Liver Transplantation

Intraoperative video-based artificial intelligence model exceeding surgeon accuracy for predicting severe fibrosis in minimally invasive liver surgery.

Accurate evaluation of liver fibrosis is essential for surgical planning in patients with hepatocellular carcinoma (HCC), as advanced fibrosis or cirrhosis can significantly alter resection strategy and postoperative outcomes. However, preoperative assessments using blood-based indices or imaging often fail to accurately reflect the true degree of fibrosis observed intraoperatively. This study aim...

Targeting cholesterol metabolism: a core regulator of tumor-associated macrophage plasticity and immunotherapy response.

Tumor-associated macrophages (TAMs) are one of the main immunosuppressive components in the tumor microenvironment (TME). Growing evidence indicates that their functional state is closely related to metabolic signaling, with cholesterol metabolism dysregulation receiving increasing attention. Abnormal cholesterol metabolism alters membrane lipid composition and signaling pathways, resulting in imp...

Machine learning-based programmed cell death gene signature for prognosis and drug sensitivity in breast cancer.

Breast cancer (BRCA) heterogeneity necessitates robust prognostic biomarkers. Programmed cell death (PCD) serves a key role in tumor progression and t...

Machine Learning in Predicting the Risk of Esophagogastric Variceal Bleeding Among Patients With Liver Cirrhosis: Systematic Review and Meta-Analysis.

BACKGROUND: Liver cirrhosis (LC) can lead to several complications. Esophageal variceal bleeding (EVB) and esophagogastric variceal bleeding (EGVB) ar...

irAE-GPT: leveraging large language models to identify immune-related adverse events in electronic health records and clinical trial datasets.

BACKGROUND: Large language models (LLMs) have emerged as transformative technologies, revolutionising natural language understanding and generation ac...

Magnetically controlled capsule endoscopy: Innovations, standardized practice, and emerging clinical roles.

Capsule endoscopy has transformed small bowel evaluation but remains limited for gastric examination because of passive, peristalsis dependent movemen...

NQO1-Mediated Anoikis Resistance and Immune Evasion Define a High-Risk Multi-Omic Subtype for Precision Management of T1 High-Grade Bladder Cancer.

T1 high-grade (T1HG) bladder cancer represents an aggressive subset of non-muscle-invasive bladder cancer (NMIBC) with frequent Bacillus Calmette-Guér...

A palmitoylation-related prognostic risk scoring model and tumor microenvironment characterization in lung adenocarcinoma, using single-cell RNA sequencing data.

BACKGROUND: Lung adenocarcinoma (LUAD) is the predominant pathological subtype of non-small cell lung cancer. Its considerable tumor heterogeneity and...

LILRB3 inhibition reverses immunosuppression in glioma: a nanoparticle-based therapeutic strategy.

Glioma is a highly aggressive brain tumor characterized by a profoundly immunosuppressive tumor microenvironment dominated by M2-polarized tumor-assoc...

Study on material basis and network mechanism of the Guizhi Fuling pills in the treatment of endometriosis and endometrial polyps.

To explore the material basis and network mechanism of the Guizhi Fuling pills in the treatment of endometriosis and endometrial polyps based on netwo...

Gut microbial extracellular vesicles modulate the development of metabolic dysfunction-associated steatohepatitis through the gut-liver axis.

Metabolic dysfunction-associated steatohepatitis (MASH) represents a growing global health challenge due to its propensity to progress to irreversible...

Deciphering risk factors for severe postherpetic neuralgia in patients with herpes zoster: an interpretable machine learning approach.

INTRODUCTION: Postherpetic neuralgia (PHN) is a common complication of herpes zoster (HZ). This study aimed to use a large real-world electronic medic...

Early Prediction of Hepatic Decompensation in Cirrhosis Using Optimised XGBoost Models at the Initial Outpatient Hepatology Visit.

BACKGROUND AND AIMS: Hepatic decompensation represents a critical transition in cirrhosis, leading to increased morbidity, mortality and healthcare ut...

A metabolite-augmented FIB-4 machine learning panel achieves superior liver fibrosis staging in chronic liver disease.

Accurate, non-invasive liver fibrosis detection is essential for chronic liver disease management, particularly with rising metabolic dysfunction-asso...

Nanoparticle-based immunotherapeutic strategies to overcome cancer drug resistance: From biological barriers to artificial intelligence-driven design.

Although cancer immunotherapy has revolutionized oncology, its clinical efficacy remains substantially limited by both primary and acquired resistance...

Univariate- and machine learning-based plasma metabolite signature differentiates PSC-IBD from IBD and is predicted to be driven by gut microbial changes.

INTRODUCTION: Inflammatory bowel disease (IBD) is a group of chronic inflammatory conditions of the gastrointestinal tract comprising two major phenot...

Proteomic profiling and pathway analyses reveal molecular signatures and immune networks in pediatric sepsis.

BACKGROUND: Sepsis remains a leading cause of childhood mortality worldwide. Most deaths occur within the first few days of presentation, underscoring...

A Deep Learning-Driven Framework Integrating Organoid-Based Functional Validation Identifies Universal Neoantigens from Recurrent Glioma Mutations.

Glioblastoma (GBM) is the most common malignant intracranial tumor in adults, with a median survival of only 16-20 months. Neoantigen therapy has show...

SGA-DT: An adaptive fusion framework for missing data imputation and interpretable healthcare classification.

Despite advances in machine learning and medical data processing, handling missing values remains a critical and complex challenge in healthcare analy...

Evaluation of large language models in supporting autoimmune liver disease diagnosis and clinical decision-making: advantages of reasoning-based models.

INTRODUCTION: Large-language models (LLMs) have demonstrated increasing potential in healthcare, including applications in clinical information retrie...