Novel role for the transient receptor potential channel TRPM2 in prostate cancer cell proliferation

We have identified a novel function for a member of the transient receptor potential (TRP) protein super-family, TRPM2, in prostate cancer cell proliferation. TRPM2 encodes a non-selective cation-permeable ion channel. We found that selectively knocking down TRPM2 with the small interfering RNA technique inhibited the growth of prostate cancer cells but not of non-cancerous cells. The subcellular localization of this protein is also remarkably different between cancerous and non-cancerous cells. In BPH-1 (benign), TRPM2 protein is homogenously located near the plasma membrane and in the cytoplasm, whereas in the cancerous cells (PC-3 and DU-145), a significant amount of the TRPM2 protein is located in the nuclei in a clustered pattern. Furthermore, we have found that TRPM2 inhibited nuclear ADP-ribosylation in prostate cancer cells. However, TRPM2 knockdown-induced inhibition of proliferation is independent of the activity of poly(ADP-ribose) polymerases. We conclude that TRPM2 is essential for prostate cancer cell proliferation and may be a potential target for the selective treatment of prostate cancer

Trends in template/fragment-free protein structure prediction

Predicting the structure of a protein from its amino acid sequence is a long-standing unsolved problem in computational biology. Its solution would be of both fundamental and practical importance as the gap between the number of known sequences and the number of experimentally solved structures widens rapidly. Currently, the most successful approaches are based on fragment/template reassembly. Lacking progress in template-free structure prediction calls for novel ideas and approaches. This article reviews trends in the development of physical and specific knowledge-based energy functions as well as sampling techniques for fragment-free structure prediction. Recent physical- and knowledge-based studies demonstrated that it is possible to sample and predict highly accurate protein structures without borrowing native fragments from known protein structures. These emerging approaches with fully flexible sampling have the potential to move the field forward

Global trends and possible future land use

This chapter explores the future global need for land by investigating four trends that drive global land use change: future energy demand; future food demand; future demand for various forest products; and climate change. These trends affect land use competition, food prices, and deforestation rates, and they interact with each other in complex ways that are difficult to foresee. In this chapter, a number of trends, their interactions, and possible implications are discussed on the basis of available scenarios and estimates. The chapter ends with a discussion of how global land use changes might influence the conditions for future Nordic forest management and forest sector transition