Objective: To explore the influencing factors of anxiety symptoms and to construct a predictive model based on machine learning algorithms, so as to provide support for the prevention and management of anxiety symptoms among junior high school students. Methods: From April to May 2023, a stratified random cluster sampling method was adopted to select 8 176 junior high school students from Zhengzhou and Shangqiu citys. All participants completed the Adolescent Self rating Life Events Checklist, the 10item Connor-Davidson Resilience Scale, the School Connectedness Scale, the Parent-Child Cohesion Questionnaire, and the 7 item Generalized Anxiety Disorder Scale. Logistic regression analysis identified the associated factors of anxiety symptoms among junior high school students. Predictive models were constructed using Logistic regression, Random Forest, and eXtreme Gradient Boosting (XGBoost) algorithms, with SHapley Additive exPlanations analysis explaining the optimal model. Results: The detection rate of anxiety symptoms among junior high school students was 16.3%. Logistic regression analysis showed that junior high school students who were female ( OR =1.22), in the ninth grade ( OR =1.27), living in urban areas ( OR =1.37), having a father with a college education or above ( OR =1.26), having a mother with a senior high school education ( OR =1.26), and experiencing higher levels of negative life events ( OR =1.05) reported a higher risk of anxiety symptoms(all P <0.05). In contrast, those with moderate family economic status ( OR =0.71), moderate academic burden ( OR =0.59), low academic burden ( OR =0.54), moderate sleep quality ( OR =0.46), good sleep quality ( OR =0.26), excellent sleep quality ( OR =0.15), higher levels of psychological resilience ( OR =0.96), higher levels of school connectedness ( OR =0.96), and higher levels of parent-child cohesion ( OR =0.98) reported a lower risk of anxiety symptoms (all P <0.05). Three machine learning models demonstrated good predictive performance for anxiety symptoms among junior high school students (all AUC>0.8), with the XGBoost model achieving the best predictive performance. SHAP analysis revealed that negative life events, sleep quality, school connectedness, psychological resilience and parent-child cohesion were the top five relevant factors for predicting anxiety symptoms. Conclusions The detection rate of anxiety symptoms among junior high school students is relatively high. The XGBoost model is the optimal predictive model for anxiety symptoms in the population. Negative life events, sleep quality, school connectedness, psychological resilience, and parent-child cohesion are significant correlates of anxiety symptoms among junior high school students.

The application of immunosuppressants has significantly reduced the incidence rate of rejection reaction after liver transplantation， but the clinical efficacy of immunosuppressants is greatly affected by individual differences between patients. This article systematically reviews the recent research advances in the interaction between immunosuppressants and gut microbiota， with a focus on the regulatory role and mechanism of intestinal microflora communities on the efficacy of immunosuppressants. Studies have shown that intestinal microbiome is one of the key factors influencing the efficacy of immunosuppressive therapy after liver transplantation. This review aims to provide a theoretical basis for in-depth research in this field and provide new insights for developing individualized immunosuppressive treatment regimens based on the regulation of intestinal microflora.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Objective To evaluate the predictive value of neutrophil/high-density lipoprotein cholesterol ratio(NHR)combined with monocyte/lymphocyte ratio(MLR)for early rebleeding after endoscopic treatment in patients with cirrhosis complicated by acute esophagogastric variceal bleeding(AEVB).Methods A total of 228 patients with cirrhosis complicated by AEVB were included in this study.According to the occurrence of early rebleeding,patients were divided into the rebleeding group(96 cases)and the non-rebleeding group(132 cases).General information and laboratory indicators of both groups were collected,and the End-Stage Liver Disease(MELD)score,Child-Turcotte-Pugh(CTP)score,Fibrosis-4(FIB-4)index,NHR,and MLR were calculated.Logistic regression analysis was used to identify the risk factors for early rebleeding in patients with cirrhosis complicated by AEVB.A nomogram model based on NHR and MLR was constructed to predict the risk of early rebleeding.The predictive performance and goodness of fit of the model were evaluated using receiver operating characteristic(ROC)curve,Hosmer-Lemeshow test,Net Reclassification Index(NRI)and Integrated Discrimination Improvement(IDI).Results Compared with the non-rebleeding group,systolic blood pressure,platelet count(PLT),albumin/globulin ratio(A/G)and low-density lipoprotein cholesterol(LDL-C)were decreased in the rebleeding group,while total bile acids(TBA),aspartate aminotransferase(AST),alanine aminotransferase(ALT),total bilirubin(TBIL),activated partial thromboplastin time(APTT),thrombin time(TT),international normalized ratio(INR),Fibrosis-4(FIB-4),NHR,MLR,MELD score and CTP score were increased(P＜0.05).NHR was positively correlated with AST,TBIL and INR(P＜0.05).MLR was negatively correlated with PLT,and positively correlated with AST,TBIL and FIB-4(P＜0.05).Logistic regression analysis results showed that prolonged TT,elevated NHR and MLR were independent risk factors for early rebleeding in patients with cirrhosis complicated by AEVB.The nomogram model based on NHR and MLR to predict early rebleeding had an area under the curve of 0.810(95%CI:0.754-0.866).The Hosmer-Lemeshow test suggested that the model fit well.IDI and NRI analyse showed that the combination of NHR and MLR had better predictive value for the early rebleeding than that of MELD score and CTP score.Conclusion NHR and MLR are effective indicators for predicting early rebleeding after endoscopic treatment in patients with cirrhosis complicated by AEVB.They are helpful in the early identification of high-risk patients and provide a reference for clinical intervention.

Objective To investigate the spectrum-efficacy relationship between the fingerprint of green tea extract and its pharmacological effects in intervention of neovascular age-related macular degeneration(nAMD),explore the phar-macodynamic material basis,and identify key active components.Methods The fingerprint of green tea extract was es-tablished using UPLC-Q-Exactive Orbitrap MS.Hierarchical cluster analysis and orthogonal partial least squares discrimi-nant analysis were used to explore differences in chemical composition among green tea samples from different origins.A zebrafish nAMD model induced by cobalt chloride was established to evaluate the pharmacological activity of green tea ex-tract in nAMD intervention.Partial least squares regression analysis(PLSR)and grey relational analysis(GRA)were em-ployed to study the spectrum-efficacy correlation,comprehensively analyze the pharmacodynamic material basis of green tea in AMD intervention,and screen for key active components.Results A fingerprint detection method for green tea ex-tract was successfully established,and 31 chemical components were qualitatively and quantitatively characterized.Hierar-chical cluster analysis and orthogonal partial least squares discriminant analysis classified 50 batches of green tea samples into two major categories,identifying 15 key differential components.Pharmacological experiments demonstrated that green tea extract inhibited abnormal vascular growth in the zebrafish retina caused by cobalt chloride.Through PLSR and GRA,six components of green tea extract were found to be significantly correlated with pharmacological activity and showed high variable importance in projection:quinic acid,epicatechin,gallocatechin,epigallocatechin,gallocatechin gal-late,and epigallocatechin gallate.Conclusion This study comprehensively characterized 31 chemical components in green tea.Based on the nAMD zebrafish model and spectrum-effect correlation theory,PLSR and GRA analyses were ap-plied to accurately identify quinic acid,epicatechin,gallocatechin,epigallocatechin,gallocatechin gallate,and epigallocate-chin gallate as the key effective substances in green tea for intervening in nAMD.This provides a foundation for the devel-opment of new drugs with therapeutic potential against nAMD,and offers data support for establishing a comprehensive quality evaluation system for green tea.

Objective:To investigate the feasibility of segmented total marrow and lymphoid irradiation(TMLI)using Helical TomoTherapy(HT)in adults,and to analyze the impact of positional errors in the treatment on the actually received dose.Methods:Imaging data from four adult patients with acute myeloid leukemia were treated at the First Medical Center of the Chinese PLA General Hospital between November 2022 and December 2024 were retrospectively selected.The prescribed dose was 12 Gy in 3 fractions,and the heights range of patient was from 162 to 178 cm.The planning target volume(PTV)included the entire bone marrow and lymphatic drainage regions.The mid-femur was used as the dividing landmark,and the segmented location of head-in first(upper segmentation)and foot-in first(lower segmentation)were adopted to design plan for each segmentation.The upper segmentation used helical tomotherapy,and the lower segmentation used tomo direct therapy.The dosimetric parameters of planning target volume,and organ at risk(OAR)included eye lens,testicles and lungs were analyzed.The located computed tomography(CT)images of patients were used to simulate the changes of dosimetric parameters of each planning target region and OAR when the positions of patients moved 3,5,10 and 15 mm to outside of rack aperture.The changes of dose distribution of connection region of upper and lower segmentation were further analyzed.Results:The segmented irradiation technique can better achieve the cover(95%)of whole target region of TMLI under the condition of protecting normal organs.Under the condition with different position errors,the cover rate of the most of target region significant decreased.The largest dose of right lens increased 9.272%than primary under the 5 mm position error,and that of left and right lens increased respectively 40.199%and 67.898%under the 10 mm position error,and the max dose and mean dose of testicles increased respectively 5.847%and 5.240%under the 3mm position error.The mean dose of whole lung increased all under the error at different grades,which increased 3.021%under the 10mm position error.The non-uniformity of dose distribution of connection region increased after the position error was introduced,and the largest variation range reached to 4 Gy.Conclusion:The technique of segmented radiotherapy of Helical Tomotherapy has feasibility for TMLI of adult.But the error of the position of patients can reduce the cover of target region,and decrease the control rate for target region,and can lead to the occurrences of excessive doses on eye lens,testicles,lung and other OAR at the same time,which can increase the probability of occurring OAR injury.It should be high pay attention in treatment and implementation.

Objective:To analyze the prevalence of the Dabie bandavirus among rats in Taipusi Banner, Xilingol League, Inner Mongolia Autonomous Region.Methods:The cytochrome b gene for the identification of rat species was amplified. Real-Time RT-PCR and RT-PCR were used to amplify and sequence DBV positive rat tissues and detected by XilinGol League Center for Disease Control and Prevention, and the gene evolution was analyzed.Results:The rat was identified as Spermophilus dauricus. Through molecular detection on 20 samples, 15 samples showed positive result in Real Time RT-PCR nucleic acid test, and 7 samples showed positive result in RT-PCR nucleic acid test. Seven base sequences were obtained through sequencing, and they were compared with those in the National Center for Biotechnology Information (NCBI) of the United States by BLAST. It was determined that they were the S gene sequences of DBV. It has been uploaded to GenBank with serial numbers PV231886, PV231887 and PV231888.Conclusions:DBV was detected for the first time in the mice of Inner Mongolia Autonomous Region. In future work, monitoring of DBV carried by rodents and ectoparasites such as ticks and fleas in this area should be strengthened. Publicity and education on severe fever with thrombocytopenia syndrome should be carried out in this area to improve the local medical system′s ability to identify such cases, ensuring early detection, early diagnosis, and early treatment, and reducing the occurrence of human cases and clustered outbreaks.

Objective:To evaluate the outcomes of intensive conservative treatment compared to conventional conservative treatment in patients with acute aortic syndrome(AAS).Methods:The study prospectively enrolled consecutive patients with AAS who were admitted to Beijing Anzhen Hospital, affiliated with Capital Medical University, and Beijing Dawanglu Emergency Rescue Hospital from January 2024 to December 2024. These patients with surgical contraindications or refused surgery for various reasons opted for conservative treatment. A total of 282 patients were included, and 15 patients with missing data or those who died without any treatment were excluded. Finally, 267 patients were enrolled, of whom 94 received intensive conservative treatment, and 173 received conventional conservative treatment, the inverse probability of treatment weighting (IPTW) was used to reduce the influence of confoundings. After adjusting of baseline datas via IPTW, the survival outcomes of the two groups were compared at 14 days, 30 days, and at the end of follow-up.Results:The results showed significant differences in acute phase survival rates between the enhanced conservative treatment group and the conventional conservative treatment group at 14 days(82.40%vs.53.20%, P<0.0001). Significant survival differences were also observed at 30 days and at 276-day mid-term follow-up (96.29% vs.51.60%, P<0.0001; 78.50% vs.48.50%, P<0.0001). In the subgroup analysis, for type A aortic dissection, the enhanced conservative treatment group had higher survival rates compared to the conventional conservative treatment group at 14, 30 and 276 days (63.46% vs.41.35%, P<0.05; 52.17% vs.37.90%, P<0.05; 50.00% vs. 31.97%, P<0.05). However, for type B aortic dissection, although the enhanced conservative treatment group had higher survival rates than the conventional conservative treatment group, no statistically significant differences were observed (96.29% vs. 80.00%, P=0.054; 95.65% vs.78.37%, P=0.067; 94.12% vs.74.20%, P=0.088). Conclusion:For patients diagnosed with AAS are forced to choose conservative treatment if emergency surgery is not possible in the first place, intensive conservative treatment strategies can significantly reduce the mortality in the acute phase compared with conventional conservative treatment. Mid-term follow-up, intensive conservative treatment still has a significant survival advantage.

Objective:To investigate the clinical characteristics of cervical adenocarcinoma and analyze the survival status and related prognostic factors.Methods:The data of 229 patients with cervical adenocarcinoma who were diagnosed pathologically in the General Hospital of Ningxia Medical University from January 2013 to October 2022 were retrospectively analyzed. Among them, 198 early stage patients were mainly treated with surgery, and 31 locally advanced stage patients were mainly treated with chemoradiotherapy. The overall survival (OS) and progression-free survival (PFS) rates in the whole cohort of patients and different treatment subgroups were calculated. Kaplan‐Meier method and log‐rank test were used for survival analysis, and Cox proportional hazards model was used for univariate and multivariate survival analyses.Results:Among the 229 patients, there were 11 subtypes of pathological classifications, predominantly of the usual‐type. At the end of follow‐up, 57 patients (24.9%) relapsed. The 3‐ and 5‐year OS rates were 86.4% and 79.3%, respectively, and the 3‐ and 5‐year PFS rates were 81.6% and 73.6%, respectively. Multivariate analysis showed that International Federation of Gynecology and Obstetrics (FIGO) staging of stages Ⅲ‐Ⅳ was an independent prognostic factor for OS and PFS ( HR=2.033, 95% CI=1.456‐2.839, P<0.001; HR=1.701, 95% CI=1.251‐2.313, P=0.001). Lymph node metastasis was an independent risk factor for PFS ( HR=1.610,95% CI=1.021‐2.539, P=0.041). Subgroup analysis of 198 patients with surgical treatment: the 3‐ and 5‐year OS rates were 90.0% and 84.9%, and the 3‐ and 5‐year PFS rates were 82.7% and 76.7%, respectively. Multivariate analysis showed that lymph node metastasis and deep invasion depth were the main risk factors for OS ( HR=6.893, 95% CI=2.592‐18.327, P<0.001; HR=1.952, 95% CI=1.164‐3.272, P=0.011) and PFS ( HR=5.507, 95% CI=2.569‐11.805, P<0.001; HR=1.638, 95% CI=1.09‐2.461, P=0.018). Ovarian preservation was an independent risk factor for PFS ( HR=3.364, 95% CI=1.115‐10.151, P=0.031). Conclusions:The pathological types of cervical adenocarcinoma are complex and diverse. Local recurrence and distant metastasis are the main reasons for treatment failure. FIGO stage, lymph node metastasis and postoperative depth of invasion are the main prognostic factors of cervical adenocarcinoma.

Artificial intelligence(AI)is reconstructing drug quality control systems with unprecedented depth.With the rapid development of the traditional Chinese medicine(TCM)industry,the quality regulation of TCM has garnered increasing attention.The efficacy and safety of TCM directly impact public health,making it imperative to enhance the scientific rigor and effectiveness of its quality control.In recent years,the application of AI technology has expanded across various fields,and its potential in TCM quality regulation has gradually been recognized.Cur-rently,AI has demonstrated advantages in multiple stages of TCM production,including cultivation and planting,authenticity identification of decoction pieces,compliance review of manufacturing processes,market circulation monitoring,and risk assessment.However,despite existing research achievements,challenges such as limited technological adoption,low standardization,and insufficient data sharing persist.This paper provides an in-depth review of innovative AI applications in TCM quality control,comprehensively analyzes their effectiveness and future prospects,and proposes a novel"AI-Digital Sensory-Blockchain"tri-synergistic quality control paradigm based on domestic and international research advancements.Furthermore,it explores potential future research directions to advance the modernization of TCM quality regulation,thereby achieving higher levels of safety assurance and scien-tifically robust supervision.