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.

Tumor treating fields (TTF) therapy is an innovative tumor treatment modality. Currently, the TTF devices predominantly employ insulated ceramic electrodes as the electric field transmission medium, resulting in low energy transfer efficiency of the electric field and poor portability of the devices. This study proposed an innovative TTF transmission mode and independently designed a conducted-electrode TTF cell culture dish utilizing inert titanium materials. The electric field conduction characteristics were verified through finite element simulations and experimental tests. Finally, based on the self-manufactured conducted-electrode TTF cell culture dish, experiments on the proliferation inhibition of U87 tumor cells by TTF were conducted. The results demonstrated that under an applied TTF voltage of 10 V and frequency of 200 kHz, the electric field intensities within the medium for conducted and insulated electrodes are approximately 2.5 V/cm and 0.7 V/cm, respectively. Compared to conventional insulated TTF systems, the conducted-electrode TTF configuration exhibited a lower electrode voltage drop and a higher electric field intensity in the culture medium, indicating superior electric field transmission efficiency. Following 36 hours of treatment with conducted-electrode TTF on U87 cells, the proliferation inhibition rate reached approximately 50%, demonstrating effective suppression of tumor cell growth. This approach presents a potential direction for optimizing TTF treatment modality and device design.
Humans ; Electrodes ; Neoplasms/pathology* ; Cell Line, Tumor ; Cell Proliferation/radiation effects* ; Electric Stimulation Therapy/methods* ; Electromagnetic Fields

Objective To evaluate the interpersonal communication competence of doctors in 10 dimensions of standardized training for specialized doctors and their communication differences with various groups,and to analyze the existing problems and solutions.Methods The 10-item short-form version of the Interpersonal Communication Competence Scale(ICCS-SF)was used to assess the communication abilities of 395 physicians undergoing training at six specialized physician training bases in Shanghai.Descriptive statistics,chi-square tests,non-parametric tests,and multiple linear regression of methods were employed to analyze the communication status and training status of specialist physicians.Results The maximum score for interpersonal communication competence is 50 points,and the average score for the specialist physicians in this study was 38.0(35.0～41.0)points.The impact of the training on the scores is reflected in the total score and the two sub-dimensions of social relaxation and self-affirmation,with statistically significant differences(P＜0.05).Compared to patients and colleagues,specialized training physicians reported the greatest difficulty in communicating with interdisciplinary teams.Physicians who recognized the importance of communication and those whose training included a greater variety of skills achieved higher ICCS-SF scores(P＜0.001).Conclusion It is necessary to further strengthen the coverage and standardization of training,and pay attention to the cultivation of communication competence between interdisciplinary teams on the basis of attaching importance to the communication competence between doctors and patients.

AIM: To analyze the reasons and clinical outcomes of intraocular lens(IOL)exchange.METHODS:This retrospective case series study included 47 patients(53 eyes)who underwent IOL exchange surgery at the Department of Ophthalmology, the First Affiliated Hospital of Zhengzhou University, between April 2020 and May 2024, aged from 5 to 87(44.8±3.6)years old. Patients' demographics, surgical indications, surgical techniques, preoperative and postoperative uncorrected visual acuity(UCVA)and best-corrected visual acuity(BCVA), as well as postoperative complications were recorded.RESULTS:The reasons for IOL exchange included refractive error(18 cases, 23 eyes, 43%), IOL dislocation(12 cases, 13 eyes, 25%), IOL opacification(12 cases, 12 eyes, 23%), neuroadaptation failure(3 cases, 3 eyes, 6%), and patient dissatisfaction with visual quality(2 cases, 2 eyes, 4%). The surgical techniques for IOL exchange included in-the-bag IOL fixation(16 eyes, 30%), ciliary sulcus fixation(27 eyes, 51%), and scleral suture fixation(10 eyes, 19%). There was statistical significant difference between preoperative UCVA(LogMAR)and UCVA(LogMAR)at 1 d postoperatively(1.03±0.64 vs 0.50±0.46, P<0.05), and there was statistical significant difference between preoperative BCVA(LogMAR)and BCVA(LogMAR)at 1 mo postoperatively(0.41±0.37 vs 0.17±0.21, P<0.05). Postoperative complications included posterior capsule opacification in 2 eyes and IOL dislocation in 1 eye.CONCLUSION:Refractive error, IOL dislocation, and IOL opacification were the three most common reasons for IOL exchange. Although less frequent, factors such as neuroadaptation issues associated with multifocal IOLs and patient-reported visual quality dissatisfaction reflect growing expectations for improved visual outcomes. IOL exchange surgery, though technically challenging, demonstrates favorable clinical efficacy and a low complication rate, representing an effective intervention for managing postoperative IOL-related issues following cataract surgery.

Objective:To screen the Alzheimer's disease(AD)-related genes and construct its diagnostic model using bioinformatics technology and machine learning(ML)algorithms,to discuss the immunological characteristics of AD patients,and to provide novel biomarkers for AD diagnosis.Methods:The AD-related gene expression dataset GSE125583 was downloaded from the Gene Expression Omnibus(GEO)database.Differentially expressed genes(DEGs)were identified through differential analysis.Gene Ontology(GO)functional enrichment and Kyoto Encyclopedia of Genes and Genomes(KEGG)signaling pathway enrichment analyses were performed to explore the biological functions and signaling pathways of DEGs.A protein-protein interaction(PPI)network was constructed,and hub genes were screened using Cytoscape software combined with three ML algorithms:Least Absolute Shrinkage and Selection Operator(LASSO),eXtreme Gradient Boosting(XGBoost),and Random Forest(RF).The screened hub genes were utilized to build an AD diagnostic model via RF,followed by feature importance ranking.The model's efficacy and key genes were evaluated using a test set.Single-sample gene set enrichment analysis(ssGSEA)was used for immune cell infiltration analysis between AD group and control group.Results:Differential analysis identified 1 287 DEGs.The GO functional enrichment analysis results revealed that DEGs were primarily involved in biological functions related to neural signaling,synapses,and vesicles.KEGG signaling pathway enrichment analysis indicated significant enrichment of DEGs in ion transport,neurotransmitter,and ligand-gated channel pathways.Nine overlapping hub genes were screened by the three ML algorithms.In the AD diagnostic model,the top four key genes with highest diagnostic performance were adenylate cyclase-activating polypeptide 1(ADCYAP1),brain-derived neurotrophic factor(BDNF),platelet-derived growth factor receptor β(PDGFRB),and C-X-C motif chemokine receptor 4(CXCR4),with corresponding area under the curve(AUC)values of 0.852,0.795,0.820,and 0.756,respectively.The model achieved an AUC of 0.828,accuracy of 81.25%,sensitivity of 84.40%,and specificity of 71.43%.The immune cell infiltration analysis results demonstrated higher infiltration of macrophages,monocytes,natural killer(NK)cells,and lymphocytes in AD tissue.Among these,NK/natural killer T(NKT)cells and plasmacytoid dendritic cells showed significant correlations with the four key genes(P<0.05).Conclusion:The feature genes screened based on bioinformatics and ML exhibit diagnostic potential for AD.Genes such as ADCYAP1 may serve as potential biomarkers for AD diagnosis,offering significant implications for early prevention and treatment.

With the improvement in the accuracy and portability of three-dimensional facial imaging de-vices,and the rapid development of medical image recognition technology in artificial intelligence,the analysis and automatic recognition of three-dimensional facial characteristics of diseases have been widely applied in multiple fields such as endocrine metabolic disorders,chronic respiratory diseases,neuromuscular diseases,ge-netic syndromes,and plastic surgery.We aim to systematically review and summarize the current research status and development trends of three-dimensional facial photogrammetry and image analysis techniques in disease di-agnosis,assessment of prognosis and treatment efficacy,in order to provide references and insights for scientific research and clinical applications of this field.

Autoimmune hepatitis （AIH） is a chronic inflammatory liver disease. The pathogenesis of AIH remains unclear， but it is mainly autoimmune injury caused by the breakdown of autoimmune tolerance due to the abnormal activation of the immune system， while the specific molecular mechanism remains unknown. Recent studies have shown that abnormal amino acid metabolism plays an important role in the development and progression of AIH. This article reviews the research advances in amino acid metabolic reprogramming in AIH， in order to provide a theoretical basis for amino acid metabolism as a new target for the clinical diagnosis and treatment of AIH.

OBJECTIVE To explore the main factors influencing the blood concentration of duloxetine， and provide a scientific basis for the individualized use of duloxetine. METHODS Retrospective analysis was conducted on 434 inpatients with depressive disorders at the First Hospital of Hebei Medical University， who were treated with duloxetine and underwent blood concentration monitoring between January 2022 and April 2024. The study examined the impact of various factors， including gender， age， body mass index （BMI）， gene phenotypes， combined medication， drug type （original/generic）， and genotyping results of gene single nucleotide polymorphism loci， on blood concentration and the concentration-to-dose （C/D） after dose adjustment. RESULTS The blood concentration of duloxetine was 76.65 （45.57， 130.31） ng/mL， and C/D was 0.96 （0.63， 1.60） ng·d/（mL·mg）. The blood concentration of duloxetine was positively correlated with the daily dose of administration （R2＝0.253 7， P＜0.001）. Blood concentration of duloxetine in 38.94% of patients exceeded the recommended range specified in the guidelines. Gender， age， BMI， combined use of CYP2D6 enzyme inhibitors， and CYP2D6 and CYP1A2 phenotypes had significant effects on C/D of duloxetine （P＜0.05）. CONCLUSIONS The patient’s age， gender， BMI， combined medication， and genetic phenotypes are closely related to the blood concentration of duloxetine.

Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

Growth and development-related diseases result from the interplay of biological, psychological, and social factors. The collaboration between healthcare, sports, and education sectors integrates multidisciplinary resources and strengths to promote standardized diagnostic and therapeutic processes. This approach establishes a comprehensive closed-loop system encompassing early screening and referral, diagnosis and comprehensive evaluation, intervention and support plan formulation, as well as long-term management andoutcome assessment. It provides systematic scientific support for the healthy growth of children and adolescents, shifting disease intervention to the subclinical stage. Against the backdrop of societal informatization and intelligent development, this diagnostic and therapeutic model not only safeguards the holistic health of children and adolescents but also offers novel perspectives and feasible pathways for managing growth and development-related diseases. The implementation of this systematic diagnostic and therapeutic paradigm presents an innovative solution with Chinese characteristics for addressing such conditions, while injecting new vitality into the advancement of national health initiatives.