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.

As a patented characteristic medicine of Yi ethnic minority， Pingxuan capsules have the effects of nourishing the liver and kidney， pacifying the liver， and subduing Yang. With the main indications of dizziness， headache， palpitations， tinnitus， insomnia， dreaminess， waist and knee soreness caused by liver-kidney deficiency and liver Yang upward disturbance， Pingxuan capsules are widely used in the treatment of posterior circulation ischemic vertigo， vestibular migraine， benign paroxysmal positional vertigo. However， the current knowledge is limited regarding the efficacy， syndrome differentiation， and safety of this medicine. On the basis of summarizing the experience of clinicians and the existing evidence， this study invites clinical experts of traditional Chinese and Western medicine， pharmaceutical experts， and methodological experts from relevant fields across China to conduct evidence-based evaluation of Pingxuan capsules. The evaluation follows the Specifications for the Development of Clinical Expert Consensus on Chinese Patent Medicines issued by the Standardization Office of the China Association of Chinese Medicine， and reaches 5 recommendations and 16 consensus suggestions. The consensus clarifies the clinical applications， efficacy， dose， course of treatment， combination of medicines， precautions， and contraindications of Pingxuan capsules in the treatment of vertigo and explains the safety of clinical application. This consensus is applicable to clinicians （traditional Chinese medicine， Western medicine， and integrated traditional Chinese and Western medicine） and pharmacists in tertiary hospitals， secondary hospitals， and community-level medical and health institutions across China， providing a reference for the rational use of Pingxuan capsules in the treatment of vertigo. It is hoped that the promotion of this consensus can facilitate the rational use of drugs in clinical practice， reduce the risk of drug use， and give full play to the advantages of Pingxuan capsules in the treatment of vertigo diseases. This consensus has been reviewed and published by the China Association of Chinese Medicine， with the number GS/CACM330-2023.

The classic formula Mulisan is the 45th of the 93 formulas in the Catalogue of Ancient Classic Formulas （second batch） of Han medicine published by the National Administration of Traditional Chinese Medicine. It consists of Ostreae Concha， Astragali Radix， Ephedrae Radix et Rhizoma， and wheat， with the effect of replenishing qi and stopping sweating. It is a common formula in the clinical treatment with traditional Chinese medicine. This study analyzes the historical evolution， composition， dosage， original plants and their processing methods， decocting method， efficacy， indications， and modern clinical application of Mulisan by tracing， comparative analysis， and bibliometric methods. The results showed that Mulisan firstly appeared in the Pulse Classic written by WANG Shuhe in the Western Jin Dynasty. The formulation idea can be traced back to the Important Prescriptions Worth a Thousand Gold for Emergency in the Tang Dynasty. The herb composition， dosage， efficacy， and indications of Mulisan were first recorded in the Treatise on Diseases， Patterns， and formulas Related to Unification of the Three Etiologies in the Southern Song dynasty. In terms of original plants and their processing methods， Ostreae Concha is the shell of Ostrea rivularis， which should be calcined before use. Astragali Radix and Ephedrae Radix et Rhizoma are the dried roots of Astragalus membranaceus var. mongholicus and Ephedra sinica， respectively， the raw material of which should be used. Wheat is the dried mature fruit of T. aestivum， which can be used without processing， while the stir-fried fruit， being thin and deflated， demonstrates better effect. The composition of Mulisan is Ostreae Concha 8.26 g， Astragali Radix 8.26 g， Ephedrae Radix et Rhizoma 8.26 g， and wheat 7.92 g. The medicinal materials should be ground into coarse powder and decocted with 450 mL water to reach a volume of 240 mL， and the decoction should be taken warm. In modern clinical practice， Mulisan has a wide range of indications， including spontaneous sweating and night sweating caused by Yang deficiency or Qi deficiency. The clinical disease spectrum treated by Mulisan involves endocrine system diseases， neurological diseases， respiratory system diseases， and cancer. This formula plays a significant role in the treatment of internal medicine diseases in traditional Chinese medicine. This study aims to provide a scientific basis for the subsequent research， development， and clinical application of Mulisan.

The classic formula Mulisan is the 45th of the 93 formulas in the Catalogue of Ancient Classic Formulas （second batch） of Han medicine published by the National Administration of Traditional Chinese Medicine. It consists of Ostreae Concha， Astragali Radix， Ephedrae Radix et Rhizoma， and wheat， with the effect of replenishing qi and stopping sweating. It is a common formula in the clinical treatment with traditional Chinese medicine. This study analyzes the historical evolution， composition， dosage， original plants and their processing methods， decocting method， efficacy， indications， and modern clinical application of Mulisan by tracing， comparative analysis， and bibliometric methods. The results showed that Mulisan firstly appeared in the Pulse Classic written by WANG Shuhe in the Western Jin Dynasty. The formulation idea can be traced back to the Important Prescriptions Worth a Thousand Gold for Emergency in the Tang Dynasty. The herb composition， dosage， efficacy， and indications of Mulisan were first recorded in the Treatise on Diseases， Patterns， and formulas Related to Unification of the Three Etiologies in the Southern Song dynasty. In terms of original plants and their processing methods， Ostreae Concha is the shell of Ostrea rivularis， which should be calcined before use. Astragali Radix and Ephedrae Radix et Rhizoma are the dried roots of Astragalus membranaceus var. mongholicus and Ephedra sinica， respectively， the raw material of which should be used. Wheat is the dried mature fruit of T. aestivum， which can be used without processing， while the stir-fried fruit， being thin and deflated， demonstrates better effect. The composition of Mulisan is Ostreae Concha 8.26 g， Astragali Radix 8.26 g， Ephedrae Radix et Rhizoma 8.26 g， and wheat 7.92 g. The medicinal materials should be ground into coarse powder and decocted with 450 mL water to reach a volume of 240 mL， and the decoction should be taken warm. In modern clinical practice， Mulisan has a wide range of indications， including spontaneous sweating and night sweating caused by Yang deficiency or Qi deficiency. The clinical disease spectrum treated by Mulisan involves endocrine system diseases， neurological diseases， respiratory system diseases， and cancer. This formula plays a significant role in the treatment of internal medicine diseases in traditional Chinese medicine. This study aims to provide a scientific basis for the subsequent research， development， and clinical application of Mulisan.

ObjectiveTo investigate the characteristics of mitochondrial translational initiation factor 2 （MTIF2） gene methylation and its association with the development and progression of hepatocellular carcinoma （HCC）. MethodsMethSurv and EWAS Data Hub were used to perform the standardized analysis and the cluster analysis of MTIF2 methylation samples， including survival curve analysis， methylation signature analysis， the association of tumor signaling pathways， and a comparative analysis based on pan-cancer database. The independent-samples t test was used for comparison between two groups； a one-way analysis of variance was used for comparison between multiple groups， and the least significant difference t-test was used for further comparison between two groups. The Cox proportional hazards model was used to perform the univariate and multivariate survival analyses of methylation level at the CpG site. The Kaplan-Meier method was used to investigate the survival differences between the patients with low methylation level and those with high methylation level， and the Log-likelihood ratio method was used for survival difference analysis. ResultsGlobal clustering of MTIF2 methylation showed that there was no significant difference in MTIF2 gene methylation level between different races， ethnicities， BMI levels， and ages. The Kaplan-Meier survival curve analysis showed that the patients with N-Shore hypermethylation of the MTIF2 gene had a significantly better prognosis than those with hypomethylation （hazard ratio ［HR］=0.492， P<0.001）， while there was no significant difference in survival rate between the patients with different CpG island and S-Shore methylation levels （P>0.05）. The methylation profile of the MTIF2 gene based on different ages， sexes， BMI levels， races， ethnicities， and clinical stages showed that the N-Shore and CpG island methylation levels of the MTIF2 gene decreased with the increase in age， and the Caucasian population had significantly lower N-Shore methylation levels of the MTIF2 gene than the Asian population （P<0.05）； the patients with clinical stage Ⅳ had significantly lower N-Shore and CpG island methylation levels of the MTIF2 gene than those with stage Ⅰ/Ⅱ （P<0.05）. Clinical validation showed that the patients with stage Ⅲ/Ⅳ HCC had a significantly lower methylation level of the MTIF2 gene than those with stage Ⅰ/Ⅱ HCC and the normal population （P<0.05）. ConclusionN-Shore hypomethylation of the MTIF2 gene is a risk factor for the development and progression of HCC.

ObjectiveTo understand the epidemiological distribution and gene evolutionary variation of influenza A (H3N2) viruses in Fengxian District, Shanghai, in the surveillance year of 2023, and to provide a reference basis for influenza prevention and control. MethodsThe prevalence of influenza virus in Fengxian District in the 2023 influenza surveillance year (April 2023‒March 2024) was analyzed. The hemagglutinin (HA) gene, neuraminidase (NA) gene, and amino acid sequences of 75 strains of H3N2 influenza viruses were compared with the vaccine reference strain for similarity matching and phylogenetic evolutionary analysis, in addition to an analysis of gene characterization and variation. ResultsIn Fengxian District, there was a mixed epidemic of H3N2 and H1N1 in the spring of 2023, with H3N2 being the predominant subtype in the second half of the year, and Victoria B becoming the predominant subtype in the spring of 2024. A total of 75 influenza strains of H3N2 with HA and NA genes were distributed in the 3C.2a1b.2a.2a.2a.3a.1 and B.4 branches, with overall similarity to the reference strain of the 2024 vaccine higher than that of the reference strain of the 2022 and 2023 vaccine. Compared with the 2023 vaccine reference strain, three antigenic sites and one receptor binding site were changed in HA, with three glycosylation sites reduced and two glycosylation sites added; where as in NA seven antigenic sites and the 222nd resistance site changed with two glycosylation sites reduced. ConclusionThe risk of antigenic variation and drug resistance of H3N2 in this region is high, and it is necessary to strengthen the publicity and education on the 2024 influenza vaccine and long-term monitoring of influenza virus prevalence and variation levels.

ObjectiveTo investigate the therapeutic effect of sequential administration of Dihuang Baoyuan granules （DHBY， the prescription for consolidating body resistance） and Fuling Yunhua granules （FLYH， the prescription for treating symptoms） on spontaneous type 2 diabetes mellitus （T2DM） in mice. MethodsAccording to the fasting blood glucose （FBG） level， 12-week-old db/db mice were randomized into six groups： model， DHBY （18.02 g·kg^-1）， FLYH （14.80 g·kg^-1）， sequential administration 1 （SEQ-1， DHBY 18.02 g·kg^-1+FLYH 14.80 g·kg^-1）， sequential administration 2 （SEQ-2， FLYH 14.80 g·kg^-1+DHBY 18.02 g·kg^-1）， and dapagliflozin （Dapa， 1.3 mg·kg^-1）. The m/m mice in the same litter were selected as the normal group. The mice were administrated with corresponding drugs by gavage for 8 consecutive weeks. During the 8 weeks of drug administration and 2 weeks after withdrawal， the retinal thickness， FBG， hemoglobin A1c （HbA1c）， and insulin were determined， and histopathological changes of the pancreas， liver， kidney， and retina were observed by hematoxylin-eosin （HE） staining. ResultsCompared with the model group， SEQ-1 for 4 weeks lowered the FBG level （P<0.05）， raised the insulin level， decreased the triglyceride （TG） level （P<0.05）， increased the number of optic ganglion cells and diminished vacuolar degeneration of pancreatic islet and liver. SEQ-2 lowered FBG and HbA1c levels （P<0.05）， rose the insulin level， increased the retinal thickness and the number of optic ganglion cells （P<0.05）， and alleviated vacuolar degeneration of pancreatic islet and liver. Two weeks after drug withdrawal， Dapa tended to increase FBG and HbA1c compared with those at the time of drug withdrawal. However， the levels of FBG and HbA1c in the SEQ-2 group remained decreasing （P<0.05）. ConclusionSEQ-1 and SEQ-2 can lower the blood glucose level and ameliorate diabetic retinopathy， and SEQ-2 outperformed DHBY and FLYH in lowering the blood glucose level. Moreover， SEQ-2 can maintain the blood glucose-lowering effect after drug withdrawal.

ObjectiveTo investigate the therapeutic effect of sequential administration of Dihuang Baoyuan granules （DHBY， the prescription for consolidating body resistance） and Fuling Yunhua granules （FLYH， the prescription for treating symptoms） on spontaneous type 2 diabetes mellitus （T2DM） in mice. MethodsAccording to the fasting blood glucose （FBG） level， 12-week-old db/db mice were randomized into six groups： model， DHBY （18.02 g·kg^-1）， FLYH （14.80 g·kg^-1）， sequential administration 1 （SEQ-1， DHBY 18.02 g·kg^-1+FLYH 14.80 g·kg^-1）， sequential administration 2 （SEQ-2， FLYH 14.80 g·kg^-1+DHBY 18.02 g·kg^-1）， and dapagliflozin （Dapa， 1.3 mg·kg^-1）. The m/m mice in the same litter were selected as the normal group. The mice were administrated with corresponding drugs by gavage for 8 consecutive weeks. During the 8 weeks of drug administration and 2 weeks after withdrawal， the retinal thickness， FBG， hemoglobin A1c （HbA1c）， and insulin were determined， and histopathological changes of the pancreas， liver， kidney， and retina were observed by hematoxylin-eosin （HE） staining. ResultsCompared with the model group， SEQ-1 for 4 weeks lowered the FBG level （P<0.05）， raised the insulin level， decreased the triglyceride （TG） level （P<0.05）， increased the number of optic ganglion cells and diminished vacuolar degeneration of pancreatic islet and liver. SEQ-2 lowered FBG and HbA1c levels （P<0.05）， rose the insulin level， increased the retinal thickness and the number of optic ganglion cells （P<0.05）， and alleviated vacuolar degeneration of pancreatic islet and liver. Two weeks after drug withdrawal， Dapa tended to increase FBG and HbA1c compared with those at the time of drug withdrawal. However， the levels of FBG and HbA1c in the SEQ-2 group remained decreasing （P<0.05）. ConclusionSEQ-1 and SEQ-2 can lower the blood glucose level and ameliorate diabetic retinopathy， and SEQ-2 outperformed DHBY and FLYH in lowering the blood glucose level. Moreover， SEQ-2 can maintain the blood glucose-lowering effect after drug withdrawal.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.