Based on the thinking of programmatization and proceduralization， this study integrated traditional Chinese medicine （TCM） classic theories with modern knowledge expression technologies to construct a "formula-symptom" syndrome differentiation thinking model centered on "symptom clustering-main syndrome screening-formula adaptation"， and explored the standardization and intelligentization path of TCM syndrome differentiation and treatment. By establishing the mapping relationship model between formulas and syndromes including quantitative weight analysis of chief， deputy， assistant and envoy medicines， designing the logical hierarchical structure of formula-syndrome decision tree （application of three-level decision tree and fuzzy logic）， and formulating the procedural design of four diagnostic methods （structured collection， correlation model， and dynamic correction mechanism）， the standardization and visualization of the syndrome differentiation process are realized. This model can be transformed into the core data set for artificial intelligence training. Through ternary knowledge graph and machine learning algorithms， it can improve the repeatability of syndrome differentiation and the efficiency of diagnosis and treatment， and implement the strategy of "group model + individual modification" to balance the conflict between quantification and individualization. The core value of this model lies in promoting the objectification and precision development of TCM syndrome differentiation and treatment through the integration of traditional syndrome differentiation thinking and modern system science.

ObjectiveTo explore the potential mechanisms by which spleen deficiency affects lipid metabolism in hyperlipidemia， from the perspective of gut microbiota and fecal endogenous metabolites. MethodsEighteen Sprague-Dawley （SD） rats were randomly divided into control group， hyperlipidemia group， and spleen-deficiency with hyperlipidemia group， with 6 rats in each group. The control group was fed with standard diet； the hyperlipi-demia group was given high-fat diet to induce hyperlipidemia model； and the spleen-deficiency with hyperlipidemia group received combination of high-fat diet， irregular feeding， and exercise restriction to induce the model. After 12 weeks of modeling， serum lipid levels including total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein cholesterol （LDL-C）， and high-density lipoprotein cholesterol （HDL-C） were measured. 16S rRNA gene sequencing was used to analyze gut microbiota composition in fecal samples， and fecal metabolites were analyzed using high-performance liquid chromatography-mass spectrometry （HPLC-MS）. Differential metabolites and microbial taxa were screened for pathway enrichment and functional prediction analysis， followed by correlation analysis. ResultsCompared with the control group， rats in the hyperlipidemia and spleen-deficiency with hyperlipidemia groups showed significantly increased serum TG， TC， and LDL-C levels， and decreased HDL-C levels （P＜0.01）. Compared with the hyperlipidemia group， the spleen-deficiency with hyperlipidemia group showed further increases in TG， TC， and LDL-C and further decrease in HDL-C （P＜0.05 or P＜0.01）. Gut microbiota analysis revealed 3,066 unique species in the control group， 2,637 in the hyperlipidemia group， and 1,581 in the spleen-deficiency group. Chao1， Simpson， and Shannon indices were significantly reduced in the spleen-deficiency group compared with the hyperli-pidemia group， with an increased Firmicutes/Bacteroidetes ratio. Differentially abundant genera such as Romboutsia， Lactobacillus， Clostridium， Allobaculum， and Xylanibacter were significantly upregulated （P＜0.05 or P＜0.01）. Metabolomics identified 25 differential metabolites in feces of spleen-deficient rats， with 18 downregulated and 7 upregulated. Key enriched pathways included serotonergic synapse， nucleotide metabolism， vascular smooth muscle contraction， and arachidonic acid metabolism. Spearman correlation analysis showed significant positive correlations between Romboutsia and Desulfovibrio and metabolites such as digalactosyldiacylglycerol （48∶5）， dehydrated artemetin， lysophosphatidylcholine （26∶4）， and glucuronosyldiacylglycerol （46∶5）； Clostridium was positively correlated with cyclopassifloric acid E1， digalactosyldiacylglycerol （48∶5）， and lysophosphatidylcholine （26∶4）； Xylanibacter was positively correlated with digalactosyldiacylglycerol （48∶5）， dehydrated artemetin， and lysophosphatidylcholine （26∶4）. ConclusionSpleen deficiency can further alter gut microbiota composition in hyperlipi-demia model rats， leading to microbial dysbiosis and metabolic disturbances that aggravate lipid metabolism disorders. This mechanism may be associated with changes in pathways such as serotonergic synapse， nucleotide metabolism， vascular smooth muscle contraction， and arachidonic acid metabolism.

AIM: To explore the effects of preoperative anterior segment parameters on the rotational stability of Toric intraocular lens(Toric IOL).METHODS:Prospective study. A total of 41 cataract patients(54 eyes)with combined corneal regular astigmatism from March to December 2023 were included and treated with cataract phacoemulsification combined with plate loop Toric IOL implantation in the Department of Ophthalmology of the First Affiliated Hospital of Zhengzhou University. The rotation degree of Toric IOL and uncorrected distance visual acuity(UCDVA)were evaluated at 1 d, 2 wk, and 1 mo postoperatively, the corrected distance visual acuity(CDVA)was evaluated at 2 wk and 1 mo after surgery, and the decentration and tilt of the Toric IOL were assessed at 2 wk postoperatively.RESULTS:A total of 33 patients(40 eyes)were included in this study. The UCDVA(LogMAR)of 1 d, 2 wk and 1 mo postoperatively were 0.10(0.10, 0.30), 0.05(0, 0.10)and 0(0, 0.10), respectively, which was improved compared with the preoperative levels of [0.80(0.49, 1.00)](P<0.001). The CDVA(LogMAR)of 2 wk and 1 mo postoperatively were 0.05(0, 0.15)and 0(0, 0.138), respectively, which was improved compared with preoperative levels of [0.52(0.40, 0.80)](P<0.001). The residual astigmatism of 2 wk and 1 mo postoperatively were 0.625(0.25, 0.75)D and 0.50(0.25, 0.75)D, respectively, which was significantly reduced compared with preoperative astigmatism of [1.82(1.31, 2.59)D](P<0.001). The preoperative anterior segment length(ASL), and lens thickness(LT)were positively correlated with Toric IOL rotation degree at 1 d(rs=0.463, P=0.003; rs=0.340, P=0.032)and 2 wk(rs=0.520, P=0.001; rs=0.409, P=0.009)postoperatively. At 1 mo postoperatively, only ASL was positively correlated with Toric IOL rotation degree(rs=0.463, P=0.003). The results of linear regression analysis showed that preoperative ASL was a predictor of rotation degree at 1 d, 2 wk and 1 mo after surgery(F1 d=10.098, P1 d=0.003; F2 wk=16.915, P2 wk<0.001; F1 mo=10.957, P1 mo=0.002). The rotation degree of Toric IOL was positively correlated with lens decentration(rs=0.360, P=0.043).CONCLUSION:The early postoperative rotation of Toric IOL is positively correlated with ASL, and the rotation is also positively correlated with lens decentration.

The Solomon four-group design， a critical method for improving internal validity in clinical research， can reduce bias and control the interference of Hawthorne effects and pretest sensitization on research results， which offers unique advantages in evaluating complex intervention outcomes. This paper systematically outlined the core framework and key points of statistical analysis of the Solomon four-group design， summarized its applications in clinical research at home and abroad， explored its advantages and limitations， and discussed the potential value in traditional Chinese medicine （TCM） clinical trials. It is believed that the Solomon four-group design can help distinguish between testing effects and intervention effects in TCM clinical studies， and reduce the bias in the evaluation of subjective indicators. Meanwhile， given the complexity of the Solomon four-group design and the particularity of TCM clinical research， it is proposed that future TCM clinical studies should focus on using psychological scales， know-ledge， attitude， and behavior measurements， and other similat evaluations as endpoints. It also advocates strengthening interdisciplinary collaboration to provide new methodological paths for TCM clinical research.

Although a single nucleotide polymorphism for N-acetyltransferase 10 (NAT10) has been identified in patients with early-onset stroke, the role of NAT10 in ischemic injury and the related underlying mechanisms remains elusive. Here, we provide evidence that NAT10, the only known RNA N4-acetylcytidine (ac4C) modification "writer", is increased in the damaged cortex of patients with acute ischemic stroke and the peri-infarct cortex of mice subjected to photothrombotic (PT) stroke. Pharmacological inhibition of NAT10 with remodelin on Days 3-7 post-stroke or astrocytic depletion of NAT10 via targeted virus attenuates ischemia-induced infarction and improves functional recovery in PT mice. Mechanistically, NAT10 enhances ac4C acetylation of the inflammatory cytokine tissue inhibitor of metalloproteinase 1 (Timp1) mRNA transcript, which increases TIMP1 expression and results in the accumulation of microtubule-associated protein 1 light chain 3 (LC3) and progression of astrocyte autophagy. These findings demonstrate that NAT10 regulates astrocyte autophagy by targeting Timp1 ac4C after stroke. This study highlights the critical role of ac4C in the regulation of astrocyte autophagy and proposes a promising strategy to improve post-stroke outcomes via NAT10 inhibition.

Under the background of rapid development of artificial intelligence(AI),this paper systematically proposes AI-based education(AIBE).It empowers the teaching process,learning process,research process,and teaching management with AI,and constructs an AI-based educational paradigm,including AI-based teaching(AIBT),AI-based learning(AIBL),AI-based re-search(AIBR),and AI-based management(AIBM).Taking the AI course of immunology teaching as an example,this paper deeply analyzes the practices and explorations of implementing AIBT,AIBL,AIBR and AIBM based on the AI course,so as to accelerate the promotion of the transformation of the fourth generation of medical education.

Knee osteoarthritis is a common joint disease within osteoarthritis,characterized by pain,swelling,and limited functionality as the main clinical manifestations.In severe cases,it affects daily life and falls under the category of"impediment syndrome"or"bone impediment"in TCM.The author believes that the theory of"bones,tendons,and muscles"is closely related to this disease.Treatment should focus on simultaneously nourishing the liver,spleen and kidneys,considering tendons,bones and muscles,while also dispelling wind,cold and dampness.The clinical application of Sanbi Decoction has shown good efficacy,and this discussion aimed to provide ideas for the diagnosis and treatment of knee osteoarthritis.

Generative Artificial Intelligence ishows a broad application prospect in the field of healthcare and has become an important technical means to promote the development of medical informatization.It addresses the multi-faceted challenges of medical record documentation,including efficiency,quality,and doctor-patient communica-tion.It analyzes the adaptability and feasibility of Generative Artificial Intelligence in different clinical scenarios of intelli-gent medical record generation.Additionally,it explores the issues present in current applications and proposes corre-sponding solutions,providing references for the effective application and continuous optimization of Generative Artifi-cial Intelligence in medical record documentation.This provides a theoretical foundation for further expanding the appli-cation scenarios of automatic medical record documentation in China's healthcare industry.

Objective:To construct a model of mitochondria-related genes (Mito-RGs) in hepatocellular carcinoma (HCC), and predict the immune, prognostic and therapeutic characteristics of HCC based on the model, so as to provide a new idea for the diagnosis and treatment of HCC.Methods:The expression profiles of HCC and corresponding clinical information were obtained from the Cancer Genome Atlas (TCGA) database. Univariate Cox regression, Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate Cox regression were used to construct a prognostic model of HCC based on Mito-RGs, and the International Cancer Genome Consortium-Liver Cancer-RIKEN-Japan ICGC-LIRI-JP dataset were used for validation. GO and KEGG analyses were performed to investigate the signaling pathways enriched for differentially expressed genes in the high- and low-risk groups. Immune infiltration was assessed using CIBERSORT. Single-cell data were used to study the proportion of immune cells in high- and low-risk groups of HCC samples and the relationship with cell proliferation. Cellminer was used to assess the relationship between risk score models and drug sensitivity.Results:A risk-prognostic model of HCC containing seven Mito-RGs ( DTYMK, ACADS, HMGCS2, CYP27A1, TOMM40L, STOM, and AKR1B10) was constructed. High-risk HCC patients had a worse prognosis. Genes upregulated in the high- and low-risk groups of differentially expressed genes were enriched in cell cycle and metabolism-related pathways. Single-cell data showed higher proportions of CD8 + T cells, macrophages and monocytes, and proliferating cells in the high-risk group. CIBERSORT analysis suggested that Treg cells and M0 macrophages were more abundant in the high-risk group, whereas CD8 + T cells and CD4 + memory T cells were less abundant. Patients in the high-risk group were more sensitive to myeloid cell leukemia sequence 1 inhibitor, vincristine, phosphatidylinositol kinase beta subunit inhibitor, and aurora kinase A, while trametinib, selumetinib, extracellular regulated protein kinase, and mitogen-activated extracellular signal-regulated kinase were more effective in the low-risk group. Conclusion:The constructed Mito-RGs model is capable of providing a more accurate assessment of the prognosis and the degree of immune cell infiltration in HCC patients.

Objective: To explore the association between negative life events and smartphone addiction among middle school students, so as to provide theoretical support and practical guidance for prevention and intervention of smartphone addiction among middle school students. Methods: Using cluster sampling, 8 890 students were selected to survey from 27 junior high schools and 3 senior high schools in a district of Shenzhen in 2022 (baseline) and 2023 (followup). Data were collected through selfresigned questionnaires on basic information, the Smartphone Addiction Scale-Short Version, and the Adolescent Selfrating Life Events Checklist. Mixedeffects models were employed to analyze the association. Results: Compared to 2022, the punishment scores of middle school students in 2023 [1.00 (0.00, 6.00) and 1.00 (0.00, 6.00)] decreased (Z=4.27), while the scores of interpersonal stress, learning stress and adaptation [4.00(0.00, 8.00), 4.00(0.00, 8.00); 4.00(1.00, 8.00), 5.00(2.00, 9.00); 2.00 (0.00, 6.00), 3.00 (0.00, 7.00)] increased (Z=-3.04, -8.36, -6.80) (P<0.01). Mixedeffects models revealed a positive doseresponse relationship between negative life events and smartphone addiction (OR=1.08-1.17, P<0.01). Stepwise regression showed independent positive effects of interpersonal stress (OR=1.05), academic stress (OR=1.03), and adaptation stress (OR=1.11) on smartphone addiction (P<0.01). Subgroup analysis of nonaddicted students in 2022 confirmed persistent associations for academic stress (OR=1.03) and adaptation (OR=1.07) (P<0.01). Conclusion Negative life events exhibit a positive doseresponse relationship with smartphone addiction, particularly interpersonal stress, academic stress, and adaptationrelated events.