Changes in the Phase of the Annual Cycle of Surface Temperature

The annual cycle in the Earth's surface temperature is extremely large—comparable in magnitude to the glacial–interglacial cycles over most of the planet. Trends in the phase and the amplitude of the annual cycle have been observed, but the causes and significance of these changes remain poorly understood—in part because we lack an understanding of the natural variability. Here we show that the phase of the annual cycle of surface temperature over extratropical land shifted towards earlier seasons by 1.7 days between 1954 and 2007; this change is highly anomalous with respect to earlier variations, which we interpret as being indicative of the natural range. Significant changes in the amplitude of the annual cycle are also observed between 1954 and 2007. These shifts in the annual cycles appear to be related, in part, to changes in the northern annular mode of climate variability, although the land phase shift is significantly larger than that predicted by trends in the northern annular mode alone. Few of the climate models presented by the Intergovernmental Panel on Climate Change reproduce the observed decrease in amplitude and none reproduce the shift towards earlier seasons.Earth and Planetary Science

MSH2/MSH6 Complex Promotes Error-Free Repair of AID-Induced dU:G Mispairs as well as Error-Prone Hypermutation of A:T Sites

Mismatch repair of AID-generated dU:G mispairs is critical for class switch recombination (CSR) and somatic hypermutation (SHM) in B cells. The generation of a previously unavailable Msh2−/−Msh6−/− mouse has for the first time allowed us to examine the impact of the complete loss of MutSα on lymphomagenesis, CSR and SHM. The onset of T cell lymphomas and the survival of Msh2−/−Msh6−/− and Msh2−/−Msh6−/−Msh3−/− mice are indistinguishable from Msh2−/− mice, suggesting that MSH2 plays the critical role in protecting T cells from malignant transformation, presumably because it is essential for the formation of stable MutSα heterodimers that maintain genomic stability. The similar defects on switching in Msh2−/−, Msh2−/−Msh6−/− and Msh2−/−Msh6−/−Msh3−/− mice confirm that MutSα but not MutSβ plays an important role in CSR. Analysis of SHM in Msh2−/−Msh6−/− mice not only confirmed the error-prone role of MutSα in the generation of strand biased mutations at A:T bases, but also revealed an error-free role of MutSα when repairing some of the dU:G mispairs generated by AID on both DNA strands. We propose a model for the role of MutSα at the immunoglobulin locus where the local balance of error-free and error-prone repair has an impact in the spectrum of mutations introduced during Phase 2 of SHM

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

Global Sustainability Under Uncertainty: How Do Multinationals Craft Regulatory Policies?

Multinational corporations are increasingly mindful of the significance of sustainability transitions and the need for operations that are energy efficient and environmentally sound. Achieving sustainability under conditions of uncertainty entails the involvement of multiple stakeholders in initiating and carrying outsustainability-focused initiatives. Using longitudinal analysis of Royal Dutch Shell’s sustainability policies, we developed an integrated model to elucidate how uncertainty influences sustainability policies in the specific context of multinational corporations (hereinafter – MNCs). We identified three phases in theevolution of Shell’s sustainability innovation: a self-reflective phase (2000–2003) characterized by intense pressure from climate advocacy groups, an investment phase (2004–2006) for which the MNC attempted to rise to the waste disposal and pollution challenge through renewable sources of energy, and a reorganization phase (2007–2010) to streamline operations. We also uncovered themes that influence how regulatory policies are crafted: responding positively to the “community’s voice”, risk spreading through joint ventures, revenue transparency for government accountability and reporting innovation that confronts hard truths. The practical implications are outlined

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