Background Chen's U-suture technique was presented with a low incidence of clinically relevant postoperative pancreatic fistula (CR-POPF) in 2014. This study aimed to compare the outcomes of Chen's U-suture technique with those of duct-to-mucosa and traditional invagination pancreaticojejunostomy. Methods The data of patients who underwent pancreaticoduodenectomy across 21 hospitals between 2014 and 2019 were analyzed and categorized into Chen's group, the duct-to-mucosa (DTM) group, and the traditional invagination (TIG) group. Propensity score matching (PSM) analysis was performed to balance the baseline differences among three groups. Subsequently, the surgical outcomes were compared across the groups. Results After PSM, 1060 patients in each group were matched, resulting in balanced baseline characteristics. The CR-POPF rate was 5.19 % in Chen's group, compared to 8.02 % in the TIG group and 7.45 % in the DTM group (P=0.025). A statistically significant difference was identified between Chen's group and the TIG group (P = 0.034), whereas no significant difference was observed when comparing Chen's group to the DTM group (P = 0.060). In the subgroup with a small pancreatic duct (≤3 mm), the CR-POPF rate in Chen's group was significantly lower than that in the DTM group (4.6 % vs 7.4 %, P = 0.019). The incidences of intra-abdominal infection and abscess in Chen's group were 7.45 % and 0.47 % respectively, compared to 10.28 % and 2.26 % in the TIG group, and 10.19 % and 1.51 % in DTM group (all P < 0.05). No significant differences were observed in the rates of severe complications or mortality among the three groups. Conclusions Chen's U-suture technique was a better invagination pancreaticojejunostomy with decreased CR-POPF and POPF-related infection. Furthermore, it was superior to the duct-to-mucosa method for the patients with a small pancreatic duct.

BACKGROUND:Hepatocellular carcinoma (HCC), one of the most prevalent cancers worldwide, has a high mortality owing to diagnostic challenges and therapeutic resistance. Lactate metabolism and protein lactylation play key roles in HCC progression; nevertheless, their regulatory mechanisms remain poorly understood. OBJECTIVE:This study aims to elucidate how lactate metabolism and protein lactylation contribute to HCC malignant progression by integrating multi-omics data, identifying key regulatory factors and exploring therapeutic strategies targeting this pathway. DESIGN:Integrated multi-omics analysis identified AARS2-AP-2γ as a key axis in HCC. Through mechanistic studies and virtual screening, we developed kukoamine A-a targeted inhibitor delivered via nanocarriers-demonstrating significant therapeutic potential. RESULTS:AARS2 was identified as a key regulator linking lactate metabolism to HCC progression through lactylation modification. It catalyses AP-2γ lactylation at K444, enhancing TRIM28 binding to promote K63-linked ubiquitination and nuclear translocation, thereby facilitating tumour progression. The inhibitor kukoamine A disrupts AARS2-AP-2γ interaction and, when delivered via zeolitic imidazolate framework-8 nanocarriers, demonstrates improved liver targeting, potent antitumour activity and synergy with PD-1 blockade, offering new strategic avenues for HCC precision therapy. CONCLUSION:AARS2 links lactate metabolism to HCC progression via lactylation. Kukoamine A nanotherapy targeting this axis shows synergistic efficacy with immunotherapy, advancing the prospects of precision oncology.

Background Dysregulation in chemotaxis and activation of neutrophils may trigger cancer. Nevertheless, the function of neutrophils and their mechanism during the prognosis of pancreatic cancer (PC) remain unclear.Methods From the databases of The Cancer Genome Atlas (TGCA) and GeneCards, the genes of tumor-associated neutrophils (TANs) were screened out leveraging the differential expression analysis. The constructed prognostic model for PC was analyzed through the least absolute shrinkage and selection operator (LASSO) regression and Cox univariate and multivariate regression. The dataset (GSE62452) provided by the Gene Expression Omnibus (GEO) database served as the validation cohort, and its potential mechanistic pathways and biological functions were analyzed leveraging Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The immune infiltration analysis, as well as the drug sensitivity prediction, were conducted. The gene expression in the prognostic model was checked through online databases, including Human Protein Atlas (HPA) and Tumor Immune Single-Cell Hub (TISCH). Finally, the genes were experimentally confirmed by immunohistochemistry (IHC) and qPCR in combination with clinical samples from patients with PC.Results AIM2, PSCA, IL18BP, and LIPE were four genes of TANs closely linked to the prognosis of PC. A model for the prognosis of PC was established utilizing these 4 genes. The AUC (area under the receiver operating characteristic curve (ROC curve)) values of this model for forecasting the survival rates of patients at 1, 2, and 3 years were 0.774, 0.841, and 0.953, respectively. The immune infiltration analysis revealed that resting dendritic cells (resting DCs), naive B cells, CD8T cells, as well as follicular helper T cells, were highly infiltrated among patients suffering from PC. According to the drug sensitivity analysis, the high-risk pancreatic ductal adenocarcinoma (PAAD) group had a significantly higher inhibitory concentration 50 (IC50) for dactolisib, docetaxel, gemcitabine, and ulixertinib compared to the group by patients with low-risk PAAD. The results of IHC and qPCR confirmed those of bioinformatics analysis.Conclusion New TANs-related biomarkers have been found that effectively forecast the prognosis of patients suffering from PAAD.

Background Patients with hepatocellular carcinoma (HCC) and clinically significant portal hypertension (CSPH) experience a poorer prognosis following hepatectomy (Hx). This study aimed to develop a calculator to estimate the survival outcomes of the cohort. Methods This study collected data from patients with BCLC stage 0/A HCC and CSPH who underwent curative Hx at 12 medical centers between 2015 and 2020. Prognostic factors for overall survival (OS) were identified using the Cox proportional hazards model. The performance of the nomogram was primarily assessed through the concordance index (C-index), compared with the Model of End-Stage Liver Disease-alpha-fetoprotein-tumor burden (MELD-AFP-TBS) and Chinese University Prognostic Index (CUPI). Results The patients were split into training (n = 370) and validation (n = 157) cohorts, with well-balanced baseline characteristics (all P > 0.05). The AUC values of the nomogram for 3- and 5-year OS were 0.776 and 0.712 in the training cohort, and 0.695 and 0.732 in the validation cohort. The C-index values for the nomogram were significantly improved (training cohort: vs. MELD-AFP-TBS, 0.148 [0.091-0.204]; vs. CUPI, 0.184 [0.134-0.234]; validation cohort: vs. MELD-AFP-TBS, 0.146 [0.054-0.238]; vs. CUPI, 0.140 [0.050-0.230]; all P <0.05). Based on the nomogram, an online calculator was developed for individualized assessment of risk level and survival outcomes. Conclusion Based on multi-center data, an accessible online calculator was developed to individually forecast the survival prognosis of patients with BCLC stage 0/A HCC and CSPH undergoing Hx.

BACKGROUND:Mitochondrial dysfunction contributes to the pathogenesis of multiple diseases. This study explores the involvement of mitochondrial dysfunction-related genes (MDRGs) in liver ischemia-reperfusion injury (LIRI). METHODS:Differentially expressed MDRGs (DE-MDRGs) were identified using public databases. We identified key hub genes by integrating functional enrichment, protein-protein interaction (PPI) network analysis, and machine learning algorithms. These candidates underwent rigorous validation using independent cohorts, an in vivo LIRI mouse model, and computational approaches including molecular docking and dynamics simulations. RESULTS:Twelve DE-MDRGs were identified, enriched in autophagy regulation, autophagosome formation, cytokine activity, and pathways linked to neurodegenerative and graft-versus-host diseases. The MCC algorithm prioritized ten DE-MDRGs, with IL-6, HTT, and SLC19A2 consistently selected across machine learning models. ROC analysis confirmed their diagnostic accuracy. A nomogram incorporating these genes demonstrated strong predictive performance for LIRI risk. Immune profiling revealed that LIRI is characterized by an elevated presence of neutrophils, naive CD4 T cells, and activated mast cells, contrasting with a significant reduction in M2 macrophages and resting populations of mast cells and memory CD4 T cells. GSEA further revealed significant enrichments of IL-6, HTT, and SLC19A2 in pathways associated with immune responses. The differential expression of these three genes was further confirmed both in an external validation cohort and in vivo in liver tissues from the murine LIRI model. In silico screening via docking and dynamic simulations suggested that the hub genes could be effectively targeted by Curcumin, Valproic Acid, or Acetylcysteine, all of which displayed promising interaction profiles. CONCLUSION:Our research uncovered an interaction between mitochondrial dysfunction and the immune microenvironment in LIRI. This finding could offer significant perspectives for the clinical management of LIRI through the regulation of mitochondrial activity.

Hepatocellular carcinoma (HCC) is a type of cancer with a high incidence rate and a high mortality rate and is a major cause of cancer-related death. The resistance of liver cancer cells to lenvatinib has become a crucial limitation that restricts the clinical therapeutic efficacy of HCC treatment. In the present study, we successfully establish lenvatinib-resistant liver cancer cell lines and perform transcriptome sequencing analysis, through which we identify the key gene tripartite motif containing protein 31 (TRIM31). As an E3 ubiquitin ligase harboring a RING domain, TRIM31 is capable of regulating the stability and biological functions of its substrate proteins through ubiquitination. Nevertheless, the specific role and underlying molecular mechanisms of TRIM31 in liver cancer cell stemness and lenvatinib resistance remain largely unclear. In this study, clinical sample analysis confirms its high expression in HCC tissues, which correlates with poor patient prognosis. The results of functional experiments demonstrate that TRIM31 knockdown inhibits HCC stemness and lenvatinib resistance, whereas TRIM31 overexpression significantly enhances these properties. Mechanistically, TRIM31 interacts with glycine decarboxylase (GLDC) and mediates K48- and K63-linked polyubiquitination through its RING domain, leading to GLDC protein degradation. GLDC degradation enhances HCC stemness and chemoresistance by relieving its suppression of PI3K/AKT/mTOR signaling. This study is the first to highlight the critical role of TRIM31 in HCC stemness and drug resistance, offering a potential new strategy for targeted therapy in HCC.

The majority of studies have predominantly used body mass index or waist circumference as measures to establish a link between urinary metals and obesity, leading to inconsistent outcomes. Visceral fat index was a simple, practical and non-invasive physical examination indicator for measuring visceral obesity, and the association between urinary metal and VFI is unclear. This study utilized a cross-sectional design and based on the baseline data of the Prospective Cohort Study of Chronic Diseases in Ethnic Minority Natural Population in Guangxi from May 2019 to December 2019. Information on demographics, health status, lifestyle, and additional variables was obtained through structured face-to-face interviews. The study employed multiple statistical models, including lasso regression, logistic regression, restricted cubic spline, quantile g-computation, weighted quantile sum, and Bayesian kernel machine regression. This study encompassed a total of 5794 participants, comprising 2641 males and 3153 females. Among the participants, 1423 (24.6

ABSTRACT Oxidative stress is a critical driver in the pathogenesis of alcohol‐related liver disease (ALD), promoting hepatic inflammation and injury. This study investigates the role of tumor necrosis factor receptor‐associated factor interacting protein (TRAIP) in ALD. We utilize in vivo ALD models with liver‐specific TRAIP overexpression (LSO) or knockout (LKO) mice. Chromatin immunoprecipitation and luciferase reporter assays confirm NF‐κB1 binding to the TRAIP promoter. In vitro, co‐immunoprecipitation and domain mapping with truncated mutants identify the interaction between the TRAIP coiled‐coil domain and the β‐catenin Armadillo domain. TRAIP is significantly upregulated in human and murine ALD tissues. Ethanol‐fed TRAIP LSO mice exhibit heightened oxidative stress and inflammation but reduced steatosis, whereas TRAIP LKO mice show the opposite. Mechanistically, ethanol‐induced NF‐κB1 activation transcriptionally upregulates TRAIP. TRAIP directly ubiquitinates β‐catenin in vitro and promotes its K48‐linked ubiquitination and proteasomal degradation in cells, independently of the canonical GSK3β/β‐TrCP pathway. Consequently, increased TRAIP suppresses the antioxidative response downstream of β‐catenin. The β‐catenin stabilizer SKL2001 effectively alleviates ethanol‐induced oxidative damage. We conclude that TRAIP promotes ALD by driving β‐catenin degradation and oxidative stress through a GSK3β/β‐TrCP‐independent mechanism, identifying the β‐catenin pathway and the compound SKL2001 as implicated in this process.

JARID1B is a member of the family of JmjC domain-containing proteins that removes methyl residues from methylated lysine 4 on histone H3 lysine 4 (H3K4). JARID1B has been proposed as an oncogene in many types of tumors; however, its role and underlying mechanisms in hepatocellular carcinoma (HCC) remain unknown. Here we show that JARID1B is elevated in HCC and its expression level is positively correlated with metastasis. In addition Kaplan-Meier survival analysis showed that high expression of JARID1B was associated with decreased overall survival of HCC patients. Overexpression of JARID1B in HCC cells increased proliferation, epithelial-mesenchymal transition, migration and invasion in vitro, and enhanced tumorigenic and metastatic capacities in vivo. In contrast, silencing JARID1B in aggressive and invasive HCC cells inhibited these processes. Mechanistically, we found JARID1B exerts its function through modulation of H3K4me3 at the PTEN gene promoter, which was associated with inactive PTEN transcription. PTEN overexpression blocked JARID1B-driven proliferation, EMT, and metastasis. Our results, for the first time, portray a pivotal role of JARID1B in stimulating metastatic behaviors of HCC cells. Targeting JARID1B may thus be a useful strategy to impede HCC cell invasion and metastasis.

Background: Long non-coding RNAs (lncRNAs) play an important regulatory role in tumorigenesis and progression. However the role of TAF1A-AS1 in hepatocellular carcinoma (HCC) remains unclear. Therefore, this study aimed to clarify the specific role of TAF1A-AS1 in regulating tumorigenesis and progression of HCC. Methods: Quantitative real-time PCR (qRT-PCR) was used to determine the expression of TAF1A-AS1, miR-664b-3p and USP22 in tissue samples and cell lines. Functional assays, including Cell Counting Kit-8 (CCK-8) assay, colony formation assay, transwell assays and chemoresistance assay, were performed to study the effects of TAF1A-AS1 in HCC cells. Dual-luciferase reporter assay and RNA immunoprecipitation (RIP) were performed to examine the interaction between TAF1A-AS1 and miR-664b-3p, as well as between miR-664b-3p and USP22. A nude mouse xenograft model was established for the in vivo experiments. Results: TAF1A-AS1 was remarkably upregulated in HCC tissues, and patients with high TAF1A-AS1 expression had poorer prognosis. Both in vitro and in vivo experiments showed that TAF1A-AS1 promoted the proliferation, invasion and tumorigenicity of HCC cells. Furthermore, mechanism study revealed that TAF1A-AS1 served as a sponge of miR-664b-3p, and USP22 was identified as a downstream target of miR-664b-3p. Additionally, TAF1A-AS1 affected HCC cells sensitivity to sorafenib and activated mTOR signaling through USP22. Conclusion: Our study demonstrated that TAF1A-AS1 regulated the progression of HCC by sponging miR-664b-3p to activate USP22. These results suggest that TAF1A-AS1 could be a novel HCC prognostic biomarker and a potential therapeutic target.

Aiming: This study aimed to develop a clinical–radiomics model based on preoperative dual-phase computed tomography to predict post-hepatectomy liver failure (PHLF) following stage I associating liver partition and portal vein ligation for staged hepatectomy (ALPPS) in patients with hepatitis B. Methods This retrospective study included 90 patients. Mixed-effects models were employed to assess the dynamic regeneration of the future liver remnant (FLR). Radiomics features were extracted using volumes of interest defined for both whole-FLR (wFLR) and partial-FLR (pFLR). Four machine learning algorithms, combined with nested cross-validation, were used to construct stable clinical-radiomics models. Interpretability analyses, as well as mediation analyses, were also performed. Results The incidence of grade B or C PHLF was 24.4%. The liver generation model demonstrated a significantly lower daily growth rate in the PHLF group compared to the non-PHLF group (3.67% vs. 5.61% per day, P = 0.003). The clinical, radiologic, and combined model based on wFLR achieved AUCs of 0.791, 0.892, and 0.894, respectively; those based on pFLR achieved AUCs of 0.791, 0.769, and 0.828. No significant difference in model performance was observed between the two segmentation strategies (P = 0.858), though pFLR segmentation substantially reduced workload. A preliminary mediation analysis suggested that 86.2% of the radiomics score’s total effect on PHLF was mediated by liver regeneration rate (OR 1.146, P < 0.001). Conclusion The proposed clinical–radiomics models effectively predict PHLF after ALPPS Stage I in patients with hepatitis B. The effect of the radiomics score on PHLF is mediated by impaired liver regeneration.

The liver is the most common metastatic target organ of pancreatic cancer (PC). Currently, imaging examination is effective for detecting liver metastases (LM) of PC, but some small metastases are difficult to detect, making it necessary to establish a comprehensive diagnostic model with which to predict LM. A total of 59 patients with PC were enrolled as the training cohort and 16 patients with PC were included as the external validation cohort. The 59 patients in the training cohort were divided into LM and No-LM groups. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for synchronous liver metastasis (SLM) in PC. Based on these findings, a diagnostic model was constructed and a nomogram was developed to facilitate practical application. The accuracy and reliability of this diagnostic model were then evaluated using the area under the receiver operating characteristic curve (AUC), Hosmer-Lemeshow (HL) curves and decision curve analysis (DCA). Multivariate analysis identified CEA [odds ratio (OR)=1.05, 95% CI: 1.01-1.08], CA153 (OR=1.18, 95% CI: 1.06-1.31), white blood cells (WBC; OR=1.71, 95% CI: 1.08-2.72) and platelets (PLT; OR=1.01, 95% CI: 1.00-1.03) as independent risk factors. In the training and external validation cohorts, the diagnostic efficacy of the model's AUC was 0.92 and 0.90, respectively, with sensitivities of 0.96 and 0.83, and specificities of 0.86 and 0.75, respectively. The HL and DCA curves indicate the excellent calibration and clinical net benefit of the model. In conclusion, the diagnostic model integrating CEA, CA153, WBC and PLTs shows high predictive performance for identifying SLM in patients with PC.

BACKGROUND:Hepatic artery infusion chemotherapy (HAIC) has become an important strategy for treating patients with unresectable hepatocellular carcinoma (uHCC). The mainstream FOLFOX regimen seriously affects the treatment experience of patients due to the need for continuous drug pumping for a long time. CapeOx regimen with oral capecitabine instead of continuous intravenous infusion of 5 - fluorouracil, is expected to be on the premise of not reduce the curative effect of treatment of convenience. METHODS:This study retrospectively analyzed 127 patients with uHCC who were treated with HAIC combined with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), including 31 cases in the CapeOx-HAIC group and 96 cases in the FOLFOX-HAIC group. The baseline differences were balanced through propensity score matching (PSM), and the differences in efficacy and safety between the two groups were compared. RESULTS:The CapeOx-HAIC group was slightly superior to the FOLFOX-HAIC group in terms of objective response rate (61.6% vs 46.1%) and disease control rate (88.5% vs 80.8%), but there was no significant statistical difference. Notably, the CapeOx-HAIC regimen was associated with significantly shorter durations of both chemotherapy and hospitalization, while maintaining a comparable safety profile to the FOLFOX-HAIC regimen. CONCLUSIONS:The CapeOx-HAIC regimen offers comparable efficacy and safety to FOLFOX-HAIC but with superior convenience due to shorter treatment and hospitalization. It represents a valuable "subtractive optimization" that is especially beneficial for frail patients, thereby simplifying clinical management and strengthening the basis for treatment plan selection.

Liver ischemia-reperfusion injury (LIRI), a significant complication following liver transplantation and surgical procedures, remains inadequately addressed due to the limited therapeutic options available. This study aims to elucidate the pivotal regulators underlying the maladaptive immune responses and mitochondrial dysfunction associated with LIRI. By integrating multiple microarray datasets (GSE12720, GSE112713, GSE23649, and GSE151648) and single-cell RNA sequencing (scRNA-seq) data (GSE171539), we employed weighted gene co-expression network analysis (WGCNA) alongside four machine learning algorithms (SVM, LASSO, RF, and XGBoost) to identify hub genes. Our analyzes highlighted MCL1 as a critical hub gene linked to mitochondrial function, exhibiting significantly elevated expression levels in LIRI, coupled with strong diagnostic accuracy. Further single-cell analysis revealed MCL1's specific enrichment in endothelial cells (ECs) and macrophages (MCs), along with the identification of a novel macrophage subset (CSF1R+IL-1B+MCL1+) characterized by a dual pro-inflammatory and pro-survival phenotype. This finding suggests enhanced intercellular crosstalk involving key pathways such as NF-κB, apoptosis, and cytokine signaling, while in silico knockout of MCL1 markedly disrupted immune-related gene networks. Validation studies confirmed MCL1 upregulation and the presence of the macrophage subset in a murine LIRI model. In conclusion, our findings position MCL1 as a vital regulator linking immune inflammation and mitochondrial dysfunction in LIRI, proposing it as a promising diagnostic biomarker and therapeutic target for managing this condition, though its optimal therapeutic direction requires further investigation.

ObjectiveThis study aims to develop a multimodal model that integrates clinical features and preoperative imaging characteristics to predict complete response (CR) in hepatocellular carcinoma (HCC) patients following ablation therapy, and to assess the therapeutic efficacy of ablation therapy.MethodsFrom October 2017 to June 2024, we collected clinical data and CT enhanced images from 108 HCC patients within one month before ablation therapy. The most important features were selected and dimensionality was reduced using the Mann-Whitney U test, Principal Component Analysis (PCA), and Least Absolute Shrinkage and Selection Operator (LASSO) regression. A multimodal feature set was constructed by integrating clinical characteristics. The dataset is randomly divided into training and validation sets at a 7:3 ratio. Using 10-fold cross-validation, we employ eight radiomic and deep learning algorithms (such as logistic regression, random forest, and MLP) to train models for predicting the CR of HCC. The performance of the optimal model is then comprehensively evaluated.ResultsA total of 14 clinical datasets were collected, resulting in the extraction of 3,192 radiomic features and 256 deep learning features. Among the clinical datasets, a significant difference was found in the rate of HBV positivity (p<0.05). From the radiomic features, 26 key features were selected and dimensionally reduced, while 5 key features were selected and reduced from the deep learning features. The multimodal feature set (Radiomics + Clinical + Deeplearning) achieved the best AUC results across MLP and several other machine learning models. Notably, the MLP model delivered the highest overall performance, with an AUC of 0.933 in the test set. The accuracy, specificity, and positive predictive value of the MLP model were 0.79, 0.99, and 0.89, respectively.ConclusionThis pilot study established a multimodal model combining radiomics and deep learning to predict the response to ablation therapy in HCC. The model demonstrated robust performance, providing a reliable tool for personalized efficacy assessment and individualized treatment strategies.

BACKGROUND:Metabolic reprogramming is a hallmark of hepatocellular carcinoma (HCC), enabling rapid tumour growth and immune evasion. Protein post-translational modification (PTM) crosstalk is a critical regulator of cellular processes; however, its contribution to metabolic reprogramming in HCC remains unclear. OBJECTIVE:To elucidate the function of the deubiquitinase JOSD1 in modulating PTM crosstalk and its impact on tumour glycolysis, progression and immunotherapy response in HCC. DESIGN:We combined multi-omics analyses with functional and mechanistic studies in cell lines, animal models and patient samples to characterise JOSD1 and its downstream pathways in HCC. RESULTS:JOSD1 was identified as a gene associated with glycolysis and correlated with a poor prognosis. Its over-expression promoted malignant phenotypes and enhanced glycolytic flux. Mechanistically, the JOSD1-AARS1 axis cooperatively regulates the ubiquitination-lactylation crosstalk at the K251 residue of PGAM1, thereby stabilising PGAM1, enhancing its enzymatic activity and promoting lactate accumulation. This metabolic shift impaired CD8+ T cell infiltration and function, promoting immune suppression. Therapeutically, liver-targeted inhibition of JOSD1 effectively suppressed tumour progression and synergised with anti-PD-1 therapy, leading to prolonged survival. CONCLUSION:The JOSD1-AARS1 axis regulates the ubiquitination-lactylation crosstalk on PGAM1, with JOSD1 acting as the critical upstream molecular switch that drives metabolic reprogramming and immune evasion in HCC. Targeting JOSD1 represents a promising therapeutic strategy to modulate tumour metabolism and improve immunotherapy efficacy.

The impact of advanced age on pancreaticoduodenectomy (PD) remains controversial, partly due to inconsistent definitions of “elderly”. To determine the optimal age cut-off for risk stratification and evaluate the safety of different surgical approaches and anastomotic techniques in elderly patients, this study retrospectively analyzed clinical data of 7,028 patients who underwent PD between 2014 and 2019 at 21 centers. Logistic regression analysis demonstrated that advancing age was significantly associated with increased risks of clinically relevant postoperative pancreatic fistula (CR-POPF), bile leakage, pulmonary infection, intra-abdominal infection, and mortality. The optimal age cut-off for predicting CR-POPF was determined as 65 years using receiver operating characteristic curve analysis and the Youden index. Patients were stratified into younger and elderly groups based on this threshold. Both before and after propensity score matching, the elderly group continued to demonstrate significantly higher rates of CR-POPF (before matching: 9.02

Background Liver transplantation is restricted by high costs and donor shortages, necessitating exploration of alternative treatments for hepatocellular carcinoma (HCC) with significant portal hypertension (CSPH). This study examined whether synchronous hepatectomy and splenectomy (HS) improves survival over hepatectomy (H) in patients with BCLC stage 0/A HCC and CSPH. Methods A total of 525 patients with BCLC stage 0/A HCC and CSPH from 12 centers were under review. Among these, 300 patients underwent H (H group) and 225 underwent HS (HS group). Propensity score matching resulted in 157 matched pairs of patients. The study compared both short-term and long-term outcomes between the two groups. Results The HS group had higher rates of massive intraoperative bleeding (15.3 % vs. 6.4 %), abdominal bleeding (5.1 % vs. 0.6 %), and portal vein thrombosis (14.0 % vs. 3.8 %), but no significant differences in 30-day mortality or overall morbidity. In terms of long-term outcomes, the HS group showed better overall survival (59.0 vs. 48.0 months, P = 0.031) and recurrence-free survival (41.0 vs. 28.0 months, P = 0.017), with lower incidences of variceal bleeding (1.9 % vs. 7.6 %) and liver failure mortality (3.8 % vs. 13.4 %). Multivariate analysis identified splenectomy as a significant prognostic factor for improved OS and RFS. Conclusion HS could be a reasonable alternative for patients with BCLC stage 0/A HCC and CSPH. This combined therapeutic strategy enhances long-term survival through various mechanisms while maintaining an acceptable level of perioperative risk.

Both laparoscopic hepatectomy (LH) and robotic hepatectomy (RH) have been performed for tumors in nearly all liver segments. However, few studies have compared the outcomes of patients who underwent open hepatectomy (OH), LH and RH for the treatment of Barcelona Clinic Liver Cancer (BCLC) stage 0-A HCC in S7/8. The clinical data of patients who underwent S7/8 resection for the treatment of BCLC stage 0-A HCC in the First Affiliated Hospital of Guangxi Medical University from July 2017 to July 2023 were retrospectively collected. To minimize selection bias, propensity score matching (PSM) analysis was performed using American Society of Anesthesiology (ASA), tumor size, body mass index (BMI), alpha-fetoprotein (AFP), tumor location, age, number of tumors, platelet (PLT), and Viral hepatitis. A total of 401 patients met the study criteria. After PSM, 61 OH (28.6