Embryonic stem cell-specific signatures in cancer: insights into genomic regulatory networks and implications for medicine

Embryonic stem (ES) cells are of great interest as a model system for studying early developmental processes and because of their potential therapeutic applications in regenerative medicine. Obtaining a systematic understanding of the mechanisms that control the 'stemness' - self-renewal and pluripotency - of ES cells relies on high-throughput tools to define gene expression and regulatory networks at the genome level. Such recently developed systems biology approaches have revealed highly interconnected networks in which multiple regulatory factors act in combination. Interestingly, stem cells and cancer cells share some properties, notably self-renewal and a block in differentiation. Recently, several groups reported that expression signatures that are specific to ES cells are also found in many human cancers and in mouse cancer models, suggesting that these shared features might inform new approaches for cancer therapy. Here, we briefly summarize the key transcriptional regulators that contribute to the pluripotency of ES cells, the factors that account for the common gene expression patterns of ES and cancer cells, and the implications of these observations for future clinical applications.Institute for Cellular and Molecular [email protected]

Exploring key economic sectors and groups of sectors in Scotland; 1998, 2004, 2007

Different methods and criteria exist for determining ‘key’ economic sectors. The Scottish Government identifies a number of ‘key’ sectors, although it is not clear which metrics it used to choose these. It is likely that these sectors are considered to be ‘key’ in delivering the Scottish Government’s policy priorities. This differs from a more formally defined economic approach to determining key sectors. However, even within the economics literature, there are different ways of thinking about which sectors are ‘key’. This short paper presents one approach to determining individual and groups of ‘key’ sectors. We will explain why these approaches are not necessarily equivalent, and what value is added in moving from considering sectors individually to analysing the impact of sectors in groups. We begin with a non-technical overview of the methods we employ, before discussing the database used in this analysis. We then present the results of applying this method for Scotland for three time periods: 1998, 2004, and 2007. We mainly focus on sectoral output, but we also include one set of results which look at key employment sectors. In the discussion of our results we concentrate on two things. First, we are interested in which sectors are identified as important in Scotland in each time period. Second, we investigate how those sectors have changed between 1998, 2004 and 2007

The Content-Dependence of Imaginative Resistance

An observation of Hume’s has received a lot of attention over the last decade and a half: Although we can standardly imagine the most implausible scenarios, we encounter resistance when imagining propositions at odds with established moral (or perhaps more generally evaluative) convictions. The literature is ripe with ‘solutions’ to this so-called ‘Puzzle of Imaginative Resistance’. Few, however, question the plausibility of the empirical assumption at the heart of the puzzle. In this paper, we explore empirically whether the difficulty we witness in imagining certain propositions is indeed due to claim type (evaluative v. non-evaluative) or whether it is much rather driven by mundane features of content. Our findings suggest that claim type plays but a marginal role, and that there might hence not be much of a ‘puzzle’ to be solved

An Analysis of Real Time Streaming of Sensor Fusion in Smart Buildings

As buildings and devices becoming increasingly “smarter,” the need for more data requires more sensors in order to provide more precise and insightful interpretations of daily applications. As a result, servers are required to become stronger and more advanced in order to compute and process the abundance of data arriving at high frequencies and to meet real-time requirements and expectations. The naive approach would be to buy new, or to upgrade, existing servers. This can potentially become costly and inconvenient for end users. In addition, placement of new equipment is constrained by building blueprints that must meet safety compliance, and in order to be efficient, the equipment must be placed in the vicinity of the sensors. However, the need for additional or upgraded servers can be prevented if you can effectively direct the incoming data and reroute it into proper queues before computation. My research compares the computation of incoming data across multiple software topology designs. The system will work under various workload intensities depending on the way data is routed. However, the trade-off of changing the way the data is routed could potentially mean a loss of accuracy. While keeping accuracy of computations a high priority, one component of my research will be implementing a system that can compute occupancy predictions on environmental sensor data that is compared across multiple software topology designs, to determine under which conditions we can reduce server workload intensity while still preserving accuracy

Adapting Sequence Models for Sentence Correction

In a controlled experiment of sequence-to-sequence approaches for the task of sentence correction, we find that character-based models are generally more effective than word-based models and models that encode subword information via convolutions, and that modeling the output data as a series of diffs improves effectiveness over standard approaches. Our strongest sequence-to-sequence model improves over our strongest phrase-based statistical machine translation model, with access to the same data, by 6 M2 (0.5 GLEU) points. Additionally, in the data environment of the standard CoNLL-2014 setup, we demonstrate that modeling (and tuning against) diffs yields similar or better M2 scores with simpler models and/or significantly less data than previous sequence-to-sequence approaches.Comment: EMNLP 201

Repository as a service (RaaS)

In his oft-quoted seminal paper ‘Institutional Repositories: Essential Infrastructure For Scholarship In The Digital Age’ Clifford Lynch (2003) described the Institutional Repository as “a set of services that a university offers to the members of its community for the management and dissemination of digital materials created by the institution and its community members.” This paper seeks instead to define the repository service at a more primitive level, without the specialism of being an ‘Institutional Repository’, and looks at how it can viewed as providing a service within appropriate boundaries, and what that could mean for the future development of repositories, our expectations of what repositories should be, and how they could fit into the set of services required to deliver an Institutional Repository service as describe by Lynch.<br/

Moonlight drives ocean-scale mass vertical migration of zooplankton during the Arctic winter

The creation of the pan-Arctic archive of ADCP data was supported by the UK Natural Environment Research Council (NERC) (Panarchive: NE/H012524/1 and SOFI: NE/F012381/1) as was mooring work in Svalbard (Oceans 2025 and Northern Sea Program). Moorings were also supported by the Research Council of Norway (NFR) projects: Circa (214271), Cleopatra (178766), Cleopatra II (216537), and Marine Night (226471).In extreme high-latitude marine environments that are without solar illumination in winter, light-mediated patterns of biological migration have historically been considered non-existent [1]. However, diel vertical migration (DVM) of zooplankton has been shown to occur even during the darkest part of the polar night, when illumination levels are exceptionally low [2 and 3]. This paradox is, as yet, unexplained. Here, we present evidence of an unexpected uniform behavior across the entire Arctic, in fjord, shelf, slope and open sea, where vertical migrations of zooplankton are driven by lunar illumination. A shift from solar-day (24-hr period) to lunar-day (24.8-hr period) vertical migration takes place in winter when the moon rises above the horizon. Further, mass sinking of zooplankton from the surface waters and accumulation at a depth of ∼50 m occurs every 29.5 days in winter, coincident with the periods of full moon. Moonlight may enable predation of zooplankton by carnivorous zooplankters, fish, and birds now known to feed during the polar night [4]. Although primary production is almost nil at this time, lunar vertical migration (LVM) may facilitate monthly pulses of carbon remineralization, as they occur continuously in illuminated mesopelagic systems [5], due to community respiration of carnivorous and detritivorous zooplankton. The extent of LVM during the winter suggests that the behavior is highly conserved and adaptive and therefore needs to be considered as “baseline” zooplankton activity in a changing Arctic ocean [6, 7, 8 and 9].Publisher PDFPeer reviewe