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 investigate the correlation between sleep patterns and myopia progression among younger school-age children at a primary school in Changning District of Shanghai, based on the data from the Shanghai Students’ Common Diseases and Health Influencing Factors Monitoring System and a sleep-specific survey, so as to provide data support for myopia prevention and control in this age group. MethodsOne primary school was selected from the common diseases and health influencing factors monitoring system for students in Changning District, Shanghai. A total of 230 first-grade students were included in the study. Myopia and refractive parameters were examined, and sleep patterns were investigated. General demographic characteristics and myopia-related behavior data of the students were also collected. Sleep patterns were evaluated in terms of sleep duration, sleep efficiency, and sleep quality, with the latter assessed using the Chinese version of the Children’s Sleep Habits Questionnaire (CSHQ). Multiple linear regression and binary logistic regression models were used to analyze the association between sleep patterns and myopia progression among these students. ResultsThe results of the regression analyses revealed that the total CSHQ score of the students at baseline survey was (48.85±7.15) points. Their sleep efficiency was (94.49±8.48)%, sleep duration was (9.58±0.93) hours, and the proportion of those with insufficient sleep (<10 hours) was 78.26%. At baseline survey, students’ higher daytime sleepiness scores were associated with lower spherical equivalent (SE) ( β=-0.18, 95%CI: -0.31 to -0.04) and an increased risk of axial length (AL) / corneal radius (CR) ratio >3 (OR=1.52, 95%CI: 1.00 to 2.29), whereas longer sleep duration and higher sleep efficiency were associated with higher SE (β=0.18, 95%CI: 0.05 to 0.32; β=0.17, 95%CI: 0.04 to 0.31, respectively), shorter (AL) (β=-0.15, 95%CI: -0.27 to -0.03; β=-0.13, 95%CI: -0.25 to 0, respectively) and a reduced risk of AL /CR>3 (OR=0.70, 95%CI: 0.51 to 0.96; OR=0.73, 95%CI: 0.53 to 0.99, respectively). At baseline survey, children’s higher propensity for sleep problems (OR=1.70, 95%CI: 1.04 to 2.78), sleep resistance (OR=2.26, 95%CI: 1.36 to 3.75), and sleep anxiety scores (OR=2.15, 95%CI: 1.33 to 3.48) were all associated with an increased risk of AL/CR >3 at follow-up (all P<0.05). Furthermore, higher sleep anxiety scores predicted prolonged AL at follow-up (β=0.03, 95%CI: 0 to 0.05). According to the mixed-effects model, higher daytime sleepiness scores and prolonged sleep duration were independently linked to reduced right-eye SE (β=-0.05, 95%CI: -0.10 to 0, P<0.05) and shorter right-eye AL (β=-0.05, 95%CI: -0.10 to 0, P<0.05). ConclusionIn this school in Shanghai, there are problems of insufficient and poor-quality sleep among young children. Sleep problems such as sleep resistance, delayed sleep onset, sleep anxiety, and daytime sleepiness among children may accelerate the risk of myopia progression, while longer sleep duration and higher sleep efficiency may serve as protective factors against the occurrence and development of myopia.

The Keap1-Nrf2 pathway has been shown to be an important defense mechanism against oxidative stress, which may be an effective therapeutic strategy for many diseases. The research progresses on Keap1-Nrf2 pathway in inflammatory diseases were mainly reviewed. The basic components and activation mechanism of Keap1-Nrf2 pathway were introduced. The relationship between Keap1-Nrf2 pathway and the crosstalk between NF-κB pathway and HO-1 pathway, the expression of inflammatory mediators and enzymes, and inflammatory bodies were expounded. Natural product-derived inhibitors, small molecule inhibitors targeting Keap1-Nrf2 pathway and their clinical progress were introduced, and the potential application value of Keap1-Nrf2 pathway in the treatment of inflammation was discussed.

Background/Aims: Reflux symptoms frequently present in patients diagnosed with functional dyspepsia (FD). This investigation sought to elucidate the contribution of gastroesophageal reflux in the overlap relationship. Methods: Consecutive patients presenting with reflux symptoms and/or FD symptoms were prospectively included. Comprehensive assessments, including symptoms evaluation, endoscopy, esophageal functional examinations (high-resolution manometry and reflux monitoring), and proton pump inhibitor (PPI) treatment efficacy evaluation, were conducted in these patients. Results: The study enrolled 315 patients, 43.2% of which had concurrent FD symptoms and overlapping reflux symptoms. Notably, a mere 28.7% of patients in the overlap symptoms group had objective gastroesophageal reflux disease evidences (the grade of esophagitis≥ B or the acid exposure time ≥ 4.2%). Functional heartburn was demonstrated to be the main cause of overlapping reflux symptoms(55.1%). Reflux parameters analysis revealed that the reflux burden in the overlap symptoms group paralleled that of the FD symptoms group, with both registering lower levels than the reflux symptoms group (P < 0.05). Furthermore, PPI response rates were notably diminished in the overlap symptoms group (P < 0.001), even for those with objective gastroesophageal reflux disease evidences. Conclusions The study illuminated that overlapping reflux symptoms in FD was common. Strikingly, these symptoms primarily diverged from reflux etiology and exhibited suboptimal responses to PPI intervention. These findings challenge prevailing paradigms and accentuate the imperative for nuanced therapeutic approaches tailored to the distinctive characteristics of overlapping reflux symptoms in the context of FD.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Objective To explore the efficacy of DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy for management of cancer pain and provide reference for its standardized clinical application.Methods and Results Recommendations were formulated based on literature review and expert group discussion,and consensus was reached following expert consultation.The consensus recommendations are comprehensive,covering the entire treatment procedures from preoperative assessment and preparation,surgical operation process,postoperative management and traditional Chinese medicine treatment to individualized treatment planning.The study results showed that the treatment plans combining traditional Chinese with Western medicine effectively alleviated cancer pain,reduced the use of opioid drugs,and significantly improved the quality of life and enhanced immune function of the patients.Postoperative follow-up suggested good treatment tolerance among the patients without serious complications.Conclusion The formulated consensus is comprehensive and can provide reference for clinicians to use DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy.The combined treatment has a high clinical value with a good safety profile for management of cancer pain.

Functional dyspepsia (FD), characterized by persistent or recurrent dyspeptic symptoms without identifiable organic, systemic or metabolic causes, is an increasingly recognized global health issue. The objective of this guideline is to equip clinicians and nursing professionals with evidence-based strategies for the management and treatment of adult patients with FD using traditional Chinese medicine (TCM). The Guideline Development Group consulted existing TCM consensus documents on FD and convened a panel of 35 clinicians to generate initial clinical queries. To address these queries, a systematic literature search was conducted across PubMed, EMBASE, the Cochrane Library, China National Knowledge Infrastructure (CNKI), VIP Database, China Biology Medicine (SinoMed) Database, Wanfang Database, Traditional Medicine Research Data Expanded (TMRDE), and the Traditional Chinese Medical Literature Analysis and Retrieval System (TCMLARS). The evidence from the literature was critically appraised using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. The strength of the recommendations was ascertained through a consensus-building process involving TCM and allopathic medicine experts, methodologists, pharmacologists, nursing specialists, and health economists, leveraging their collective expertise and empirical knowledge. The guideline comprises a total of 43 evidence-informed recommendations that span a range of clinical aspects, including the pathogenesis according to TCM, diagnostic approaches, therapeutic interventions, efficacy assessments, and prognostic considerations. Please cite this article as: Zhang SS, Zhao LQ, Hou XH, Bian ZX, Zheng JH, Tian HH, Yang GH, Hong WS, He YY, Liu L, Shen H, Li YP, Xie S, Shu J, Zeng BF, Li JX, Liu Z, Xiao ZH, Xiao JD, Zheng PY, Huang SG, Chen SL, Fei GJ. International clinical practice guideline on the use of traditional Chinese medicine for functional dyspepsia (2025). J Integr Med. 2025; 23(5):502-518.
Dyspepsia/drug therapy* ; Humans ; Medicine, Chinese Traditional/methods* ; Practice Guidelines as Topic ; Drugs, Chinese Herbal/therapeutic use*

Objective To explore the diagnostic and therapeutic strategies for primary small round cell malignant tumor of the seminal vesicle,so as to provide reference for the early prevention and treatment of this disease.Methods The clinical features,diagnostic approaches and treatment strategies of this case were reported based on literature review.Results A 26-year-old male patient was admitted due to"progressive dysuria complicated with painful urination and difficult defecating for two weeks."Pelvic MRI revealed a large,round,heterogeneous signal mass in the pelvic cavity(rectovesical pouch,posterior-superior to the prostate).Needle biopsy indicated a small round cell malignant tumor.Based on ancillary tests and clinical features,the case was diagnosed as advanced-stage malignancy with no opportunity for surgical intervention,and conservative treatment was initiated.The patient ultimately died two months after pathological diagnosis.A review of literature on seminal vesicle small round cell tumors over the past 20 years indicated that Ewing's sarcoma and rhabdomyosarcoma were the predominant subtypes.Conclusion Primary small round cell malignant tumor of the seminal vesicle is exceptionally rare,and clinically atypical with poor outcomes.While it is diagnostically and therapeutically challenging,early surgical intervention may significantly improve the prognosis and quality of life.

Thoracic anesthesia with spontaneous respiration represents a form of precision anesthesia meticulously customized to individual patients.Considering the more stringent requirements this anesthesia approach imposes on the regulation of respiratory function,the writing group of the"Consensus of Experts on the Management of Thoracic Anesthesia with Spontaneous Respiration"has formulated elaborate guidelines regarding indications and contraindications,preoperative evaluation,anesthesia implementation,common complications,and treatment strategies.This was accomplished by referencing relevant domestic and international literature and integrating it with actual clinical requirements.The objective is to standardize the rational application of this anesthesia method.

Porphyromonas gingivalis is an important pathogenic bacterium causing a variety of oral and systemic diseases. The LuxS/AI-2 quorum sensing system plays a key role in regulating numerous physiological processes such as biofilm formation, virulence factors and drug resistance in Porphyromonas gingivalis. Quorum sensing inhibitors are a new potential antibiotic substitute, a new method to control bacterial infection under the inhibition of biofilm formation, bacterial virulence and no induction of antibiotic resistance. This review is a summary of the research progress of the LuxS/AI-2 quorum sensing system in regulating biofilm formation, virulence, resistance and quorum sensing inhibitors in Porphyromonas gingivalis, and provides a theoretical basis for further research on the inhibitory targets of the LuxS/AI-2 quorum sensing system in Porphyromonas gingivalis.