Liver regeneration necessitates coordinated cytoskeletal dynamics, yet the key molecular orchestrators remain incompletely defined. Intriguingly, recent studies reveal a novel role for hepatocyte-derived Igκ in promoting hepatocyte survival during liver injury. However, the precise mechanisms by which immunoglobulin κ (Igκ) governs liver regeneration and its potential as a central coordinator remain elusive. This study aims to elucidate the role of Igκ in liver regeneration following injury and to define the underlying molecular mechanisms. Igκ expression was assessed in liver biopsies from patients with drug-induced liver injury (DILI) using immunohistochemistry. To investigate its role in regeneration, hepatocyte-specific Igκ-knockout mice were subjected to partial hepatectomy (PHx) or acetaminophen (APAP)-induced acute liver injury. Functional and mechanistic studies were performed in the normal human hepatocyte cell line THLE-2 through Igκ knockdown or overexpression, combined with multi-omics profiling, immunoprecipitation, and mass spectrometry. The therapeutic potential of Igκ was validated by AAV8-mediated hepatic delivery of Igκ in knockout mice. Igκ expression is significantly upregulated in both human DILI patients and murine injury models upon hepatic damage. Hepatocyte-specific Igκ deletion impaired liver regeneration, characterized by disrupted cytoskeletal organization and diminished hepatocyte proliferation. Mechanistically, Igκ directly binds to myosin light chain kinase (MYLK), shielding it from K48-linked ubiquitination and proteasomal degradation, thereby preserving cytoskeletal integrity and facilitating Yes-associated protein (YAP) nuclear translocation to activate proliferative pathways. Crucially, AAV8-mediated hepatic Igκ delivery in knockout mice rescues MYLK protein levels, restores cytoskeletal integrity, and promotes liver regeneration. Our study identifies Igκ as a pivotal regulator of liver regeneration by stabilizing MYLK to maintain cytoskeletal dynamics and potentiate YAP-dependent proliferative signaling, thereby proposing a potential therapeutic strategy for enhancing hepatic repair.
Liver fibrosis is a key pathological process in the progression of chronic liver disease toward cirrhosis and liver failure. The development of liver fibrosis is closely related to a variety of etiologies, including alcoholic hepatitis, metabolic dysfunction-associated steatotic liver disease (MASLD), viral hepatitis, and drug-induced liver injury. Although advances in antiviral therapies for hepatitis B have contributed to a decline in its incidence, other etiologies such as MASLD and alcoholic hepatitis are becoming the main drivers for liver fibrosis. Currently, the management of liver fibrosis primarily focuses on controlling the underlying causes of liver fibrosis, including antiviral therapy and the cessation of alcohol or drug exposure. However, effective therapeutic options for advanced fibrosis remain limited, resulting in severe complications such as hepatic encephalopathy and portal hypertension, which markedly increase patient mortality and socioeconomic burden. Therefore, early diagnosis and timely intervention for liver fibrosis are essential to prevent disease progression. With the ongoing advancement of modern molecular biology technologies, our understanding of the pathogenesis and pathophysiology of liver fibrosis continues to deepen. In this review, we summarize the molecular mechanisms, diagnostic approaches, current treatments, and potential therapeutic targets for liver fibrosis.
Early intra-abdominal infections (EIAIs) are among the most frequent and life-threatening complications following liver transplantation (LT). Early identification of high-risk patients remains challenging, and no standardized risk stratification tool is currently available. To develop and externally validate interpretable machine learning (ML) models for preoperative and postoperative prediction of EIAIs after LT. A multicenter retrospective cohort study. A total of 363 adult LT recipients were included (Center 1: n = 285; Center 2: n = 78). EIAIs were defined as intra-abdominal infections occurring within 30 days after LT. From 120 candidate variables, predictors were selected using random forest, LASSO regression, and univariate logistic regression. Seven ML algorithms were evaluated, and stacking ensemble models were selected as the final preoperative (pre-liver transplantation early intra-abdominal infection forecast tool (LIFT)) and postoperative (post-LIFT) models. Internal testing and external validation were performed. Model interpretability was assessed using SHapley Additive exPlanations (SHAP). The stacking models demonstrated superior performance. For pre-LIFT, the areas under receiver operator characteristic curve (ROC) curves (AUCs) were 0.995 ± 0.004 (training), 0.818 ± 0.056 (testing), and 0.796 ± 0.024 (external validation). For post-LIFT, AUCs were 0.996 ± 0.003, 0.847 ± 0.055, and 0.858 ± 0.026, respectively. Both models significantly outperformed model for end-stage liver disease and Child-Turcotte-Pugh scores (all p < 0.05). SHAP analysis revealed that baseline liver dysfunction, inflammatory markers, and immune status were key determinants in the pre-LIFT model, whereas perioperative factors such as intraoperative blood loss, ICU stay, and drainage duration predominated in the post-LIFT model. We developed and externally validated interpretable ML-based models (LIFT) for predicting EIAIs after LT. These models enable individualized risk stratification at both preoperative and postoperative stages and may support personalized infection surveillance and management strategies. Prospective validation is warranted. Using artificial intelligence to predict early abdominal infections before and after liver transplantation: a study developing easy-to-use computer models to help doctors prevent and manage postoperative infections Liver transplantation can save the lives of people with severe liver disease, but infections in the abdomen are a common and dangerous problem soon after surgery. These infections can be hard to detect early because symptoms are often unclear, and test results may take time. Doctors often use broad antibiotics to prevent infections, but this can lead to side effects and antibiotic resistance. In this study, we used artificial intelligence-based methods, known as machine learning, to help predict which patients are most likely to develop early abdominal infections after liver transplantation. We collected information from 285 transplant patients at Beijing Friendship Hospital between 2020 and 2024 and 78 patients from Tianjin First Central Hospital. The information included patient characteristics, blood test results, and details from the surgery and recovery period. Two artificial intelligence models were developed: one that predicts infection risk before the operation (called pre-LIFT) and one that predicts risk after surgery (post-LIFT). These models combined data from several advanced algorithms and showed high accuracy in identifying patients at risk. Important factors included whether the patient had a repeat transplant, blood albumin and bilirubin levels, lymphocyte count, and how long the surgical drain remained in place. By using these models, doctors can better identify high-risk patients before and after surgery. This will allow them to adjust antibiotic use, monitor patients more closely, and provide care that matches each patient’s needs. This study provides interpretable artificial intelligence models (LIFT) for predicting early abdominal infections after liver transplantation. It supports more personalized prediction and may help reduce complications and improve patient recovery.
Liver fibrosis represents a critical stage in the progression of chronic liver diseases to cirrhosis and hepatocellular carcinoma; however, effective therapeutic options remain limited. Although quercetin, a natural flavonol, possesses potent antifibrotic properties, its clinical utility is severely hindered by poor aqueous solubility and low bioavailability. To address this limitation, we developed a nanoparticle-based drug delivery system using quercetin-loaded human umbilical cord mesenchymal stem cell (hUC-MSC)-derived exosomes (hUC-MSC-exo-Que). Leveraging the innate biocompatibility and targeting capability of exosomes, this strategy aims to improve the pharmacokinetic limitations of quercetin and amplify its therapeutic efficacy. Our results demonstrate that hUC-MSC-exo-Que significantly attenuates liver fibrosis in a carbon tetrachloride-induced mouse model, outperforming free quercetin at the equivalent dose. This enhanced efficacy is attributed to the superior inhibition of hepatic stellate cell activation, as confirmed by in vitro studies. The engineered exosomes exhibited a sustained drug release profile (up to 48 h) and maintained excellent stability for at least 1 week. Integrating network pharmacology with experimental validation, we identify the antifibrotic mechanism involving potent inhibition of the PI3K/Akt signaling pathway, with hUC-MSC-exo-Que achieving markedly greater pathway suppression than free quercetin. By successfully transforming a potent but poorly bioavailable phytochemical into a targeted nanotherapeutic, we present a promising preclinical strategy for liver fibrosis treatment and demonstrate a proof-of-concept platform for hydrophobic drug delivery.
Primary liver cancer (represented by hepatocellular carcinoma and intrahepatic cholangiocarcinoma) is a common clinical malignant liver tumor with a high mortality burden. The disease has high heterogeneity, and diagnosis stratification and efficacy evaluation heavily rely on imaging. Among imaging modalities, ultrasound, with its advantages of real-time imaging, gradually improving resolution, and dynamic assessment of multi-parameter information such as blood flow perfusion, is continuously expanding its application scenarios in the liver cancer diagnosis and treatment chain along with the rapid development of a series of new technologies. In recent years, technologies such as microvascular blood flow ultrasound, super-resolution ultrasound, three-dimensional multi-parameter contrast-enhanced ultrasound, viscoelasticity, and dispersive imaging have developed rapidly, enabling more refined acquisition of blood flow, perfusion, and mechanical information related to liver cancer. Simultaneously, workflow technologies such as integrated navigation and artificial intelligence-assisted procedures have promoted more precise and visual positioning, quantification, and evaluation during interventional procedures and provided a foundation for the further introduction of closed-loop simulation and decision support frameworks represented by digital twins. This article focuses on the two key aspects of liver cancer diagnosis and treatment, systematically reviews the above-mentioned ultrasound technologies' new clinical value and applicable scenarios and limitations, and looks forward to directions such as standardization, multi-center validation, and workflow integration, with the aim of providing a reference for clinical practice and research design. 原发性肝癌（以肝细胞癌和肝内胆管癌为代表）是临床常见且死亡负担沉重的肝脏恶性肿瘤，疾病异质性强，诊断分层与疗效评估高度依赖影像学。其中，超声凭借实时、分辨率逐步提高及对血流灌注等多参数信息动态评估的优势，正随着一系列新技术快速发展而不断拓展其在肝癌诊疗链条中的应用场景。近年来，微血流成像、超分辨率超声、三维多参数对比增强超声、黏弹性与频散成像等技术快速发展，使肝癌相关的血流、灌注与力学信息获取更精细；与此同时，融合导航与人工智能辅助等工作流技术推动介入过程定位、量化、评估更为精准可视，并为进一步引入以数字孪生为代表的闭环仿真与决策支持框架提供基础。该文围绕肝癌诊断与治疗两大关键环节，系统梳理上述超声新技术的临床价值、适用场景与局限，并对标准化、多中心验证与工作流整合等方向进行展望，以期为临床实践与研究设计提供参考。.
Autoimmune hepatitis (AIH) is an immune-mediated chronic liver disease with an increasing incidence. The complex pathogenesis of AIH poses significant challenges for clinical treatment. In recent years, with the introduction of cutting-edge concepts such as "immune-metabolic interplay" and "intercellular communication networks," along with novel detection methods and technologies, research on the pathogenesis of AIH has shifted from a single-molecular-mechanism perspective to a systematic regulatory network analysis. This shift has not only provided more research evidence for a deeper understanding of the molecular biological mechanisms underlying AIH but also offers a potential reference for the development of targeted therapeutic drugs for AIH based on novel targets. Therefore, this review starts with aberrant activation signals from key immune cells-including dendritic cells (DCs), macrophages (Mφ), and T/B cells-and integrates the intercellular signaling communication mechanisms between hepatocytes, cholangiocytes, and immune cells to systematically summarize the key molecular biological mechanisms and targets identified in recent years, providing a reference for future elucidation of the critical mechanisms of AIH. On this basis, the review further integrates the current application and research progress of clinically used AIH therapeutic drugs, as well as those at various stages of development, including potential therapeutic compounds. It discusses the limitations of current clinical drugs and evaluates the feasibility and future application potential of potential compounds for AIH treatment in preclinical and clinical studies, thereby offering comprehensive research evidence for the management of AIH.
The nuclear receptor Nurr1 (NR4A2) is a transcriptional regulator of inflammatory homeostasis, but its systemic effects on orchestrating inter-organ communications are largely unknown. Here we show that Nurr1 haplo-insufficiency results in a lethal coupled disorder across the liver-gut axis. Using a CRISPR-Cas9 generated murine model, we find that metabolically-activated heterozygous deficiency of Nurr1 results in profound hepatocellular necrosis and marked hepatic activation of inflammatory and pro-fibrotic genes coupled with dysregulation of the intestinal barrier, and severe small-intestinal dysbiosis. Multi-omics integration reveals a highly penetrant transcriptional signature of this herein termed liver-gut disorder, achieving up to 0.950 accuracy (SVM-RBF, 10-fold cross-validation) in classifying genotypes from integrated multi-omics features. Notably, we also demonstrate that these gene level perturbations in Nurr1 haplo-insufficiency can be thought of as learnable tissue 'morphologies' detectable by AI. Next, we created deep convolutional neural networks that accurately classify genotype from routine histopathology. Our algorithm achieves 99.50% accuracy in classifying hepatic fibrosis (Sirius Red), 99.20% in liver inflammation (H&E) and 92.31% in intestine (H&E). We provide the first multi-omics phenotype of Nurr1 deficiency, revealing its pivotal regulatory role in coordinating liver-gut homeostasis, and establishing a histopathological AI-driven framework. Grad-CAM saliency analysis confirms biological interpretability. Translational relevance is supported by human transcriptomic data (E-GEOD-61260) showing concordant upregulation of COL1A1 (log2FC= + 0.725, p < 0.01), TGFB1 (+ 0.429, p < 0.05), and MMP9 (+ 0.969, p < 0.01) alongside reduced NR4A2/NURR1 in human liver disease.
Benzovindiflupyr (BZF) is a newly developed succinate dehydrogenase inhibitor (SDHI) fungicide that is widely used in crop protection, but its potential effects on non-target aquatic organisms remain a concern. In this study, we exposed adult zebrafish (Danio rerio) to 5.0 and 50 μg/L BZF for 28 days. We investigated its impact on the gut-liver axis using a combination of microbiome, biochemical, histological, and metabolomic analyses. BZF exposure damaged intestinal structure, downregulated barrier-related genes, and altered the composition of the gut microbiota. At the same time, serum lipopolysaccharide (LPS) levels increased, which indicates impaired intestinal barrier integrity and microbial dysbiosis. In the liver, BZF caused histopathological alterations, increased serum ALT, AST, and ALP activities, enhanced oxidative stress, and upregulated inflammation-related genes. Liver metabolomic profiling further showed marked disturbances in redox balance and metabolic homeostasis. Correlation analysis also revealed significant associations between altered microbial taxa and differential liver metabolites. Taken together, these results suggest that BZF exposure disrupted intestinal homeostasis and was associated with hepatic metabolic disturbance in zebrafish, potentially through gut-liver axis perturbation. This study expands current understanding of the toxic effects of SDHI fungicides and provides useful evidence for the ecological risk assessment of BZF in aquatic environments.
Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the most prevalent chronic liver disorder worldwide, characterized by complex molecular regulatory networks driving its pathogenesis. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), serve as critical regulators of gene expression and have been increasingly recognized for their pivotal roles in MASLD development. Rather than functioning in isolation, these ncRNAs form intricate regulatory networks that integrate and amplify disease signals across multiple cellular compartments and pathological stages. This review provides a comprehensive overview of how these ncRNA networks orchestrate MASLD progression, focusing on their roles in metabolic dysregulation, inflammation, and fibrosis. We further evaluate the diagnostic potential of circulating ncRNAs as stable, non-invasive biomarkers for disease stratification and monitoring, and discuss emerging therapeutic strategies targeting ncRNAs, including antisense oligonucleotides, synthetic mimics, and advanced delivery platforms such as lipid nanoparticles and engineered exosomes. Despite significant progress, challenges related to delivery efficiency, tissue specificity, and safety remain barriers to clinical translation. By synthesizing current knowledge of ncRNA networks in MASLD and highlighting opportunities for therapeutic intervention, this review provides a roadmap for translating ncRNAs into clinical applications for this increasingly prevalent metabolic liver disease.
The use of laparoscopic procedures for liver transplantation (LT) remains controversial. This study aimed to present our preliminary experience with a minimally invasive pediatric living donor liver transplantation (LDLT). The medical records of pediatric patients who underwent laparoscopy-assisted LDLT, namely laparoscopic mobilization of the diseased liver followed by open explant hepatectomy and graft implantation using an upper midline incision at Beijing Friendship Hospital between November 2019 and March 2023, were retrospectively reviewed, focusing on demographics and pre-, intra-, and postoperative outcomes. Laparoscopy-assisted LDLT was successfully performed in all 13 pediatric patients. The mean total operative time was 478 min (range, 315-615 min), the median portal vein clamping time was 47 min (range, 33-107 min), the average time required to remove the liver was 229 min (range, 115-357 min), and the median cold ischemia time was 85 min (range, 29-214 min). The intraoperative course for all the recipients was uneventful. All patients recovered well without any significant acute postoperative problems, with only one patient presenting with hepatic artery thrombosis on postoperative day 1 who made a good recovery after immediate thrombectomy and re-anastomosis. During a median follow-up of 41.8 (range, 24.3-64.3 months), all recipients survived with 100% graft survival. This is the world's largest single-center cohort study of pediatric laparoscopy-assisted LDLT using an upper midline incision. Our results provide preliminary evidence for the safety and feasibility of minimally invasive LDLT in selected pediatric patients, which may be a reasonably compromised strategy before attempting pure laparoscopic LT. Chinese Clinical Trial Registry Identifier: ChiCTR2400086319.
The liver and kidneys are often synchronously affected by various diseases, posing significant health challenges. Simultaneously monitoring their damage would benefit rational drug use. Herein, a new probe, SQE-715-CD, was developed to concurrently assess liver and kidney injuries using in vivo NIR-II fluorescence imaging. In addition to diagnostic advancements, this research delves into the therapeutic potential of flavonoids in protecting against liver and kidney damage caused by cisplatin. Among the seven flavonoids tested, Apigenin stands out for its substantial reduction in cisplatin-induced toxicity in both organs. Further experiments reveal that Apigenin's pretreatment lowers kidney inflammation and inhibits the activation of crucial signaling molecules p38, ERK, and JNK. These results suggest a possible mechanism behind Apigenin's protective effects and underscore its significance in reducing nephrotoxicity. The capability for in vivo simultaneous monitoring of liver and kidney functions proposed in this study could provide another therapeutic drug evaluation and screening method.
Liver cancer (LC) remains one of the most prevalent tumors globally. Despite considerable advancements in its clinical treatment in recent years, the global burden of this disease is projected to increase. According to World Health Organization statistics, the number of LC deaths worldwide in 2022 was 760,000, ranking third among all cancers. Therefore, there is an urgent need to delve deeper into the realms of LC diagnosis, prognosis, and treatment. Proteomics, as an emerging technology leveraging mass spectrometry (MS)-based protein identification, liquid chromatography separation, and bioinformatics-driven data integration, enables the systematic characterization of proteome dynamics to address critical challenges in LC research. These challenges include the discovery of diagnostic and prognostic biomarkers as well as therapeutic targets. By scrutinizing the expression of specific proteins in both normal and cancerous tissues through high-throughput protein microarrays, researchers can uncover novel biomarkers. The use of these biomarkers alone or in combination with established ones holds the potential to significantly advance the fields of LC diagnosis, prognosis, and treatment. In general, the application of proteomics has significantly promoted the development of LC research. In this review, we summarized the latest advancements in the application of proteomics in LC, with a particular focus on diagnosis, prognosis, and treatment. We also concluded selected protein markers, aiming to offer guidance for further applications and present additional therapeutic targets for LC.
As the central metabolic organ, the liver coordinates fundamental biological processes through its specialized cellular architecture and regulatory networks, encompassing metabolism, immunity, and regeneration. Kupffer cells (KCs), the liver-resident macrophages, exhibit functional heterogeneity beyond classical polarization paradigms. Currently, multiple classification systems for KCs have been established utilizing distinct surface markers. However, there is no systematic theoretical framework for the classification of KCs. The strategic positioning of KCs within the hepatic Disse space enables intricate intercellular communication networks with neighboring hepatocytes for coordinated physiological regulation. Their functional plasticity critically regulates systemic iron and metabolic homeostasis, with KC-driven metabolic reprogramming directly influencing hepatic pathophysiology. Furtherly, KC activity shows spatiotemporal regulation by circadian rhythms and nutrient signals, reshaping the liver microenvironment to affect function. This review summarizes advances in liver macrophage biology, highlighting the classification challenges of KCs and their roles in hepatic physiology. Additionally, we discuss how circadian rhythms, aging, diet, and exercise dynamically influence KC functionality, which provides a framework to interpret their regulatory logic and dysfunction in disease.
Metabolic dysfunction-associated steatotic liver disease (MASLD) has emerged as the leading cause of chronic liver disease worldwide, coinciding with the growing burden of obesity and type 2 diabetes mellitus. While liver biopsy remains the gold standard for assessing hepatic steatosis and fibrosis, its invasiveness, sampling variability, and limited feasibility have necessitated the establishment of non-invasive diagnostic alternatives. Among non-invasive alternatives, conventional B-mode ultrasound (US) has retained a central role as the first-line imaging modality owing to its wide availability, low cost, and reasonable sensitivity and specificity, particularly in moderate-to-severe steatosis. However, traditional B-mode US has several limitations, including operator dependence, poor sensitivity in mild steatosis, and reduced accuracy in obese individuals. Semi-quantitative scoring systems and emerging technologies such as attenuation imaging, shear wave elastography, and vibration-controlled transient elastography, have been recently introduced to improve diagnostic accuracy. Additionally, artificial intelligence (AI) is increasingly being integrated into US platforms to enhance image interpretation, standardize assessments, and reduce interobserver variability. This review provides a comprehensive appraisal of the diagnostic performance, strengths, and limitations of conventional B-mode US and its advanced products in the context of MASLD. US-based techniques are also compared with magnetic resonance spectroscopy and histological assessment, highlighting the evolving role of AI in US diagnostics. Given the global rise of MASLD, optimizing and standardizing US-based approaches are essential to improve early detection, risk stratification, and monitoring strategies. With continued technological refinement and integration of AI, US remains a cornerstone of MASLD diagnosis in clinical practice.
Xiangsu Tongjiang Hewei Granules are an herbal preparation that has shown potential for controlling symptoms of nonerosive gastroesophageal reflux disease (NERD) in preliminary studies. However, high-quality randomized controlled evidence for its use in NERD remains lacking. To verify the efficacy and safety of Xiangsu Tongjiang Hewei Granules in treating NERD with liver stomach stagnation heat syndrome. This randomized, double-blind, placebo-controlled, multicentre phase III trial included 480 patients (aged 18-65 years) with confirmed NERD (GerdQ≥8; negative H. pylori) and traditional Chinese medicine (TCM) liver stomach stagnation heat syndrome. Patients were randomized 3:1 to receive either Xiangsu Tongjiang Hewei Granules or placebo, thrice daily for 8 weeks. The primary outcomes were the effective rate of the response based on visual analog scale (VAS) scores for heartburn and acid regurgitation at week 8. The secondary outcomes included reductions in the TCM syndrome score, etc. RESULTS: 479 participants (mean age 48.5 years, SD10.2; 54.3% female) entered the full analysis set and safety set (360 tests group; 119 control group, 1 participant in the control group withdrawing before medication). At week 8, compared with the control group, the test group demonstrated significantly better effective rate of VAS score response for heartburn(76.39% vs 21.01%, 95% CI 55.38 (45.98, 62.94) %, p <0.01),acid regurgitation (79.72% vs 23.53 %, 95% CI56.39 (46.90, 64.12) %, p <0.01), and TCM syndrome score (69.23% vs 30.13%, p < 0.01) at week 8. In this selected population of NERD patients with liver-stomach stagnation heat syndrome (e.g., negative H. pylori, no pH-impedance phenotype, and low anxiety/depression scores), Xiangsu Tongjiang Hewei Granules demonstrated efficacy and safety in improving heartburn, acid regurgitation, and TCM syndrome scores. However, generalizability to the broader NERD population and its comparative effectiveness against standard proton pump inhibitor therapy require further investigation.
Fatty liver disease (FLD) is among the most prevalent chronic liver disorders worldwide. Tomato-derived lycopene has received considerable attention as a functional bioactive compound due to its strong antioxidant and anti-inflammatory effects on molecular pathways associated with FLD progression. Nevertheless, an integrated assessment of lycopene sources, chemistry, extraction technologies, stability, and functional efficacy remains limited. Lycopene bioavailability is restricted by its lipophilic nature and instability during food processing and gastrointestinal digestion. Degradation pathways including photo-oxidation, thermal trans-cis isomerization, and oxidative cleavage are intensified during high-temperature drying (>70 °C), prolonged storage, light exposure, and oxygen-rich processing conditions, resulting in reduced stability and biological activity. Advanced emerging delivery systems such as nanoencapsulation, nanoemulsions, and lipid-based carriers have shown promising improvements in lycopene protection, absorption, and efficacy. Future approaches including biofortification, personalized nutrition, and synergistic formulations may support the development of innovative functional foods for FLD prevention and management.
Background The optimal sequencing of thermal ablation relative to systemic therapy for colorectal liver oligometastases (CLOM) remains controversial, with limited evidence to guide treatment planning. Purpose To compare the long-term survival outcomes of patients with CLOM receiving upfront ablation (UA) versus delayed ablation (DA) in combination with systemic therapies. Materials and Methods Patients with five or fewer CLOM (maximum lesion diameter, <5 cm) from 21 Chinese tertiary hospitals were included in this multicenter cohort study (October 2009 to March 2024). Patients were categorized into UA and DA groups based on the decisions of multidisciplinary teams. UA consisted of microwave ablation followed by adjuvant systemic therapy administered within 1 month. DA involved neoadjuvant systemic therapy (delivered over 2-3 months) combined with subsequent ablation. The primary outcome was progression-free survival (PFS), and a secondary outcome was overall survival (OS), both assessed using multivariable-adjusted Cox regression analysis and Kaplan-Meier survival curves. Procedure-related complication rates were analyzed. Sensitivity analyses, including propensity score matching, inverse probability treatment weighting, and overlap weighting, were performed to adjust for confounders. Results A total of 1047 patients were included (DA group [n = 536]: mean age, 57.53 years ± 10.99 [SD]; 381 male; UA group [n = 511]: mean age, 60.96 years ± 11.77; 356 male). The follow-up duration was 15 years. Median PFS (1.48 vs 0.98 years; hazard ratio [HR], 0.70 [95% CI: 0.61, 0.81]; P < .001) and OS (6.94 vs 4.74 years; HR, 0.70 [95% CI: 0.57, 0.87]; P = .001) were longer in the UA group compared with the DA group. Sensitivity analyses confirmed robustness (PFS HR, 0.67-0.80; OS HR, 0.73-0.77). UA benefits persisted across subgroups, including synchronous metastases (HR, 0.67 [95% CI: 0.55, 0.81]; P = .04) and lesions smaller than 3 cm (HR, 0.68 [95% CI: 0.58, 0.80]; P = .005). Elevated carcinoembryonic antigen levels (≥5 µg/L) and multiple metastases independently predicted worse survival (HR, 1.30 and 1.47, respectively; P < .001 for both). Conclusion UA combined with systemic therapy significantly improved long-term survival compared with DA, with similar complication rates. © RSNA, 2026 Supplemental material is available for this article. See also the editorial by Woodrum in this issue.
Hepatitis B virus (HBV) infection poses a significant challenge to global health, particularly in developing countries such as China, where HBV-related acute liver failure (HBV-ALF) is a prominent cause of acute liver failure. This study investigated the effect of cuproptosis, a recently identified form of cell death, on immune infiltration in HBV-ALF. We mined the gene expression data of HBV-ALF from the Gene Expression Omnibus database. Through enrichment analysis of differentially expressed genes (DEGs), pathways related to the response to metal/copper ions and the acute inflammatory response were found to be enriched. We subsequently found that HBV-ALF tissues contained more copper ions and conducted an intersection analysis of DEGs and cuproptosis-related genes (CRGs), which resulted in the identification of 7 core cuproptosis-related DEGs (CR-DEGs) for further investigation with a diagnostic model. Immune infiltration analysis and unsupervised clustering analysis revealed distinct patterns in HBV-ALF and the possibility of crosstalk between ferroptosis and cuproptosis. Furthermore, we identified 17 transcription factors, 90 miRNAs, and 15 drugs that might interact with the 7 CR-DEGs. To validate our findings and their clinical significance, we verified the diagnostic value and immune infiltration patterns of the 7 CR-DEGs in both the testing dataset, cell line, and clinical samples. In conclusion, our findings indicated that these 7 CR-DEGs demonstrate promising diagnostic value and may represent viable therapeutic targets for individuals with HBV-ALF.
The mechanism of cholestatic liver injury (CLI) is unclear, and effective therapies are lacking. While peroxisome proliferator-activated receptor alpha (PPARα) agonists show potential hepatoprotective effect and pyroptosis is implicated in hepatocellular damage, how PPARα activation mitigates lithocholic acid (LCA)-induced pyroptosis remains unknown. The hepatoprotective effect of PPARα agonists was evaluated in a mouse model of intrahepatic cholestasis induced by LCA. Liver injury was assessed via serum biochemistry, hematoxylin and eosin and TUNEL staining, and electron microscopy. Pyroptosis pathways were analyzed using real-time quantitative polymerase chain reaction, Western blot, and co-immunoprecipitation. Combined morphological, histopathological, and biochemical analyses confirmed that PPARα activation protects against CLI. Compared with LCA treatment alone, PPARα activation significantly attenuated the elevation of serum lactate dehydrogenase (LDH), the increased TUNEL-positive cells, and the formation of hepatocyte membrane pores. Mechanistically, PPARα activation suppressed both NOD-like receptor protein 3 (NLRP3) inflammasome-mediated pyroptosis and apoptosis protease-activating factor-1 (APAF-1)/CASPASE-3/GSDME-mediated pyroptosis. Furthermore, PPARα agonist pretreatment inhibited activation of the nuclear factor-kappa B (NF-κB) and forkhead box O1 (FOXO1) signaling pathways. PPARα protects against LCA-induced CLI by inhibiting both NLRP3 inflammasome-mediated pyroptosis associated with NF-κB and APAF-1/CASPASE-3/GSDME-mediated pyroptosis associated with the FOXO1 signaling pathway.
Circulating tumor DNA (ctDNA) enables noninvasive tumor genotyping, yet its concordance with tissue remains unclear. Using a 437-gene panel in 1111 pan-cancer patients, we compared somatic variants between ctDNA and matched tissues. ctDNA detection sensitivity (61.5%) correlated with advanced stage (r = 0.955, p = 0.045) and tumor size (r = 0.955, p = 0.045). Actionable alterations were detected in 49.2% (ctDNA) and 77.1% (tissue) of patients. Both shared frequently mutated genes (TP53, APC, KRAS, LRP1B, PIK3CA) and pathways (RTK-RAS, p53, DNA repair). ctDNA-specific mutations were predominantly subclonal (61.5% vs. 9.7% in tissue-concordant variants) and less frequently drivers. Machine learning linked elevated concordance to progressive disease, liver metastasis, and larger tumors. ctDNA-positivity predicted worse prognosis (HR = 2.019, p < 0.001), exacerbated by subclonal enrichment. These findings underscore ctDNA's capacity to reveal subclonality for risk stratification. While tissue remains superior for initial detection, ctDNA complements biopsies by capturing clonal heterogeneity.