The epigenetic landscape of renal cancer

This is an accepted manuscript of an article published by Nature in Nature Reviews: Nephrology on 28/11/2016, available online: https://doi.org/10.1038/nrneph.2016.168 The accepted version of the publication may differ from the final published version.The majority of kidney cancers are associated with mutations in the von Hippel-Lindau gene and a small proportion are associated with infrequent mutations in other well characterized tumour-suppressor genes. In the past 15 years, efforts to uncover other key genes involved in renal cancer have identified many genes that are dysregulated or silenced via epigenetic mechanisms, mainly through methylation of promoter CpG islands or dysregulation of specific microRNAs. In addition, the advent of next-generation sequencing has led to the identification of several novel genes that are mutated in renal cancer, such as PBRM1, BAP1 and SETD2, which are all involved in histone modification and nucleosome and chromatin remodelling. In this Review, we discuss how altered DNA methylation, microRNA dysregulation and mutations in histone-modifying enzymes disrupt cellular pathways in renal cancers

Changeability and flexibility of assembly line balancing as a multi-objective optimization problem

Data supports the submission Fisel, Exner, Stricker, Lanza: Changeability and flexibility of assembly line balancing as a multi-objective optimization problem to the Journal of Manufacturing Systems It has been obtained within the research project EFFECT 360°. Results have been calculated applying a NSGA-II algorithm

Changeability and flexibility of assembly line balancing as a multi-objective optimization problem

Data supports the submission Fisel, Exner, Stricker, Lanza: Changeability and flexibility of assembly line balancing as a multi-objective optimization problem to the Journal of Manufacturing Systems It has been obtained within the research project EFFECT 360°. Results have been calculated applying a NSGA-II algorithm

Multiregime states of Arctic atmospheric circulation

[1] Ensemble simulations of Arctic circulation can develop multiple dynamical regimes. We use ensemble simulations for June–December 2007 by the Advanced Research Weather Research and Forecasting model to examine regime development and to understand differences in the atmospheric circulation regimes caused by sea ice. Multiple regimes are common in our ensemble simulations, although there are differences through the period. Multiple-regime states tend to be preferred slightly more in June, July, and August than October, November, and December. September has the fewest multiple-regime periods. September is also the month of sea ice minimum, suggesting that open ocean may inhibit the occurrence of multiple regimes in ensemble simulations compared to periods when substantial sea ice is present. The regime behavior occurring here suggests that as future summer ice cover wanes in the Arctic, the predictability of the atmosphere may increase.This article is from Journal of Geophysical Research: Atmospheres 116 (2011): D20122, doi:10.1029/2011JD015790. Posted with permission.</p