iLIVER最新文献

{"title":"Nucleic acid therapeutics for liver diseases: A decade of technological convergence and clinical challenges","authors":"Yufei Pan ,&nbsp;Mingyue Pan ,&nbsp;Yuanzheng Huang ,&nbsp;Baoping Lian ,&nbsp;Yutian Feng ,&nbsp;Juan Liu ,&nbsp;Xiaoxuan Liu","doi":"10.1016/j.iliver.2025.100178","DOIUrl":"10.1016/j.iliver.2025.100178","url":null,"abstract":"<div><div>This review synthesizes a decade of advancements in nucleic acid therapeutics for liver diseases, incorporating bibliometric analysis and translational evaluation. The field has evolved from foundational viral vector engineering to precision genome editing and RNA-based modulation, with advancements in CRISPR-Cas9 and innovations in non-viral delivery systems. Our analysis highlights the concentrated research efforts made in metabolic disorders and hepatocellular carcinoma, and reveals an emerging emphasis on multifactorial pathologies. Although clinical milestones highlight important advancements in targeting strategies, significant challenges remain in immune compatibility and preclinical translation. The integration of computational modeling, human-relevant disease models, and combinatorial strategies places nucleic acid therapies in a unique position to tackle the evolving global liver disease burden through mechanism-driven interventions.</div></div>","PeriodicalId":100657,"journal":{"name":"iLIVER","volume":"4 3","pages":"Article 100178"},"PeriodicalIF":0.0,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517883","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “A retrospective cohort study to examine the association between the persistence of abdominal pain after cholecystectomy and ejection fraction on HIDA scan in patients with biliary dyskinesia” [iLIVER 2 (2023) 208–213]","authors":"Baldeep Kaur Mann ,&nbsp;Janpreet Singh Bhandohal ,&nbsp;Ishaan Kalha ,&nbsp;Brian Jean","doi":"10.1016/j.iliver.2025.100162","DOIUrl":"10.1016/j.iliver.2025.100162","url":null,"abstract":"","PeriodicalId":100657,"journal":{"name":"iLIVER","volume":"4 2","pages":"Article 100162"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144336022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Effects of Raf kinase inhibitor protein on biological characteristics of hepatocellular carcinoma cells and its potential therapeutic effects” [iLIVER 1 (2022) 275–282]","authors":"Zhang Lin,&nbsp;Zhu Jianhua,&nbsp;Wu Kai,&nbsp;Hou Yanhong,&nbsp;Liu Haorun","doi":"10.1016/j.iliver.2025.100161","DOIUrl":"10.1016/j.iliver.2025.100161","url":null,"abstract":"","PeriodicalId":100657,"journal":{"name":"iLIVER","volume":"4 2","pages":"Article 100161"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144335920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating mixed reality, augmented reality, and artificial intelligence in complex liver surgeries: Enhancing precision, safety, and outcomes","authors":"Xianxing Wang ,&nbsp;Jiali Yang ,&nbsp;Beichuan Zhou ,&nbsp;Li Tang ,&nbsp;Yongxing Liang","doi":"10.1016/j.iliver.2025.100167","DOIUrl":"10.1016/j.iliver.2025.100167","url":null,"abstract":"<div><div>Hepatobiliary surgeries, particularly hepatectomy and liver transplantation, are critical interventions for hepatic malignancies and end-stage liver diseases. These complex procedures face challenges due to the liver's intricate anatomy and vascularization. The integration of Mixed Reality (MR), Augmented Reality (AR), and Artificial Intelligence (AI) is increasingly enhancing the precision, safety, and outcomes of these surgeries. MR and AR improve visualization of anatomical structures, assist in preoperative planning, and support patient education through immersive 3D models. AI-driven technologies provide real-time intraoperative feedback and navigation, optimizing surgical decisions and minimizing risks. Postoperatively, these technologies aid in patient education and recovery management, ultimately improving outcomes. This review explores the applications of MR, AR, and AI in liver surgeries and their potential to transform surgical practice by enhancing precision, safety, and patient engagement.</div></div>","PeriodicalId":100657,"journal":{"name":"iLIVER","volume":"4 2","pages":"Article 100167"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to previously published articles","authors":"","doi":"10.1016/j.iliver.2025.100157","DOIUrl":"10.1016/j.iliver.2025.100157","url":null,"abstract":"","PeriodicalId":100657,"journal":{"name":"iLIVER","volume":"4 2","pages":"Article 100157"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144335917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “Ascorbic acid ameliorates isoniazid-rifampicin-induced hepatocellular damage in rats” [iLIVER 1 (2022) 72–77]","authors":"Shubham Patel,&nbsp;Aman Chaturvedi,&nbsp;Nazneen Dubey,&nbsp;Abhishek Shrivastava,&nbsp;Aditya Ganeshpurkar","doi":"10.1016/j.iliver.2025.100159","DOIUrl":"10.1016/j.iliver.2025.100159","url":null,"abstract":"","PeriodicalId":100657,"journal":{"name":"iLIVER","volume":"4 2","pages":"Article 100159"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144335918","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Corrigendum to “A HRG novel mutation associated with idiopathic portal hypertension: Case report and literature review” [iLIVER 1 (2022) 90–95]","authors":"Shan Tang ,&nbsp;Li Bai ,&nbsp;Wei Zhang ,&nbsp;Wenyan Song ,&nbsp;Hui Liu ,&nbsp;Lei Li ,&nbsp;Chen Liang ,&nbsp;Zhongping Duan ,&nbsp;Sujun Zheng","doi":"10.1016/j.iliver.2025.100160","DOIUrl":"10.1016/j.iliver.2025.100160","url":null,"abstract":"","PeriodicalId":100657,"journal":{"name":"iLIVER","volume":"4 2","pages":"Article 100160"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144335919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy and safety of PD-1 inhibitors for advanced intrahepatic cholangiocarcinoma with or without MAFLD","authors":"Teng Long ,&nbsp;Zhenyun Yang ,&nbsp;Weijie Wu ,&nbsp;Minshan Chen ,&nbsp;Dandan Hu","doi":"10.1016/j.iliver.2025.100169","DOIUrl":"10.1016/j.iliver.2025.100169","url":null,"abstract":"<div><h3>Background</h3><div>This study sought to evaluate the efficacy and safety of programmed cell death protein-1 (PD-1) inhibitor immunotherapy specifically in metabolic dysfunction-associated fatty liver disease (MAFLD)-associated intrahepatic cholangiocarcinoma (ICC) patients, in comparison to those without MAFLD.</div></div><div><h3>Methods</h3><div>We retrospectively included 161 ICC patients, both with and without MAFLD, who underwent PD-1 inhibitors between March 2019 and August 2024. Subsequent locoregional interventions (e.g., hepatic arterial infusion chemotherapy) and second-line systemic agents (e.g., lenvatinib) were allowed. The primary endpoints included overall survival (OS) and progression-free survival (PFS), while the secondary endpoints comprised objective response rate (ORR), disease control rate (DCR), and adverse events (AEs).</div></div><div><h3>Results</h3><div>The MAFLD group included 20 patients, while the Non-MAFLD group comprised 141 patients. The OS was 18.0 months for the MAFLD group and 20.1 months for the Non-MAFLD group, while the median PFS was 8.0 and 11.5 months, respectively. According to the modified RECIST (mRECIST) criteria, the Non-MAFLD group exhibited a greater clinical benefit, reflected in higher ORR and DCR (45.4% vs. 20.0%, <em>p</em> = 0.031; 92.9% vs. 75.0%, <em>p</em> = 0.024). Multivariate Cox proportional hazard analysis identified carcinoembryonic antigen (CEA), tumor number, and C-reactive protein (CRP) as independent prognostic factors for OS, whereas CEA and tumor number were significant predictors of PFS. Additionally, the overall incidence of AEs was notably lower in the Non-MAFLD group compared to the MAFLD group.</div></div><div><h3>Conclusion</h3><div>This study demonstrated that PD-1 inhibitors resulted in similarly prolonged OS and PFS between ICC patients with and without MAFLD, but a superior tumor response was observed in patients without MAFLD. Additionally, the Non-MAFLD group experienced a significantly lower incidence of AEs than the MAFLD group undergoing PD-1 inhibitors.</div></div>","PeriodicalId":100657,"journal":{"name":"iLIVER","volume":"4 2","pages":"Article 100169"},"PeriodicalIF":0.0,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144205447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advances in magnetic resonance imaging for the evaluation of colorectal liver metastases in context of individualized precision medicine","authors":"Yidi Chen ,&nbsp;Yu Zhang ,&nbsp;Yi Wei ,&nbsp;Hanyu Jiang ,&nbsp;Ling Zhang ,&nbsp;Liling Long ,&nbsp;Bin Song ,&nbsp;Tao Peng","doi":"10.1016/j.iliver.2025.100168","DOIUrl":"10.1016/j.iliver.2025.100168","url":null,"abstract":"<div><div>Colorectal liver metastases (CRLM) represent a significant clinical challenge, as they are a leading cause of morbidity and mortality in patients with colorectal cancer (CRC). Early detection, accurate diagnosis, and precise treatment planning are crucial for improving patient outcomes. Magnetic resonance imaging (MRI) has emerged as a cornerstone in evaluating CRLM. This article provides a comprehensive review of recent innovations in MRI for CRLM diagnosis and treatment, with a particular focus on precision surgical models. Additionally, the application of artificial intelligence (AI) and radiomics is explored, highlighting their potential in automating lesion detection, evaluating treatment response, and predicting patient survival. The integration of these advanced imaging techniques and AI-based models holds promise for enhancing clinical decision-making, enabling personalized treatment strategies, and improving patient outcomes in CRLM. As these technologies continue to evolve, they could revolutionize the management of CRLM, offering non-invasive, accurate, and cost-effective solutions for early detection, monitoring, and prognosis prediction in CRC patients.</div></div>","PeriodicalId":100657,"journal":{"name":"iLIVER","volume":"4 2","pages":"Article 100168"},"PeriodicalIF":0.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144134609","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiphase MRI radiomics model for predicting microvascular invasion in HCC: Development and clinical validation","authors":"Yue Peng ,&nbsp;Songxiong Wu ,&nbsp;Bing Xiong ,&nbsp;Fuqiang Chen ,&nbsp;Nazar Zaki ,&nbsp;Ruodai Wu ,&nbsp;Wenjian Qin","doi":"10.1016/j.iliver.2025.100165","DOIUrl":"10.1016/j.iliver.2025.100165","url":null,"abstract":"<div><h3>Background and aims</h3><div>Accurate preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) is crucial for treatment planning. This study aimed to develop and validate a multi-phase magnetic resonance imaging (MRI)-based radiomics model for predicting MVI in HCC patients.</div></div><div><h3>Methods</h3><div>This retrospective study included 110 HCC patients (training: <em>n</em> = 77; validation: <em>n</em> = 33) who underwent preoperative multi-phase MRI. Radiomics features were extracted from four MRI phases (non-contrast, arterial, portal, and hepatobiliary). Feature selection was performed using least absolute shrinkage and selection operator regression, and five machine learning classifiers were evaluated. Model performance was assessed using standard metrics including area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and accuracy.</div></div><div><h3>Results</h3><div>The four-phase radiomics model with logistic regression classifier showed optimal performance in both the training (AUC = 0.896; 95% confidence interval, 0.792–0.963) and validation cohorts (AUC = 0.889, 95% confidence interval, 0.781–0.982), outperforming the single-phase (AUC = 0.789), two-phase (AUC = 0.815), and three-phase models (AUC = 0.848) in the validation cohort. In the validation cohort, the model achieved balanced performance with sensitivity, specificity, accuracy, and precision all reaching 0.857.</div></div><div><h3>Conclusions</h3><div>The multi-phase MRI-based radiomics model significantly improves MVI prediction accuracy in HCC patients. This non-invasive approach could enhance preoperative assessment and treatment planning.</div></div>","PeriodicalId":100657,"journal":{"name":"iLIVER","volume":"4 2","pages":"Article 100165"},"PeriodicalIF":0.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144099544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}