Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

Anxiety is a major emotional disorder manifested in the individual's expectation of future threats.The incidence rate of anxiety is about 7.3％,with the highest lifetime prevalence rate among mental health conditions.The mechanism of anxiety overlaps with depression,and anxiety is a typical symptom of various mental diseases or emotional disorders in traditional Chinese medicine.The high rates of comorbidity and disability pose serious threats to people's health.Animal models are important tools for studying anxiety and are of great use for deciphering the pathogenesis of anxiety and for developing drugs.The traditional paradigm of stress-induced anxiety,however,is relatively limited.Based on traditional theory combined with clinical and animal experimental data,we propose a new hypothesis of"insufficiency of ZhiYi'causing anxiety,defined as"an anxiety state induced by the inability of an individual to meet their own needs,limited or lacking after multiple attempts,rendered hindered and powerless by an inability to meet their desires".This hypothesis is more in line with the typical manifestations of despair,lack of pleasure,and social withdrawal in clinical patients,and is supported by traditional theory and experimental data showing"hunger but unable to eat,food but unable to obtain,and gain but not full".Based on this,the established modeling paradigm is easy to apply,with good repeatability and low cost,and can be used to establish anxiety models in rats and mice,to provide a theoretical and model basis for the development and pharmacological evaluation of anti-anxiety drugs.

Anxiety is a major emotional disorder manifested in the individual's expectation of future threats.The incidence rate of anxiety is about 7.3％,with the highest lifetime prevalence rate among mental health conditions.The mechanism of anxiety overlaps with depression,and anxiety is a typical symptom of various mental diseases or emotional disorders in traditional Chinese medicine.The high rates of comorbidity and disability pose serious threats to people's health.Animal models are important tools for studying anxiety and are of great use for deciphering the pathogenesis of anxiety and for developing drugs.The traditional paradigm of stress-induced anxiety,however,is relatively limited.Based on traditional theory combined with clinical and animal experimental data,we propose a new hypothesis of"insufficiency of ZhiYi'causing anxiety,defined as"an anxiety state induced by the inability of an individual to meet their own needs,limited or lacking after multiple attempts,rendered hindered and powerless by an inability to meet their desires".This hypothesis is more in line with the typical manifestations of despair,lack of pleasure,and social withdrawal in clinical patients,and is supported by traditional theory and experimental data showing"hunger but unable to eat,food but unable to obtain,and gain but not full".Based on this,the established modeling paradigm is easy to apply,with good repeatability and low cost,and can be used to establish anxiety models in rats and mice,to provide a theoretical and model basis for the development and pharmacological evaluation of anti-anxiety drugs.

Objective:To analyze the relationship between 24-hour urinary calcium (24 h UCa) level and the risk of end-stage kidney disease (ESKD), cardiovascular disease (CVD), and all-cause mortality.Methods:In the Chinese Cohort Study of Chronic Kidney Disease, we examined 3 375 patients aged 18-74 years with CKD stages 1-4. Kaplan-Meier survival and Cox proportional hazard regression models were used to test a time-to-event association between levels of 24 h UCa and incidence of ESKD, CVD, and all-cause mortality.Results:During a follow-up of 4.17 (3.37, 5.20) years, 179, 145, 104 and 38 ESKD events occurred in <0.60, 0.60-, 1.20-, ≥2.32 mmol 24 h UCa groups. Higher levels of 24 h UCa (1.20-,≥2.32 mmol) were independently associated with a lower incidence of ESKD events in patients with CKD, with HR (95% CI) of 0.71 (0.54-0.93) and 0.43 (0.29-0.64), respectively. No significant associations with CVD and all-cause mortality endpoints were detected. Conclusion:Among patients with CKD, levels of 24 h UCa displayed an association with the risk of ESKD among patients with CKD stages 1-4.

Liver cancer is one of the most common malignant tumors worldwide. Currently, the available treatment methods cannot fully control its recurrence and mortality rate. Establishing appropriate animal models for liver cancer is crucial for developing new treatment technologies and strategies. The patient-derived xenograft (PDX) model preserves the tumor's microenvironment and heterogeneity, which makes it advantageous for biological research, drug evaluation, personalized medicine, and other purposes. This article reviews the development, preparation techniques, application fields, and challenges of PDX models in liver cancer, providing insights for the research and exploration of PDX models in diagnostic and therapeutic strategies of liver cancer.
Liver Neoplasms/drug therapy* ; Animals ; Humans ; Xenograft Model Antitumor Assays/methods* ; Mice ; Disease Models, Animal

After ischemic stroke,intracranial cells experience stress due to ischemic and hypoxic injury,leading to a series of aseptic immune response processes.The oxidative stress process in microglias triggers the activation of the NLRP3 inflammasome,which promotes the release of inflammatory factors such as IL-1β and IL-18,contributing to the inflammatory reaction caused by isch-emic stroke.In addition,NLRP3 inflammasome is involved in the polarization,pyroptosis and autophagy of microglias,regulating the prognosis of ischemic stroke.This review summarizes the specific mechanisms of NLRP3 inflammasome in regulating microglial status and its involvement in ischemia-reperfusion injury.It also discusses the associated treatment strategies,identifies the current research focus and blanks,and provides some guidance and ideas for future research.

Objective: To evaluate the safety and efficacy of therapeutic whole blood exchange combined with lymphoplasmapheresis in the treatment of refractory autoimmune hemolytic anemia (AIHA). Methods: A retrospective analysis was performed on the clinical data of AIHA patients who underwent therapeutic whole blood exchange combined with lymphoplasmapheresis at our hospital from March 2022 to May 2025. Efficacy was assessed by comparing changes in hemoglobin, platelet count, and bilirubin levels before and after treatment. Safety was evaluated by analyzing vital signs before and after the procedure, parameters during the exchange, and adverse reactions. Results: A total of 12 AIHA patients were enrolled, completing 19 exchange procedures. The number of procedures per patient ranged from 1 to 3. The median treatment duration was 67 (65-73) minutes, with a median exchange volume of 2 025 (1 851-2 121) mL, comprising 4.5 (4-6) units of red blood cells and 1 350 (1 200-1 400) mL of plasma. Ten patients achieved partial remission, one achieved complete remission, and one showed no response, yielding an response rate of 91% (11/12). After a single session, hemoglobin increased significantly by 17.58±9.85 g/L (P<0.01), while platelets counts decreased by 45 (17.5, 79)×10 /L (P<0.05), and both systolic and diastolic blood pressure showed a significant elevation (P<0.05). However, no statistically significant differences were observed in total bilirubin, indirect bilirubin, white blood cell count, or heart rate. During the procedures, 4 adverse reactions occurred in 3 patients: one child experienced severe heart rate fluctuation twice consecutively, and two adults developed plasma allergies. All reactions resolved spontaneously without pharmacological intervention. Conclusion: The combination of therapeutic whole blood exchange and lymphoplasmapheresis appears to be a safe and effective treatment for refractory AIHA patients.

Female reproductive system diseases,such as premature ovarian insufficiency(POI),premature ovarian failure(POF),polycystic ovary syndrome(PCOS),intrauterine adhesions(IUA),ulterus scar diverticulum,salpingitis,and tubal obstruction,may induce infertility,severely impacting patients'physical and mental health and quality of life.Currently,the umbilical cord mesenchymal stem cells(UCMSCs)have emerged as a research focus in gynecological and obstetric fields,demonstrating significant therapeutic potential for female reproductive system disorders.UCMSCs secrete various cytokines,activate relevant signaling pathways and key molecules,reduce inflammation mediators and oxidative stress,and prevent excessive cellular damage and apoptosis,thereby achieving therapeutic effects.In recent years,extensive studies have explored the therapeutic effects of UCMSCs on female reproductive system diseases.This article review the current in vitro and in vivo research progress in UCMSCs for treating female reproductive system diseases,aiming to provide the novel strategies and directions for future research and clinical applications.

Objective To investigate changes in gut microbiota during diabetic nephropathy(DN)pro-gression using 16S rDNA sequencing technology.Methods A total of 90 male SD rats were randomly divided into a normal control group(n=10,no modeling,regular feeding)and a model group(diabetes model).The diabetes model was established by a single intraperitoneal injection of streptozotocin(STZ)at 60 mg/kg,with regular feeding.According to the feeding time after modeling,the rats were divided into 2-week,4-week,8-week,and 12-week model groups(fed for 2,4,8,and 12 weeks after model establishment),with 20 rats in each group.Blood urea nitrogen(BUN)was measured using the urease method,serum creatinine(Scr)was deter-mined by the picric acid method,and ELISA was used to detect urinary kidney injury molecule-1(KIM-1)and neutrophil gelatinase-associated lipocalin(NGAL)levels.HE,PAS,and Masson staining were used to observe renal tissue pathological changes.Gut microbiota was collected from the rats,and 16S rDNA gene sequencing was used to analyze the gut microbiota to understand changes in the gut microbiota.Results Compared with the normal control group,the levels of KIM-1 and NGAL in urine of rats in all model groups were significantly increased(P<0.05).Pathological staining results showed that,compared with the normal control group,rats in all model groups exhibited diffuse thickening of the glomerular basement membrane and pathological chan-ges such as local necrosis and vacuolar degeneration in renal tubular epithelial cells.16S rDNA sequencing re-sults indicated that the abundance and structure of intestinal microbiota in rats of all model groups changed.Compared with the normal control group,in the 8-week and 12-week model groups,the relative abundance of Bacteroides and Akkermansia decreased,while the relative abundance of Roseburia,Alloprevotella,Prevotel-laceae-Ga6A1,and Ruminococcaceae UCG-005 increased.Compared with the normal control group,in the 12-week model group,the abundance of Akkermansia decreased and that of Prevotellaceae-NK3B31 increased.Conclusion The abundance and structure of gut microbial community in DN rats under conventional feeding at different time points change significantly,further confirming the"gut-kidney axis"theory.