LIN28 promotes tumorigenesis in colorectal cancer but is not associated with metastatic spread.

Background: Tumor stem cells play a role in metastatic spread in colorectal cancer (CRC). The oncogene LIN28A/B, a prognostic marker in CRC, is involved in tumorigenesis and maintains stem cell function. Therefore, it was the aim of the present study to clarify whether LIN28A/B is involved in metastatic spread in CRC.

The FeoC [4Fe-4S] Cluster Is Redox-Active and Rapidly Oxygen-Sensitive.

The acquisition of iron is essential to establishing virulence among most pathogens. Under acidic and/or anaerobic conditions, most bacteria utilize the widely distributed ferrous iron (Fe) uptake (Feo) system to import metabolically-required iron. The Feo system is inadequately understood at the atomic, molecular, and mechanistic levels, but we do know it is composed of a main membrane component (FeoB) essential for iron translocation, as well as two small, cytosolic proteins (FeoA and FeoC) hypothesized to function as accessories to this process.

Over-expression of a human CD62L ecto-domain and a potential role of RNA pseudoknot structures in recombinant protein expression.

L-selectin (CD62L) is an extracellular protein with a lectin-like domain that mediates rolling adhesion of leukocytes to vascular endothelial cell surfaces. Currently, there are no solved structures for the ectodomain of CD62L, nor of CD62L in complex with its ligand. We have developed a rapid mammalian recombinant protein expression system using an amplifiable glutamine synthase based vector.

Mixed adenoneuroendocrine carcinoma of the ampulla of Vater: A case report.

Mixed adenoneuroendocrine carcinomas (MANECs) are rare biphasic tumour types, which are morphologically recognisable as both gland-forming and neuroendocrine neoplasms. Within the gastrointestinal tract, MANECs occur predominantly in the stomach or colorectum. The present study described a case of a MANEC originating from the ampullary region.

Genetic algorithm based approach to optimize phenotypical traits of virtual rice.

How to select and combine good traits of rice to get high-production individuals is one of the key points in developing crop ideotype cultivation technologies. Existing cultivation methods for producing ideal plants, such as field trials and crop modeling, have some limits. In this paper, we propose a method based on a genetic algorithm (GA) and a functional-structural plant model (FSPM) to optimize plant types of virtual rice by dynamically adjusting phenotypical traits.