Objective: To explore the relationship between snack consumption and depressive symptoms in first year junior high school students with different left behind experiences in Yunnan Province, so as to provide a basis for improving depressive symptoms among first year junior high school students with different left behind experiences. Methods: From October to December 2022,a cluster random sampling method was used to select 8 500 first year junior high school students from 11 ethnic minority areas (Fugong County, Longling County, Longyang District, Luchun County, Mojiang County, Nanjian County, Qiaojia County, Shuangjiang County, Tengchong City, Yuanmou County, Zhenyuan County) in Yunnan Province for a questionnaire survey. The Chinese version of Depression Anxiety Stress Scale-21 was applied to assess depressive symptoms in first year junior high school students, and snack consumption was collected by employing food frequency questionnaire. The generalized linear model was used to analyze the association between first year junior high school students snack consumption and depressive symptoms, and the analysis was stratified according to left behind experience. Results: The detection rates of depressive symptoms among firstyear junior high school students with and without left behind experience were 36.25% and 26.91%, respectively. After controlling for confounding variables, the generalized linear model analysis showed that sweet snacks ( β=0.16, 95%CI =0.07-0.25), fast food ( β=0.14, 95%CI =0.04-0.23) and carbonated drinks ( β=0.09, 95%CI =0.01-0.17) of first year junior high school students with left behind experience (all P <0.05). Compared with those without such behavior, the risk of depressive symptoms was higher in consumption of fast food ( β=0.13, 95%CI =0.07-0.18) and carbonated drinks ( β=0.10, 95%CI =0.06-0.15)among first year junior high school students without left behind experience (both P <0.05). Conclusion Snack consumption among first year junior high school students in Yunnan may increase the risk of developing depressive symptoms, while first year junior high school students with left behind experience may have a greater risk of developing depressive symptoms.

ObjectiveTo investigate the association between immunoglobulin G （IgG）/immunoglobulin M （IgM） ratio and prognosis in patients with initially unresectable hepatocellular carcinoma （iuHCC） receiving TTP triple therapy with transcatheter arterial chemoembolization （TACE）， tyrosine kinase inhibitor （TKI）， and programmed cell death protein-1 （PD-1） inhibitors. MethodsA retrospective analysis was performed for the clinical data of 151 iuHCC patients who received TTP triple therapy in Department of Hepatobiliary Surgery， Guangxi Medical University Cancer Hospital， from November 2019 to December 2022， and according to IgG/IgM ratio， they were divided into high IgG/IgM group （IgG/IgM ratio >13.23） and low IgG/IgM group （IgG/IgM ratio ≤13.23）. The t-test was used for comparison of continuous data between groups， and the chi-square test was used for comparison of categorical data between groups. The Kaplan-Meier method and the log-rank test were used for survival analysis， and the Cox proportional hazards model was used to investigate the potential influencing factors for overall survival （OS）. ResultsThe 151 patients had a median OS of 26.7 months （95% confidence interval ［CI］： 19.8-not reached） and a median progression-free survival of 12.5 months （95%CI： 10.4 — 15.8）. The objective response rate was 83.4% and the disease control rate was 94.0%. There were no significant differences in baseline data between the high IgG/IgM group and the low IgG/IgM group （all P>0.05）. There was a significant difference in median OS between the high IgG/IgM group and the low IgG/IgM group （20.6 months vs not reached， P=0.016）. In both the high IgG/IgM group and the low IgG/IgM group， salvage hepatectomy was significantly associated with the improvement in OS （χ²=8.297 and 10.307， both P<0.05）. The multivariate analysis showed that high IgG/IgM ratio （hazard ratio ［HR］=1.799， 95%CI： 1.077 — 3.006， P=0.025）， baseline alpha-fetoprotein >400 ng/mL （HR=1.762， 95%CI： 1.017 — 3.050， P=0.043）， and BCLC stage （HR=2.265， 95%CI： 1.212 — 4.232， P=0.010） were independent influencing factors for OS. ConclusionHigh IgG/IgM ratio is associated with a poorer prognosis in iuHCC patients receiving TTP triple therapy， and salvage hepatectomy has a potential value in improving the prognosis of patients with a high IgG/IGM ratio.

Objective: To evaluate the implementation process of a school-family collaborative "online+offline" tobacco control intervention program in junior high school in Beijing and to explore the execution status, influencing factors and sustainability potential of the intervention, so as to provide evidence for optimizing youth tobacco control strategies. Methods: In November 2024, using the random number table method, four first year junior high school classes were selected from three schools each in Fengtai District, Tongzhou District, and Fangshan District of Beijing. One class served as the control group, while the other three classes were designated as intervention groups (one each for online intervention, offline intervention, and combined online offline intervention). The control group received only conventional education.The online intervention group was engaged in WeChat push interventions, including watching micro videos, viewing promotional materials, participating in online quizzes and mini games; the offline intervention group attended knowledge lectures, played peer games, and participated in offline knowledge competitions; the combined online offline intervention group integrated all the aforementioned online and offline intervention measures. The intervention period was from November 2024 to June 2025, spanning a total of 7 months. Based on the Practical, Robust Implementation and Sustainability Model(PRISM) framework, a qualitative research design was employed to conduct semi structured interviews with 48 participants (12 in each of the intervention groups and 12 organizational staff members) from the Centers for Disease Control and Prevention (CDC) in 3 districts and 3 sampled schools. The interview outlines were designed according to the intervention plan. Data was managed using Nvivo 12.0 software and analyzed following Colaizzi s seven step phenomenological analysis method. Theoretical saturation was assessed using a reserved subset of transcripts. Results: Four core themes were identified in the tobacco control intervention process. Overall fidelity of intervention implementation was largely consistent with the original plan, and students showed strong willingness and positive evaluations toward interactive formats such as knowledge contests and peer games, though occasional breakdowns in school-family communication and blurred boundaries between online and offline components were observed; the participants showed a polarized response in terms of satisfaction and participation, most students and parents recognized the significance of the activity, and some parents observed a reduction in smoking behavior; the implementation of internal tobacco control policies in the school was strict, and the atmosphere was favorable, but there was still room for improvement, such as the scarcity of community tobacco control activities and the difficulty in implementing smoke free units; implementation and sustainability infrastructure were preliminarily established, such as through homeroom teacher supervision and training student assistants to assisted in activities, while the sustainability support system required further refinement. Conclusion The school-family collaborative "online+offline" tobacco control intervention has demonstrated significant positive effects, but further optimization of activity design, enhancement of community reward mechanisms, and standardized training are required to improve the efficacy and sustainability of the intervention.

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 evaluate the efficacy and safety of amoxicillin combined with proton pump inhibitor （PPI） or potassium-competitive acid blocker （P-CAB） for Helicobacter pylori （Hp） eradication. METHODS Randomized controlled trial （RCTs） on amoxicillin combined with PPI or P-CAB for Hp eradication were retrieved from PubMed， Embase， the Cochrane Library， Web of Science， CNKI， Wanfang， and VIP data. The search time frame was from database inception to September 5， 2025. After literature screening， data extraction， and quality assessment， a network meta-analysis was performed using Stata 17.0 software. RESULTS A total of 12 RCTs involving 5 515 patients were included， encompassing 8 therapeutic regimens： PPI combined with high-dose amoxicillin for 14 days （TR1）， PPI combined with low-dose amoxicillin for 14 days （TR2）， P-CAB combined with high-dose amoxicillin for 7 days （TR3）， P-CAB combined with high-dose amoxicillin for 14 days （TR4）， P-CAB combined with high-dose amoxicillin for 10 days （TR5）， P-CAB combined with low-dose amoxicillin for 7 days （TR6）， P-CAB combined with low-dose amoxicillin for 14 days （TR7）， and P-CAB combined with low-dose amoxicillin for 10 days （TR8）. The network meta-analysis results showed that， in terms of intention-to-treat Hp eradication rates， the eradication rates of TR5 and TR4 were significantly higher than those of TR3， TR8， TR6 and TR1 （ P ＜0.05）. The surface under the cumulative ranking curve （SUCRA） values from highest to lowest were： TR4 （89.7%）＞TR5 （82.3%）＞TR7 （71.5%）＞ TR2 （48.6%）＞TR1 （43.9%）＞TR8 （28.7%）＞TR3 （22.7%）＞TR6 （12.6%）. Regarding safety， the incidence of adverse reactions in TR3 and TR5 was significantly lower than that in TR1 （ P ＜0.05）. The SUCRA values from highest to lowest were： TR1 （91.3%）＞TR4 （79.8%）＞TR5 （55.0%）＞TR7 （50.9%）＞TR8 （41.3%）＞TR2 （36.4%）＞TR3 （27.6%） ＞TR6 （17.7%）. CONCLUSIONS Although the regimen of P-CAB combined with high-dose amoxicillin for 14 days demonstrates the best efficacy， the combination of P-CAB with high-dose amoxicillin for 10 days exhibits a better balanced profile in terms of both efficacy and safety.

Objective: To explore the association between vegetable intake with glucose and lipid metabolism levels among school aged children, so as to provide scientific basis for dietary intervention on children s metabolic health. Methods: Based on a natural population cohort in Jiulongpo District and Fengdu County of Chongqing, 2 133 school aged children aged 6-9 years were enrolled in the baseline survey in 2014, and 2 029 children completed the follow up in 2019. Questionnaire surveys were used to collect vegetable intake, general demographic and lifestyle data. Height, weight and waist circumference were measured, and glucose and lipid metabolism indicators such as fasting blood glucose (FBG), triglyceride (TG) and total cholesterol (TC), low densith lipoprotein triglyceride (LDL-C), high densith lipoprotein triglyceride (HDL-C) were detected. Mann-Whitney U test and Kruskal-Wallis H test were used for intergroup comparisons in multivariate analysis, and mixed effects linear regression model was used to analyze the association between vegetable intake and glucose and lipid metabolism. Results: The levels of FBG, TG, TC, HDL-C and LDL-C at baseline and follow up were [4.09(3.90,4.48), 0.84(0.60,1.14), 3.49(3.09,3.91), 1.25(1.09,1.46), 1.69 ( 1.39 ,2.02)；4.31(4.00,4.64), 0.92(0.71,1.22), 3.49(3.12,3.87), 1.36(1.16,1.57), 1.77(1.51,2.06)] mmol/L, respectively. Among these indicators, FBG, TG, HDL-C and LDL-C all increased significantly ( Z =-12.08, -7.82, -9.82, -5.37, all P < 0.01 ). The detection rate of low HDL-C levels at follow up (13.11%) was significantly lower than that at baseline (18.10%) ( χ 2=19.57, P <0.05). At baseline, there were significant differences in FBG, TC, TG, HDL-C and LDL-C among children with different vegetable intake levels ( H =68.47, 30.16, 11.02, 13.27, 44.70); at followup, only HDL-C showed significant intergroup differences ( H =13.10)(all P <0.05). Mixed effects linear regression model showed that after adjusting for confounding factors, vegetable intake was significantly negatively correlated with blood glucose levels among school aged children ( β=-0.03, 95%CI = -0.05 to -0.01, P <0.01). Conclusion Higher vegetable intake can independently reduce the risk of abnormal blood glucose in school aged children, which is of great significance for maintaining glucose metabolic health.

Amyotrophic lateral sclerosis (ALS) is an irreversible, fatal neurodegenerative disorder whose incidence is positively correlated with the aging population. ALS is characterized by the progressive loss of motor neurons, leading to muscle weakness, atrophy, and ultimately respiratory failure. The pathogenesis of ALS involves multiple factors, including genetic and environmental influences, with genetic factors playing a particularly significant role. To date, several causative genes have been identified in ALS, such as the Cu/Zn superoxide dismutase 1 (Cu/Zn SOD1, also known as SOD1) gene, transactive response DNA-binding protein 43 (TDP-43) gene, fused in sarcoma (FUS) gene, and chromosome open reading frame 72 (C9orf72). Mutations in these genes have been found not only in familial ALS but also in sporadic ALS. Based on the identified ALS risk genes, various ALS animal models have been established through multiple approaches, including transgenic models, gene knockout/knock-in models, and adeno-associated virus-mediated overexpression models. These models simulate some typical pathological features of human ALS, such as motor neuron loss, ubiquitinated inclusions, and neuromuscular junction degeneration. However, these models still have limitations: (1) single-gene mutation models are insufficient to fully replicate the complex multi-factorial pathogenesis of sporadic ALS; (2) significant differences in microenvironmental regulation mechanisms and the rate of neurodegeneration between model organisms and humans may affect the accurate reproduction of disease phenotypes and the reliable evaluation of drug efficacy. To better understand the pathogenesis of ALS and promote the development of effective therapies, constructing and optimizing ALS animal models is crucial. This review aims to summarize commonly used ALS gene mutation mouse models, analyze their phenotypes and pathological characteristics, including transgenic mouse models, gene knockout/knock-in mouse models, and adeno-associated virus-mediated overexpression mouse models, and further discuss their specific applications in ALS pathogenesis research and drug development by comparing the advantages and limitations of each model.

Amyotrophic lateral sclerosis (ALS) is an irreversible, fatal neurodegenerative disorder whose incidence is positively correlated with the aging population. ALS is characterized by the progressive loss of motor neurons, leading to muscle weakness, atrophy, and ultimately respiratory failure. The pathogenesis of ALS involves multiple factors, including genetic and environmental influences, with genetic factors playing a particularly significant role. To date, several causative genes have been identified in ALS, such as the Cu/Zn superoxide dismutase 1 (Cu/Zn SOD1, also known as SOD1) gene, transactive response DNA-binding protein 43 (TDP-43) gene, fused in sarcoma (FUS) gene, and chromosome open reading frame 72 (C9orf72). Mutations in these genes have been found not only in familial ALS but also in sporadic ALS. Based on the identified ALS risk genes, various ALS animal models have been established through multiple approaches, including transgenic models, gene knockout/knock-in models, and adeno-associated virus-mediated overexpression models. These models simulate some typical pathological features of human ALS, such as motor neuron loss, ubiquitinated inclusions, and neuromuscular junction degeneration. However, these models still have limitations: (1) single-gene mutation models are insufficient to fully replicate the complex multi-factorial pathogenesis of sporadic ALS; (2) significant differences in microenvironmental regulation mechanisms and the rate of neurodegeneration between model organisms and humans may affect the accurate reproduction of disease phenotypes and the reliable evaluation of drug efficacy. To better understand the pathogenesis of ALS and promote the development of effective therapies, constructing and optimizing ALS animal models is crucial. This review aims to summarize commonly used ALS gene mutation mouse models, analyze their phenotypes and pathological characteristics, including transgenic mouse models, gene knockout/knock-in mouse models, and adeno-associated virus-mediated overexpression mouse models, and further discuss their specific applications in ALS pathogenesis research and drug development by comparing the advantages and limitations of each model.

Objective To explore the effect of community pharmacy outpatient service on patients with type 2 diabetes mellitus. Methods A non-randomized controlled study was conducted, and type 2 diabetes patients managed in the community were divided into an intervention group of 112 cases and a control group of 110 cases. The control group received routine medication guidance during general practice outpatient visits, while the intervention group received comprehensive pharmacy outpatient service intervention based on routine medication guidance in general practice. Follow-up visits were conducted every 3 months. Repeated measurement analysis of variance and multivariate linear regression analysis were used to evaluate the intervention effect of the pharmacy outpatient service. Results Fasting blood glucose and glycosylated hemoglobin levels in the intervention group showed a decreasing trend with the increase of intervention time compared to pre-intervention time （P<0.01）, with increased duration of weekly exercise, decreased staple food intake, increased vegetable intake, and increased medication adherence score （P<0.01）. After adjusting for confounding factors through multivariate linear regression model, pharmacy outpatient intervention was found to be an independent protective factor for fasting blood glucose level （β=−0.891, P<0.01） and glycosylated hemoglobin level （β=−0.760, P<0.01） in the study subjects. Conclusion The community pharmacy outpatient service could enhance the self-management ability of patients with type 2 diabetes mellitus, and effectively improve patients’ fasting blood glucose and glycosylated hemoglobin.