GAL3ST1 Deficiency Reduces Epithelial-Mesenchymal Transition and Tumorigenic Capacity in a Cholangiocarcinoma Cell Line.

Cholangiocarcinoma (CCA), or bile duct cancer, is the second most common liver malignancy, with an increasing incidence in Western countries. The lack of effective treatments associated with the absence of early symptoms highlights the need to search for new therapeutic targets for CCA. Sulfatides (STs), a type of sulfoglycosphingolipids, have been found in the biliary tract, with increased levels in CCA and other types of cancer.

Towards Realistic 3D Models of Tumor Vascular Networks.

For reliable in silico or in vitro investigations in, for example, biosensing and drug delivery applications, accurate models of tumor vascular networks down to the capillary size are essential. Compared to images acquired with conventional medical imaging techniques, digitalized histological tumor slices have a higher resolution, enabling the delineation of capillaries. Volume rendering procedures can then be used to generate a 3D model.

Identifying radiomics signatures in body composition imaging for the prediction of outcome following pancreatic cancer resection.

Background: Computerized radiological image analysis (radiomics) enables the investigation of image-derived phenotypes by extracting large numbers of quantitative features. We hypothesized that radiomics features may contain prognostic information that enhances conventional body composition analysis. We aimed to investigate whether body composition-associated radiomics features hold additional value over conventional body composition analysis and clinical patient characteristics used to predict survival of pancreatic ductal adenocarcinoma (PDAC) patients.

Vessel Delineation Using U-Net: A Sparse Labeled Deep Learning Approach for Semantic Segmentation of Histological Images.

Semantic segmentation is an important imaging analysis method enabling the identification of tissue structures. Histological image segmentation is particularly challenging, having large structural information while providing only limited training data. Additionally, labeling these structures to generate training data is time consuming.

[Future of University Medicine: How Important are Research and Teaching? - An Inventory].

The requirements and challenges for the university hospitals in Germany are changing. Especially in surgical subjects, it is more and more difficult to adequately serve these three pillars of university medicine - clinic, research and education. This survey was intended to determine the status quo of general and visceral surgery at universities, in order to provide a basis for proposed solutions.