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Error in: Artificial Intelligence-Assisted Capsule Endoscopy Versus Conventional Capsule Endoscopy for Detection of Small Bowel Lesions: A Systematic Review and Meta-Analysis: Request for Correction. 错误:人工智能辅助胶囊内窥镜与传统胶囊内窥镜检测小肠病变:系统回顾和荟萃分析:要求纠正。
IF 3.4 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Pub Date : 2026-01-15 DOI: 10.1111/jgh.70248
Ian Io Lei, Ramesh P Arasaradnam
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引用次数: 0
Response to the Letter on "Role of ALBI Grade as a Predictive Factor for Long-Term Mortality in Patients With Hepatocellular Carcinoma (HCC) Undergoing Transarterial Chemoembolization (TACE)". 对“ALBI分级作为肝细胞癌(HCC)经动脉化疗栓塞(TACE)患者长期死亡率预测因素的作用”的回复。
IF 3.4 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Pub Date : 2026-01-15 DOI: 10.1111/jgh.70246
Kyoung A Ko, Won Sohn
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引用次数: 0
Response to: An Overview of Predictive Biomarkers and Detection Approaches for Immunotherapy Response in GI Malignancies. 响应:胃肠道恶性肿瘤免疫治疗反应的预测性生物标志物和检测方法综述。
IF 3.4 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Pub Date : 2026-01-15 DOI: 10.1111/jgh.70242
Eunjae Yoo, Amiko M Uchida
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引用次数: 0
Nomogram Predicting Survival in Gastroesophageal Variceal Bleeding Treated With Sclerotherapy and Cyanoacrylate 用硬化疗法和氰基丙烯酸酯治疗胃食管静脉曲张出血的Nomogram生存率预测。
IF 3.4 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Pub Date : 2026-01-14 DOI: 10.1111/jgh.70212
Yingzhi Pang, Han Wang, Linggui Ding, Yao Chen, Liangliang Ye, Wei Yan

Background and Aims

This study aimed to develop and validate a survival prediction model for patients with gastroesophageal variceal bleeding treated with combined sclerotherapy and cyanoacrylate injection.

Methods

Patient data were retrospectively collected and randomly divided into training and validation cohorts (7:3). Key prognostic variables in the training cohort were identified using random survival forest (RSF), least absolute shrinkage and selection operator (LASSO) regression, and extreme gradient boosting (XGBoost). A nomogram was developed with the Cox proportional hazards model. Kaplan–Meier (KM) curves assessed stratified survival, SHapley Additive exPlanations (SHAP) analysis interpreted variable contributions, and bootstrap resampling was used for internal validation. Model performance was evaluated by receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA).

Results

The concordance index for 1- and 3-year survival was 0.736 and 0.735 in the training cohort and 0.847 and 0.865 in the validation cohort. Time-dependent ROC analysis showed AUCs of 0.736 (95% CI: 0.648–0.824) and 0.735 (95% CI: 0.657–0.813) in the training cohort and 0.869 (95% CI: 0.794–0.944) and 0.879 (95% CI: 0.812–0.945) in the validation cohort. Calibration curves demonstrated good agreement, and DCA confirmed substantial net clinical benefit across threshold probabilities ranging from 0.2 to 0.6.

Conclusions

The prognostic nomogram integrating age, MELD score, and the risk of rebleeding after combined endoscopic therapy demonstrated good clinical applicability and may provide a valuable reference for individualized treatment and follow-up management.

背景与目的:本研究旨在建立并验证经硬化剂联合氰基丙烯酸酯注射治疗胃食管静脉曲张出血患者的生存预测模型。方法:回顾性收集患者资料,随机分为训练组和验证组(7:3)。使用随机生存森林(RSF)、最小绝对收缩和选择算子(LASSO)回归以及极端梯度增强(XGBoost)来确定训练队列中的关键预后变量。采用Cox比例风险模型建立了nomogram。Kaplan-Meier (KM)曲线评估分层生存,SHapley加性解释(SHAP)分析解释变量贡献,bootstrap重采样用于内部验证。通过受试者工作特征(ROC)曲线、校正图和决策曲线分析(DCA)评估模型的性能。结果:训练组1年和3年生存率的一致性指数分别为0.736和0.735,验证组为0.847和0.865。时间相关ROC分析显示,训练组auc分别为0.736 (95% CI: 0.648-0.824)和0.735 (95% CI: 0.657-0.813),验证组auc分别为0.869 (95% CI: 0.794-0.944)和0.879 (95% CI: 0.812-0.945)。校准曲线显示出良好的一致性,DCA确认了在0.2至0.6的阈值概率范围内的实质性净临床效益。结论:综合年龄、MELD评分和内镜联合治疗后再出血风险的预后图具有较好的临床适用性,可为个体化治疗和随访管理提供有价值的参考。
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引用次数: 0
Multicenter Analysis of the Learning Curve for Endoscopic Ultrasound-Guided Gallbladder Drainage: A Cumulative Sum Approach. 超声内镜引导胆囊引流学习曲线的多中心分析:累积和法。
IF 3.4 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Pub Date : 2026-01-12 DOI: 10.1111/jgh.70239
Dongwook Oh, Ho Seung Lee, Sung Hyun Cho, Gunn Huh, Dong-Wan Seo, Min-Ju Kim, Seong-Hun Kim, Tae Jun Song

Objectives: Endoscopic ultrasound-guided gallbladder drainage (EUS-GBD) is effective and safe for poor surgical candidates; however, it remains technically challenging with potential serious adverse events. This study evaluated the learning curve for EUS-GBD for safe and effective procedures.

Methods: From January 2016 to January 2024, 146 patients underwent EUS-GBD performed by three endosonographers. We analyzed the baseline characteristics, procedural outcomes, and learning curves using cumulative sum (CUSUM) analysis.

Results: No significant differences were found among the three operators regarding technical success (96.4% vs. 94% vs. 95.1%; p = 0.85), clinical success (96.4% vs. 92% vs. 95.1%; p = 0.61), mean procedure time (8.0 ± 5.7 vs. 9.9 ± 7.9 vs. 9.9 ± 5.1 min; p = 0.24), or procedural adverse events (12.7% vs. 20% vs. 9.8%; p = 0.35). CUSUM analysis revealed that proficiency in procedure time was achieved after performing 27 procedures. Comparing procedure time before and after achieving technical proficiency, technical success (90.6% vs. 98.8%, p = 0.04), clinical success (89.1% vs. 98.8%, p = 0.02), and procedure time (14.45 ± 6.13 min vs. 5.09 ± 2.23 min, p < 0.01) were improved. Adverse event proficiency was reached in 23 procedures, with notable improvements post-proficiency; technical success (87.5% vs. 99%, p = 0.02), clinical success (85.4% vs. 99%, p = 0.01), and procedure time were also improved (15.04 ± 6.43 min vs. 6.33 ± 3.99 min, p < 0.01).

Conclusions: Based on CUSUM analysis, approximately 23 procedures may be required to achieve technical proficiency in EUS-GBD with regard to minimizing adverse events, while 27 procedures are necessary to reach proficiency in terms of procedure time.

目的:超声内镜下胆囊引流术(EUS-GBD)对手术条件差的患者是安全有效的;然而,由于潜在的严重不良事件,它在技术上仍然具有挑战性。本研究评估了EUS-GBD安全有效治疗的学习曲线。方法:2016年1月至2024年1月,146例患者接受3位超声检查。我们使用累积和(CUSUM)分析基线特征、程序结果和学习曲线。结果:三名手术人员在技术成功率(96.4%比94%比95.1%,p = 0.85)、临床成功率(96.4%比92%比95.1%,p = 0.61)、平均手术时间(8.0±5.7比9.9±7.9比9.9±5.1分钟,p = 0.24)和手术不良事件(12.7%比20%比9.8%,p = 0.35)方面均无显著差异。CUSUM分析显示,在完成27个手术后,熟练掌握了手术时间。比较技术熟练前后的手术时间、技术成功率(90.6% vs. 98.8%, p = 0.04)、临床成功率(89.1% vs. 98.8%, p = 0.02)和手术时间(14.45±6.13 min vs. 5.09±2.23 min, p)。结论:基于CUSUM分析,在减少不良事件方面,达到EUS-GBD技术熟练可能需要大约23个手术,而在手术时间方面达到熟练需要27个手术。
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引用次数: 0
Artificial Intelligence Model for Automated Identification of Bowel Preparation for Colonoscopy (AI-PREPOO): A Multicenter Study 结肠镜检查肠准备自动识别的人工智能模型(AI-PREPOO):一项多中心研究。
IF 3.4 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Pub Date : 2026-01-12 DOI: 10.1111/jgh.70235
Kosuke Kojima, Kazuya Takahashi, Hiroki Maruyama, Nao Nakajima, Hiroki Sato, Ken-ichi Mizuno, Shuji Terai

Background

Adequate bowel preparation is crucial for high-quality colonoscopy; however, assessing preparation adequacy can be burdensome for both healthcare providers and patients. In this study, we aimed to develop artificial intelligence (AI) models for the automated identification of bowel PREParation for cOlonoscOpy (AI-PREPOO).

Methods

On the day of colonoscopy, participants were instructed to use smartphones to photograph their stool in the toilet after each bowel movement following initiation of polyethylene glycol solution and upload the images to a secure web server. All images were labeled as “ready” or “not ready” for colonoscopy based on clarity and the absence of solid content. Using these labeled images, four image-recognition models based on different deep learning architectures (AI-PREPOO 1–4) were developed using transfer learning to classify stool status as “ready” or “not ready.”

Results

A total of 282 stool images were collected from 37 patients, with 141 images labeled as “ready” and 141 as “not ready.” These images were divided into training (224 images) and test (58 images) sets, and the training set was augmented to 2240 images. All models trained on the augmented dataset achieved high performance, with area under the curve (AUC) values exceeding 0.90. AI-PREPOO 1, based on MobileNetV3-Small, demonstrated the most balanced sensitivity–specificity profile (AUC, 0.95; sensitivity, 0.93; specificity, 0.86).

Conclusions

We developed AI-based models capable of accurately assessing bowel preparation adequacy. AI-PREPOO 1 showed a well-balanced diagnostic performance, suggesting its potential to facilitate bowel preparation assessment and reduce the burden on healthcare providers and patients.

背景:充分的肠道准备是高质量结肠镜检查的关键;然而,对医疗保健提供者和患者来说,评估准备是否充分可能是一项繁重的工作。在这项研究中,我们旨在开发人工智能(AI)模型,用于自动识别肠准备结肠镜检查(AI- prepoo)。方法:在结肠镜检查当天,参与者被指示在每次大便后使用智能手机拍摄他们在厕所里的粪便,并将图像上传到安全的web服务器上。根据清晰度和缺乏固体内容物,所有图像被标记为“准备好”或“未准备好”进行结肠镜检查。使用这些标记的图像,使用迁移学习开发了基于不同深度学习架构(AI-PREPOO 1-4)的四种图像识别模型,将粪便状态分类为“准备好”或“未准备好”。结果:共收集了37例患者的282张大便图像,其中141张标记为“准备好”,141张标记为“未准备好”。将这些图像分为训练集(224张)和测试集(58张),并将训练集扩充为2240张。在增强数据集上训练的所有模型都取得了良好的性能,曲线下面积(AUC)值超过0.90。基于MobileNetV3-Small的AI-PREPOO 1表现出最平衡的敏感性-特异性特征(AUC, 0.95;敏感性,0.93;特异性,0.86)。结论:我们开发了基于人工智能的模型,能够准确评估肠道准备的充分性。AI-PREPOO 1显示出平衡良好的诊断性能,表明其有可能促进肠道准备评估并减轻医疗保健提供者和患者的负担。
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引用次数: 0
Therapies Targeting Mucosal Eosinophils in Eosinophilic Gut Diseases From Esophagus to Colon 从食道到结肠嗜酸性肠道疾病中针对粘膜嗜酸性粒细胞的治疗。
IF 3.4 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Pub Date : 2026-01-09 DOI: 10.1111/jgh.70221
Khaliun Batkhurel, Sharmila Prasad, Michael Potter, Jennifer H. Martin, Simon Keely, Nicholas J. Talley

Eosinophilic gastrointestinal disorders (EGIDs) comprise eosinophilic oesophagitis (EoE) and non-EoE EGIDs; these diseases may be increasing in prevalence and are likely underdiagnosed. Mortality is not increased in EoE but is in gastric and small intestinal EGIDs. A subtle increase in eosinophils has also been observed in other GI diseases including functional dyspepsia in the duodenum. Targeted drug therapy can markedly reduce eosinophil infiltration, although symptom response is more variable, suggesting that non–eosinophil pathways play a role in pathogenesis. Current standard therapies for EoE supported by randomized trials include proton pump inhibitors, corticosteroids (topical), diet restriction, and dupilumab, inhibiting IL-4/IL-13 signaling. In non-EoE EGIDs where little randomized trial data exist, management is based on a combination of dietary elimination and corticosteroids or immunomodulators; mast cell stabilizers and antihistamine therapy may have a role. The role of combination therapies is unclear. Pharmacologic approaches in testing include new steroid preparations and delivery systems; dupilumab in eosinophilic gastritis; and anti-IL-13, anti-IL-5, anti-IL-2, and anti-IL-15 receptor targeting monoclonal antibodies.

嗜酸性胃肠道疾病(EGIDs)包括嗜酸性食管炎(EoE)和非EoE型EGIDs;这些疾病的患病率可能正在上升,而且可能未得到充分诊断。EoE的死亡率不增高,但胃和小肠egid的死亡率增高。在包括十二指肠功能性消化不良在内的其他胃肠道疾病中也观察到嗜酸性粒细胞的轻微增加。靶向药物治疗可显著减少嗜酸性粒细胞浸润,但症状反应变化较大,提示非嗜酸性粒细胞途径在发病机制中起作用。随机试验支持的目前EoE的标准治疗包括质子泵抑制剂、皮质类固醇(局部)、饮食限制和抑制IL-4/IL-13信号传导的杜匹单抗。在没有随机试验数据的非eoe egid中,管理是基于饮食消除和皮质类固醇或免疫调节剂的组合;肥大细胞稳定剂和抗组胺治疗可能有作用。联合治疗的作用尚不清楚。药理学测试方法包括新的类固醇制剂和给药系统;Dupilumab治疗嗜酸性胃炎;抗il -13、抗il -5、抗il -2和抗il -15受体靶向单克隆抗体。
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引用次数: 0
LETIM Robustly Predicts Immune Checkpoint Blockade Efficacy for Liver Cancer Patients Using Multiple Immune-Related Genesets LETIM使用多个免疫相关基因集稳健地预测肝癌患者免疫检查点阻断疗效。
IF 3.4 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Pub Date : 2026-01-09 DOI: 10.1111/jgh.70232
Siqi Tang, Wenbin Xie, Zijie Wu, Jiawei Yang, Qiang Liu, Xiangdong Gao, Hong Tian, Wenbing Yao

Background and Aims

Immune checkpoint blockade (ICB) is an important liver cancer treatment but shows obvious variability in clinical response due to the tumor immune microenvironment (TIME) heterogeneity. Reliable models that identify TIME characteristics to predict potential beneficiaries remain lacking.

Methods

We analyzed single-cell RNA sequencing (scRNA-seq) data from ICB responsive and nonresponsive liver cancer patients to establish genesets with both intragroup stability and intergroup variability for immune cell status evaluation. These genesets were applied to bulk RNA sequencing (RNA-seq) data from large cohorts to score and construct an ICB response prediction model.

Results

The study identified immune-related genesets characterizing the influence of 21 immune cell types on ICB response. Using these genesets, we developed the Liver Cancer ExtraTrees Immune-response Model (LETIM). LETIM effectively predicted response by distinguishing TIME features. LETIM surpassed existing models in predictive performance and exhibited excellent generalizability in other large liver cancer sequencing cohorts (area under the receiver operating characteristic curve: 0.88–0.92).

Conclusions

Through comprehensive analysis of the effects of multiple immune cells on ICB response, LETIM achieved accurate prediction of ICB outcomes in liver cancer. Its cross-cohort applicability and robust predictive performance may support clinical translation to enable precision medicine and maximize patient benefits.

背景与目的:免疫检查点阻断(Immune checkpoint blockade, ICB)是一种重要的肝癌治疗方法,但由于肿瘤免疫微环境(TIME)的异质性,其临床反应存在明显的变异性。确定时间特征以预测潜在受益者的可靠模型仍然缺乏。方法:我们分析了来自ICB反应性和非反应性肝癌患者的单细胞RNA测序(scRNA-seq)数据,以建立具有组内稳定性和组间变异性的基因集,用于免疫细胞状态评估。这些基因集被应用于来自大型队列的大量RNA测序(RNA-seq)数据,以评分并构建ICB反应预测模型。结果:该研究鉴定了21种免疫细胞类型对ICB反应影响的免疫相关基因集。利用这些基因集,我们建立了肝癌外树免疫反应模型(LETIM)。LETIM通过识别时间特征有效预测响应。LETIM在预测性能上超越了现有模型,并在其他大型肝癌测序队列中表现出出色的通用性(受试者工作特征曲线下面积:0.88-0.92)。结论:LETIM通过综合分析多种免疫细胞对ICB应答的影响,能够准确预测肝癌患者的ICB结局。它的跨队列适用性和强大的预测性能可能支持临床翻译,以实现精准医学和最大化患者利益。
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引用次数: 0
Practice Guidelines for the Diagnosis and Treatment of Subepithelial Lesion Observed in Upper Gastrointestinal Endoscopy 上消化道内窥镜下上皮下病变的诊断和治疗实践指南。
IF 3.4 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Pub Date : 2026-01-08 DOI: 10.1111/jgh.70225
Beom Jin Kim, Seung Joo Kang, Su Youn Nam, Chang Seok Bang, Byung-Hoon Min, Sung Eun Kim, Seung Young Kim, Hyunchul Lim, Chung Hyun Tae, Moon Won Lee, Seung Han Kim, Sang Hoon Kim, Jong Yeul Lee, Byung-Wook Kim, Jeong Seop Moon, Jong-Jae Park, Hwoon-Yong Jung, Korean College of Helicobacter and Upper Gastrointestinal Research

Subepithelial lesions (SELs) of the upper gastrointestinal tract are commonly detected during endoscopic examinations and encompass a broad spectrum of benign, potentially malignant, and malignant tumors. While most SELs are asymptomatic and incidentally found, accurate diagnosis remains challenging due to their subepithelial location, necessitating advanced imaging and tissue acquisition techniques. Endoscopic ultrasound (EUS) plays a crucial role in differentiating SELs, but its diagnostic accuracy remains limited. In response to the need for standardized clinical management, the Korean College of Helicobacter and Upper Gastrointestinal Research has developed evidence-based practice guidelines for the diagnosis and endoscopic treatment of SELs. These guidelines were established through a systematic review of existing literature and expert consensus, resulting in 11 key recommendations addressing diagnostic strategies, surveillance intervals, biopsy techniques, and indications for endoscopic or surgical resection.

上消化道上皮下病变(SELs)通常在内镜检查中发现,包括广泛的良性,潜在的恶性和恶性肿瘤。虽然大多数SELs无症状且偶然发现,但由于其位于上皮下,因此准确诊断仍然具有挑战性,需要先进的成像和组织采集技术。内镜超声(EUS)在诊断SELs中起着至关重要的作用,但其诊断准确性仍然有限。为了应对规范化临床管理的需要,韩国幽门螺杆菌和上消化道研究学院制定了以证据为基础的sel诊断和内镜治疗实践指南。这些指南是通过对现有文献和专家共识的系统回顾而建立的,产生了11项关键建议,涉及诊断策略、监测间隔、活检技术以及内窥镜或手术切除的指征。
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引用次数: 0
Shikonin Attenuates Liver Ischemia-Reperfusion Injury Through Direct Interaction With HMGB1 Protein 紫草素通过与HMGB1蛋白直接相互作用减轻肝脏缺血再灌注损伤。
IF 3.4 3区 医学 Q2 GASTROENTEROLOGY & HEPATOLOGY Pub Date : 2026-01-07 DOI: 10.1111/jgh.70200
Libang Zhang, Fang Liu, Pingping Shen, Xuewa Jiang, Richa Raj, Jian Zhang, Guolong Li

Background and Aim

Hepatic ischemia-reperfusion (IR) injury represents a critical clinical challenge characterized by excessive inflammation. HMGB1, known as a proinflammatory mediator released after liver IR injury, has been reported to worsen the damage and inflammation via a positive feedback loop. Herein, shikonin has been explored to alleviate hepatic IR injury through direct interaction with HMGB1.

Methods

The ligation on the hilum of the right liver lobe lasted for 90 min and then removed to induce hepatic IR injury in SD rats. Serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were determined. At the cellular level, HMGB1-induced NO release from RAW264.7 was assessed to test the inhibitory effect of shikonin. The surface plasmon resonance (SPR), saturation transfer difference nuclear magnetic resonance (STD-NMR), and molecular dynamics simulation were employed to study the interaction between shikonin and HMGB1.

Results

After administration of shikonin, the degree of liver IR damage in rats was attenuated significantly in a dose-dependent manner. In vitro, shikonin can effectively inhibit HMGB1 activation. Furthermore, mechanistic studies indicated that shikonin could directly bind to HMGB1. The results of 1H STD-NMR confirmed that shikonin interacted with HMGB1, and multiple protons in shikonin participated in the binding process. Notably, shikonin exhibits a selective binding affinity toward the I122 and L129-bearing region of HMGB1, which were supported by molecular dynamics simulation.

Conclusion

In general, our results suggest that shikonin is a promising natural candidate that directly targets HMGB1 to exert hepatoprotection for the development of clinical therapeutic anti-IR agents.

背景和目的:肝缺血再灌注损伤是一种严重的临床挑战,其特征是过度炎症。HMGB1是肝脏IR损伤后释放的促炎介质,有报道称其通过正反馈回路加重损伤和炎症。本研究探讨了紫草素通过与HMGB1直接相互作用减轻肝脏IR损伤的作用。方法:SD大鼠右肝门部结扎90 min后取出肝IR损伤。测定血清天冬氨酸转氨酶(AST)和丙氨酸转氨酶(ALT)。在细胞水平上,通过hmgb1诱导RAW264.7释放NO来检测紫草素的抑制作用。采用表面等离子体共振(SPR)、饱和转移差核磁共振(STD-NMR)和分子动力学模拟等方法研究了紫草素与HMGB1的相互作用。结果:紫草素给药后,大鼠肝脏IR损伤程度明显减轻,且呈剂量依赖性。在体外,紫草素能有效抑制HMGB1的激活。此外,机制研究表明,紫草素可以直接与HMGB1结合。1H STD-NMR结果证实了紫草素与HMGB1相互作用,并且紫草素中的多个质子参与了结合过程。值得注意的是,紫草素对HMGB1的I122和l129承载区具有选择性的结合亲和性,这一点得到了分子动力学模拟的支持。结论:总的来说,我们的研究结果表明,紫草素是一种有前景的直接靶向HMGB1发挥肝保护作用的天然候选药物,可用于临床治疗性抗ir药物的开发。
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引用次数: 0
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Journal of Gastroenterology and Hepatology
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