Cyclodextrin Conjugated α-Bisabolol Suppresses FAK Phosphorylation and Induces Apoptosis in Pancreatic Cancer.

Background/aim: α-Bisabolol is an essential oil component extracted from plants, such as chamomile. We have previously reported that α-bisabolol suppressed proliferation, invasion, and motility of pancreas cancer. Cyclodextrin improved the solubility of α-bisabolol, therefore it enabled to administer intravenously.

Antitumor Effects of Deep Ultraviolet Irradiation for Pancreatic Cancer.

Background/aim: Deep ultraviolet (DUV) light spans within the 250 nm to 350 nm invisible wavelength range. Although it strongly damages various cells, the efficacy of DUV irradiation on pancreatic cancer cells has never been clarified. The purpose of this study was to reveal the antitumor effects of DUV irradiation on pancreatic cancer cells.

Cloth manipulation planning on basis of mesh representations with incomplete domain knowledge and voxel-to-mesh estimation.

Cloth manipulation is common in both housework and manufacturing. However, robotic cloth manipulation remains challenging, especially for less controlled and open-goal settings. We consider the problem of open-goal planning for robotic cloth manipulation, with focus on the roles of cloth representation and epistemic uncertainty.

Trefoil factor 1 inhibits the development of esophageal adenocarcinoma from Barrett's epithelium.

Trefoil factor family 1 (TFF1) is one of three members of the trefoil factor family that are abundantly expressed in the gastrointestinal mucosal epithelium. Recent studies have shown that TFF1 acts as a tumor suppressor in gastric, pancreatic and hepatocellular carcinogenesis; however, little is known about its function in esophageal carcinogenesis, especially in esophageal adenocarcinoma (EAC). Barrett's epithelium is the metaplastic columnar epithelium of the esophagus and a known premalignant lesion of EAC.

Fast and Flexible Multi-Step Cloth Manipulation Planning Using an Encode-Manipulate-Decode Network (EM*D Net).

We propose a deep neural network architecture, the Encode-Manipulate-Decode (EM*D) net, for rapid manipulation planning on deformable objects. We demonstrate its effectiveness on simulated cloth. The net consists of 3D convolutional encoder and decoder modules that map cloth states to and from latent space, with a "manipulation module" in between that learns a forward model of the cloth's dynamics w.