Deep Learning in Endoscopic Ultrasound: A Breakthrough in Detecting Distal Cholangiocarcinoma.

Introduction: Cholangiocarcinoma (CCA) is a highly lethal malignancy originating in the bile ducts, often diagnosed late with poor prognosis. Differentiating benign from malignant biliary tumors remains challenging, necessitating advanced diagnostic techniques.

Objective: This study aims to enhance the diagnostic accuracy of endoscopic ultrasound (EUS) for distal cholangiocarcinoma (dCCA) using advanced convolutional neural networks (CCNs) for the classification and segmentation of EUS images, specifically targeting dCCAs, the pancreas, and the bile duct.

Chaotropic Agent-Assisted Supported Lipid Bilayer Formation.

Supported lipid bilayers (SLBs) are useful structures for mimicking cellular membranes, and they can be integrated with a variety of sensors. Although there are a variety of methods for forming SLBs, many of these methods come with limitations in terms of the lipid compositions that can be employed and the substrates upon which the SLBs can be deposited. Here we demonstrate the use of an all-aqueous chaotropic agent exchange process that can be used to form SLBs on two different substrate materials: SiO, which is compatible with traditional SLB formation by vesicle fusion, and AlO, which is not compatible with vesicle fusion.

CHARMM GUI Membrane Builder for oxidized phospholipid membrane modeling and simulation.

Oxidative stress leads to the production of oxidized phospholipids (oxPLs) that modulate the biophysical properties of phospholipid monolayers and bilayers. As many immune cells are responsible for surveilling cells and tissues for the presence of oxPLs, oxPL-dependent mechanisms have been suggested as targets for treating chronic kidney disease, atherosclerosis, diabetes, and cancer metastasis. This review details recent experimental and computational studies that characterize oxPLs' behaviors in various monolayers and bilayers.