International journal of surgery最新文献

{"title":"Effects of TBK1 genetic polymorphisms and their interactions with hepatitis B virus mutations on the risk of hepatocellular carcinoma in Han Chinese population: a case-control study.","authors":"Ge Zhang, Hui Yang, Mingyan Fu, Ying Qin, Wenqing Cai, Yunning Hu, Yuxi Zhang, Yubao Zhao, Haibo Chen, Lu Ding, Zhenhong Sun, Yang Deng","doi":"10.1097/JS9.0000000000005145","DOIUrl":"10.1097/JS9.0000000000005145","url":null,"abstract":"<p><strong>Background: </strong>TANK-binding kinase 1 (TBK1) plays a critical role in driving inflammation and carcinogenesis. We aimed to investigate whether <i>TBK1</i> single nucleotide polymorphisms (SNPs) were associated with the selection of hepatitis B virus (HBV) mutations, and to explore their interaction in modulating the risk of hepatocellular carcinoma (HCC).</p><p><strong>Methods: </strong>Four <i>TBK1</i> SNPs (rs12313449, rs73122364, rs7486100, and rs11175413) were genotyped in 3405 participants using quantitative PCR. HBV mutations were determined by Sanger sequencing. Interactions of <i>TBK1</i> polymorphisms and HBV mutations were examined on both additive and multiplicative scales. A dual-luciferase assay was performed to assess the transcriptional activity of fragments containing rs12313449, rs73122364, rs7486100, and rs11175413 polymorphic genotypes. We evaluated the association between <i>TBK1</i> SNPs and HCC prognosis in 397 surgically treated HCC patients.</p><p><strong>Results: </strong>Variant genotypes of rs12313449, rs73122364, and rs7486100 were associated with an increased risk of HCC. In genotype C HBV-infected subjects, GA and AA genotypes at rs12313449, AT and TT genotypes at rs73122364, and TA and AA genotypes at rs7486100 were associated with a higher prevalence of HBV mutations including T1753A/C, A1762T/G1764A, G1896A, and preS deletion, which increase HCC risk. The interactions of variant genotypes of rs12313449, rs73122364, and rs7486100 with T1753A/C, A1762T/G1764A, and G1896A were significantly associated with an increased HCC risk. <i>TBK1</i> promoter with rs12313449-A showed a higher activity than that with rs12313449-G and was more strongly up-regulated by TNF-α and IL-6 stimulation. GA and AA genotypes at rs12313449 were associated with worse overall survival and recurrence-free survival and were unfavorable prognostic factors for HCC.</p><p><strong>Conclusions: </strong><i>TBK1</i> genetic polymorphisms may facilitate immune selection of HCC-associated HBV mutations and are associated with HCC development, possibly through synergistic interactions with specific HCC-associated HBV mutations.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":"112 7","pages":"13008-13019"},"PeriodicalIF":9.0,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13336618/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148874323","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Potential of RAD51C as a hub gene and therapeutic target in bladder cancer: insights from bioinformatics and experimental analysis.","authors":"Ying Xiao, Xiang Zhang, Zhe Xie, Li Tao, Xingwei Jin, Xianjin Wang, Boke Liu, Xuejian Zhou, Junwei Pan, Yuan Shao","doi":"10.1097/JS9.0000000000005112","DOIUrl":"10.1097/JS9.0000000000005112","url":null,"abstract":"<p><strong>Background: </strong>The global incidence of tumors is rising sharply. Immune checkpoint inhibitors (ICIs) represent the mainstream of immunotherapeutic approaches. Despite the remarkable clinical benefits of immunotherapy in various tumors, ICIs resistance remains an urgent challenge to be addressed. The transcription factors cAMP response element-binding protein 1(CREB1) and c-Jun converge to regulate oncogenesis and immune modulation.</p><p><strong>Methods: </strong>Based on the 'CREBP1CJUN_01' gene set from the Molecular Signatures Database and single-cell RNA sequencing data, we identified 116 CREB-c-Jun transcription factor target-related differential genes (CR.Sig) and refined to 20 CREB-c-Jun transcription factor target-related important feature genes (Hub-CR.Sig) through multi-algorithm machine learning. This Hub-CR.Sig enabled prognostic risk modeling, molecular subtyping of bladder cancer, and somatic mutation stratification.</p><p><strong>Results: </strong>Among these 20 signatures, RAD51C emerged as a top-ranked driver that was correlated with advanced T/N/M stages, associated with poor survival outcomes and is highly expressed in bladder cancer tissues. Functional assessment revealed that RAD51C knockdown suppressed bladder cancer cell proliferation, invasion, migration, and DNA repair capacity <i>in vitro</i>, while also reducing tumor formation <i>in vivo</i>. RNA sequencing analysis implicated the enrichment of JAK-STAT signaling pathways. Meanwhile, we identified an additional type of RAD51C⁺ fibroblast that was significantly associated with the depth of tumor invasion.</p><p><strong>Conclusions: </strong>The study establishes the Hub-CR.Sig as an immunotherapy response classifier and nominates RAD51C targeting as a promising therapeutic strategy for bladder cancer.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":"112 7","pages":"13049-13072"},"PeriodicalIF":9.0,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13336610/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148874320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on: Global burden and trends of primary liver cancer are attributable to high BMI among hepatitis B patients: based on the 2021 global burden of disease study.","authors":"Zeya Xu, Shuai Yin, Ningning Kuang","doi":"10.1097/JS9.0000000000005113","DOIUrl":"10.1097/JS9.0000000000005113","url":null,"abstract":"","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":"112 7","pages":"13269-13272"},"PeriodicalIF":9.0,"publicationDate":"2026-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13336691/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148874329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving pediatric hip fracture detection using deep learning: multicenter validation and clinical reader study.","authors":"Tongtong Huo, Xiaoliang Chen, Pengran Liu, Jin Liu, Zineng Yan, Jiaming Yang, Songxiang Liu, Lin Lu, Jiayao Zhang, Jia Shao, Wei Wu, Mingdi Xue, Zhewei Ye","doi":"10.1097/JS9.0000000000005138","DOIUrl":"10.1097/JS9.0000000000005138","url":null,"abstract":"<p><strong>Background: </strong>To develop and evaluate a deep learning model for automated localization and diagnosis of femoral neck fractures in children under 8 years of age using hip radiographs.</p><p><strong>Materials and methods: </strong>This retrospective multicenter study included 794 hip radiographs from 640 pediatric patients (median age, 4.1 years; 62.5% male) collected from four tertiary hospitals between June 2013 and December 2024. A YOLOv11-based object detection model was trained on 712 radiographs and externally validated on 82 radiographs. Diagnostic performance was measured by area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. A multi-reader study was conducted using the external test set, where five physicians (two senior radiologists, one junior radiologist, two emergency physicians) interpreted radiographs with and without AI assistance. Statistical analysis included DeLong's test, McNemar tests, and Fleiss' κ.</p><p><strong>Results: </strong>The model achieved AUROCs of 0.911 (95% CI: 0.864-0.949) on the internal test set and 0.873 (95% CI: 0.792-0.935) on the external test set. Sensitivity and specificity were 84.9% and 85.5% internally, and 80.8% and 91.1% externally. Among junior readers, AI assistance significantly improved diagnostic accuracy (mean ΔAUROC = + 0.083; <i>P</i> = 0.007) and interobserver agreement (κ from 0.49 to 0.61). The model localized fractures in real time with a mean inference time of 56.2 ms.</p><p><strong>Conclusion: </strong>A YOLOv11-based deep learning model accurately detected femoral neck fractures in children and significantly improved diagnostic accuracy and consistency among less experienced readers. These findings support its integration as a real-time assistive tool in pediatric trauma care.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":"112 7","pages":"13179-13189"},"PeriodicalIF":9.0,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13336705/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148874272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical landscape of urachal carcinoma: a two-decade real-world study.","authors":"Wenjie Li, Zhiming Wu","doi":"10.1097/JS9.0000000000005099","DOIUrl":"10.1097/JS9.0000000000005099","url":null,"abstract":"","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":"112 7","pages":"13285-13287"},"PeriodicalIF":9.0,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13336673/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148874195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comment on \"FANS-UAS under local anesthesia for urinary stones with high risk postoperative urosepsis\".","authors":"Xingxing Zhang, Wei Chang, Yaojing Yang","doi":"10.1097/JS9.0000000000005075","DOIUrl":"10.1097/JS9.0000000000005075","url":null,"abstract":"","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":"112 6","pages":"12983-12984"},"PeriodicalIF":9.0,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13249227/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148873937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretable machine learning model predicts the early gastrointestinal dysfunction risk in severely burned patients: a multicenter-based study.","authors":"Liwei Liu, Baigong Feng, Yujue Cao, Qihang Liu, Ran Yan, Yan Lian, Meizhuo Li, Chuanan Shen","doi":"10.1097/JS9.0000000000005044","DOIUrl":"10.1097/JS9.0000000000005044","url":null,"abstract":"<p><strong>Background: </strong>Gastrointestinal (GI) dysfunction is a life-threatening complication following severe burn injury, significantly increasing risks of multi-organ failure and mortality. This study aimed to develop and validate the first machine learning (ML)-based clinical prediction model for GI dysfunction after severe burns by leveraging explainable artificial intelligence (AI) techniques to support early clinical intervention.</p><p><strong>Methods: </strong>In this retrospective multicenter study, 570 patients with severe burns were enrolled: 469 from Hospital A [randomly split into training (<i>n</i> = 328) and internal validation (<i>n</i> = 141) sets] and 101 from Hospital B (external validation set). Predictors of GI dysfunction were identified using least absolute shrinkage and selection operator (LASSO) regression and Boruta algorithm. Eight ML algorithms were developed and evaluated using a 7:3 training-validation split and external validation. Model performance was assessed by area under the curve (AUC), accuracy, specificity, and decision curve analysis (DCA). Model interpretability was provided using SHapley Additive exPlanations (SHAP).</p><p><strong>Results: </strong>Among 570 patients, the incidence of GI dysfunction was 35.61% (203/570). The XGBoost algorithm showed superior discrimination, with an AUC of 0.910 (95% CI: 0.878-0.941) in the training set, 0.851 (0.790-0.913) in the internal validation set, and 0.908 (0.837-0.979) in the external validation set. SHAP analysis identified five key predictors by importance: SOFA score, TBSA, inhalation injury, blood culture result, and hematuria.</p><p><strong>Conclusion: </strong>We developed and validated the first interpretable ML-based model for predicting GI dysfunction after severe burn injury, with XGBoost achieving high performance. This model could help identify high-risk patients for personalized pre-emptive management.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":"112 6","pages":"12844-12855"},"PeriodicalIF":9.0,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13249312/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148874134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A closed-loop comprehensive analysis of global burden data, future projections, risk factors, and molecular mechanisms on nasopharyngeal carcinoma.","authors":"Yilong Xu, Sihai Dai, Huaqiang Dai, Qiuyu Chen, Yanling Xu, Yanyu Xu, Mingyan Hong, Xi Wang","doi":"10.1097/JS9.0000000000005083","DOIUrl":"10.1097/JS9.0000000000005083","url":null,"abstract":"<p><strong>Background: </strong>Nasopharyngeal carcinoma (NPC), a frequent malignant tumor, exhibits a high propensity for both metastasis and recurrence. This study provided a comprehensive analysis of the burden, risk factors, and potential molecular mechanisms of NPC.</p><p><strong>Methods: </strong>Utilizing data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021, we analyzed NPC burden in relation to age, sex, risk factors, and the sociodemographic index (SDI). The average annual percent change (AAPC) was computed through joinpoint regression. To assess causal links between risk factors and NPC, we employed two-sample Mendelian randomization (MR). Future NPC incidence trends (2022-2050) were projected using the Bayesian age-period-cohort model. We also elucidated the molecular mechanisms that trigger NPC by a bioinformatics analysis.</p><p><strong>Results: </strong>Global NPC mortality (AAPC: -1.817) and disability-adjusted life years (DALYs) rates (AAPC: -1.932) declined from 1990 to 2021. However, rising prevalence (AAPC: +0.317) and persistent high burden in East/Southeast Asia [e.g., Malaysia age-standardized incidence rate (ASIR): 6.09/100 000]. Socioeconomic disparities are widening, with low-SDI regions experiencing slower burden reduction. Projections suggest continued ASIR decline to 1.08/100 000 by 2050. MR analysis confirms smoking as a causal risk [current smokers odds ratio (OR) = 3.10; former smokers OR = 7.00, compared to never smoking], while Secretoglobin family 1A member 1 (SCGB1A1) downregulation emerges as a key mechanistic link-driving immunosuppression via Th2/Treg infiltration and hub genes (CXCL11, CD19).</p><p><strong>Conclusion: </strong>We innovatively constructed a closed-loop on NPC by multiple bioinformatic techniques. Global NPC mortality and DALYs have significantly declined, while this progress is counterbalanced by a rising prevalence and persistently high burden in East/Southeast Asia. Smoking was detected as a strong causal risk factor for NPC, while SCGB1A1 downregulation served as a novel key molecular driver of NPC pathogenesis.</p>","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":"112 6","pages":"12749-12768"},"PeriodicalIF":9.0,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13249253/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148873044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A commentary on \"CT-based radiomics signature of visceral adipose tissue for prediction of early recurrence in patients with NMIBC: a multicentre cohort study\".","authors":"Chungan Liu, Lan Yu, Xiaotao Zhang","doi":"10.1097/JS9.0000000000005108","DOIUrl":"10.1097/JS9.0000000000005108","url":null,"abstract":"","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":"112 7","pages":"13273-13274"},"PeriodicalIF":9.0,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13336706/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148874137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Commentary on: Beneficial outcomes of surgical combination therapy for patients with N3M0 non-small cell lung cancer: a retrospective cohort study.","authors":"Jiandong Cao, Chengsen Liu, Yi Ren","doi":"10.1097/JS9.0000000000005119","DOIUrl":"10.1097/JS9.0000000000005119","url":null,"abstract":"","PeriodicalId":14401,"journal":{"name":"International journal of surgery","volume":"112 7","pages":"13265-13266"},"PeriodicalIF":9.0,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13336596/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148874284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}