Ceramides bind VDAC2 to trigger mitochondrial apoptosis

Ceramides draw wide attention as tumor suppressor lipids that act directly on mitochondria to trigger apoptotic cell death. However, molecular details of the underlying mechanism are largely unknown. Using a photoactivatable ceramide probe, we here identify the voltage-dependent anion channels VDAC1 and VDAC2 as mitochondrial ceramide binding proteins. Coarse-grain molecular dynamics simulations reveal that both channels harbor a ceramide binding site on one side of the barrel wall. This site includes a membrane-buried glutamate that mediates direct contact with the ceramide head group. Substitution or chemical modification of this residue abolishes photolabeling of both channels with the ceramide probe. Unlike VDAC1 removal, loss of VDAC2 or replacing its membrane-facing glutamate with glutamine renders human colon cancer cells largely resistant to ceramide-induced apoptosis. Collectively, our data support a role of VDAC2 as direct effector of ceramide-mediated cell death, providing a molecular framework for how ceramides exert their anti-neoplastic activity

Novel thermal image classification based on techniques derived from mathematical morphology: case of breast cancer

Image processing (IP) is a method of converting an image to digital form by performing operations on it to obtain an improved image or to extract useful information from it. It is a type of signal distribution in which the input is an image such as a video image or a photograph, and the output can be an image or associated characteristics. Besides, this system includes the processing of images in the form of two-dimensional signals, while applying signal processing methods already defined for them. One of the essential steps in IP is a combined application of erosion and dilation procedures, which is part of the mathematical morphology. This article presents a novel thermal image classification based on techniques derived from mathematical morphology. In the processing of grayscale breast cancer images, this method reveals the region of interest as the whitest area