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background: There is an acute need to uncover biomarkers that reflect the molecular pathologies, underpinning prostate cancer progression and poor patient outcome. We have previously demonstrated that in prostate cancer cell lines PDE4D7 is downregulated in advanced cases of the disease. To investigate further the prognostic power of PDE4D7 expression during prostate cancer progression and assess how downregulation of this PDE isoform may affect disease outcome, we have examined PDE4D7 expression in physiologically relevant primary human samples.\ud methods: About 1405 patient samples across 8 publically available qPCR, Affymetrix Exon 1.0 ST arrays and RNA sequencing data sets were screened for PDE4D7 expression. The TMPRSS2-ERG gene rearrangement status of patient samples was determined by transformation of the exon array and RNA seq expression data to robust z-scores followed by the application of a threshold >3 to define a positive TMPRSS2-ERG gene fusion event in a tumour sample.\ud results: We demonstrate that PDE4D7 expression positively correlates with primary tumour development. We also show a positive association with the highly prostate cancer-specific gene rearrangement between TMPRSS2 and the ETS transcription factor family member ERG. In addition, we find that in primary TMPRSS2-ERG-positive tumours PDE4D7 expression is significantly positively correlated with low-grade disease and a reduced likelihood of progression after primary treatment. Conversely, PDE4D7 transcript levels become significantly decreased in castration resistant prostate cancer (CRPC).\ud conclusions: We further characterise and add physiological relevance to PDE4D7 as a novel marker that is associated with the development and progression of prostate tumours. We propose that the assessment of PDE4D7 levels may provide a novel, independent predictor of post-surgical disease progression.

We present FooPar, an extension for highly efficient Parallel Computing in the multi-paradigm programming language Scala. Scala offers concise and clean syntax and integrates functional programming features. Our framework FooPar combines these features with parallel computing techniques. FooPar is designed to be modular and supports easy access to different communication backends for distributed memory architectures as well as high performance math libraries. In this article we use it to parallelize matrix-matrix multiplication and show its scalability by a isoefficiency analysis. In addition, results based on a empirical analysis on two supercomputers are given. We achieve close-to-optimal performance wrt. theoretical peak performance. Based on this result we conclude that FooPar allows programmers to fully access Scalas design features without suffering from performance drops when compared to implementations purely based on C and MPI.

Polymers of hydrogen cyanide and their hydrolysis products constitute a plausible, but still poorly understood proposal for early prebiotic chemistry on Earth. HCN polymers are generated by the interplay of more than a dozen distinctive reaction mechanisms and form a highly complex mixture. Here we use a computational model based on graph grammars as a means of exploring the chemical spaces of HCN polymerization and hydrolysis. A fundamental issue is to understand the combinatorial explosion inherent in large, complex chemical systems. We demonstrate that experimental data, here obtained by mass spectrometry, and computationally predicted free energies together can be used to guide the exploration of the chemical space and makes it feasible to investigate likely pathways and chemical motifs even in potentially open-ended chemical systems.

Background: A classical problem in metabolic design is to maximize the production of a desired compound in a given chemical reaction network by appropriately directing the mass flow through the network. Computationally, this problem is addressed as a linear optimization problem over the flux cone. The prior construction of the flux cone is computationally expensive and no polynomial-time algorithms are known. Results: Here we show that the output maximization problem in chemical reaction networks is NP-complete. This statement remains true even if all reactions are monomolecular or bi-molecular and if only a single molecular species is used as influx. As a corollary we show, furthermore, that the detection of autocatalytic species, i.e., types that can only be produced from the influx material when they are present in the initial reaction mixture, is an NPcomplete computational problem. Conclusions: Hardness results on combinatorial problems and optimization problems ar e important to guide the development of computational tools for the analysis of metabolic networks in particular and chemical reaction networks in general. Our results indicate that efficient heuristics and approximate algorithms need to be employed for the analysis of large chemical networks since even conceptually simple flow problems are probably intractable.

The data to which the South African anchovy and sardine assessments are tuned are not raw data. Some of the data have already been subjected to a number of analyses and refinements. These associated calculations are often done “behind the scenes” and their details are seldom recorded. This lack of record can result in a discontinuity in the method used to calculate data for subsequent assessments, particularly if assumptions made in the calculations are not documented and/or a new person becomes responsible for developing the data to be used for input to the assessment. This document serves to record the generation from the raw data of the data used in the anchovy and sardine assessments carried out in 2012. It is an update of de Moor et al. 2011 to include data from November 2010 to October 2011 and new proportions and weights-at-age for anchovy. All files referred to below are available from the first author.

The data to which the South African anchovy and sardine assessments are tuned are not raw data. Some of the data have already been subjected to a number of analyses and refinements. These associated calculations are often done “behind the scenes” and their details are seldom recorded. This lack of record can result in a discontinuity in the method used to calculate data for subsequent assessments, particularly if assumptions made in the calculations are not documented and/or a new person becomes responsible for developing the data to be used for input to the assessment. This document serves to record the generation from the raw data of the data used in the anchovy and sardine assessments carried out in 2010 and 2011. All files referred to below are available from the first author.

During the 1990s and early 2000s, populations of surface-nesting seabirds at Marion Island showed different trends, but for the majority of species numbers decreased. Reduced numbers of gentoo penguins Pygoscelis papua, eastern rockhopper penguins Eudyptes chrysocome filholi, Crozet shags Phalacrocorax [atriceps] melanogenis and probably macaroni penguins E. chrysolophus are most plausibly attributed to an altered availability of food. Decreases in numbers of dark-mantled sooty albatrosses Phoebetria fusca, light-mantled sooty albatrosses P. palpebrata, southern giant petrels Macronectes giganteus and possibly northern giant petrels M. halli may have resulted from mortality of birds in longline fisheries. However, populations of wandering Diomedea exulans and grey-headed Thalassarche chrysostoma albatrosses fluctuated around a stable level. Numbers of Subantarctic skuas Catharacta antarctica and kelp gulls Larus dominicanus breeding at Marion Island also decreased. Kerguelen Sterna virgata and Antarctic S. vittata terns remain scarce at the island. Trends for king penguins Aptenodytes patagonicus were not reliably gauged, but numbers probably remained stable or increased. There were large fluctuations in numbers of king penguin chicks surviving to the end of winter.