Liver Transplantation

Efferocytosis-associated transcriptomic patterns characterize prognosis and immune landscape in osteosarcoma.

BACKGROUND: Osteosarcoma (OS) is the most common primary malignant bone tumor in adolescents, characterized by high heterogeneity and poor prognosis. Efferocytosis, the clearance of apoptotic cells, has been implicated in tumor progression and immune evasion, but its role in OS remains unclear. METHODS: We integrated TARGET-OS as a training cohort with three GEO datasets for validation. Efferocyto...

Incidence and implications of abstinence-induced recompensation in alcohol-related cirrhosis.

BACKGROUND & AIMS: Alcohol abstinence enables hepatic recompensation in patients with decompensated alcohol-related cirrhosis. This study investigated the incidence, predictors, and impact of abstinence-induced recompensation. METHODS: This multicentre study included patients with decompensated alcohol-related cirrhosis at time of abstinence until 12/2022. Recompensation was defined by Baveno-VII ...

A machine learning-based prediction model for poor prognosis in sepsis using lymphocyte count: a national, multicenter prospective cohort.

Sepsis-induced immunosuppression leads to poor prognosis. Circulating lymphocyte count (LC), as an easily accessible clinical marker, closely reflects...

Numerical modeling and prediction of late estimated glomerular filtration rate in kidney transplant recipients based on machine learning models and the Monte Carlo simulation method.

OBJECTIVES: This paper presents an experimental numerical method for modeling and analyzing stochastic systems. For this purpose, various machine pred...

Longitudinal Peripheral Blood Transcriptomics Reveal Novel Signatures During Cardiac Allograft Rejection.

BACKGROUND: Acute cellular rejection (ACR) remains a major cause of morbidity after heart transplantation despite advances in immunosuppression. Whole...

Unbiased clustering of acute-on-chronic liver failure patients using machine learning in a real-world ICU cohort.

Acute-on-chronic liver failure is a complex condition with varied definitions, complicating risk stratification and targeted management. We apply unsu...

Large-scale serum N-glycomics tracks N-glycosylation dynamics in hepatocellular carcinoma progression and enables early diagnosis.

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality, yet the role of N-glycosylation in its pathogenesis remains unclear. We applied...

Semi-Supervised Fatty Liver Classification Using Attention-Based Graph Neural Network Models.

BACKGROUND: Fatty liver disease is a common condition linked to metabolic syndrome, cardiovascular diseases, and liver cirrhosis, and timely, accurate...

Integrated multi-omics analysis of prognostic model and immune microenvironment in intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (iCCA) is an aggressive malignancy originating from the epithelial lining of second-order bile ducts. Desp...

Morphological characterization of a novel model of steatohepatitis in the FAH-/- pig.

Metabolic dysfunction-associated steatohepatitis (MASH) is a global health care burden. Appropriate large animal models mimicking the main MASH charac...

Liver cancer risk stratification using deep learning on nationwide longitudinal health screening data: a retrospective cohort study.

BACKGROUND: Current liver cancer screening in Korea focuses on viral hepatitis or cirrhosis, despite rising risks from metabolic and alcohol-related l...

Integrating multi-omics and machine learning systematically deciphers cellular heterogeneity and fibrotic regulatory networks in the progression from MASLD to MASH.

The progression from metabolic dysfunction-associated steatotic liver disease (MASLD) to metabolic dysfunction-associated steatohepatitis (MASH) is a ...

An interpretable machine learning model for prediction of significant liver fibrosis in comorbid chronic hepatitis B and nonalcoholic fatty liver disease: a retrospective development and validation study.

A Comparative Study of Machine Learning Models for Identification of Antiviral Peptides Using Various Encoded Features.

Viruses are a significant threat to human life, as demonstrated by the global COVID-19 pandemic and the Ebola outbreak. Diseases such as smallpox, AID...

B-cell-directed Immunotherapy for Solid Tumors.

B-cell-directed immunotherapy holds great promise for treating solid tumors, where barriers such as desmoplastic stroma and low immunogenicity have li...

Performance analysis of liver segmentation using nn-UNet TotalSegmentator: Focus on atypical livers, pathologies, and variants.

RATIONALE AND OBJECTIVES: This study evaluates the accuracy of the nn-UNet TotalSegmentator (TS) by Wasserthal et al. (2023) in segmenting atypical li...

Integrating CAR-T therapy with PD-1/PD-L1 blockade: Mechanisms, synergy, and optimized strategies in NSCLC.

Non-small cell lung cancer (NSCLC) presents persistent challenges in immunotherapy, as the clinical benefit of programmed cell death protein 1 (PD-1) ...

Comprehensive review on immunotherapy for hepatocellular carcinoma: Current status and future perspectives.

Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, remains a major global health concern due to its high incidence and mort...

Nerves Stimulates Crosstalk between Gastric Cancer and Group 3 Innate Lymphoid Cells to Enhance Immunosuppression.

The immunosuppressive tumor microenvironment (TME) enables cancer cells to evade clinical immunotherapies. Neural networks are vital components of the...

Programmable Smart CAR-T design: A new paradigm in precision immunotherapy driven by logic gates, conditional activation, allogeneic strategies, and artificial intelligence.

Chimeric antigen receptor T-cell (CAR-T) therapy has achieved unprecedented success in hematological malignancies but faces formidable challenges in s...