Pancreatic Diseases

Acute pancreatitis: mechanisms and therapeutic approaches.

Acute pancreatitis is a complex inflammatory condition characterized by sudden onset and rapid progression, with severe cases often associated with high mortality. In recent years, the global incidence of acute pancreatitis has been increasing, with marked regional differences. This increasing trend not only places a considerable burden on healthcare systems but also significantly affects the phys...

Exploring structural diversity and dynamic stability of small-molecule PRMT5 inhibitors through machine learning-based QSAR and molecular modelling.

Protein arginine methyltransferase 5 (PRMT5) is a key epigenetic enzyme that catalyses symmetric arginine methylation on histone and non-histone proteins, influencing chromatin organisation, RNA splicing, and oncogenic signalling. Its overexpression and dependency in MTAP-deleted cancers such as glioblastoma, pancreatic adenocarcinoma, and non-small cell lung carcinoma highlight its therapeutic re...

Systematic Review on Deep Learning Algorithms for Blood Glucose Forecasting in Type 1 Diabetes.

Type 1 Diabetes (T1D) is a chronic metabolic disease characterized by elevated blood glucose (BG) concentrations, resulting from the immune-mediated d...

Nalmefene and naltrexone reduce alcohol intake via selective efficacy in subpopulations distinguished by behavioral and blood-based biomarkers.

BACKGROUND: The relative efficacies of nalmefene versus naltrexone for alcohol use disorder is the subject of intense and ongoing debate. The two pan-...

Comparative study of 11 machine learning algorithms for predicting recurrence risk after atrial fibrillation catheter ablation based on a real-world cohort: a retrospective study.

BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia worldwide, with catheter ablation being an effective yet recurrence-prone treatment...

Automated detection of gallbladder stones using a deep learning algorithm on computed tomography scans.

PURPOSE: To develop and evaluate the diagnostic accuracy of a deep learning algorithm for automated gallstone detection on CT. METHODS: This retrospec...

Multi-center evaluation of radiomics and deep learning to stratify malignancy risk of IPMNs.

PURPOSE: Distinguishing high-risk intraductal papillary mucinous neoplasms (IPMNs) from low-risk lesions remains a clinical challenge, often resulting...

Toward clinical implementation of interpretable machine learning for early risk stratification in acute pancreatitis.

C2HFusion: Clinical context-driven hierarchical fusion of multimodal data for personalized and quantitative prognostic assessment in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy. Accurate prognostic modeling enables reliable risk stratification to identi...

Uncovering the potential of pathomics: prognostic prediction and mechanistic investigation of pancreatic cancer.

A machine learning-based pathomics model was investigated for its value and biological significance in predicting overall survival (OS) after surgery ...

Emerging Diagnostic Indications for Endoscopic Ultrasound.

Endoscopic ultrasound (EUS) has evolved from a diagnostic imaging tool into a versatile platform that enables high-precision access, sampling, and the...

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...

Acceleration of chemical shift encoding-based water-fat imaging for pancreatic proton density fat fraction mapping in a single breath-hold: Data from the LION study.

PURPOSE: With the rising prevalence of obesity and metabolic syndrome, there is an increasing need for noninvasive quantification of pancreatic fat as...

Development and validation of interpretable machine learning models for dynamic prediction of prognosis in acute pancreatitis complicated by acute kidney injury: A multicenter study.

OBJECTIVE: This study aims to develop and validate interpretable machine learning (ML) models to dynamically predict mortality risk among intensive ca...

Precision prediction of posttraumatic stress disorder symptom surges: A pilot study integrating real-time daily data with supervised learning.

The application of machine learning algorithms to daily diary data represents a valuable tool for improving dynamic prediction of posttraumatic stress...

Molecular mechanism and structure-activity relationships of natural source polysaccharides in intervening type 2 diabetes mellitus through antioxidant effects: A systematic review.

Type 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder closely associated with oxidative stress. Natural source polysaccharides (NSPs) show...

A bibliometric analysis of the 100 most cited radiology papers on pancreatic diseases (1990-Present).

PURPOSE: To map the intellectual evolution of pancreatic radiology through a comprehensive bibliometric analysis of the 100 most-cited articles, ident...

The basis for future personalized therapy approaches - Machine learning-generated 1-year survival rate, metastatic status and therapy-dependent survival in pancreatic cancer patients.

BACKGROUND: Pancreatic adenocarcinoma (PDAC) remains one of the most lethal types of cancer, characterized by its unspecific symptoms, aggressive natu...

Co3[Co(CN)6]2-Mediated Olfactory and Visual Dual-Modality Ammonia Sensing.

In the emerging ammonia (NH3) economy, both olfactory and visual sensing are desired for leakage detection, in which olfactory sensing enables a fast ...

Modulating tumor mechanics and vascular barriers to enhance chemotherapy efficacy in pancreatic tumors and melanoma.

Pancreatic ductal adenocarcinoma (PDAC) is characterized by a dense stroma and dysfunctional vasculature, limiting drug delivery and immune infiltrati...