ObjectiveTo explore the relationship between negative life events and depression severity in adolescent patients with depressive disorder， as well as the chain mediating role of insomnia symptoms and quality of life. Methods374 outpatient patients and hospitalized patients with adolescent depressive disorders were enrolled. The Adolescent Life Event Scale （ASLEC）， the Insomnia Severity Index （ISI）， the World Health Organization Quality of Life Questionnaire Short Form （WHOQOL-BREF）， and the Center for Epidemiology Depression Scale （CES-D） were used to evaluate the negative life event situation， insomnia symptoms， quality of life level and depression severity of the subjects， respectively. In addition， the PROCESS 4.0 macroprogram was used to analyze the chain mediating effect of insomnia symptoms and quality of life between negative life events and depression severity in patients with adolescent depressive disorder. ResultsThe results of correlation analysis showed that there was a significant correlation between negative life events and insomnia symptoms， quality of life， and depression severity （all P<0.05）. In addition， the results of chain mediation showed that negative life events had a significant direct effect on depression severity， with an effect size of 0.12 （P<0.001）. Insomnia symptoms and quality of life played a mediating role in the relationship between negative life events and depression severity in patients with adolescent depressive disorders， with indirect effect sizes of 0.062 （95%CI： 0.040-0.087） and 0.091 （95%CI： 0.059-0.123）， respectively. It could also play a chain mediation role， and the effect size was 0.039 （95%CI： 0.024-0.057）. ConclusionNegative life events experienced by patients with adolescent depressive disorder not only directly affect the severity of depressive symptoms， but may also indirectly exacerbate depression through insomnia symptoms and quality of life.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Objective: To address the dual challenges of long-tail distribution and feature sparsity in traditional Chinese medicine (TCM) syndrome differentiation within real clinical settings, we propose a data-efficient learning framework enhanced by knowledge graphs. Methods: We developed Agent-GNN, a three-stage decoupled learning framework, and validated it on the Traditional Chinese Medicine Syndrome Diagnosis (TCM-SD) dataset containing 54 152 clinical records across 148 syndrome categories. First, we constructed a comprehensive medical knowledge graph encoding the complete TCM reasoning system. Second, we proposed a Functional Patient Profiling (FPP) method that utilizes large language models (LLMs) combined with Graph Retrieval-Augmented Generation (RAG) to extract structured symptom-etiology-pathogenesis subgraphs from medical records. Third, we employed heterogeneous graph neural networks to learn structured combination patterns explicitly. We compared our method against multiple baselines including BERT, ZY-BERT, ZY-BERT + Know, GAT, and GPT-4 Few-shot, using macro-F1 score as the primary evaluation metric. Additionally, ablation experiments were conducted to validate the contribution of each key component to model performance. Results: Agent-GNN achieved an overall macro-F1 score of 72.4%, representing an 8.7 percentage points improvement over ZY-BERT + Know (63.7%), the strongest baseline among traditional methods. For long-tail syndromes with fewer than 10 samples, Agent-GNN reached a macro-F1 score of 58.6%, compared with 39.3% for ZY-BERT + Know and 41.2% for GPT-4 Few-shot, representing relative improvements of 49.2% and 42.2%, respectively. Ablation experiments confirmed that the explicit modeling of etiology-pathogenesis nodes contributed 12.4 percentage points to this enhanced long-tail syndrome performance. Conclusion This study proposes Agent-GNN, a knowledge graph-enhanced framework that effectively addresses the long-tail distribution challenge in TCM syndrome differentiation. By explicitly modeling manifestation-mechanism-essence patterns through structured knowledge graphs, our approach achieves superior performance in data-scarce scenarios while providing interpretable reasoning paths for TCM intelligent diagnosis.

Objective To analyze Chinese and English publications pertaining to Oncomelania hupensis control from 2005 to 2024, so as to decipher the research status and hotspots of O. hupensis control. Methods Chinese and English publications pertaining to O. hupensis control from 2005 to 2024 were retrieved in the Web of Science Core Collection Database and China National Knowledge Infrastructure. The annual number of publications was analyzed from 2005 to 2024, and the author and institution cooperation networks were mapped using the software CiteSpace 6.3.1. Keywords were extracted from publications to map the co-occurrence, burst and timeline of keywords to identify the research hotspots of O. hupensis control. Results A total of 158 English publications and 771 Chinese publications were included for bibliometric analyses. The overall output of English publications was relatively small from 2005 to 2024, the annual average publication was 7.90 publications. Parasites & Vectors was the most productive journal by the number of publications (21 publications). The three most productive authors included Li Shizhu (24 publications), Zhou Xiaonong (13 publications), and Yang Kun (12 publications), and the three most productive institutions included Chinese Center for Disease Control and Prevention (49 publications), the WHO (27 publications), and Fudan University (25 publications). The annual average number of Chinese publications was high from 2005 to 2015 (57.73 publications), and reduced to 15.11 publications during the period from 2016 to 2024, with Chinese Journal of Schistosomiasis Control as the most productive journal (241 publications). The three most productive authors included Wang Wanxian (18 publications), Sun Qixiang (16 publications), and Dai Jianrong (16 publications), and the three most productive institutions included Jiangsu Institute of Parasitic Diseases (55 publications), Chinese Center for Disease Control and Prevention (47 publications), and Hubei Uni-versity (38 publications). Among the 158 English publications, molluscicidal effect, climate change, geographic information, biological control, machine learning were current research hotspots, and the Yangtze River and elimination were emerging research hotspots. Among the 771 Chinese publications, molluscicidal effect, niclosamide, comprehensive management, molluscicide, effectiveness evaluation, marshland, and endophyte were current research hotspots, and the future research hotspots shifted to molluscicidal effect and pyriclobenzuron. Conclusions Limited attention is paid to the research on O. hupensis control across the world. The Yangtze River, elimination, molluscicidal effect, and pyriclobenzuron may be future research hotspots. High attention is recommended to be paid to the research on O. hupensis control, and development of diverse approaches for O. hupensis control is of urgent needs. We should continue to attach importance to the control research of O. hupensis and strengthen the exploration of diverse snail extermination and control methods.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has become the most prevalent chronic liver disease worldwide, affecting approximately 32%-38% of the adult population and posing a growing public health burden. MASLD represents a continuous disease spectrum ranging from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH), progressive hepatic fibrosis, cirrhosis, and ultimately hepatocellular carcinoma (HCC). The pathological core of MASLD lies in disruption of hepatic lipid metabolic homeostasis, characterized by an imbalance among de novo lipogenesis, fatty acid β-oxidation, and very-low-density lipoprotein (VLDL)-mediated lipid export. This metabolic disequilibrium subsequently drives inflammatory injury and fibrotic progression. Among the multiple regulatory pathways involved, thyroid hormone (TH) signaling has emerged as a central regulator of hepatic metabolic homeostasis. The liver is a major peripheral target organ of TH action, where TH predominantly exerts its metabolic effects through thyroid hormone receptor β (TRβ). Large-scale epidemiological studies and meta-analyses have demonstrated that hypothyroidism is significantly associated with increased MASLD prevalence, more severe histological injury, and advanced hepatic fibrosis, suggesting that dysregulation of TH signaling may participate throughout the entire MASLD disease spectrum. At the molecular level, TH regulates hepatic lipid metabolism by coordinating suppression of lipogenesis, enhancement of mitochondrial fatty acid oxidation, and promotion of VLDL assembly and secretion through integrated genomic actions of the T3-TRβ axis and non-genomic signaling pathways. Across different stages of MASLD, TH signaling exerts stage-dependent protective effects. In the steatosis stage, TH improves metabolic flexibility by modulating insulin sensitivity, glucose metabolism, and lipid droplet clearance, thereby alleviating early lipotoxic stress. During progression to MASH, TH attenuates inflammatory amplification by improving mitochondrial homeostasis, suppressing activation of the NOD-like receptor family pyrin domain containing 3 (NLRP3) inflammasome, and modulating the gut-liver axis microenvironment. In advanced stages, TH signaling influences hepatic stellate cell activation and extracellular matrix deposition, partly through interaction with the transforming growth factor-β (TGF-β)/SMAD pathway, while alterations in intrahepatic TH availability, mediated by dynamic changes in iodothyronine deiodinase 1 (DIO1), contribute to fibrosis progression and hepatocellular dedifferentiation. In hepatocellular carcinoma, coordinated downregulation of TRβ and DIO1 establishes a tumor-associated hypothyroid state that promotes metabolic reprogramming and tumor progression. The clinical relevance of TH signaling in MASLD has been underscored by the recent approval of Resmetirom, a liver-targeted TRβ‑selective agonist, for the treatment of non-cirrhotic MASH with moderate-to-severe fibrosis (F2-F3). This approval represents a landmark transition from mechanistic understanding to metabolism-centered precision therapy in MASLD. Clinical trials have demonstrated that Resmetirom not only improves key histological endpoints, including MASH resolution and fibrosis regression, but also favorably modulates atherogenic lipid profiles, highlighting the therapeutic potential of selectively targeting hepatic TH pathways. This review systematically summarizes the multidimensional regulatory roles of TH across the MASLD disease spectrum and discusses emerging diagnostic and therapeutic implications of TH-based interventions, aiming to inform future mechanistic research and optimize clinical management strategies.

The study focuses on the concept of multifunctional traditional Chinese medicine (TCM) formulas and aims to evaluate the efficacy of the classical formula Xiaoyao San (逍遥散). Study employs the integrated evidence chain (Eff-iEC) method to organize, integrate, and evaluate its therapeutic efficacy in treating different diseases with the same therapy, and to investigate the feasibility of using Eff-iEC to evaluate the multifunctionality of TCM formulas. The evaluation covered Xiaoyao San's therapeutic effects on depression, premenstrual syndrome, chronic hepatitis, irritable bowel syndrome, dyspepsia, and menopausal syndrome. Concurrently, the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system was used for evaluation, and authoritative medical documents were incorporated to corroborate the recognition of Xiaoyao San within the medical community. Depression and menopausal syndrome received higher ratings than other conditions in the Eff-iEC, GRADE, and Medical Community Recognition assessments. The Eff-iEC evidence grade for Xiaoyao San was rated as "High" or above for chronic hepatitis, irritable bowel syndrome, dyspepsia, and menopausal syndrome. Premenstrual syndrome received a "Moderate ⁺" rating. The GRADE evidence level was "Low-〇〇⨁⨁" for depression, premenstrual syndrome, and chronic hepatitis; "Moderate-〇⨁⨁⨁" for dyspepsia and menopausal syndrome; and "Very Low-〇〇〇⨁" for irritable bowel syndrome. Depression and menopausal syndrome had the highest inclusion frequency, appearing in all 4 categories. Premenstrual syndrome, chronic hepatitis, and dyspepsia are not recommended in Western medical guidelines, but they are included in TCM guidelines, the China National Basic Medical Insurance Drug List, and the China National Essential Drug List. Irritable bowel syndrome appears only in the China National Basic Medical Insurance Drug List and China National Essential Drug List. The evaluation results obtained using the Eff-iEC method align with Medical Community Recognition, providing an objective and comprehensive assessment of Xiaoyao San's efficacy. The findings suggest that Xiaoyao San has strong evidence for treating depression and menopausal syndrome. However, further experimental and clinical trials are needed to assess its efficacy in treating premenstrual syndrome, chronic hepatitis, irritable bowel syndrome, and dyspepsia. These results support the clinical efficacy and rational use of Xiaoyao San, expand the application scope of the Eff-iEC method, and offer valuable insights and methodological references for the comparative evaluation of multifunctional TCM formulas.

Objective: To conduct screening for rare blood types within important blood group systems for the Chinese population, such as Rh, Duffy, Kidd, P1Pk, Diego, and MNS, in the Guangzhou region, and to establish a corresponding rare blood type database and physical repository. Methods: The saline medium microplate method was used to screen blood donors with the ccDEE phenotype combined with either Jk(a-) or Jk(b-). The polybrene microplate method was employed to screen for donors with Fy(a-), s(-), Lu(b-), Di(b-), k(-), and p phenotypes. The urea lysis microplate method was applied to screen for the Jk(a-b-) phenotype. A high-resolution melting (HRM) curve method was established for screening some donors with the Di(b-) phenotype. Subsequently, expanded phenotyping of antigens in the Rh, Kidd, MNS, Duffy, P1Pk, Lewis, Kell, and Lutheran blood group systems was performed on identified rare blood type donors using monoclonal antibodies. The test results are entered into the Rare Blood Type Bank Management System of the Guangzhou Blood Center, enabling functions such as confirmation reminders and cryopreservation storage when the donor donates again. Red blood cells of rare blood types are processed into frozen red blood cells for long-term storage. Results: Among voluntary blood donors, 16 cases of the ccDEE combined with Jk(a-) phenotype were identified (0.221 7%, 16/7 216); 10 cases of the ccDEE combined with Jk(b-) phenotype (0.138 6%, 10/7 216); 78 cases of the Fy(a-) phenotype (0.169 5%, 78/46 012); 39 cases of the Lu(b-) phenotype (0.138 2%, 39/28 214); 31 cases of the s(-) phenotype (0.081 8%, 31/37 913); 22 cases of the Di(b-) phenotype (0.029 9%, 22/73 691); 30 cases of the Jk(a-b-) phenotype (0.010 1%, 30/298 250); and 1 case of the k(-) phenotype (0.001 3%, 1/77 382), which was further identified as KELnull phenotype (K0). No p phenotype donors were identified (0/88 528). A total of 228 units of frozen red blood cells were prepared. The screening results were compared and analyzed with rare blood type data from other regions. Conclusion: This study, through a combination of different screening methods, significantly improved the efficiency of rare blood type screening while remaining cost-effective. By conducting large-scale screening and performing data informatization processing, a database and physical repository of rare blood types in the Guangzhou region were successfully established. This provides a strong guarantee for the timely supply of blood to patients with difficult-to-match and rare blood types in the region, effectively enhances the level of transfusion safety in the region, and offers a practical paradigm for constructing a comprehensive blood transfusion support system.

ObjectiveTo investigate the therapeutic effects and mechanisms of modified Huangqi Jianzhong decoction （HQJZ） on gastric precancerous conditions （GPC）. MethodsIn the cell experiment， human gastric mucosal epithelial cells underwent malignant transformation induced by N-methyl-N′-nitro-N-nitrosoguanidine （MNNG） for the modeling of GPC （MC cells）. The cells were allocated into four groups： control ， model， low-dose HQJZ （HQJZ-L）， and high-dose HQJZ （HQJZ-H）. The control and model groups were cultured with the complete medium， while HQJZ-L and HQJZ-H groups received additional interventions with HQJZ at low （0.5 g·L^-1） and high （1.0 g·L^-1） doses， respectively. Cell counting kit-8 （CCK-8） assay was used to evaluate cytotoxicity， Transwell assay to assess cell invasion， Annexin V-FITC/PI staining to detect apoptosis， immunofluorescence assay to analyze reactive oxygen species （ROS） expression and mitochondrial autophagy， and Western blot to verify expression of proteins in key pathways. In the animal experiment， the GPC model was established in healthy BALB/c mice through MNNG induction. Twenty-four mice were allocated into four groups： control， model， HQJZ-L， and HQJZ-H. Control and model groups received normal saline （10 mL·kg^-1·d^-1） orally， while HQJZ-L and HQJZ-H groups were administrated with low-dose （6.24 g·kg^-1·d^-1） and high-dose （12.48 g·kg^-1·d^-1） HQJZ， respectively. After treatment， hematoxylin‑eosin （HE） staining and AB-PAS staining were performed to observe histopathological changes in the gastric tissue. Immunofluorescence assay was used to detect reactive oxygen species （ROS） and microtubule-associated protein 1 light chain 3 （LC3） levels in the gastric mucosa， TdT-mediated dUTP nick-end labeling （TUNEL） staining to assess apoptosis rates， and Western blotting and immunohistochemistry （IHC） to analyze the expression levels of Ki67， proliferating cell nuclear antigen （PCNA）， and foxhead box O3 （FoxO3）. ResultsCell viability assays showed that HQJZ dose-dependently reduced MC cell viability compared with the control group （P<0.05， P<0.01）. Transwell assays revealed that the model group exhibited enhanced cell invasion compared with the control group （P<0.05）. Compared with the model group， HQJZ treatment attenuated the cell invasion （P<0.05）. Gastric mucosal pathology in mice demonstrated that compared with the control group， the model group showed elevated HE and AB-PAS pathological scores （P<0.05）， while HQJZ treatment reduced these scores （P<0.05）. Transmission electron microscopy revealed increased mitochondrial number and volume in the model group compared with the control group. HQJZ treatment resulted in abnormal mitochondrial structure and significant alterations in rough endoplasmic reticulum morphology and distribution， presenting as dilated and hollow forms. Mitochondrial and apoptosis assessments indicated that compared with the control group， the model group exhibited enhanced Mito Tracker Green fluorescence （P<0.05）， no significant change in DCFH-DA fluorescence， Mito Tracker Red CMXRos fluorescence， ROS immunofluorescence， or malondialdehyde （MDA） level， increased GSH level （P<0.05）， enhanced LC3 fluorescence （P<0.05）， no significant change in apoptosis rate， and elevated ATP content in cells and mouse serum （P<0.05）. Compared with the model group， HQJZ treatment reduced Mito Tracker Green fluorescence （P<0.05）， increased DCFH-DA fluorescence， Mito Tracker Red fluorescence， MDA level， LC3 fluorescence， and apoptosis rate （P<0.05）， and decreased cellular ATP content （P<0.05）. The HQJZ-L group showed no significant change in ROS immunofluorescence or GSH level， whereas the HQJZ-H group demonstrated enhanced ROS immunofluorescence and glutathione （GSH） level （P<0.05）. Immunohistochemistry and Western blotting revealed that compared with the control group， the model group exhibited increased numbers of PCNA- and Ki67-positive cells （P<0.05） and elevated protein levels of FoxO3， sirtuin 1 （SIRT1）， and B-cell lymphoma 6 （Bcl-6） （P<0.05）. HQJZ treatment reduced the numbers of PCNA- and Ki67-positive cells （P<0.05） and lowered the protein levels of FoxO3， SIRT1， and Bcl-6 （P<0.05）. ConclusionHQJZ alleviates the progression of gastric precancerous lesions by regulating mitochondrial function via the FoxO3/ROS pathway and promoting apoptosis of GPC-malignant cells.

ObjectiveTo explore whether fluoroethylnormemantine （FENM）， an NMDA receptor antagonist， could improve compulsive-like behaviors and to investigate its underlying mechanisms in the RU24969-induced obsessive-compulsive disorder （OCD） mouse model. MethodsThirty-two mice were randomly assigned to four groups： Saline （n=8）， RU24969 （n=8）， RU+FENM （n=8）， and FENM （n=8）. Mice received FENM or an equivalent volume of saline for pre-treatment， followed by RU24969 or saline for model induction 30 minutes later. Behavioral tests were performed 1 hour after modeling， and serum samples were collected to measure the level of brain-derived neurotrophic factor （BDNF）. Evans Blue dye was intravenously injected to assess dye content in brain tissue， thereby evaluating potential blood-brain barrier damage. ResultsFENM treatment significantly improved repetitive stereotyped circling behavior （F=39.850， P＜0.001） and alleviated persistent motor activity （F=50.200， P＜0.001） in RU24969 model mice. Additionally， FENM treatment significantly increased serum BDNF level in RU24969-induced OCD mice （F=18.930， P＜0.001）. ConclusionsFENM ， an NMDA receptor antagonist， may alleviate compulsive behaviors in OCD mice by modulating BDNF levels ， thereby exerting anti-compulsive effects. Neither the RU24969 model nor FENM treatment significantly affectes blood-brain barrier integrity.