 h after surgery minus the preoperative SOFA score). Secondary outcomes included major adverse cardiovascular events (MACE), acute kidney injury (AKI), respiratory failure, severe liver injury, and infection. Results: The mean age of enrolled patients was 57±10 years. Of these, 52% (62/120) were male and 90% (108/120) underwent valve surgery. During the rewarming to the end of CPB, neutrophil counts rapidly increased (7.39×10 /L vs preoperative 3.07×10 /L, P<0.001), with significant upregulation of CD11b (7.30×10 /L vs preoperative 3.05×10 /L, P<0.001) and CD54 (7.15×10 /L vs preoperative 2.99×10 /L, P<0.001). Lymphocyte counts increased at the end of CPB (1.75×10 /L vs preoperative 1.12×10 /L, P<0.001) but decreased significantly at 24 h after surgery (0.59×10 /L vs preoperative 1.12×10 /L, P<0.001). Plasma analysis showed that multiple pro-inflammatory cytokines increased during CPB and remained elevated up to 24 h after surgery; five chemokines and the anti-inflammatory cytokine IL-10 peaked at the end of CPB. The SOFA score increased from 1 (1, 2) preoperatively to 7 (5, 10) at 24 h after surgery, with a ΔSOFA of 6 (4, 8). Within 30 days after surgery, 48 patients (40.0%) developed AKI, 17 (14.2%) developed infection, 4 (3.3%) developed severe liver injury, 3 (2.5%) developed respiratory failure, and 3 (2.5%) experienced MACE. During the 2-year follow-up, 8 patients (6.7%) experienced MACE and 5 (4.2%) died. Conclusion: Multi-organ dysfunction is common after cardiac surgery under CPB (median ΔSOFA, 6), accompanied by perioperative activation of multiple immune-cell subsets and upregulation of pro-inflammatory, anti-inflammatory, and chemotactic mediators. This study provides data-driven evidence and research clues for further investigation of the associations between CPB-related immune perturbations and postoperative organ dysfunction and clinical outcomes.

ObjectiveTo investigate the mechanism of Zuogui Wan （ZGW） in improving ovarian inflammatory microenvironment and stemness of ovarian germline stem cells （OSCs） for treating ovarian aging via the cyclic guanosine monophosphate/adenosine monophosphate synthase （cGAS）/stimulator of interferon genes （STING） signaling pathway. MethodsForty C57BL/6 female mice were randomly divided into a blank group， a model group， a low-dose ZGW group （2.7 g·kg^-1）， a high-dose ZGW group （5.4 g·kg^-1）， and an estradiol valerate group （0.15 mg·kg^-1）， with 8 mice in each group. Except the blank group， all other groups received a single intraperitoneal injection of cyclophosphamide at 120 mg·kg^-1 to establish an ovarian aging mouse model. After successful modeling， each group was continuously administered for 4 weeks， once daily. The physiological status of the mice was observed， and the ovarian index was calculated. The estrus cycle of the mice was monitored. Hematoxylin-eosin （HE） staining was used to observe pathological changes in ovarian tissue. Enzyme-linked immunosorbent assay （ELISA） was used to detect serum sex hormone levels. Serum inflammatory factors interleukin-1β （IL-1β）， tumor necrosis factor-α （TNF-α）， and mouse interleukin-6 （IL-6） levels were detected using kits. Western blot was used to detect the protein expression of ovarian cGAS， STING， p-STING， TANK-binding kinase 1 （TBK1）， p-TBK1， interferon-induced transmembrane protein 3 （Fragilis）， and Vasa homolog protein （MVH）. Quantitative real-time polymerase chain reaction （Real-time PCR） was used to detect the mRNA expression of inflammatory factors in ovarian tissue. Immunofluorescence double labeling was performed to locate OSCs in ovarian tissues， and fluorescence intensities of OSCs markers MVH and octamer binding transcription factor 4 （Oct4） were calculated. ResultsCompared with the blank group， the model group showed reduced body weight， ovarian wet weight， and ovarian index （P<0.01） and a disordered estrus cycle （P<0.01）. In addition， the levels of serum follicle-stimulating hormone （FSH）， TNF-α， IL-6， and IL-1β were increased （P<0.01）， while anti-Müllerian hormone （AMH） and estradiol （E₂） levels were decreased （P<0.01）. The protein expression of cGAS， p-STING/STING， and p-TBK1/TBK1 in ovarian tissue was increased （P<0.05， P<0.01）， while that of OSCs stemness factors MVH and Fragilis was reduced （P<0.01）. Immunofluorescence indicated a reduction in MVH and Oct4 expression in OSCs （P<0.01）. The mRNA expression of inflammatory factors TNF-α， IL-6， and IL-1β in ovarian tissue was increased （P<0.05， P<0.01）. Compared with the model group， the treatment groups exhibited improved body weight， ovarian wet weight， and ovarian index （P<0.05） and a reduced rate of estrus cycle disorder （P<0.05， P<0.01）. The levels of serum FSH， TNF-α， IL-6， and IL-1β were decreased （P<0.05， P<0.01）， while AMH and E₂ levels were increased （P<0.01）. The protein expression levels of cGAS， p-STING/STING， and p-TBK1/TBK1 in ovarian tissue were decreased （P<0.05）， while the protein expression of MVH and Fragilis was increased （P<0.05）， and the fluorescence intensities of MVH and Oct4 were increased （P<0.05， P<0.01）. The mRNA expression of inflammatory factors in ovarian tissue was decreased （P<0.05）. ConclusionZGW alleviate ovarian inflammatory response， regulate ovarian microenvironment homeostasis， and maintain stemness of OSCs in ovarian aging mice probably by modulating the cGAS-STING signaling pathway， thereby improving ovarian function and delaying ovarian aging.

Objective: To systematically characterize the developmental trajectory and interdisciplinary integration of intelligent diagnosis in traditional Chinese medicine (TCM) through quantitative topic evolution analysis, we addressed the fragmentation of existing research and clarified the long-term research structure and evolutionary patterns of the field. Methods: A topic evolution analysis was performed on Chinese-language literature pertaining to intelligent diagnosis in TCM. Publications were retrieved from the China National Knowledge Infrastructure (CNKI), Wanfang Data, and China Science and Technology Journal Database (VIP), covering the period from database inception to July 3, 2025. A hybrid segmentation approach, based on cumulative publication growth trends and inflection point detection, was applied to divide the research timeline into distinct stages. Subsequently, the latent Dirichlet allocation (LDA) model was used to extract research topics, followed by alignment and evolutionary analysis of topics across different stages. Results: A total of 3 919 publications published between 2003 and 2025 were included, and the research trajectory was divided into five stages based on data-driven breakpoint detection. The field exhibited a clear evolutionary shift from early rule-based systems and tongue-pulse image and signal analysis (2006 – 2010), to machine-learning-based syndrome and prescription modeling (2011 – 2015), followed by deep-learning-driven pattern recognition and formula association (2016 – 2020). Since 2021, research has increasingly emphasized knowledge-graph construction, multimodal integration, and intelligent clinical decision-support systems, with recent studies (2024 – 2025) showing the emergence of large language models and agent-based diagnostic frameworks. Topic evolution analysis further revealed sustained cross-stage continuity in syndrome modeling and prescription association analysis, alongside the progressive consolidation of integrated intelligent diagnostic platforms. Conclusion By identifying key technological transitions and persistent core research themes, our findings offer a structured reference framework for the design of intelligent diagnostic systems, the construction of knowledge-driven clinical decision-support tools, and the alignment of AI models with TCM diagnostic logic. Importantly, the stage-based evolutionary insights derived from this analysis can inform future methodological choices, improve model interpretability and clinical applicability, and support the translation of intelligent TCM diagnosis from experimental research to real-world clinical practice.

It is believed that the occurrence and development of squamous cell carcinoma （SCC） is closely associated with inflammatory responses. The theory of fire and heat， advocated by LIU Wansu， provides significant clinical guidance for understanding the pathogenesis and treatment of SCC. Based on this theory， the pathological mechanisms and clinical characteristics of SCC at different stages were analyzed. In the precancerous and early stages， the primary pathogenesis is qi stagnation leading to internal generation of constrained heat； in post-surgery， the condition shifts to qi deficiency with latent yin fire； during the treatment phase， the pathogenesis involves accumulation of pathogenic factors， excess toxins， and severe heat toxicity； in the late stage， the main pathology is yin deficiency with toxic heat， and phlegm-stasis obstruction of the internal organs. Corresponding stage-based treatment strategies are proposed. In the early stage， regulating qi movement to dissipate constrained heat； for post-surgery， tonifying qi and raising yang to dispel latent fire； during treatment stage， clearing heat and detoxifying to eliminate cancerous toxins； and in the late stage， nourishing yin and unblocking the bowels to clear deficiency heat.

ObjectiveTo explore the spatial distribution patterns of flavonoid glycosides in Epimedium sagittatum and the influences of environmental factors on the accumulation of these components. MethodsThe spatial statistical analysis and GeoDetector model were used to analyze the distribution patterns of epimedin A，epimedin B，epimedin C，icariin，and total flavonoid glycosides in E. sagittatum samples from 92 different production areas in 36 cities of 13 provinces/municipalities/autonomous regions of China，as well as the effects of 28 environmental factors on the accumulation of each component. ResultsThe average content of flavonoid glycosides 64 （69.56%） producing areas and 30 （83.33%） cities met the quality standard of no less than 1.50% of total flavonoid glycosides in the 2020 edition of Chinese Pharmacopoeia.Epimedin A，epimedin B，epimedin C，icariin，and their sum showed significantly high accumulation.The hot spots regions of epimedin A and epimedin B were similar with each other，mainly located in western Hunan，eastern Hubei，eastern Guizhou，and northern Guangxi.The common hot spot areas of epimedin C and total flavonoid glycosides were in western and southwestern Hunan，southern Henan，northern Anhui，eastern Guizhou，and southern Chongqing.The hot spots areas of icariin were in southern Chongqing，western Hunan，and eastern and northeastern Guizhou.The interactions between environmental factors had stronger explanatory power for the accumulation of components than single factors.The strongest single factor and interactive factor affecting the accumulation of epimedin C were precipitation of wettest quarter （q=0.16） and its interaction with temperature seasonality （q=0.35），respectively.The strongest single factor influencing both the accumulation of icariin and total flavonoid glycosides was the precipitation of coldest quarter （q equals 0.15 and 0.22，respectively）.The strongest interactions were observed between precipitation of coldest quarter and gravel content （q=0.34），as well as between precipitation of coldest quarter and aspect （q=0.35）. ConclusionThirteen cities，including Zhumadian and Nanyang in Henan，Huaihua，Shaoyang，and Zhangjiajie in Hunan，and Zunyi，Qiandongnan，and Tongren in Guizhou，were hot spots of total flavonoid glycosides in E.sagittatum.Precipitation，gravel content，temperature seasonality，and aspect significantly influence the accumulation of flavonoid glycosides in E.sagittatum.This study provides reference for the utilization and production zoning of E.sagittatum.

Objective: To examine the reciprocal relationships of anxiety and depressive symptoms,uncertainty stress with academic buoyancy among college students, providing evidence for mental health promotion and academic resilience enhancement. Methods: A multi stage cluster random sampling method was used to selected 741 undergraduates from grade 1 to 2 of a university in Xuzhou, Jiangsu Province. Participants completed two waves of surveys (T1: October 2022; T2: October 2023) using the Uncertainty Stress Scale, Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), and Academic Buoyancy Scale. Cross lagged models analyzed bidirectional relationships between three mental health variables and academic buoyancy, followed by latent variable modeling integrating all mental health dimensions. Results: Cross lagged model results revealed that T1 uncertainty stress negatively predicted T2 academic buoyancy ( β =-0.14), while T1 academic buoyancy negatively predicted T2 uncertainty stress ( β =-0.11); T1 depressive symptom negatively predicted T2 academic buoyancy ( β =-0.08), while T1 academic buoyancy negatively predicted T2 depressive symptom ( β =-0.09); furthermore, T1 academic buoyancy negatively predicted T2 anxiety symptom( β =-0.10) ( P <0.05). Results from the latent variable cross lagged model of psychological problems (constructed from the three mental health variables) indicated that T1 psychological problems negatively predicted T2 academic buoyancy ( β =-0.09), while T1 academic buoyancy negatively predicted T2 psychological problems ( β =-0.09) ( P <0.05). Conclusions Longitudinal bidirectional relationships exist between mental health status and academic buoyancy in college students. Better mental health facilitates higher academic buoyancy.

Intravitreal injection of anti-vascular endothelial growth factor(VEGF)agents has become the primary treatment for macular edema associated with retinal vascular disease such as diabetic retinopathy and retinal vein occlusion, but there are limitations such as variable treatment efficacy and insufficient durability of therapeutic effects. As the first bispecific antibody applied in ophthalmic treatment, Faricimab achieves favorable outcomes by simultaneously targeting both VEGF-A and angiopoietin-2(Ang-2)pathways. Based on evidence from recent clinical trials and real-world studies, this article reviews the research progress on Faricimab for the treatment of diabetic macular edema(DME), retinal vein occlusion-associated macular edema(RVO-ME)and refractory macular edema compared to the therapeutic effects of other agents. Additionally, based on Faricimab's safety characteristics and future potential, its therapeutic prospects for macular edema associated with retinal vascular diseases are discussed. This review aims to provide evidence-based references for optimizing clinical treatment strategies, thereby contributing to mitigating the risk of vision loss due to macular edema.

Tryptophan(Trp), an essential amino acid of mammals, is decomposed mainly through kynurenine pathway(KP)and 5-hydroxytryptamine(5-HT) pathway, and the rest were metabolized by intestinal flora. KP is the main pathway, which is co-initiated by the rate-limiting enzyme tryptophan 2,3-dioxygenase(TDO) and interferon-reactive indoleamine 2,3-dioxygenase(IDO). The Trp decomposition products produced through the above pathways play a key role in immune regulation and maintenance of intestinal homeostasis by binding with aryl hydrocarbon receptor(AhR). Based on current studies on Trp metabolism, this paper systematically discusses the relationship between Trp pathway and immune system, as well as focuses on intestinal immunity and new potential therapeutic targets.

Abstract Modern western medicine typically focuses on treating specific symptoms or diseases, and traditional Chinese medicine (TCM) emphasizes the interconnections of the body’s various systems under external environment and takes a holistic approach to preventing and treating diseases. Phenomics was initially introduced to the field of TCM in 2008 as a new discipline that studies the laws of integrated and dynamic changes of human clinical phenomes under the scope of the theories and practices of TCM based on phenomics. While TCM Phenomics 1.0 has initially established a clinical phenomic system centered on Zhenghou (a TCM definition of clinical phenome), bottlenecks remain in data standardization, mechanistic interpretation, and precision intervention. Here, we systematically elaborates on the theoretical foundations, technical pathways, and future challenges of integrating digital medicine with TCM phenomics under the framework of “TCM phenomics 2.0”, which is supported by digital medicine technologies such as artificial intelligence, wearable devices, medical digital twins, and multi-omics integration. This framework aims to construct a closed-loop system of “Zhenghou–Phenome–Mechanism–Intervention” and to enable the digitization, standardization, and precision of disease diagnosis and treatment. The integration of digital medicine and TCM phenomics not only promotes the modernization and scientific transformation of TCM theory and practice but also offers new paradigms for precision medicine. In practice, digital tools facilitate multi-source clinical data acquisition and standardization, while AI and big data algorithms help reveal the correlations between clinical Zhenghou phenomes and molecular mechanisms, thereby improving scientific rigor in diagnosis, efficacy evaluation, and personalized intervention. Nevertheless, challenges persist, including data quality and standardization issues, shortage of interdisciplinary talents, and insufficiency of ethical and legal regulations. Future development requires establishing national data-sharing platforms, strengthening international collaboration, fostering interdisciplinary professionals, and improving ethical and legal frameworks. Ultimately, this approach seeks to build a new disease identification and classification system centered on phenomes and to achieve the inheritance, innovation, and modernization of TCM diagnostic and therapeutic patterns.