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.

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.

Diabetes is a chronic disease that requires lifelong medication and long-term management. The longer the duration of the disease, the more likely it is to lead to progressive chronic complications affecting the eyes, kidneys, nervous system, and cardiovascular system. These complications may result in gradual functional decline or even organ failure, and may also trigger severe acute metabolic disorders. The cumulative financial burden on patients and their families can be substantial, giving rise to what is known as financial toxicity, which in turn may negatively affect patients' health outcomes. This review comprehensively explores the concept of financial toxicity in diabetic patients, including its assessment tools, influencing factors, and coping strategies. It also offers targeted suggestions aimed at informing the development of more scientific and effective systemic interventions, with the ultimate goal of improving treatment outcomes and quality of life for individuals living with diabetes.

Objective To establish an inductively coupled plasma-mass spectrometry(ICP-MS)method for the analysis of 29 mineral elements in Artemisiae Argyi Folium(AAF),and to develop a model for judging the origin of AAF based on the elemental fingerprint combined with chemometrics.Methods The variance method was used to compare the contents of 29 mineral elements in AAF samples from Qichun of Hubei province,Hebei province and Henan province,respectively.The discriminant models of AAF from different habitats were established by discriminant analysis,PLS-DA and PCA-Logistic regression algorithms.Results The differences of the 22 elements(V,Cr,Ni,As,Se,Rb,Mo,Cd,Sb,Ba,Hg,Pb,K,Li,B,Mg,Al,P,Ca,Fe,Zn,and Ga)in samples from Qichun of Hubei province,Hebei province and Henan province are extremely significant(P＜0.01).The discriminant analysis model showed that eight kinds of element variables(P,Cr,K,Li,Hg,Ba,Mg,and Mo),which have a significant effect on the origin discrimination are gradually introduced into the discriminant model,and the correct rate of back test is 100％.The correct rate of"leave one method"cross-validation is 96.7％.The PLS-DA model showed good prediction ability,and the variable importance projection values of K,P and Mg elements were greater than one,which could be used as the difference marker of AAF from different habitats.The accuracy of the origin discrimination model constructed by PC A-Logistic regression analysis was 100％.The elements with high first principal component loadings were Li,B,Mg,Al,P,K,Ca,V,Cr,Fe,Ni,Zn,As,Rb,Cd,Sb,and Ba.Conclusion This study shows that elemental fingerprint technology combined with chemometric analysis can identify AAF from Qichun of Hubei province,Hebei province,or Henan,providing technical support for the traceability of the origin of Artemisia argyi.

Diabetes is a chronic disease that requires lifelong medication and long-term management. The longer the duration of the disease, the more likely it is to lead to progressive chronic complications affecting the eyes, kidneys, nervous system, and cardiovascular system. These complications may result in gradual functional decline or even organ failure, and may also trigger severe acute metabolic disorders. The cumulative financial burden on patients and their families can be substantial, giving rise to what is known as financial toxicity, which in turn may negatively affect patients' health outcomes. This review comprehensively explores the concept of financial toxicity in diabetic patients, including its assessment tools, influencing factors, and coping strategies. It also offers targeted suggestions aimed at informing the development of more scientific and effective systemic interventions, with the ultimate goal of improving treatment outcomes and quality of life for individuals living with diabetes.

Objectives:To preliminarily investigate the safety and efficacy of same-day discharge(SDD)following radiofrequency catheter ablation for arrhythmia.Methods:A total of 50 consecutive patients who underwent radiofrequency catheter ablation for arrhythmia in the SDD strategy at Fuwai Hospital from 8 July 2024 to 18 September 2024 were included in this analysis.The study evaluated the immediate success rate of the ablation,the rate of all-cause and arrhythmia-related readmission,outpatient or emergency visits and incidence of complications within 30 days post ablation,and recurrence rate of arrhythmias over a 3-month follow-up period.Results:The average age of the 50 patients was(47.2±16.1)years old,32 patients(64.0%)were male.Radiofrequency catheter ablation was performed in 47 patients(94.0%),including 18(36.0%)atrial fibrillation(AF)ablation.Three patients(6.0%)underwent electrophysiological study only.The immediate success rate for ablation patients was 100%(47/47).None of the patients developed vascular puncture-related or ablation-related complications.The average hospital stay and postoperative observation time were(6.84±1.13)hours and(3.40±1.12)hours,respectively.The all-cause and arrhythmia-related readmission,outpatient or emergency visits rates within 30 days were 12.0%(6/50)and 2.0%(1/50),respectively.Two patients(4.0%)post ablation experienced AF recurrence during the 3-months follow-up period.Conclusions:Radiofrequency catheter ablation for arrhythmias in SDD strategy is safe,effective,and feasible.

Objectives:To preliminarily investigate the safety and efficacy of same-day discharge(SDD)following radiofrequency catheter ablation for arrhythmia.Methods:A total of 50 consecutive patients who underwent radiofrequency catheter ablation for arrhythmia in the SDD strategy at Fuwai Hospital from 8 July 2024 to 18 September 2024 were included in this analysis.The study evaluated the immediate success rate of the ablation,the rate of all-cause and arrhythmia-related readmission,outpatient or emergency visits and incidence of complications within 30 days post ablation,and recurrence rate of arrhythmias over a 3-month follow-up period.Results:The average age of the 50 patients was(47.2±16.1)years old,32 patients(64.0%)were male.Radiofrequency catheter ablation was performed in 47 patients(94.0%),including 18(36.0%)atrial fibrillation(AF)ablation.Three patients(6.0%)underwent electrophysiological study only.The immediate success rate for ablation patients was 100%(47/47).None of the patients developed vascular puncture-related or ablation-related complications.The average hospital stay and postoperative observation time were(6.84±1.13)hours and(3.40±1.12)hours,respectively.The all-cause and arrhythmia-related readmission,outpatient or emergency visits rates within 30 days were 12.0%(6/50)and 2.0%(1/50),respectively.Two patients(4.0%)post ablation experienced AF recurrence during the 3-months follow-up period.Conclusions:Radiofrequency catheter ablation for arrhythmias in SDD strategy is safe,effective,and feasible.

Neuronal intranuclear inclusion disease（NIID）is a rare hereditary neurodegenerative disorder that can affect multiple systems. However，it is uncommon for urinary dysfunction to be the initial symptom. This article reports five cases. The five patients began to experience voiding dysfunction such as frequent urination，weak urination，and incomplete urination at the mean ages of 55.4（47 - 65）years old. Four months to twelve years after urinary onset，neurological symptoms such as headache，memory decline，transient loss of consciousness，and unsteady gait began to appear. Four of the five cases had a family history. Brain MRI revealed the “ribbon sign” or “crest sign” in all cases. Skin biopsy revealed eosinophilic inclusions in the cell nuclei，and NOTCH2NLC gene testing identified abnormal GGC mutations. Three of the five patients underwent cystostomy due to secondary hydronephrosis，while the other two received no special treatment. After a follow-up of 18 to 35 months since diagnosis，the patients who underwent cystostomy had normal renal function. Neurological symptoms in all five patients worsened to varying degrees.

Objective To establish an inductively coupled plasma-mass spectrometry(ICP-MS)method for the analysis of 29 mineral elements in Artemisiae Argyi Folium(AAF),and to develop a model for judging the origin of AAF based on the elemental fingerprint combined with chemometrics.Methods The variance method was used to compare the contents of 29 mineral elements in AAF samples from Qichun of Hubei province,Hebei province and Henan province,respectively.The discriminant models of AAF from different habitats were established by discriminant analysis,PLS-DA and PCA-Logistic regression algorithms.Results The differences of the 22 elements(V,Cr,Ni,As,Se,Rb,Mo,Cd,Sb,Ba,Hg,Pb,K,Li,B,Mg,Al,P,Ca,Fe,Zn,and Ga)in samples from Qichun of Hubei province,Hebei province and Henan province are extremely significant(P＜0.01).The discriminant analysis model showed that eight kinds of element variables(P,Cr,K,Li,Hg,Ba,Mg,and Mo),which have a significant effect on the origin discrimination are gradually introduced into the discriminant model,and the correct rate of back test is 100％.The correct rate of"leave one method"cross-validation is 96.7％.The PLS-DA model showed good prediction ability,and the variable importance projection values of K,P and Mg elements were greater than one,which could be used as the difference marker of AAF from different habitats.The accuracy of the origin discrimination model constructed by PC A-Logistic regression analysis was 100％.The elements with high first principal component loadings were Li,B,Mg,Al,P,K,Ca,V,Cr,Fe,Ni,Zn,As,Rb,Cd,Sb,and Ba.Conclusion This study shows that elemental fingerprint technology combined with chemometric analysis can identify AAF from Qichun of Hubei province,Hebei province,or Henan,providing technical support for the traceability of the origin of Artemisia argyi.

Neuronal intranuclear inclusion disease（NIID）is a rare hereditary neurodegenerative disorder that can affect multiple systems. However，it is uncommon for urinary dysfunction to be the initial symptom. This article reports five cases. The five patients began to experience voiding dysfunction such as frequent urination，weak urination，and incomplete urination at the mean ages of 55.4（47 - 65）years old. Four months to twelve years after urinary onset，neurological symptoms such as headache，memory decline，transient loss of consciousness，and unsteady gait began to appear. Four of the five cases had a family history. Brain MRI revealed the “ribbon sign” or “crest sign” in all cases. Skin biopsy revealed eosinophilic inclusions in the cell nuclei，and NOTCH2NLC gene testing identified abnormal GGC mutations. Three of the five patients underwent cystostomy due to secondary hydronephrosis，while the other two received no special treatment. After a follow-up of 18 to 35 months since diagnosis，the patients who underwent cystostomy had normal renal function. Neurological symptoms in all five patients worsened to varying degrees.