Hepatitis

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 critical link leading to cirrhosis and hepatocellular carcinoma. Yet the responsible cellular programs remain unclear. We integrated public single-cell, spatial, and bulk transcriptomic datasets to map microenvironmental remodeling and regulatory net...

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.

Integrative Bioinformatics and Machine Learning Identify Novel Diagnostic Biomarkers and Molecular Mechanisms in Sjögren's Syndrome.

BACKGROUND: Sjögren's syndrome (SS) is a chronic autoimmune disorder characterized by significant diagnostic challenges due to nonspecific symptoms an...

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...

Tuning pH for the Controlled Formation of Ultrasmall Nanoparticles with Direct Cytosolic Access.

Direct cytosolic delivery of nanoparticles offers advantages by circumventing the endocytic pathway, thereby reducing associated intracellular traffic...

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...

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...

Disentangling direct and pleiotropic SNP effects in alfalfa (Medicago sativa L.) using causal graph learning.

Alfalfa (Medicago sativa L.) is a critical forage crop whose improvement depends on resolving the complex genetic architecture of agronomic traits. Wh...

Bergenin attenuates traumatic brain injury via inhibition of microglial PFKFB3-driven glycolytic-inflammatory crosstalk.

Traumatic brain injury (TBI) initiates a complex cascade of neuroinflammatory and metabolic disturbances that exacerbate neuronal loss and neurologica...

RINet: synthetic data training for indirect estimation of clinical reference distributions.

BACKGROUND: Indirect methods for estimating clinical reference intervals (RIs) use statistical analysis to identify non-pathological sub-distributions...

Programmable lipid nanoparticles for RNA therapeutics: Design principles and clinical translation.

RNA therapeutics have come of age as clinically validated modalities including mRNA, siRNA, antisense oligonucleotides (ASOs), and in vivo genome edit...

Advances in melanoma immunotherapy: harnessing vaccination as a potential novel immunotherapeutic strategy.

Melanoma, an aggressive form of skin cancer, demands innovative immunotherapeutic strategies to improve patient outcomes. This review explores recent ...

A multicenter multinational retrospective study of the 1-year natural history of LI-RADS 3 observations in patients with cirrhosis.

OBJECTIVES: To assess the 1-year natural history of liver imaging reporting and data system (LI-RADS) 3 observations on contrast-enhanced MRI in cirrh...

Construction and validation of a screening model for minimal hepatic encephalopathy in patients with cirrhosis: A multi-center study.

BACKGROUND: Clinical practice currently lacks objective and accurate screening tools for minimal hepatic encephalopathy (MHE). Therefore, we aimed to ...

UDV-Net: A hybrid CNN and transformer vein segmentation network with vascular prior and spatial awareness.

CNNs handling multi-scale variations and Transformers modeling long-range dependencies are crucial for vascular segmentation. The fusion of these two ...

Artificial Intelligence Applications in the Diagnosis, Treatment, and Prognosis of Hepatocellular Carcinoma.

The global burden of hepatocellular carcinoma (HCC) has shifted from viral to nonviral etiologies. However, successful antiviral therapy does not full...

Machine Learning-Based Multi-Omics Integration for Identification of Hepatocellular Carcinoma Biomarkers in an Egyptian Cohort.

Hepatocellular carcinoma (HCC) ranks among the most common causes of cancer-related deaths globally. The high incidence of HCC is largely linked to ch...

Artificial Intelligence-Enhanced Quantitative 3D Analysis of Distal Radioulnar Ligament Insertion Footprints of the Triangular Fibrocartilage Complex With Interactive Validation.

OBJECTIVES: The distal radioulnar ligaments (DRULs) serve as primary stabilizers to the distal radioulnar joint (DRUJ). Existing cadaveric studies rep...

HERC5, IFI6, IFIT3, and OASL as potential diagnostic biomarkers for systemic lupus erythematosus: an integrated bioinformatics, machine learning and clinical validation.

OBJECTIVES: Systemic lupus erythematosus (SLE) is a life-threatening autoimmune disorder causing multi-organ damage. Current diagnostic methods are hi...

Dynamic Analysis of the Substrate Tolerance Mechanism and Domain Synergistic Engineering of CYP450 Fusion Protein (CYPLY).

CYP450 enzymes are important in natural product biosynthesis and industrial catalysis. A significant challenge in their engineering is alleviating sub...