Hepatocellular carcinoma(HCC)remains highly prevalent in China and worldwide,with less than 20%of newly diagnosed patients eligible for radical resection and a postoperative 5-year recurrence rate as high as 70%.Perioperative therapy is a key strategy to reduce recurrence,yet evidence for neoadjuvant therapy in HCC is still limited.In recent years,immune checkpoint inhibitors(ICIs)have shown significant progress in HCC treatment,and their potential in the neoadjuvant setting has attracted growing attention.Neoadjuvant immunotherapy can utilize the primary tumor as an antigen reservoir to induce sustained antitumor immunity,and its combination with targeted agents or local therapies may yield synergistic effects.Early studies have demonstrated acceptable safety and preliminary efficacy;however,optimal patient selection,ideal combination strategies,and reliable predictive biomarkers remain to be established.High-quality randomized controlled trials are warranted to verify its impact on long-term survival and to optimize treatment approaches.

In recent years,immunotherapy represented by immune checkpoint inhibitors(ICIs)has created new opportunities for conversion therapy in intermediate to advanced hepatocellular carcinoma(HCC).The combination of ICIs with locoregional treatments,such as transcatheter arterial chemoembolization and hepatic arterial infusion chemotherapy,has demonstrated significant advantages in improving tumor response rates and eliciting systemic immune reactions,markedly enhancing the conversion rate of HCC compared to traditional approaches.However,the application of ICIs prior to liver transplantation also brings potential safety concerns,particularly the risk of graft rejection.These risks are exacerbated by the lack of standardized drug withdrawal intervals and the unpredictability of donor liver allocation,posing substantial challenges in clinical practice.This article systematically reviews the current status of ICIs in downstaging treatment prior to liver transplantation for HCC and discusses risk management strategies,aiming to provide reference for clinical decision-making and guideline development.

Most patients with hepatocellular carcinoma(HCC)are diagnosed at an intermediate or advanced stage,losing the opportunity for surgical resection.Conversion therapy,which uses non-surgical approaches to render initially unresectable tumors resectable,has gradually become part of routine clinical practice and a research focus.However,multiple challenges remain,including the lack of clear criteria for identifying"potentially resectable"cases,difficulty in selecting individualized systemic regimens from multiple approved options and determining whether to combine them with locoregional therapy,controversy over the necessity of surgery in patients achieving radiological complete response,the need for optimization of perioperative assessment and management,uncertainty in determining the optimal timing of surgery,and the absence of consensus on postoperative sequential systemic therapy regimens and duration.Addressing these issues requires multidisciplinary collaboration and high-quality evidence from multicenter randomized controlled trials.With the accumulation of clinical experience,growing evidence,and advances in treatment,more patients with initially unresectable HCC are expected to gain surgical opportunities and achieve long-term disease-free survival.

Background and Aims:Colorectal cancer liver metastasis(CRCLM)is a major cause of poor prognosis in patients with colorectal cancer.Accurate and noninvasive preoperative diagnosis is essential for treatment planning.Conventional clinical biomarkers have limited specificity.This study aimed to develop an efficient predictive model for CRCLM by integrating multimodal MRI imaging omics features with machine learning algorithms,and to evaluate its clinical value.Methods:A total of 150 patients with colorectal cancer who underwent preoperative MRI and were pathologically confirmed at Nanyang First People's Hospital between May 2022 and May 2024 were retrospectively analyzed.Patients were randomly divided into a training set(n=120)and a validation set(n=30),including 57 cases with CRCLM and 93 cases without.Univariate and multivariate analyses were performed to identify independent risk factors for CRCLM and to construct a clinical diagnostic model.Radiomics features were extracted from multimodal MRI,and the least absolute shrinkage and selection operator(LASSO)method was used for feature selection.Logistic regression(LR),support vector machine(SVM),and random forest(RF)models were built and compared for diagnostic performance.A combined clinical-imaging omics model was further established,and its performance and clinical utility were assessed using receiver operating characteristic curves and decision curve analysis(DCA).Results:Carcinoembryonic antigen(OR=1.323,95%CI=1.079-1.567),carbohydrate antigen 19-9(OR=2.512,95%CI=1.225-3.799),and neutrophil-to-lymphocyte ratio(OR=1.881,95%CI=1.354-2.409)were identified as independent risk factors for CRCLM(all P<0.05).The clinical model constructed with these three factors achieved an AUC of 0.793.Among radiomics models,the RF model demonstrated the highest AUC in both training and validation sets(0.770 and 0.763),outperforming LR and SVM.The combined RF-based model yielded AUC of 0.913 and 0.947 in the training and validation sets,respectively,significantly exceeding the performance of the clinical or imaging omics models alone.DCA confirmed the superior net clinical benefit of the combined model.Conclusion:The RF model showed the best diagnostic performance among imaging omics models.When integrated with clinical features,the combined RF model significantly improved the noninvasive diagnostic efficacy of CRCLM and demonstrated high potential for clinical application.

Background and Aims:Hepatocellular carcinoma(HCC)is the most prevalent type of liver malignancy,accounting for 80%of all primary liver cancer cases.Partial hepatectomy is widely considered to be the treatment of choice for HCC.However,post-hepatectomy liver failure(PHLF)is the most serious complication and the leading cause of perioperative death.Therefore,an accurate assessment of the risk of PHLF is particularly critical.Patients with large hepatocellular carcinoma have larger tumors(tumor diameter≥5 cm)and more resected liver tissue,and are more likely to develop PHLF.Previous studies have used various methods to assess the risk of PHLF,including liver function,Child-Pugh classification,model for end-stage liver disease,albumin-bilirubin(ALBI),and aspartate aminotransferase-to-platelet ratio index score.However,no model has been developed for data on hepatectomy for large HCC.Therefore,this study aims to analyze the risk factors of PHLF in HCC patients with large tumor and to construct a preoperative nomogram prediction model to guide and optimize clinical decision-making.Methods:The clinical data of 927 patients with large liver cancer who underwent radical hepatectomy in the First Affiliated Hospital of Anhui Medical University(721 cases,training cohort)and the Second Affiliated Hospital of Anhui Medical University(206 cases,validation cohort)from January 2018 to June 2023 were retrospectively collected.The patients'baseline data,laboratory examination,imaging data,and surgical information were collected.Univariate analysis combined with multivariate analysis was used to screen out the independent risk factors for inducing PHLF,and binary Logistic regression was used to construct a prediction model for PHLF.ROC,calibration,and clinical decision curves verified the model's performance.Results:There were no significant differences in all preoperative data between the training and validation cohorts(P>0.05).Grade B or C PHLF occurred in 192 of 927 patients(20.7%),including 8 patients with grade C PHLF.Univariate and multivariate Logistic regression analyses were used to determine the independent risk factors of PHLF,including tumor diameter,ALBI score,liver cirrhosis,vascular tumor thrombus,and intraoperative blood loss.These factors were included in the Logistic regression analysis,and a nomogram model was constructed to predict PHLF.The nomogram model was validated,and the C-index of the nomogram was 0.757.The ROC curve analysis of the prediction probability of the model showed that the AUC of the training set was 0.757(95%CI=0.703-0.811),and the AUC of the validation set was 0.779(95%CI=0.702-0.863).The validation showed that the model had good predictive ability.Conclusions:Tumor diameter,ALBI score,liver cirrhosis,vascular tumor thrombus,and intraoperative blood loss are independent risk factors for PHLF.The nomogram prediction model constructed in this study can accurately assess the risk of preoperative PHLF,which is helpful for better clinical management,reducing the occurrence of PHLF,and improving the postoperative prognosis of patients.

Background and Aims:Primary hepatic diffuse large B-cell lymphoma(DLBCL)is rare and carries a poor prognosis,with no large-scale evidence supporting the value of chemotherapy.This study used real-world,large-sample data from the SEER database to evaluate the prognostic impact of chemotherapy in patients with primary hepatic DLBCL.Methods:Clinical data of patients pathologically diagnosed with primary hepatic DLBCL between 2000 and 2019 were extracted from the SEER database and grouped according to whether they received chemotherapy.Kaplan-Meier survival analysis,Cox proportional hazards models,and random survival forest models were employed to identify factors influencing overall survival(OS)and cancer-specific survival(CSS),and subgroup analyses were performed.Results:A total of 594 patients were included,with a median age of 66 years;435(73.2%)received chemotherapy.After a median follow-up of 17.5 months,the median OS was 81(7-173)months in the chemotherapy group versus 11(2-171)months in the non-chemotherapy group.The OS and CSS rates in the chemotherapy group were significantly higher than those in the non-chemotherapy group(67.99%vs.47.77%;71.03%vs.52.87%,both P<0.05).Multivariate analysis showed that chemotherapy was an independent protective factor for OS(HR=0.39,95%CI=0.31-0.48)and CSS(HR=0.37,95%CI=0.29-0.48).In the random survival forest model,chemotherapy ranked highest in variable importance.Subgroup analyses produced consistent results.Conclusion:Chemotherapy is an independent prognostic factor for patients with primary hepatic DLBCL and can significantly improve survival.The R-CHOP regimen may be the preferred therapeutic option.

Background and Aims:Pancreatic cancer(PC)is a highly lethal gastrointestinal malignancy with poorly understood pathogenesis.Previous studies suggest that alterations in plasma metabolomics may be associated with PC development;however,traditional observational studies are prone to confounding and reverse causation,making it difficult to establish causal relationships.This study employed a two-sample Mendelian randomization(MR)approach to systematically evaluate the potential causal relationship between 325 nuclear magnetic resonance(NMR)metabolites and PC risk.Methods:Genome-wide association study(GWAS)data of 325 NMR metabolites from the UK Biobank were integrated with GWAS data of PC from FinnGen.Single nucleotide polymorphisms(SNPs)significantly associated with metabolites were selected as instrumental variables.The inverse variance weighted method served as the primary analysis,supplemented by MR-Egger regression,weighted median,weighted mode,Bayesian weighted Mendelian randomization(BWMR),and constrained maximum likelihood(cML)for validation.Multiple sensitivity analyses were performed to assess the robustness of the results.Results:Four metabolites were identified to have significant causal associations with PC risk.Higher phospholipid-to-total lipid ratios in intermediate-density lipoproteins(IDL)(GCST90445881)and small high density lipoproteins(HDL)(GCST90446027),as well as higher free cholesterol-to-total lipid ratios in extremely large very-low-density lipoproteins(VLDL)(GCST90446151),were inversely associated with PC risk.Conversely,an elevated triglyceride-to-total lipid ratio in chylomicrons and extremely large VLDL(GCST90446157)was positively associated with increased PC risk.The findings were consistently supported by multiple sensitivity analyses.Conclusion:This study provides genetic evidence linking lipid metabolism alterations to PC risk.Elevated phospholipid and free cholesterol ratios appear protective,whereas increased triglyceride levels act as risk factors.These metabolite profiles may serve as promising biomarkers for early diagnosis and intervention in PC,offering novel insights for risk assessment and potential metabolic-targeted therapies.

Iatrogenic bile duct injury(IBDI)is a common type of bile duct injury,most frequently occurring during cholecystectomy.With the widespread use of laparoscopic cholecystectomy,its incidence is significantly higher than that of open surgery,and the number of complex cases combined with vascular injury(VI)has been increasing,posing greater challenges for diagnosis and treatment.In severe cases,it may result in hepatic ischemia and atrophy.Hepaticojejunostomy is the standard reconstructive procedure after bile duct injury,whereas hepatectomy may be required when VI is involved.We report the case of a 53-year-old woman who was admitted with bile leakage following cholecystectomy.After two multidisciplinary team(MDT)discussions,preoperative evaluation revealed injury to the right hepatic artery and a portal vein branch,accompanied by atrophy of the right anterior lobe.Based on intraoperative findings,the patient underwent right hepatectomy combined with Roux-en-Y hepaticojejunostomy of the left hepatic duct.Postoperative recovery was uneventful,and the patient remained symptom-free during a 6-month follow-up.By reviewing the diagnosis and management of this case in conjunction with relevant literature,we summarize the clinical features,treatment strategies,and the value of MDT management in complex IBDI,aiming to provide reference for clinical practice.

Background and aims:Obesity is a major global health challenge,and laparoscopic sleeve gastrectomy(LSG)is a widely used bariatric procedure.However,weight loss outcomes vary considerably among patients.Psychological factors and eating behaviors are increasingly recognized as important determinants of postoperative success,yet the underlying mechanisms remain unclear.This study aimed to examine the relationship between self-control and 12-month postoperative weight loss(%EWL)after LSG,and to test the independent and chain mediating roles of depression and emotional eating.Methods:In a cross-sectional study,202 LSG patients from the Third Xiangya Hospital of Central South University completed the Brief Self-Control Scale(BSCS),Patient Health Questionnaire-9(PHQ-9),and the emotional eating subscale of the Dutch Eating Behavior Questionnaire(DEBQ).%EWL within 12 months after surgery was calculated.Pearson correlations were conducted,and mediation was tested using Process v4.0(model 6)with 5 000 bootstrap samples while controlling for sex and postoperative time.Results:Overall,BSCS,PHQ-9,DEBQ-EE,and%EWL averaged 21.76±4.15,5.54±3.91,30.72±11.25,and(60.94±31.61)%,respectively.Self-control correlated negatively with depression(r=-0.697)and emotional eating(r=-0.441)and positively with%EWL(r=0.566;all P<0.01).%EWL correlated negatively with depression(r=-0.467)and emotional eating(r=-0.348,P<0.01).Adjusted regression showed positive prediction of%EWL by self-control(β=0.291 9,P<0.01)and negative prediction by depression(β=-0.155 6,P<0.05)and emotional eating(β=-0.115 8,P<0.05).Mediation analysis showed that the indirect effect through the path"self-control → depression →%EWL"was 0.848 8(95%CI=0.178 7-1.573 0).The indirect effect through the path"self-control → emotional eating →%EWL"was 0.259 8(95%CI=0.033 4-0.564 3).The chain indirect effect through the path"self-control →depression → emotional eating →%EWL"was 0.131 7(95%CI=0.005 9-0.322 8);the total indirect effect accounted for 35.83%of the total effect.Conclusion:Higher self-control after LSG enhances weight loss both directly and indirectly by alleviating depression and emotional eating.Routine psychological screening and eating-behavior interventions are warranted to consolidate long-term benefits.

Background and Aims:Acute pancreatitis(AP)is a common acute abdominal disease,with some patients progressing to moderately severe(MSAP)or severe acute pancreatitis(SAP).Secondary infection is a major determinant of prognosis.Carbapenem-resistant Acinetobacter baumannii(CRAB)has emerged as an important pathogen in AP,characterized by high drug resistance and mortality.This study aimed to comprehensively analyze the clinical characteristics,mortality risk factors,and antimicrobial resistance patterns of CRAB infection in MSAP/SAP patients,and to develop a predictive model.Methods:A retrospective cohort of 108 MSAP/SAP patients with CRAB infection admitted to Xiangya Hospital,Central South University,between January 2012 and August 2022 was analyzed.Clinical data,laboratory parameters,and antimicrobial susceptibility results were collected.Cox regression was performed to identify independent mortality risk factors,and a nomogram prediction model was constructed and validated.Results:The cohort comprised 108 patients(mean age 48 years,71.3%male).The leading etiologies were hypertriglyceridemia(61.1%)and biliary causes(33.3%).The most common infection sites were the pancreas/peripancreatic region(44.4%)and the lungs(43.5%).Overall mortality was 42.6%(46/108).Compared with survivors,deceased patients were older,more frequently had biliary etiology,ICU admission,mechanical ventilation,hemorrhage,and septic shock(all P<0.05).Multivariate Cox regression identified age>60 years(HR=6.694),hemorrhage(HR=4.466),septic shock(HR=4.495),and hemoglobin<80 g/L(HR=2.343)as independent predictors of death.Among 175 CRAB isolates,resistance rates exceeded 60%for most antibiotics,while tigecycline showed the lowest resistance(<40%).The nomogram model demonstrated excellent discrimination(C-index=0.897)and calibration,with an AUC of 0.897 for 90-day survival prediction.Conclusion:CRAB infection significantly worsens clinical outcomes in MSAP/SAP patients,with advanced age,hemorrhage,septic shock,and severe anemia as key mortality risk factors.The nomogram provides an effective tool for early identification of high-risk patients.Tailored therapeutic strategies,rational antibiotic use,and prevention of complications are essential to improving prognosis in this population.