This paper outlines the development of artificial intelligence （AI） and its applications in traditional Chinese medicine （TCM） research， and elucidates the roles and advantages of large language models， knowledge graphs， and natural language processing in advancing syndrome identification， prescription generation， and mechanism exploration. Using spleen-stomach diseases as an example， it demonstrates the empowering effects of AI in classical literature mining， precise clinical syndrome differentiation， efficacy and safety prediction， and intelligent education， highlighting an upgraded research paradigm that evolves from data-driven and knowledge-driven approaches to intelligence-driven models. To address challenges related to privacy protection and regulatory compliance in cross-institutional data collaboration， a "trusted federated evidence-based analysis platform for TCM spleen-stomach diseases" is proposed， integrating blockchain-based smart contracts， federated learning， and secure multi-party computation. The deep integration of AI with privacy-preserving computing is reshaping research and clinical practice in TCM spleen-stomach diseases， providing feasible pathways and a technical framework for building a high-quality， trustworthy TCM big-data ecosystem and achieving precision syndrome differentiation.

ObjectiveTo observe the prevention and control effect of processed Polygonatum cyrtonema on depression induced by chronic unpredictable mild stress （CUMS） in female rats. MethodsForty rats were assigned into control， model， and low-， medium-， and high-dose processed P. cyrtonema groups according to the random number table method， with 8 rats in each group. The rat model of depression was established with the CUMS method. The body mass， open field test， forced swimming test， Morris water maze test， levels of neurotransmitters ［dopamine （DA）， 5-hydroxytryptamine （5-TH）， and acetylcholine （ACh）］， serum levels of sex hormones ［gonadotropin-releasing hormone（GnRH）， testosterone （T）， and estradiol （E₂）］ and inflammatory factors ［tumor necrosis factor-α （TNF-α）， interleukin （IL）-6， and IL-10］， and mRNA and protein levels of factors in the brain-derived neurotrophic factor （BDNF）/tyrosine kinase receptor B （TRKB）/cAMP-response element binding protein （CREB） pathway were employed to evaluate the effect of processed P. cyrtonema on the CUMS-induced depression in female rats. ResultsThe body mass， open field test results， and forced swimming test results showed that the rat model of depression was successfully established. The comparison of behaviors， neurotransmitters， sex hormones， inflammatory factors， and neural pathways among groups showed that processed P. cyrtonema had different effects of preventing the development of depression in female rats. SPSS 25 was used for statistical analysis of error and significance. T test was conducted between groups. Each treatment group showed significant therapeutic effect compared with the model group （P<0.05）. Processed P. cyrtonema elevated the level of 5-TH （P<0.01） and lowered the levels of DA and ACh （P<0.01） in the brain tissue of female rats. In addition， it reduced the serum levels of GnRH， T， E₂， TNF-α， and IL-6 （P<0.05） and up-regulated the mRNA levels of BDNF and TRKB in the rat brain. ConclusionProcessed P. cyrtonema has a non-hyperactive preventive effect on CUMS-induced depression in rats， which provides a theoretical basis for the development of processed P. cyrtonema as a functional food product.

ObjectiveTo observe the prevention and control effect of processed Polygonatum cyrtonema on depression induced by chronic unpredictable mild stress （CUMS） in female rats. MethodsForty rats were assigned into control， model， and low-， medium-， and high-dose processed P. cyrtonema groups according to the random number table method， with 8 rats in each group. The rat model of depression was established with the CUMS method. The body mass， open field test， forced swimming test， Morris water maze test， levels of neurotransmitters ［dopamine （DA）， 5-hydroxytryptamine （5-TH）， and acetylcholine （ACh）］， serum levels of sex hormones ［gonadotropin-releasing hormone（GnRH）， testosterone （T）， and estradiol （E₂）］ and inflammatory factors ［tumor necrosis factor-α （TNF-α）， interleukin （IL）-6， and IL-10］， and mRNA and protein levels of factors in the brain-derived neurotrophic factor （BDNF）/tyrosine kinase receptor B （TRKB）/cAMP-response element binding protein （CREB） pathway were employed to evaluate the effect of processed P. cyrtonema on the CUMS-induced depression in female rats. ResultsThe body mass， open field test results， and forced swimming test results showed that the rat model of depression was successfully established. The comparison of behaviors， neurotransmitters， sex hormones， inflammatory factors， and neural pathways among groups showed that processed P. cyrtonema had different effects of preventing the development of depression in female rats. SPSS 25 was used for statistical analysis of error and significance. T test was conducted between groups. Each treatment group showed significant therapeutic effect compared with the model group （P<0.05）. Processed P. cyrtonema elevated the level of 5-TH （P<0.01） and lowered the levels of DA and ACh （P<0.01） in the brain tissue of female rats. In addition， it reduced the serum levels of GnRH， T， E₂， TNF-α， and IL-6 （P<0.05） and up-regulated the mRNA levels of BDNF and TRKB in the rat brain. ConclusionProcessed P. cyrtonema has a non-hyperactive preventive effect on CUMS-induced depression in rats， which provides a theoretical basis for the development of processed P. cyrtonema as a functional food product.

Liver failure is a common severe syndrome of liver diseases with high mortality. The function and structural integrity of the intestinal barrier as an entity are closely associated with the development and progression of liver failure. The cGAS-STING signaling pathway can participate in innate immune response by recognizing DNA produced by pathogen invasion and host cell damage and inducing the production of type I interferon. Numerous studies have shown that activation of the cGAS-STING pathway can significantly impact the cellular structure， mucosal components， and commensal bacteria of the intestinal barrier. This article reviews the interplay between the cGAS-STING signaling pathway and intestinal barrier disruption in liver failure， in order to provide novel insights for the clinical management of liver failure.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

OBJECTIVE To build a Tibetan-language medication service platform based on “internet+” and evaluate its effect on improving medication compliance and safety of Tibetan patients with chronic disease. METHODS Medication guidance contents of commonly used drugs in the outpatient department were summarized， translated and recorded in Tibetan-language or video to form a “text-audio-video” multi-dimensional “internet+ ” Tibetan-language medication service platform. A total of 387 Tibetan outpatients with chronic disease in our hospital after the implementation of “internet+” Tibetan-language medication service platform （from January 2024 to June 2024） in our hospital were selected as the intervention group， and 387 Tibetan outpatients before the implementation （from January 2023 to June 2023） were selected as the control group. Patients in the control group received conventional window-based Chinese-language medication services， while patients in the intervention group received both conventional window-based Chinese-language medication service and “internet+ ” Tibetan-language medication service. The medication compliance of patients was evaluated using the 12-item Medication Compliance Scale. A six-level causality assessment was conducted as the principles for analyzing adverse drug reactions （ADR） set by the National Center for ADR Monitoring. Additionally， statistics were compiled on the occurrence of ADR that were assessed as “definite”“probable” or “possible” in the causality assessment. RESULTS The proportion （31.0%） of patients with good medication compliance and compliance scores [39.0 （37.0，42.0）] of patients in the intervention group were significantly better than control group [7.0%， 21.0（19.0， 23.0）]（ P＜0.05）. There were no statistically significant differences in the incidence of various types of ADR or the overall incidence between the two groups （P＞0.05）. CONCLUSIONS The “internet+” Tibetan-language medication service platform is constructed successfully； the service can effectively improve the medication compliance of Tibetan-language patients， but its effect on improving the medication safety of patients is limited.

Objective: To improve the efficiency and standardization of preoperative anemia diagnosis and treatment by establishing a systematic intelligent management platform for preoperative anemia. Methods: A multidisciplinary collaborative model was adopted to develop a preoperative anemia management system that integrates intelligent early warning, standardized treatment pathways, and quality control. The system utilizes natural language processing technology to automatically capture laboratory data and establish evidence-based medical decision support functions. A pre-post study design was employed to compare changes in preoperative anemia screening rates, preoperative anemia intervention rates, reasonable use of iron supplements, and perioperative red blood cell transfusion rates before and after system implementation. Results: After system implementation, the standardization of anemia diagnosis and treatment significantly improved: 1) Screening effectiveness: The anemia screening rate increased to 50.00% (an increase of 27.24%); 2) Intervention effectiveness: The anemia treatment rate rose to 56.30% (an increase of 14.02%); 3) Treatment standardization: The reasonable use rate of iron supplements increased to 55.33% (an increase of 21.02%); the red blood cell transfusion rate decreased to 18.29% (a decrease of 4.07%), and the amount of red blood cell transfusions was reduced by 291 units. Conclusion: This system achieves full-process management of preoperative anemia through information technology, significantly enhancing the standardization of diagnosis and treatment as well as intervention effectiveness, providing an effective solution for perioperative anemia management.

The rapid development of the pharmaceutical research and development (R&D) has brought new challenges to occupational health management, including the high uncertainty in the R&D process, emerging hazards, and compliance complexities associated with novel business models. Traditional management approaches exhibit limitations in effectively addressing the occupational health risks associated with these challenges. Based on the perspective of agile governance, this paper proposed an optimized pathway characterized by dynamic response, adaptive flexibility, and multi-stakeholder collaboration. It further offered countermeasures and recommendations from three aspects: concept renewal, mechanism innovation, and tool empowerment, aiming to provide reference for the effective management and control of occupational health risks in the innovation and development of the pharmaceutical R&D industry.