World Journal of Gastroenterology最新文献

Li et al's recent work on the risk factors for autoimmune gastritis provides clinical context for the vast majority of gastric neuroendocrine tumors (G-NETs). However, a deeper understanding of the underlying pathology is needed for precise clinical management. Our letter details the predictable stepwise progression of type 1 G-NETs from autoimmune-driven corporal atrophy and hypergastrinemia to a clear microscopic sequence of enterochromaffin-like cell precursor lesions, including linear hyperplasia, micronodular hyperplasia, and dysplasia. We highlight the definitive diagnostic thresholds that separate these precursors from overt neoplasia: The 0.5 mm size rule and the presence of submucosal invasion. We advocate for a "prognostic biopsy protocol" in which pathologists actively report these precursor lesions and use Ki-67 to grade G-NETs, providing a quantitative risk assessment. This pathology-centric approach transforms surveillance, allowing clinicians to act on objective microscopic milestones rather than waiting for macroscopically visible tumors.

With the global rise in sedentary lifestyles, obesity, and unhealthy dietary patterns, dyslipidemia has emerged as a leading modifiable risk factor for atherosclerotic cardiovascular disease. Beyond host genetics and diet, the gut microbiota has gained recognition as a critical regulator of lipid homeostasis through mechanisms involving bile acid metabolism, short-chain fatty acid signaling, and microbial modulation of inflammation. Lv et al provide a comprehensive synthesis of the diet microbe-lipid axis and therapeutic strategies, including probiotics, prebiotics, and fecal microbiota transplantation. In this correspondence, we expand on their framework by highlighting underexplored yet clinically relevant dimensions, including circadian rhythm alignment, pharmacotherapy microbe crosstalk, population-specific microbial signatures, and functional microbial phenotyping. Addressing these overlooked aspects could accelerate the translation of microbiome science into precision dyslipidemia management, with the potential to improve cardiovascular outcomes worldwide.

Background: Liver fibrosis is a global health issue that lacks effective treatments. Tibetan medicine, with a long history, has accumulated rich experience in the treatment of chronic liver diseases. The saffron (Saf) and Calculus bovis (Cal b) combination is among the most commonly used medicines in clinical practice in Tibetan medicine for hepatic disease. Its characteristic therapies and drug compatibility provide unique ideas for the treatment of liver fibrosis and have research value and application potential.

Aim: To investigate the efficacy of the Saf-Cal b therapy in treating liver fibrosis and explored its underlying mechanism.

Methods: We initially established a carbon tetrachloride-induced rat liver fibrosis model to assess Saf-Cal b's anti-fibrotic effects. Subsequently, we conducted network pharmacology analysis to identify the potential therapeutic targets and pathways of Saf-Cal b in liver fibrosis intervention. Finally, we performed in vivo validation of key regulatory targets.

Results: Saf-Cal b combination therapy exerted superior effects in ameliorating liver fibrosis in model rats compared with Saf or Cal b monotherapy. Through network pharmacology prediction, key targets of the combination were identified. Mechanistic validation revealed that Saf-Cal b inhibited the p38 mitogen-activated protein kinases pathway, which in turn suppressed the transforming growth factor-β/small mother against decapentaplegic pathway. This sequential inhibition led to reduced activation of hepatic stellate cells, a central event in liver fibrosis progression.

Conclusion: These findings demonstrate that Saf-Cal b combination therapy is more effective than either monotherapy in alleviating liver fibrosis, with its therapeutic effect mediated through the p38 mitogen-activated protein kinases/transforming growth factor-β/small mother against decapentaplegic signaling axis, providing a potential therapeutic strategy for liver fibrosis.

Background: As a prominent drainage method, endoscopic retrograde cholangiopancreatography (ERCP) with stenting has been universally employed to treat malignant perihilar biliary obstruction (MPHBO). Nonetheless, postoperative biliary infection (PBI) constitutes a remarkable complication associated with this procedure, which can result in fatal outcomes under some circumstances.

Aim: To investigate the risk factors and predict the occurrence of PBI following ERCP drainage in patients suffering from MPHBO.

Methods: This retrospective study analyzed data from patients who underwent ERCP drainage at three different centers. Independent risk factors for PBI were identified by adopting multivariate analyses. Logistic regression model and artificial neural network (ANN) models were developed and validated to predict PBI.

Results: A total of 288 patients who underwent 403 ERCP procedures were included in the study. The incidence of PBI was 39% (158/403). As evidently demonstrated by multivariate analysis, the Bismuth-Corlett classification (odds ratio [OR] = 1.412; 95% confidence interval [CI]: 1.144-1.743; P = 0.001), hypokalemia (OR = 4.080; 95%CI: 1.958-8.505; P < 0.001), and aspartate transaminase (AST) (OR = 1.003; 95%CI: 1.000-1.006; P = 0.021) were independent risk factors for PBI. Simultaneously, both a logistic regression model (area under the curve [AUC] = 0.734) and an ANN model (AUC = 0.867) were developed by adopting these factors. As suggested by a validation through 45 additional cases, the ANN model demonstrated an AUC of 0.940, surpassing the logistic regression model's AUC of 0.791.

Conclusion: The Bismuth-Corlett classification, hypokalemia, and AST levels were identified as independent risk factors for PBI following ERCP drainage. The ANN model was proven to be an effective approach for the anticipation of the PBI occurrence.

Existing literature indicates that prolonged insertion time is associated with procedural complexity and may influence adenoma detection. Xu et al recently reported that longer insertion time correlates with lower adenoma detection, but this effect can be mitigated by sufficient withdrawal duration. Insertion time should not be regarded merely as a numeric variable but rather as a multidimensional marker of technical difficulty. Integrating the insertion-to-withdrawal ratio with composite indicators such as looping or bowel preparation quality may enhance predictive models of colonoscopy performance. Conceptualizing insertion time in this way provides a more nuanced understanding of its role in adenoma detection and highlights the need for improved frameworks that link procedural complexity with quality outcomes.

Background: Split liver transplantation (SLT) effectively expands the donor pool but carries a higher risk of early postoperative complications (EPC) due to the extensive transection surface and altered hemodynamics of partial grafts.

Aim: To establish an interpretable machine learning framework to identify risk factors for EPC in adult recipients undergoing right tri-segment SLT.

Methods: We retrospectively analyzed 109 adult SLT recipients, including 37 who developed EPC. A comprehensive set of perioperative donor and recipient variables was evaluated using four machine learning algorithms (random forest, support vector machine, extreme gradient boosting, and logistic regression). SHapley Additive exPlanations were employed to rank variable importance. Independent predictors were further validated through multivariate logistic regression, and a diagnostic nomogram was constructed. Restricted cubic spline, receiver operating characteristic, and survival analyses were conducted to evaluate model performance and clinical outcomes.

Results: EPC occurred in 33.9% of recipients. Among the machine learning models, random forest demonstrated the best predictive performance. SHapley Additive exPlanations analysis identified the log-transformed systemic immune-inflammation index (LnSII), albumin-to-fibrinogen ratio, model for end-stage liver disease (MELD) score, partial lobectomy of segment IV (IV PL), intraoperative blood loss, and operation time as major contributors to the model. Multivariate logistic regression confirmed LnSII, MELD scores, IV PL, and blood loss as independent predictors of EPC. The nomogram constructed from these factors showed good discrimination and calibration (area under the curve = 0.788, 95% confidence interval: 0.734-0.906). Kaplan-Meier analysis revealed that both LnSII and MELD scores were associated with five-year overall survival (P < 0.05), while MELD score and IV PL were significantly correlated with early postoperative liver function recovery.

Conclusion: IV PL during right tri-segment SLT appears to reduce the risk of EPC and enhance postoperative liver function recovery. Together with LnSII, blood loss, and MELD score, these factors offer a reliable foundation for individualized perioperative risk stratification and management.

Background: Tumor necrosis factor-α (TNF-α) has been implicated in the development of diabetes following chronic pancreatitis. However, its role in abnormal glucose metabolism (AGM) after acute pancreatitis (AP) and post-pancreatitis diabetes mellitus remains unclear.

Aim: To investigate the role of TNF-α in AP-associated AGM and its effects on islet β-cell apoptosis, focusing on the underlying molecular mechanisms.

Methods: Clinical data were collected to assess AGM's incidence and identify the characteristics in 369 AP patients. In vitro, AP models were established using lipopolysaccharide in 266-6 acinar cells and MIN-6 β-cells. Cell proliferation, apoptosis, and protein expression were analyzed using the Cell Counting Kit-8 assay, terminal deoxynucleotidyl transferase dUTP nick-end labeling assay, and western blotting. The TNF-α and insulin concentration in co-culture medium was measured by enzyme-linked immunosorbent assay. In vivo, an AP mouse model was induced using sodium taurocholate, and pancreatic tissues were analyzed through hematoxylin and eosin staining, terminal deoxynucleotidyl transferase dUTP nick-end labeling, and western blotting. TNF-α levels were assessed by enzyme-linked immunosorbent assay. A TNF-α inhibitor was applied to the AP cell model to reassess apoptosis and protein expression.

Results: AGM occurred in 40.38% of AP patients. Body mass index, severity grade, recurrence frequency, and lung injury were significantly associated with AGM. AP models in 266-6 and MIN-6 cells showed reduced β-cell proliferation, insulin secretion, and increased apoptosis, which correlated with inflammation severity. Similar findings of β-cell apoptosis were confirmed in the mouse model. TNF-α levels were significantly elevated in AP models, with higher levels in severe inflammation. Increased Bax and caspase-3 expression and decreased Bcl-2 expression were observed in both in vitro and in vivo models. These changes intensified with increasing inflammation. TNF-α inhibition reduced apoptosis and altered protein expression patterns, decreasing Bax and caspase-3, while increasing Bcl-2 in MIN-6 cells.

Conclusion: TNF-α contributes to β-cell apoptosis and AGM in AP through the Bax/Bcl-2/caspase-3 signaling pathway, suggesting TNF-α as a potential therapeutic target for preventing AP-associated AGM.

Gastrointestinal (GI) cancers represent a major global health concern due to their high incidence and mortality rates. Foundation models (FMs), also referred to as large models, represent a novel class of artificial intelligence technologies that have demonstrated considerable potential in addressing these challenges. These models encompass large language models (LLMs), vision FMs (VFMs), and multimodal LLMs (MLLMs), all of which utilize transformer architectures and self-supervised pre-training on extensive unlabeled datasets to achieve robust cross-domain generalization. This review delineates the principal applications of these models: LLMs facilitate the structuring of clinical narratives, extraction of insights from medical records, and enhancement of physician-patient communication; VFMs are employed in the analysis of endoscopic, radiological, and pathological images for lesion detection and staging; MLLMs integrate heterogeneous data modalities, including imaging, textual information, and genomic data, to support diagnostic processes, treatment prediction, and prognostic evaluation. Despite these promising developments, several challenges remain, such as the need for data standardization, limited diversity within training datasets, substantial computational resource requirements, and ethical-legal concerns. In conclusion, FMs exhibit significant potential to advance research and clinical management of GI cancers. Future research efforts should prioritize the refinement of these models, promote international collaborations, and adopt interdisciplinary approaches. Such a comprehensive strategy is essential to fully harness the capabilities of FMs, driving substantial progress in the fight against GI malignancies.

Background: Helicobacter pylori (H. pylori) infection is highly prevalent worldwide, and rising antibiotic resistance has reduced the efficacy of standard therapy, underscoring the need for simplified and better-tolerated regimens.

Aim: To evaluate the efficacy, safety, and optimal dosing of vonoprazan (VPZ)-amoxicillin (AMO) dual therapy in a non-inferiority randomized trial for H. pylori eradication.

Methods: In this multi-center, randomized trial conducted at 17 hospitals in Sichuan Province, China, 1717 adults with confirmed infection were assigned (1:1:1) to 14-day regimens: (1) VPZ 20 mg BID + AMO 0.5 g QID; (2) 0.75 g QID; or (3) 1.0 g TID. The primary endpoint was the eradication rate based on intention-to-treat (ITT) and per-protocol (PP) analyses; secondary endpoints included adverse events (AEs) and treatment compliance.

Results: Eradication rates were consistently high (92.35%-97.43%). In the 0.5 g QID group, ITT and PP eradication rates were 93.3% (95%CI: 91.2-95.1) and 97.4% (95%CI: 95.7-98.5), respectively, with no significant differences among groups (P > 0.05). Compliance ranged from 98.1% to 98.3%, and AEs were infrequent (5.2%-7.5%), predominantly mild gastrointestinal symptoms, which occurred least often in the 0.5 g QID group.

Conclusion: VPZ-AMO dual therapy achieved excellent eradication, safety, and patient compliance. All regimens were similarly effective, whereas the 0.5 g QID dosing strategy offered the most favorable balance of efficacy and tolerability, supporting its use as a first-line option in high-prevalence settings.