Animal model research on spleen and stomach diseases in traditional Chinese medicine （TCM） is of great significance for elucidating the nature of diseases and syndromes and for revealing the mechanisms of action of Chinese herbal medicinals. At present， studies on classical TCM syndrome models of spleen and stomach diseases mainly focus on spleen deficiency syndrome， liver constraint syndrome， and damp-heat syndrome. Model construction is mostly based on the etiological and pathophysiological characteristics of syndrome， and model evaluation primarily involves macroscopic manifestations and physicochemical indicators. This paper summarizes the current research status of animal models integrating disease and syndrome for seven common spleen and stomach diseases， including chronic gastritis and gastric precancerous lesions， gastroesophageal reflux disease， functional dyspepsia， inflammatory bowel disease， irritable bowel syndrome， functional constipation， and functional diarrhea. The modeling methods and characteristics of disease-syndrome combined animal models for each disease are analyzed. It is proposed that future research on disease-syndrome integration in spleen and stomach diseases should move toward syste-matic， precise， and integrative development， and that interdisciplinary and cross-disciplinary research approaches should be adopted to enhance the predictive value and application efficiency of disease-syndrome combined animal models.

ObjectiveTo investigate the therapeutic effect and mechanism of Huatan Qushi Huoxue prescription on rats with metabolic dysfunction-associated steatohepatitis （MASH）. MethodsA total of 60 specific pathogen-free Sprague-Dawley rats were randomly divided into blank control group， model A group， model B group， Western medicine group （polyene phosphatidylcholine， 143.64 mg/kg）， high-dose Chinese medicine group （Huatan Qushi Huoxue prescription， 20.16 g/kg）， and middle-dose Chinese medicine group （Huatan Qushi Huoxue prescription， 10.08 g/kg）. All rats except those in the blank control group were given high-fat diet. Samples were collected from the model A group at week 8， and since week 12， the other groups were given the corresponding drug once a day for 8 consecutive weeks， with samples collected at week 20. Body weight， liver wet weight， and liver index were measured for all rats； the microplate method was used to measure the serum levels of alanine aminotransferase （ALT）， aspartate aminotransferase （AST）， total cholesterol （TC）， triglycerides （TG）， high-density lipoprotein cholesterol （HDL-C）， low-density lipoprotein cholesterol （LDL-C）， and free fatty acids （FFA）； ELISA was used to measure the serum levels of tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， interleukin-6 （IL-6）， and soluble triggering receptor expressed on myeloid cells 2 （sTREM2）； HE staining and oil red O staining were performed to observe liver histopathological changes； immunofluorescence assay was used to measure CD68⁺TREM2⁺ cells in liver tissue and calculate the phagocytosis rate of macrophages； quantitative real-time PCR was used to measure the mRNA expression levels of sphingosine 1-phosphate （S1P）， sphingosine 1-phosphate receptor 1 （S1PR1）， a disintegrin and metalloproteinase 17 （ADAM17）， and triggering receptor expressed on myeloid cells 2 （TREM2） in liver tissue， and immunohistochemistry was used to measure the protein expression levels of S1P， S1PR1， ADAM17， and TREM2 in liver tissue. A one-way analysis of variance was used for comparison of normally distributed continuous data with homogeneity of variance between groups， and the least significant difference t-test was used for further comparison between two groups； the Welch’s test was used for comparison of normally distributed continuous data with heterogeneity of variance between groups， and the Tamhane’s test was used for further comparison between two groups. The Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between groups， and the Dunn’s test was used for further comparison between two groups. ResultsCompared with the blank control group， the model A group and the model B group had significant increases in body weight and liver wet weight， and the model B group had a significant increase in liver index （all P<0.05）. HE staining showed diffuse macrovesicular steatosis of liver tissue in the model A group and a large number of hepatocytes with ballooning degeneration in liver tissue in the model group B， with the presence of mixed inflammatory cell infiltration and mild perisinusoidal fibrosis in the lobules and the portal area. Compared with the blank control group， the model A group and the model B group had significant increases in NAS score and oil red O-positive area （all P<0.05）， and the model B group had significant increases in these two indicators than the model A group （both P<0.05）. Compared with the blank control group， the model A group and the model B group had significant increases in the serum levels of TC， TG， LDL-C， FFA， IL-1β， IL-6， and sTREM2 and a significant reduction in the serum level of HDL-C， and the model B group had significant increases in the serum levels of ALT， AST， and TNF-α （all P<0.05）； compared with the model A group， the model B group had significant increases in the serum levels of ALT， AST， TC， TG， FFA， TNF-α， IL-1β， IL-6， and sTREM2 and a significant reduction in the serum level of HDL-C （all P<0.05）. Immunofluorescence assay showed that compared with the blank control group， the model A group had a significant increase in the phagocytosis rate of macrophages （P<0.05）， while the model B group had a significantly lower phagocytosis rate of macrophages than the model A group （P<0.05）. Quantitative real-time PCR showed that compared with the blank control group， the model A group and the model B group had a significant increase in the mRNA expression level of TREM2， and the model B group had significant increases in the mRNA expression levels of S1P and S1PR1 （both P<0.05）； moreover， compared with the model A group， the model B group had significant increases in the mRNA expression levels of S1PR1 and TREM2 （both P<0.05）. Immunohistochemistry showed that compared with the blank control group， the model A group and the model B group had significant increases in the protein expression levels of S1P， S1PR1， and ADAM17， and the model A group had a significant increase in the protein expression level of TREM2 （all P<0.05）； compared with the model A group， the model B group had significant increases in the protein expression levels of S1P， S1PR1， and ADAM17 and a significant reduction in the protein expression level of TREM2 （all P<0.05）. Compared with the model B group， each medication group had significant reductions in body weight， liver wet weight， and liver index （all P<0.05）； each medication group had significant improvements in hepatic steatosis and inflammatory damage， with significant reductions in NAS score and oil red O-positive area （all P<0.05）； each medication group had significant reductions in the serum levels of ALT， AST， TC， TG， FFA， IL-1β， and IL-6 （all P<0.05） and a significant increase in the serum level of HDL-C （P<0.05）， and the high-dose Chinese medicine group had a significant reduction in the serum level of TNF-α （P<0.05）； each medication group had a significant increase in the phagocytosis rate of macrophages （all P<0.05）； the high- and middle-dose Chinese medicine groups had a significant reduction in the protein expression level of ADAM17， and the high-dose Chinese medicine group had a significant increase in the protein expression level of TREM2 （all P<0.05）. ConclusionHuatan Qushi Huoxue prescription improves lipid metabolism and inflammation in the liver of MASH rats by regulating hepatic macrophage phagocytosis.

Liver fibrosis is the core pathological stage of the progression of various chronic liver diseases to liver cirrhosis， and hepatic stellate cell （HSC） activation and the abnormal accumulation of collagen fibers are important processes for the development and progression of liver fibrosis. In recent years， studies have shown that HSC activation is regulated by the complex interactions between various organelles （including mitochondria， endoplasmic reticulum， Golgi apparatus， lysosome， and peroxisomes）， and such interactions affect the key cellular processes such as energy metabolism， protein synthesis and folding， reactive oxygen species balance， and autophagy， thereby participating in the progression of liver fibrosis. Meanwhile， traditional Chinese medicine and its active ingredients with multi-target synergistic effects have attracted wide attention. From the perspective of the interaction between organelles， this article systematically elaborates on the specific mechanism of such interactions in the progression of liver fibrosis and reviews how traditional Chinese medicine inhibits HSC activation and collagen production by regulating the function of these organelle and their interaction networks， thereby exerting an anti-liver fibrosis effect， in order to provide a theoretical basis for in-depth understanding of the pathological mechanism of liver fibrosis and the development of new traditional Chinese medicine intervention strategies.

Metabolic dysfunction-associated fatty liver disease （MAFLD） is a chronic metabolic liver disorder with complex etiologies. Different clinical phenotypes of MAFLD （such as obesity， hyperlipidemia， type 2 diabetes mellitus， the postmenopausal state， and chronic hepatitis B） have different mechanisms of action in the development and progression of MAFLD， leading to high heterogeneity in its clinical progression and prognosis. This article systematically reviews the pathogeneses and clinical features of the above five clinical phenotypes of MAFLD and elaborates on the corresponding individualized diagnosis and treatment regimens integrating traditional Chinese medicine and Western medicine， in order to provide a reference for clinical practice and improve clinical diagnosis and treatment.

Objective: To map the research landscape of artificial intelligence (AI)-assisted tongue diagnosis through bibliometric analysis and to quantify its diagnostic accuracy and clinical interpretability through a diagnostic test accuracy (DTA) meta-analysis. Methods: For the bibliometric analysis, the Web of Science Core Collection (WoSCC) was queried for English-language articles and reviews on AI-assisted tongue diagnosis published between January 1, 2014 and December 31, 2025, and analysed using Bibliometrix, VOSviewer, and CiteSpace, with major output dimensions including annual publication output and disciplinary distribution, journal and citation characteristics, country/region and institutional collaboration, author networks, keyword co-occurrence, and keyword burst detection. For the DTA meta-analysis, four databases [Scopus, PubMed, Web of Science, and China National Knowledge Infrastructure (CNKI)] were searched in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses of Diagnostic Test Accuracy (PRISMA-DTA) guidelines. A bivariate random-effects model hierarchical summary receiver operating characteristic (HSROC) was used to pool sensitivity and specificity, with subgroup analyses by disease category, AI model architecture, and sample-size strata. Methodological quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2) tool, and publication bias was evaluated by Deeks’ funnel plot asymmetry test. Results: A total of 198 publications met the bibliometric eligibility criteria. Annual output increased 24.5-fold (from 2 in 2014 to 49 in 2025), with the period 2022 – 2025 alone accounting for 65.2% of all publications. China contributed approximately 83.5% of all institutional affiliations, with Shanghai University of Traditional Chinese Medicine and Jiatuo Xu being the most productive institution and author, respectively. Keyword analysis identified four thematic clusters (AI and deep-learning architectures, image processing and segmentation, traditional Chinese medicine (TCM)-specific applications, and disease-specific applications) and a temporal evolution from traditional machine learning to deep learning and transformer-based, explainable, and multimodal AI architectures. Sixteen DTA meta-analysis studies (14 755 participants) covering metabolic and hepatic disorders, oncological and oral lesions, cardiovascular risk, diabetes, and other clinical applications were included in the DTA meta-analysis. The pooled sensitivity was 90.3% [95% confidence interval (CI): 86.7% – 93.1%] and the pooled specificity was 93.0% (95% CI: 90.6% – 94.7%); the area under the summary receiver operating characteristic (SROC) curve (AUC) was 0.961. Heterogeneity was substantial (I2 = 95.8% for sensitivity; I2 = 92.1% for specificity). Subgroup performance was broadly consistent across disease categories, AI architectures, and sample-size strata, and Deeks’ test indicated no significant publication bias (P = 0.258). Conclusion AI-assisted tongue diagnosis has progressed rapidly and shows pooled diagnostic performance comparable to established screening modalities, supporting its potential as a complementary and easily accessible decision-support tool.

Metabolic associated fatty liver disease （MAFLD） is a chronic liver disease with a rapidly increasing incidence rate worldwide， and its complex pathogenesis is closely associated with O-linked β-N-acetylglucosamine （O-GlcNAc） modification. As a dynamic and reversible post-translational modification of proteins， O-GlcNAc modification is mainly regulated by O-GlcNAc transferase and O-GlcNAcase. O-GlcNAc modification can drive hepatic steatosis， exacerbate insulin resistance， and impair mitochondrial function， thereby leading to the aggravation of metabolic disorders， promoting inflammation response， and driving the progression of MAFLD to metabolic associated steatohepatitis and hepatic fibrosis. This article systematically reviews the latest research advances in the role of O-GlcNAc modification in the development and progression of MAFLD， in order to provide theoretical support and research direction for a deeper understanding of the pathological mechanism of MAFLD and the development of effective therapeutic strategies.

Objective:To explore the application effectiveness of Artificial Intelligence Generated Content(AIGC)in immuno-logy education and optimize teaching models to enhance students'clinical thinking and self-directed learning abilities.Methods:A questionnaire survey was conducted to analyze the current application status of AIGC among 105 university teachers.Taking"TypeⅠHypersensitivity"as an example,integrating AI tools to generate dynamic case scenarios and multimodal resources.Teaching effective-ness was evaluated through classroom practices and student questionnaires.Results:88.32%of teachers recognized AIGC's role in im-proving preparation efficiency,and 61.54%of students reported significantly improved learning outcomes.However,71.43%of teach-ers expressed concerns about increased student dependency,and 55.84%of teachers emphasized challenges in content quality control.Conclusion:AIGC effectively enhances teaching interactivity and personalized learning.Future efforts should focus on optimizing con-tent authority,establishing ethical guidelines,and promoting the development of human-AI collaborative educational models.

Breast cancer is the main cause of death from cancer in women. Early diagnosis and treatment are very important to improve patient prognosis. As an important means of breast cancer screening, ultrasound plays a key role in the clinical diagnosis and treatment of cancer, but the accuracy of ultrasound diagnosis is greatly affected by subjective and objective, and it is easy to miss diagnosis and misdiagnosis. In recent years, with the development of big data and computer algorithms, the research and application of artificial intelligence (AI) technologies such as imaging omics and deep learning in the field of ultrasound have become increasingly extensive, making accurate and efficient imaging evaluation possible. This article mainly reviews the application status and clinical application potential of AI in ultrasound diagnosis of breast cancer.

Objective To investigate the potential mechanisms of action of Huatan Qushi Huoxue Recipe in treating non-alcoholic steatohepatitis(NASH)through network pharmacology and animal experiments.Methods The differentially expressed genes in NASH were obtained from the GEO database.The active components and potential targets of Huatan Qushi Huoxue Recipe were obtained from the TCMSP.The treatment targets were obtained by intersecting the diseases and drug targets.The protein-protein interaction network was analyzed,the drug-active component-target network was constructed,and the enrichment analysis was performed.The key pathways were verified by animal experiments.Results A total of 74differentially expressed genes,97 active components,and 295 potential targets were identified in NASH.Five genes,including JUN,were selected as key targets through intersection.Seven active components,inclu-ding kaempferol and quercetin,were identified.Enrichment analysis revealed that the AGE-RAGE and IL-17 pathways may play a key role in the treatment of NASH by Huatan Qushi Huoxue Recipe.Animal experiments showed that Huatan Qushi Huoxue Recipe could reduce the levels of total cholesterol(TC),triglyceride(TG),and blood glucose(GLU),and down-regulate the expression of RAGE and activator protein 1(AP-1)in the AGE-RAGE and IL-17 pathways,thus,exerting a therapeutic effect on NASH.Conclusion Huatan Qushi Huoxue Recipe can treat NASH by lowering TC,TG and GLU levels and inhibiting the expression of RAGE and AP-1 pro-tein.

Objective:To investigate the value of T helper 17 cells（Th17）/regulatory T cells（Treg）imbalance in the evaluation of intravenous immunoglobulin（IVIG）resistance in children with Kawasaki disease and Kobayashi score≤4.Methods:A total of 78 children with Kawasaki disease and Kobayashi score ≤ 4 admitted to Hunan Children's Hospital from January 2020 to December 2023 were prospectively selected as the study subjects，all of whom received IVIG treatment.In the acute phase，the proportion of Th17 cells and Treg cells was detected.Children were divided into IVIG sensitive group and IVIG resistance group based on their responsiveness to IVIG treatment.Baseline data of children with different IVIG treatment responsiveness，acute Th17 cell inflammatory factors [interleukin（IL）-17，IL-21，tumor necrosis factor-α（TNF-α）]，Treg cell inflammatory factors [IL-10，IL-35，transforming growth factor-β（TGF-β）] levels，and Th17/Treg values were compared.The correlation between Th17/Treg values and IVIG resistance in children with Kawasaki disease was analyzed using a restricted cubic spline model（RCS）.According to the threshold of correlation between Th17/Treg values obtained from RCS analysis and drug resistance in children，Th17/Treg was grouped，with a focus on analyzing the predictive value and clinical benefits of Th17/Treg values for IVIG resistance in children with Kawasaki disease.Results:Among the 78 children with Kawasaki disease，16 were resistant to IVIG treatment，accounting for 20.51%.The levels of C-reactive protein（CRP）,IL-17,and Th17/Treg in the acute phase of children in the IVIG resistance group were higher than those in the IVIG sensitive group，while the levels of IL-10 were lower than those in the IVIG sensitive group（ P<0.05）.RCS analysis showed that there was a non-linear dose-response relationship between IVIG resistance and acute Th17/Treg values in children with Kawasaki disease（ P<0.05）.When the acute Th17/Treg value was greater than 1.05，the risk of IVIG resistance in children with Kawasaki disease increased with the increase in indicator levels.The levels of CRP and IL-17 in the acute phase of children with Th17/Treg>1.05 were higher than those in the Th17/Treg < 1.05 group，while IL-10 levels were lower than those in the Th17/Treg<1.05 group.The proportion of children resistant to IVIG treatment was higher than that in the Th17/Treg<1.05 group（ P<0.05）.Multivariate Logistic regression analysis showed that CRP，IL-17，IL-10，and Th17/Treg were the influencing factors of IVIG resistance in children with Kawasaki disease（ P<0.05）.It was found through a nomogram that the C-index of the acute phase Th17/Treg values and their secretion of inflammatory factors in children with Kawasaki disease and Kobayashi score ≤ 4，as well as other major indicators，predicted the risk of IVIG resistance.The C-index was 0.975（95% CI 0.944-1.000），indicating good discrimination.When drawing the decision curve，it was found that compared to using each indicator separately，the Th17/Treg value and its secreted inflammatory factors in the acute phase assisted other major indicators in drawing the decision curve with a higher net benefit rate，with a maximum net benefit rate of 0.205. Conclusion:IVIG resistance in children with Kawasaki disease and Kobayashi score≤4 is related to Th17/Treg imbalance.When the Th17/Treg value in the acute phase of the disease is greater than 1.05，the risk of IVIG resistance is higher.The inflammatory factors IL-17 and IL-10 secreted by the two can assist other known indicators related to IVIG resistance in Kawasaki disease patients，improving the accuracy of predicting resistance risk.