Liver Transplantation

Novel Machine-Learning Models Outperform Noninvasive Tests in Metabolic Dysfunction-Associated Steatohepatitis With Fibrosis.

BACKGROUND & AIMS: Noninvasive tests (NITs) have not yet been systematically evaluated or optimized to detect metabolic dysfunction-associated steatohepatitis (MASH) with fibrosis stages F2 to F3, the current treatment-eligible group defined by the United States Food and Drug Administration for emerging treatments, or, separately, for cirrhosis (F4). We aimed to assess the performance of existing ...

4-Nonylphenol mediated tumor progression and immune modulation through CDK2: Computational and experimental validation.

As an endocrine-disrupting chemical, 4-nonylphenol (4-NP) has been found above safe limits in global water systems and associated with cancer progression. This multidisciplinary study systematically investigated the carcinogenic mechanisms of 4-NP by integrating network toxicology, machine learning, molecular docking simulations, single-cell RNA sequencing, and spatial transcriptomics. We identifi...

CSF1R and macrophage infiltration: Integrated magnetic resonance imaging radiomics and deep learning-driven models for the preoperative assessment of glioma.

BACKGROUND: Colony-stimulating factor-1 receptor (CSF1R) signaling is crucial for the ability of tumor-associated macrophages (TAMs) to establish an i...

Blood-based Vienna 3P/5P risk models accurately predict first hepatic decompensation in compensated advanced chronic liver disease.

BACKGROUND & AIMS: Invasive measurement of hepatic venous pressure gradient (HVPG) is the gold standard for diagnosing clinically significant portal h...

Amplification-free detection of mycoplasma pneumoniae via CRISPR-Cas12a and deep learning-optimized crRNAs on a lateral flow platform.

Accurate and rapid diagnosis of Mycoplasma pneumoniae infection is essential for reducing its significant health burden. An amplification-free CRISPR-...

Accurate fatty liver disease diagnosis with a multi-source feature fusion model on the segmented tongue image dataset.

INTRODUCTION: More than 100 million individuals in rural areas of China are suffered from Fatty Liver Disease (FLD). However, health clinics in remote...

Improving the performance of the echinococcosis diagnosis model based on serum Raman spectroscopy via the integration of convolutional neural network and support vector machine.

Echinococcosis is a zoonotic parasitic disease characterized by its insidious nature and severe health impacts. Rapid and accurate screening is crucia...

A Retrospective Cohort Study on 28-Day Mortality in Immunosuppressed Sepsis: An Interpretability-Based Predictive Model Using MIMIC-IV V2.2.

BACKGROUND: Sepsis in immunosuppressed patients is associated with significantly higher mortality rates, yet predictive models tailored to this high-r...

Advanced liver fibrosis detection using a two-stage deep learning approach on standard T2-weighted MRI.

OBJECTIVES: To develop and validate a deep learning model for automated detection of advanced liver fibrosis using standard T2-weighted MRI. METHODS: ...

QDCRNet: Quantum dilated convolutional recurrent network for virus detection using gene expression data.

Viral Infections cause several common human illnesses, like the common cold, flu, mouth blisters, and chickenpox. However, numerous viruses, including...

Toward a unified pipeline for natural product discovery: tools and strategies for NRPS and PKS pathway exploration and engineering.

Covering: up to 2025.Non-ribosomal peptide synthetases and polyketide synthases are modular biosynthetic systems that produce structurally diverse and...

Assessment and management of portal hypertension in patients with MASLD: advances and caveats.

INTRODUCTION: Metabolic dysfunction-associated steatotic liver disease (MASLD) is increasingly gaining relevance both as a public health issue and a c...

Cost-effectiveness analysis of artificial intelligence (AI) in earlier detection of liver lesions in cirrhotic patients at risk of hepatocellular carcinoma in Italy.

BACKGROUND: Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and the third most common cause of cancer-related death. Cirrhosi...

Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics.

Glioma is a highly heterogeneous and aggressive brain tumour that demands an integrated understanding of its molecular and immunological landscape. We...

Gut microbiome alterations and hepatic encephalopathy post-TIPS in liver cirrhosis patients.

BACKGROUND: The transjugular intrahepatic portosystemic shunt (TIPS), a crucial tool for treating complications related to portal hypertension in pati...

Prediction of postoperative infection through early-stage salivary microbiota following kidney transplantation using machine learning techniques.

Kidney transplantation (KT) is an effective treatment for end-stage renal disease; however, the lifelong immunosuppressive regimen increases the risk ...

Deep learning-driven insights into the transmission dynamics of hepatitis B virus with treatment.

Viral infections have spread globally, profoundly affecting social and economic aspects of life and causing widespread suffering. Infection caused by ...

Machine learning-assisted multi-dimensional transcriptomic analysis of cytoskeleton-related molecules and their relationship with prognosis in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide, with a poor prognosis due to its aggressive nature and limited tr...

Folate metabolism-associated CYP26A1 is a clinico-immune target in colorectal cancer.

Folic acid plays a crucial role in cellular regulation and metabolism, commonly included in dietary supplements. Despite this, its involvement in colo...

Differential Phase Contrast Imaging to Predict MSC Immune Function.

Mesenchymal stromal cells (MSCs) exhibit significant immunomodulatory potential, making them promising candidates for cell-based therapies in autoimmu...