Objective: To understand the current status of psychological sub health among secondary vocational school students and explore its related factors, so as to provide a scientific basis for improving their mental health. Methods: From September to December 2024, a convenience sampling method was used to conduct a questionnaire survey among 5 141 secondary vocational school students from 16 schools across 8 provinces and municipalities (Fujian, Chongqing, Guangdong, Guangxi, Hubei, Jiangxi, Shanghai, Zhejiang). A self designed questionnaire was used to collect data on students demographic characteristics and lifestyle behaviors. The Multidimensional Sub health Questionnaire of Adolescents was adopted to assess psychological sub health status. Multivariate binary Logistic stepwise regression analysis was performed to explore the related factors of psychological sub health among secondary vocational school students. Results: The detection rate of psychological sub health among secondary vocational school students was 11.0%, with detection rates of emotional problems, conduct problems, and social adaptation difficulty being 12.3 %, 12.5%, and 9.5%, respectively. Logistic regression analysis revealed that boys and students whose fathers had an educational level of primary school or below, and junior high school, had relatively lower risks of developing psychological sub health or emotional problems, conduct problems, and social adaptation difficulty ( OR =0.55-0.64, all P <0.05). Conversely, students with urban household registration, those with left behind experience, those with poor self rated family economic status, those from other family structures, those classified as overweight and obesity, and those with sleep disorders, frequent consumption of sugar sweetened beverages, frequent consumption of takeout/delivery food, smoking, alcohol consumption, and low to moderate physical activity levels exhibited significantly higher risks across psychological sub health or emotional problems,conduct problems, and social adaptation difficulty ( OR =1.25-4.79, all P <0.05). Conclusions The psychological sub health condition of secondary vocational school students should not be neglected. Psychological sub health of secondary vocational school students is related to multiple factors such as demographic characteristics and lifestyle behaviors. Multi dimensional intervention measures should be implemented to improve their mental health.

ObjectiveThis paper aims to investigate and evaluate the staged efficacy and safety of the representative empirical prescription of the “Zhu Ke Jiao” theory， Qijia Rougan prescription， combined with entecavir in the treatment of hepatic fibrosis in chronic hepatitis B. MethodsA multicenter randomized controlled clinical study was conducted， and 101 patients diagnosed with chronic hepatitis B-related hepatic fibrosis （CHB-HF） who met the diagnosis and inclusion criteria were randomly assigned to an observation group （Qijia Rougan prescription + entecavir） and a control group （entecavir）. The treatment duration was 24 weeks. Liver stiffness measurement （LSM）， fibrosis-4 index （FIB-4）， portal vein diameter， hepatitis B serology， biochemical indicators， hepatic fibrosis markers in serum ［hyaluronic acid （HA）， laminin （LN）， procollagen Ⅲ peptide （PⅢP）， and type Ⅳ collagen （Ⅳ-C）］， and traditional Chinese medicine syndrome scores were used as efficacy evaluation indicators. Efficacy assessments and explorations of different staged subgroups of Qijia Rougan prescription were conducted according to LSM values based on the Metavir pathological staging standard. ResultsA total of 98 cases were included for statistical analysis， with 49 cases in the observation group and 49 in the control group. The general data of the patients in both groups were comparable. Compared with the same group before treatment， the observation group showed a significant reduction in LSM and FIB-4 （P<0.01）， as well as notable improvements in LN， Ⅳ-C， and various TCM syndrome scores （P<0.05， P<0.01）. When compared to the control group after treatment， the observation group demonstrated significant improvements in LSM， FIB-4， and various TCM syndrome score indicators （P<0.05， P<0.01）， indicating that the observation group performed better than the control group. Subgroup analysis of the regression of hepatic fibrosis stages showed that compared to the same group before treatment， the observation group had better improvement in regression of stages F2 and F3 （P<0.05）. When compared to the control group after treatment， the observation group exhibited superior improvement in regression of stage F3 （P<0.05）. No adverse events occurred in either group during the treatment period. ConclusionCompared with entecavir alone， the combination of Qijia Rougan prescription and entecavir significantly improves the degree of hepatic fibrosis and clinical TCM symptoms in patients. The optimal intervention period is primarily during stage F3， which is a potential “interception” point of the “Zhu Ke Jiao” theory.

Chronic liver diseases are a group of diseases in which the liver is subjected to a variety of injuries over a long period of time， resulting in irreversible pathological changes that last longer than 6 months. Emodin （EMO） is a natural anthraquinone derivative derived from Rheum officinale， and its pharmacological effect has been extensively studied， exhibiting a variety of biological properties and involving multiple signaling molecules and pathways. Western medicine or surgical treatment is currently the main treatment regimen for chronic liver diseases， and the advance in treatment is limited by various reasons such as side effects and high costs. Due to its natural origin and efficacy， EMO has unique advantages in the treatment of chronic liver diseases and has now become a research hotspot. This article summarizes the therapeutic effect of EMO on chronic liver diseases and its mechanism， in order to provide a certain scientific basis for the traditional Chinese medicine treatment of chronic liver diseases and the development of drugs in clinical practice.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

Background/Aims: Cholangiocarcinoma (CCA) is a primary malignant neoplasm with an extremely poor prognosis. While combined chemoradiotherapy has been demonstrated to delay CCA progression to a certain extent, the absence of specific molecular biomarkers or targets significantly hinders the diagnosis and treatment of CCA. Methods: Through cross-analysis of proteomics and ADMA modificationomics, we identified DDX1 overexpressed in CCA with elevated R602-ADMA modifications. HPLC-MS/MS identified PRMT1 as the methyltransferase and USP10 as the deubiquitinating enzyme for DDX1. Immunofluorescence and nuclear-cytoplasmic partitioning experiments confirmed DDX1’s nuclear localization. GO and KEGG analyses clarify the biological functions of DDX1 in response to hypoxia. RNA-seq transcriptomics analyzed key pathways influenced by DDX1. A hydrodynamic in situ CCA mouse model was established to validate the chemopreventive effects of the PRMT1-specific inhibitor GSK715 on CCA development. Results: DDX1 promotes CCA progression both in vivo and in vitro and can be inhibited by GSK715. Mechanistically, PRMT1 mediates ADMA modification at position R602 of DDX1. This modification promotes DDX1 nuclear localization by recruiting USP10 to deubiquitinate DDX1, while simultaneously inhibiting PRMT1 degradation. DDX1 promotes the transcription of PRMT1 and USP10 by binding to the mRNA 3’UTR region, establishing a positive feedback regulatory pathway. This mechanism promotes the occurrence and development of CCA and can serve as a target for the inhibitor GSK715 to suppress CCA progression. Conclusions Our study identified DDX1-R602-ADMA modification as a novel ADMA modification in CCA. It further confirmed its pivotal role in CCA progression. Targeting the USP10-PRMT1-DDX1 axis may represent a significant therapeutic approach for CCA.

Objective To compare the long-term survival outcomes of patients with T_1-2N₀M₀ duodenal neuroendocrine tumor (DNET) after endoscopic resection (ER) or surgical resection (SR). Methods Patients diagnosed with T_1-2N₀M₀ DNET between January 1, 2004, and December 31, 2015, were extracted from the SEER database. Kaplan-Meier survival curve and log-rank test were used to compare overall survival (OS) rate and cancer-specific survival (CSS) rate between patients undergoing ER or SR. Propensity score matching (PSM) was used to reduce grouping differences, and multivariate Cox regression was used to analyze factors affecting OS and CSS before and after PSM. Results A total of 656 patients were included, with 457 in ER group and 199 in SR group. Before PSM, there was no significant difference in the 5-year OS rate between the ER and SR groups (88.9% vs 89.6%), but there was a significant difference in the 5-year CSS rate (99.3% vs 96.9%, P＝0.017). Before PSM, multivariate Cox regression analysis showed advanced age was an independent risk factor for decreased OS (P＜0.001). After PSM, there was no significant difference between the ER group (n＝187) and SR group (n＝187) in 5-year OS rate (90.2% vs 88.9%) or CSS rate (98.9% vs 96.7%). After PSM, multivariate Cox regression also showed advanced age was an independent risk factor for decreased OS, while resection method was not an independent factor for OS or CSS. Conclusions There is no significant difference in OS or CSS after endoscopic treatment and surgical treatments for patients with T_1-2N₀M₀ DNET, and advanced age is an independent factor for OS.

Objective:To analyze the dynamic changes of serum exosome miR-552 and miR-653 levels in pa-tients with gastric cancer before and after chemotherapy and their relationship with clinical benefit.Methods:IA total of 128 patients with gastric cancer received chemotherapy from January 2022 to January 2024.According to the chemo-therapy effect,the two groups were divided into disease progression group and disease remission group.The levels of serum exosome miR-552 and miR-653 before and after chemotherapy were detected in the two groups,the risk fac-tors affecting the chemotherapy effect of gastric cancer patients were screened,the risk nomogram model was con-structed,and the efficacy was evaluated.Results:The proportion of TNM stage(Ⅲ+Ⅳ),lymph node metastasis,dis-tant metastasis,tumor size(>5 cm),invasion depth(T3/T4)and tumor growth pattern(invasive type)in disease progres-sion group was higher than that in disease remission group(P<0.05).The levels of serum exosomes miR-552 and miR-653 in disease progression group were higher than those in remission group before and after chemotherapy(P<0.05).Compared with before chemotherapy,miR-552 and miR-653 levels in both groups decreased(P<0.05).Logistic regres-sion analysis showed that TNM stage,lymph node metastasis,distant metastasis,tumor size,invasion depth,miR-552 and miR-653 were all risk factors affecting the chemotherapy efficacy of gastric cancer(P<0.05).ROC curve results showed that the AUC,95%CI,sensitivity and specificity of risk nomogram model to predict chemotherapy efficacy of gastric cancer were 0.867,0.672～0.991,92.80%and 80.40%,respectively(P<0.001).Calibration curve results showed that both predicted and actual predicted values were near the ideal curve,and the Hosmer-Lemeshow goodness of fit curve test χ2=1.869,P=0.782.Conclusion:The levels of serum exosomes miR-552 and miR-653 are closely related to the chemotherapy efficacy of gastric cancer,and dynamic monitoring of the above indexes is helpful for the evaluation of the disease and prognosis of gastric cancer.In this study,the risk nomogram model constructed based on the above indexes and other risk factors has high predictive value and clinical practicability for chemotherapy efficacy in patients with gastric cancer.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.

Objective To explore the brain damage of SD rats under different time points of hypobaric hypoxia exposure.Methods A rat high-altitube cerebral edema(HACE)model was constructed by simulating an altitude of 6 000 m in a hypobaric hypoxia animal experimental chamber.Thirty-six SD male rats were randomly divided into the control group and the hypobaric hypoxia exposure 3,7 and 14 d groups,with 9 rats in each group.Except for the control group,the rats in each group were continuously exposed to hypobaric hypoxia for 3,7,and 14 d.At the end of the modeling period,serum was collected by blood sampling via the abdominal aorta,and brain tissue samples were taken.The wet-to-dry ratio(W/D)of brain tissue was calculated,and the levels of relevant oxidative enzymes in serum and brain tissue were measured.The expression levels of hypoxia-inducible factor-1α(HIF-1α)and aquaporin 4(AQP4)mRNAs in brain tissue were detected by real-time fluorescence quantitative polymerase chain reaction.Results The W/D of brain tissues in the control group and the group exposed to hypobaric hypoxia for 3,7 and 14 d were 4.46±0.12,4.98±0.16,5.07±0.18 and 4.95±0.07;the superoxide dismutase contents were(111.86±2.45),(90.73±1.48),(79.64±2.56)and(55.33±1.45)U·g-1;the glutathione contents were(126.91±5.18),(125.26±1.53),(56.20±2.17)and(122.73±1.78)μg·mL-1;the malondialdehyde contents were(230.94±2.00),(362.65±3.28),(407.34±3.47)and(237.50±1.59)nmol·g-1;the relative expression levels of HIF-1 α mRNA were 1.00±0,2.99±0.49,4.72±0.49 and 1.91±0.28;the relative expression levels of AQP4 mRNA were 1.00±0,2.62±0.34,8.38±0.84 and 5.27±0.42,respectively.Statistically significant differences were found between the above indexes in the 3,7 and 14 d of hypobaric hypoxia exposure group compared with the control group(P＜0.05,P＜0.01).Conclusion Different time of hypobaric hypoxia exposure can up-regulate the expression of AQPs proteins in HACE rats and cause the disruption of the blood-brain barrier,and the HACE model constructed in the hypobaric hypoxia chamber with 6 000 m intervention for 7 d was more stable.

Objective To compare and find an optimal model for predicting the risk of DKD occurrence in patients with type 2 diabetes mellitus(T2DM).Methods A total of 2005 patients with T2DM were enrolled in this study from The Second Hospital of Shijiazhuang City during December 2017 to December 2022.All the subjects were divided into a training set(n=1403)and a validation set(n=602)according to the ratio of 3∶1 by simple random sampling.With the occurrence of DKD as the outcome variablein the training set,important feature variables were screened by LASSO regression.Six different machine learning models were established according to the feature variables,thenthe optimal model was determined by comparison,and anonlinerisk predictor for DKD occurrence was constructed in patients with T2DM.Results Taking the occurrence of DKD as the outcome variable in the training set,the results of LASSO regression analysis showed that the optimal value of the model was 10-fold cross validation lambda.1se=0.01662473,and 15 characteristic variables with nonzero coefficient were screened out to be related to the occurrence of DKD.The data included sex,age,family history of DM,DM duration,LDL-C,HbA1c,WBC,PDW,Scr,urine α1-microglobulin,urine β2-microglobulin,urine microalbumin,hypertension,hypokalemia,and DR.In the training set and validation set,the prediction performance of XGBoost model was better than that of other models(AUC=0.872,0.893,95%CI 0.853～0.891,0.865～0.921),the sensitivity was 0.779,0.863,and the specificity was 0.721,0.758,respectively.The F1 scores were 0.774 and 0.787.DCA analysis showed that the XGBoost model had a greater net benefit and threshold probability.According to the XGBoost model,the online predictor of DKD risk in T2DM patients was laid out,and two patients were selected for application,the results showed that the predictive value of the model was 0.185 in non-DKD patients,and the predictive value was 0.510 in DKD patients.Conclusions The XGBoost model is the best model for predicting the occurrence of DKD in T2DM patients,and an online predictor was successfully built.