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.

BACKGROUND:Various proteins,signaling pathways,and inflammatory mediators are involved in the pathophysiological process of osteoarthritis.The development of small molecule drugs targeting these proteins,signaling pathways,and inflammatory mediators can effectively delay the progression of osteoarthritis and ameliorate its clinical manifestations. OBJECTIVE:To review the research progress of small molecule drugs in the treatment of osteoarthritis based on the pathogenesis of osteoarthritis. METHODS:PubMed,CNKI,and WanFang databases were searched with English search terms"osteoarthritis,arthritis,osteoarthrosis,degenerative,arthritides,deformans,small molecule drugs,small molecule inhibitors,small molecule agents"and Chinese search terms"osteoarthritis,small molecule drugs,small molecule inhibitors."A total of 68 articles were included for review according to the inclusion and exclusion criteria. RESULTS AND CONCLUSION:(1)Currently,studies concerning the pathogenesis of osteoarthritis remain unclear.The occurrence and development of osteoarthritis are strongly associated with proteins,cytokines,and signal transduction pathways,so its therapeutic mechanism is relatively complex.Currently,targeting proteins,cytokines,and signal transduction pathways related to osteoarthritis with small molecule drugs has become a major research focus.(2)Small molecule drugs frequently possess visible intracellular or extracellular targets and efficacy,containing enhancing cartilage repair,resisting joint degradation,attenuating inflammation,and relieving pain.Other anti-osteoarthritis small molecule drugs have shown promise in promoting stem cell chondrogenic differentiation and cartilage matrix reconstruction.(3)At present,small molecule drugs targeting the pathophysiological process of osteoarthritis to delay the progression of osteoarthritis are still in the experimental stage,but most of these small molecule drugs have shown the expected results in the experimental process,and there are no relevant studies to illustrate the efficacy of small molecule drugs in the treatment of osteoarthritis.(4)Small molecule drugs for the treatment of osteoarthritis have reached the expected experimental results in the basic experimental stage.Numerous studies have exhibited that small molecule drugs can target the suppression of specific proteins,cytokines,and signal transduction pathways that cause osteoarthritis,so as to treat osteoarthritis.Nevertheless,its safety and effectiveness still need to be identified by further basic and clinical studies.This process needs to be investigated and studied by more scholars.(5)At present,many scholars in and outside China have made contributions to the treatment of osteoarthritis.Compared with traditional treatment methods,small molecule drugs reveal better efficacy and safety in the basic experimental stage,and it is expected to become an emerging method for the treatment of osteoarthritis in the future to rid patients of pain.

AIM:To analyze differential proteins associated with the pathogenesis of dry eye(DE)using bioinformatics methods, in order to reveal their potential molecular mechanisms.METHODS: Articles published in PubMed and EMBASE databases from the inception of the database to August 31, 2023, that used proteomic methods to detect protein expression in clinical samples of dry eye were searched. Differential proteins were selected and further analyzed using the STRING database and Cytoscape software for hub gene screening and module analysis. Protein-protein interaction(PPI)analysis, gene ontology(GO)functional annotation, and Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis were performed.RESULTS: A total of 21 articles were included, identifying 74 differentially expressed proteins. The most frequently occurring differential proteins were calgranulin A(SA1008), lipocalin-1(LCN1), lysozyme C(LYZ), mammaglobin-B(SCGB2A1), proline-rich protein 4(PRR4), transferrin(TF), and calgranulinB(S100A9). The top 10 hub genes were serum albumin(ALB), tumor necrosis factor(TNF), interleukin 6(IL6), IL1B, IL8, matrix metalloproteinase 9(MMP9), alpha-1-antitrypsin(SERPINA1), IL10, complement component 3(C3), and lactotransferrin(LTF). Module analysis suggested MMP9 and PRR4 as seed genes. KEGG analysis showed that differential proteins were mainly enriched in the IL17 signaling pathway(61.9%).CONCLUSION: The results reveal potential molecular targets and pathways for DE and confirm the association between the pathogenesis of DE and inflammation. Further in-depth research is needed to confirm the significance of these biomarkers in clinical practice.

ObjectiveTo investigate the effect of 1，25（OH）₂D₃ on the level of peroxisome proliferator-activated receptor-γ （PPAR-γ） in the liver， the phenotype of hepatic macrophages， and liver inflammation in a rat model of nonalcoholic steatohepatitis （NASH）， as well as the mechanism of 1，25（OH）₂D₃ improving liver inflammation. MethodsAfter 1 week of adaptive feeding， 24 specific pathogen-free Wistar rats were randomly divided into normal group ［choline-supplemented L-amino acid-defined （CSAA） diet］， normal+1，25（OH）₂D₃ group ［CSAA diet+1，25（OH）₂D₃］， model group ［choline-deficient L-amino acid-defined diet （CDAA） diet］， and model+1，25（OH）₂D₃ group ［CDAA diet+1，25（OH）₂D₃］， with 6 rats in each group. The dose of 1，25（OH）₂D₃ was 5 μg/kg for intraperitoneal injection twice a week for 12 weeks. The serum levels of aspartate aminotransferase （AST） and alanine aminotransferase （ALT） were measured， liver histopathology was observed， and SAF score was assessed. M1 hepatic macrophages and M2 hepatic macrophages were measured to analyze in the change in the phenotype of hepatic macrophages， and ELISA was used to measure the levels of tumor necrosis factor-α （TNF-α）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， and interleukin-10 （IL-10） in liver tissue， and qPCR was used to measure the mRNA level of PPAR-γ. The two-factor analysis of variance was use for comparison between groups， and the least significant difference t-test was used for further comparison； the Pearson method was used for correlation analysis. ResultsCompared with the normal group， the model rats with CDAA diet-induced NASH had significant increases in the serum levels of AST and ALT （P=0.019 and P<0.001）， the SAF score of liver histopathology （P<0.001）， the level of M1 hepatic macrophages （P<0.001）， and the ratio of M1 and M2 hepatic macrophages （P<0.001）， as well as a significant increase in the level of TNF-α （P<0.001） and a significant reduction in the level of IL-4 in liver tissue （P=0.025）. The 1，25（OH）₂D₃ group had significant reductions in the serum levels of ALT （P<0.001）， the SAF score of liver histopathology （P<0.001）， the level of M1 hepatic macrophages （P<0.001）， and the ratio of M1 and M2 hepatic macrophages （P=0.001）， the level of IL-1β （P<0.001） and a significant increase in the level of M2 hepatic macrophages （P=0.017）， the level of IL-10 （P=0.039）， the level of IL-4 （P<0.001）， the level of PPAR-γ （P=0.016）. There were significant interactions between CDAA diet-induced NASH model and 1，25（OH）₂D₃ in serum the levels of AST and ALT （P=0.007 and P=0.008）， the SAF scores of liver histopathology （P<0.001）， the level of M1 hepatic macrophages （P<0.001）， the level of M2 hepatic macrophages （P=0.008）， the ratio of M1 and M2 of hepatic macrophages （P=0.005）， the level of TNF-α （P<0.001）， the level of IL-10 （P=0.038）， the level of IL-4 （P<0.001） and the level of PPAR-γ （P=0.009）. The correlation analysis showed that PPAR-γ was negatively correlated with the ratio of M1 and M2 hepatic macrophages （r=-0.415， P=0.044） and was positively correlated with M2 hepatic macrophages （r=0.435， P=0.033）， IL-10 （r=0.433， P=0.035）， and IL-4 （r=0.532， P=0.007）. ConclusionThis study shows that 1，25（OH）₂D₃ improves liver inflammation in NASH by activating PPAR-γ to regulate the phenotypic transformation of hepatic macrophages.

Objective: To investigate the efficacy and safety of intelligent temperature-pressure-controlled flexible ureteroscopy combined with negative-pressure suction sheath lithotripsy in the treatment of upper urinary tract stones ≤2.5 cm. Methods: The clinical data of 225 patients with ≤2.5 cm upper urinary tract stones treated with this surgical method in our department during Aug. 2023 and Jul. 2024 were retrospectively analyzed. The patients were divided into the dual-control group (n=36) and conventional group (n=189) according to whether or not the intelligent temperature and pressure control device was used during operation. In the dual-control group，the intraoperative temperature and pressure in the renal pelvis were monitored and controlled in real time by the temperature and pressure sensors distributed at the end of the ureteral soft lens. The perioperative parameters，stone-removal rate，complication rate and renal function were compared between the two groups. Results: All operations were successfully completed in both groups. The postoperative procalcitonin (PCT) level [(22.75±5.85) ng/L vs. (29.08±6.60) ng/L，P=0.001]，difference in the white blood cell (WBC) level [(0.24±2.12)×10 cells/L vs. (1.19±2.17)×10 cells/L，P=0.016]，incidence of fever (2.8% vs. 16.9%，P=0.028) and overall complication rate (5.6% vs. 19.6%，P=0.042) were significantly lower in the dual-control group than in the conventional group，while the stone-clearance rate was slightly higher (88.9% vs. 82.5%，P=0.346)，with no significant difference. Conclusion: For upper urinary tract stones ≤2.5 cm，intelligent temperature-pressure-controlled ureteroscopy combined with negative-pressure suction sheath lithotripsy has a satisfactory stone-removal rate and a low rate of complications，which is worthy of clinical promotion.

Objective To analyze the risk factors associated with the occurrence of rectal neuroendocrine tumors (RNETs) and construct a risk prediction model. Methods Clinical data of patients who underwent electronic colonoscopy were collected. The clinical information on patients with and without RNETs were compared, and potential risk factors for RNETs were identified. Binary logistic regression was performed to analyze the relevant risk factors and construct a risk prediction model. Results Among 164 patients, 66 were diagnosed with RNETs, and 98 who did not have such a condition were randomly selected. Univariate logistic regression analysis revealed that age, fatty liver, anxiety and depression, total cholesterol, triglyceride levels, and carcinoembryonic antigen (CEA) were significant factors influencing the occurrence of RNETs (P<0.05). Multivariate logistic regression analysis identified age (P=0.015), anxiety and depression (P=0.031), cholesterol level (P=0.009), fatty liver (P=0.001), and CEA (P<0.001) as independent risk factors for RNETs. The participants were randomly divided into training and test sets at a 7:3 ratio. The training set was used to construct a nomogram-based risk prediction model, and the testing set was used for internal validation. The area under the curve values for the training and testing sets were 0.843 and 0.772, respectively (P>0.05). These findings indicate a good discriminative performance. The calibration curves for the training and testing sets were in good agreement with the 45° standard line, which suggests that the predicted probabilities were consistent with the actual outcomes. Decision curve analysis showed that the model provided a high net benefit within a threshold range of 0.2 to 0.7 for clinical decision making. Conclusion Young age, fatty liver, high CEA levels, high cholesterol levels, and anxiety and depression are independent risk factors for RNETs. The nomogram model constructed based on these risk factors exhibits a strong capability to predict the occurrence of RNETs, and clinical intervention can be considered based on the predicted probability values.

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

Objective:To investigate the predictive value of telomerase reverse transcriptase (TERT) promoter C228T/C250T mutations in tumor tissues of patients with hepatocellular carcinoma (HCC) for postoperative recurrence after hepatectomy.Methods:Clinical data of 66 patients with HCC who underwent curative surgical resection at the Cancer Hospital, Chinese Academy of Medical Sciences, between January 2013 and May 2016 were retrospectively analyzed, including 54 males and 12 females, aged (53.5±11.1) years. Tumor tissues were collected from all patients. Droplet digital ploymerase chain reation (ddPCR) was employed to detect the TERT promoter C228T/C250T mutations. Survival outcomes were estimated using the Kaplan-Meier method and compared by the log-rank test. Univariate and multivariate Cox regression were used to analyze the impact of TERT promoter C228T/C250T mutations on postoperative recurrence. The predictive performance of TERT mutations for postoperative recurrence was further assessed using receiver operating characteristic (ROC) curve analysis.Results:The prevalence of TERT C228T and C250T mutations in tumor tissues was 43.9% (29/66) and 3.0% (2/66), respectively. Patients were stratified into a TERT promoter mutation group ( n=31) and a non-mutation group ( n=35). Those harboring C228T/C250T mutations exhibited significantly lower recurrence-free survival compared with non-mutated cases ( χ2=10.10, P=0.002). Multivariate Cox regression analysis showed that TERT promoter C228T mutation ( HR=2.24, 95% CI: 1.18-4.25, P=0.013) and TERT promoter C228T/C250T mutations in tumor tissue ( HR=2.49, 95% CI: 1.31-4.75, P=0.006) were associated with an increased risk of postoperative recurrence in patients with HCC. ROC analysis demonstrated the predictive accuracy for recurrence, with an area under the curve of 0.68 (95% CI: 0.55-0.81) for TERT C228T mutation and 0.71 (95% CI: 0.58-0.84) for combined C228T/C250T mutations. Conclusion:TERT promoter C228T/C250T mutations in tumor tissues of HCC patients detected by ddPCR are risk factors for postoperative recurrence and may serve as indicators for predicting recurrence.