Pancreatic Diseases

Interpretable machine-learning survival prediction of breast cancer prognosis from lifestyle factors: evidence from UK biobank.

BACKGROUND: Understanding how lifestyle habits influence breast cancer survival is crucial for improving long-term outcomes and guiding individualized care. The purpose of this study is to comprehensively understand how dietary habits, exercise frequency, sleep quality and the frequency of tobacco and alcohol use affect the survival of breast cancer patients by analyzing the synergistic effects of...

Membrane Fusion-Assisted Laser Desorption/Ionization Mass Spectrometry for In Situ Extracellular Vesicle Metabolic Fingerprinting.

Metabolites packaged within extracellular vesicles (EVs) are increasingly recognized for their role in intercellular communication and metabolic regulation. However, their comprehensive characterization remains challenging due to the low abundance of metabolites in EVs, interference from complex biological matrixes, and poor ionization efficiency of certain metabolite classes. Here, we developed a...

Machine Learning-Guided Near-Infrared Laser Processing for Precise Geometry Control in Microneedles with Downstream microLED-Triggered Photothermal Functionality.

Transdermal drug delivery and sensing provide non-invasive routes for localized therapy and biomarker detection. Microneedles (MNs) enable pain-free a...

MoCaPS: a machine learning model for stratification of cancer-associated cachexia based on blood biomarkers.

Identification of minimally invasive biomarkers of cancer-associated cachexia may help to recognize high risk patients for progression to more severe ...

Deep Learning Predicts Imminent Tumor Progression in Advanced Pancreatic Adenocarcinoma Using Serial CT Scans During Chemotherapy.

Advanced pancreatic ductal adenocarcinoma (PDAC) often progresses rapidly during chemotherapy despite initial assessments of stable disease or partial...

Identifying Potential Exosome-Derived mRNA Biomarkers for Diagnosis and Prediction of Breast Cancer Using Machine-Learning Approaches.

INTRODUCTION: Breast cancer remains a major global health burden, underscoring the urgent need for reliable early detection strategies. Exosomes, as m...

A prospective development and evaluation of a 2D convolutional neural network-based auto-segmentation model for cervical cancer radiotherapy.

BACKGROUND: Accurate delineation of target volumes and organs at risk (OAR) is essential in radiotherapy planning for cervical cancer. Deep learning (...

A framework for assessing algorithmic discrimination risks in training data: a case of pediatric type 1 diabetes.

OBJECTIVES: To develop a generalizable framework for identifying algorithmic discrimination risks arising from subgroup imbalances in machine learning...

A bio-inspired, soft-bodied jumper.

Some species of fly larvae and nematodes achieve rapid locomotion by forming loops with their bodies, latching their heads and tails, and storing elas...

Gut microbiome in pediatric acute pancreatitis and Crohn's disease versus irritable bowel syndrome and healthy controls.

OBJECTIVES: Pediatric acute pancreatitis (AP), Crohn's disease (CD), and irritable bowel syndrome (IBS) are associated with gut dysbiosis, but differe...

User Perspectives on Conversational Agents for Preventive Alcohol Self-Help: Qualitative Exploratory Study.

BACKGROUND: Alcohol use remains a major public health concern, and although preventive alcohol self-help interventions aim to support individuals in n...

Interpretable single-cell machine learning identifies PINK1-centred mitophagy as a determinant of metabolic fitness in type 2 diabetes.

BACKGROUND: Progressive pancreatic β-cell dysfunction constitutes a hallmark of type 2 diabetes (T2D), yet the molecular programmes governing metaboli...

Deep learning-based respiratory-triggered magnetic resonance cholangiopancreatography: comparison with conventional respiratory-triggered and breath-hold magnetic resonance cholangiopancreatography.

PURPOSE: To evaluate whether deep learning-based respiratory-triggered (DL) 3D magnetic resonance cholangiopancreatography (MRCP) improves acquisition...

Specimen quality shapes the actionable genomic landscape in comprehensive cancer genomic profiling.

Comprehensive genomic profiling (CGP) is widely used to identify actionable alterations and guide precision oncology, yet only a minority of tested pa...

Development of non-destructive durian fruit maturity detection tool based on multi-variable sensor for harvest quality optimisation.

Durian maturity critically affects consumer acceptance, market value, and postharvest losses, yet its assessment remains largely subjective. This stud...

Assessing collagenase-a and type-II mediated degradation of human type-I collagen by photoacoustic spectroscopy toward clinical translation in cancer progression.

The current study reports the design and development of a compact photoacoustic (PA) sensor for label‑free detection of collagen degradation, a key ha...

Explainable early prediction of short-term severe deterioration in gallstone-related biliary disease using MIMIC-IV, eICU, and local real-world data.

BACKGROUND: Patients with gallstone-related biliary disease may deteriorate rapidly before definitive source control. This study aimed to develop an i...

Periodic surveillance of intraductal papillary mucinous neoplasms: gaps in evidence and future directions.

Intraductal papillary mucinous neoplasm (IPMN) is a well-established precursor to pancreatic cancer; however, its generally indolent biological behavi...

Topological imaging of single-cell CAF heterogeneity for predicting prognosis and adjuvant chemotherapy benefit in pancreatic cancer.

PURPOSE: Cancer-associated fibroblasts (CAFs) are central drivers of PDAC progression and therapeutic resistance, yet their preoperative clinical util...

Week-Ahead Prediction of High-Risk Drinking Episodes Among Young Adults Using Wearable Biosignals and Psychological Vulnerabilities: Prospective Observational Machine Learning Study.

BACKGROUND: Although machine learning has increasingly been used to predict mental health symptoms and maladaptive behaviors, real-world prediction of...