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 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 key genetic mutations during the progressive disease (PD) /leukemic transformation (LT) course in MDS by analyzing the dynamic changes of genetic mutations in patients with myelodysplastic neoplasms (MDS) with or without PD/LT.Methods:This study enrolled 84 patients with sequential MDS from May 2019 to August 2023 at ZhongDa Hospital Southeast University and used the next generation sequencing to detect gene mutations. The dynamic changes of genetic mutations in patients with MDS with or without PD/LT were retrospectively analyzed.Results:①This study analyzed data from 84 patients diagnosed with MDS with a median age of 63 (range: 31-95) years and consisting of 51 males and 33 females. Participants were distributed to the PD cohort ( n=20), LT cohort ( n=13), and non-PD/LT cohort ( n=51). Patients from the PD/LT cohorts demonstrated a higher proportion of bone marrow blasts than the non-PD/LT cohort at the first sequencing (1.6% vs. 0.4%, P=0.013). ②The most frequently mutated genes that were detected at first sequencing were ASXL1 ( n=21, 25.0%), TP53 ( n=17, 20.2%), TET2 ( n=12, 14.3%), DNMT3A ( n=11, 13.1%), and U2AF1 ( n=11, 13.1%). Further, patients from the PD/LT cohorts exhibited a higher median number of mutated genes than the non-PD/LT cohort (2 vs.1, P=0.014) at first sequencing. TET2 (27.3% vs. 5.9%, P=0.010), SETBP1 (15.2% vs.2.0%, P=0.033), and RUNX1 (18.2% vs. 2.0%, P=0.013) mutations were enriched in the PD/LT cohorts than in the non-PD/LT cohort. ③The most frequently detected acquired mutations (Ⅰ mutations) and clonally expanded mutations (Ⅱ mutations) were TP53 ( n=9, 10.7%), TET2 ( n=7, 8.3%), ASXL1 ( n=7, 8.3%), and RAS pathway ( n=7, 8.3%). Furthermore, patients from the PD/LT cohorts showed a higher median number of Ⅰ/Ⅱ genes than the non-PD/LT cohort (2 vs. 0, P<0.001), and Ⅰ/Ⅱ RAS pathway (21.2% vs. 0, P=0.001), TP53 (27.3% vs. 0, P<0.001), and TET2 (18.2% vs. 2.0%, P=0.013) mutations were enriched in PD/LT cohorts than in the non-PD/LT cohorts. ④Most of the TP53 mutations (9/12, 75.0%) in PD/LT cohorts were Ⅰ/Ⅱ mutations, whereas all of the TP53 mutations in non-PD/LT cohort were clone-decrease mutations (Ⅲ mutations) (5/8, 62.5%) or clone-stable mutations (Ⅳ mutations) (3/8, 37.5%). Most of the RAS pathway mutations (7/8,87.5%) in the PD/LT cohorts were Ⅰ/Ⅱ mutations, whereas only one patient in the non-PD/LT cohort demonstrated RAS pathway mutations, which belonged to Ⅳ mutations. Conclusion:Patients from the PD/LT cohorts demonstrated a higher proportion of bone marrow blasts and a higher median number of mutations than the non-PD/LT cohort at first sequencing; TET2, SETBP1, and RUNX1 mutations were enriched in the PD/LT cohorts than in the non-PD/LT cohort at first sequencing. Patients from the PD/LT cohorts exhibited a higher number of Ⅰ/Ⅱ mutations than the non-PD/LT cohort. Further, Ⅰ/Ⅱ TP53, RAS pathway, and TET2 mutations were enriched in the PD/LT cohorts, and Ⅰ/Ⅱ TP53 and RAS pathway mutations may contribute to the PD/LT.

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.

Digital technologies have become an integral part of complete denture restoration. With advancement in computer-aided design and computer-aided manufacturing (CAD/CAM), tools such as intraoral scanning, facial scanning, 3D printing, and numerical control machining are reshaping the workflow of complete denture restoration. Unlike conventional methods that rely heavily on clinical experience and manual techniques, digital technologies offer greater precision, predictability, and efficacy. They also streamline the process by reducing the number of patient visits and improving overall comfort. Despite these improvements, the clinical application of digital complete denture restoration still faces challenges that require further standardization. The major issues include appropriate case selection, establishing consistent digital workflows, and evaluating long-term outcomes. To address these challenges and provide clinical guidance for practitioners, this expert consensus outlines the principles, advantages, and limitations of digital complete denture technology. The aim of this review was to offer practical recommendations on indications, clinical procedures and precautions, evaluation metrics, and outcome assessment to support digital restoration of complete denture in clinical practice.
Humans ; Denture, Complete ; Computer-Aided Design ; Denture Design/methods* ; Consensus ; Printing, Three-Dimensional

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.