Pancreatic Diseases

Deep Learning-Enhanced Generation and Screening of Antihyperuricemic Peptides from Chickpea Proteins: from Multienzyme Optimization to Molecular Mechanisms.

Food-derived bioactive peptides have emerged as promising functional ingredients for hyperuricemia management. However, multienzyme hydrolysis strategies remain underexplored because of inefficient screening methods. Herein, a large language model (LLM)-guided strategy integrating deep learning-assisted enzyme selection with experimental validation was developed to generate antihyperuricemic pepti...

Phenotypic AI-based design of cell-specific small molecule cytotoxics.

Artificial intelligence is transforming drug discovery by enabling exploration of vast chemical spaces and the design of new molecules with tailored properties. However, most approaches focus on chemical features or protein binding, leaving phenotypic discovery underexplored. Here, we present a framework to design small molecules with selective toxicity in pancreatic cancer cells by combining larg...

PancDS in Real-World Practice: A Prospective Multicenter Validation of a Clinical Decision-Support System Bridging Experience Gaps in Pancreatic Lesion Diagnosis.

Distinguishing pancreatic ductal adenocarcinoma (PDAC) from mass-forming pancreatitis (MFP) is challenging due to imaging mimicry and reader-dependent...

Artificial intelligence-based anatomical recognition improves surgeon decision-making during robotic gastrectomy.

BACKGROUND: Artificial intelligence (AI)-based anatomical recognition has emerged to support intraoperative cognition; however, its clinical utility b...

Machine Learning Prediction Model for Dyslipidemia and Its Association With Atherothrombotic Events in 3 Independent Cohorts From South Korea, Japan, and the United Kingdom: Algorithm Development and Validation Study.

BACKGROUND: Dyslipidemia is a multifactorial and complex condition that warrants investigation through advanced analytical approaches such as machine ...

Peptides as integrative modulators for clinical prognosis and targeted therapy in pancreatic cancer.

Pancreatic cancer remains a formidable global health challenge, ranking as the twelfth most common malignancy yet claiming an outsized toll with disma...

Identification of GCNT3 as a glycometabolism-associated biomarker in endometrial cancer.

Endometrial carcinoma (EC) incidence is increasing, with diabetes mellitus (DM) elevating EC risk. This study investigates the glycometabolism-associa...

Integrative multi-omics analysis identifies a core ferroptosis signature and validates resveratrol as a novel inducer in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis due to treatment resistance and an immunosuppressive, fibrotic microenvironment. Ferrop...

SPIRAL: A probabilistic deep learning framework for Chinese liquor (Baijiu) classification via near-infrared hyperspectral imaging.

Chinese liquor (Baijiu) is a complex alcoholic beverage whose chemical composition determines its alcohol content, aroma type, and brand. Accurate ide...

Heterogeneous pathways to depressive and anxiety disorders: A cluster-based predictive study in a nationwide longitudinal cohort.

BACKGROUND: Early prediction of depressive and anxiety disorders is challenging due to substantial heterogeneity in risk pathways. Conventional machin...

The role of MRCP in characterizing ductal communication and high-risk features in pancreatic cystic lesions.

Pancreatic cystic lesions are increasingly detected due to the widespread use of high-resolution cross-sectional imaging, particularly MRI and CT. The...

HIV and Substance Use Reduction for Youth Experiencing Homelessness: Development and Usability Study.

BACKGROUND: Youth experiencing homelessness face heightened vulnerability to HIV infection and substance use due to complex structural, psychosocial, ...

Artificial intelligence in pancreatic cancer: applications in early detection, tumor staging, and survival prediction-a comprehensive review.

In the rapidly developing world, artificial intelligence (AI) is one of the emerging applications in the medical domain. Early detection of cancer is ...

Metabolic, demographic, and behavioral risk factors predict brain structural variability in the general population: an analysis of the human connectome project young adults.

BACKGROUND: Understanding whether commonly available metabolic, demographic, and behavioral factors can explain variability in brain structure may sup...

Clinically interpretable nomogram incorporating radiomics and deep learning feature fusion from abdominal CT for preclinical type 2 diabetes.

OBJECTIVE: To develop and externally validate a multimodal artificial intelligence framework for opportunistic detection of preclinical type 2 diabete...

Deep Learning Framework for Early Detection of Pancreatic Cancer Using Multi-modal Medical Imaging Analysis.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal forms of cancer, with a five-year survival rate below 10% primarily due to late...

Interpreting MALDI imaging data for rare types of ampullary cancer using machine learning.

Rare tumor diseases are difficult to diagnose and there is a lack of routine diagnostic procedures. Approaches must be found that allow comprehensive ...

Development of Models for Predicting the 7-Month Risk of Venous Thromboembolism and Clinically Relevant Bleeding in Ambulatory Patients with Cancer: Analysis from the AVERT Trial.

BACKGROUND: Patients with cancer are at elevated risk of venous thromboembolism (VTE). While primary thromboprophylaxis reduces VTE incidence, it also...

Seeing the unseen: AI radiomics unmasking occult pancreatic cancer?

Spatial concordance metrics and related risk factors of brain-peripheral barrier axes: unveiling distinct concordance patterns for mental and neurological axes.

Numerous studies have documented bidirectional interactions between the central nervous system and barrier organs (skin, gut, and lung). While genome-...