Inference on inspiral signals using LISA MLDC data

In this paper we describe a Bayesian inference framework for analysis of data obtained by LISA. We set up a model for binary inspiral signals as defined for the Mock LISA Data Challenge 1.2 (MLDC), and implemented a Markov chain Monte Carlo (MCMC) algorithm to facilitate exploration and integration of the posterior distribution over the 9-dimensional parameter space. Here we present intermediate results showing how, using this method, information about the 9 parameters can be extracted from the data.Comment: Accepted for publication in Classical and Quantum Gravity, GWDAW-11 special issu

Hypoxia enhances human myoblast differentiation: involvement of HIF1α and impact of DUX4, the FSHD causal gene.

peer reviewed[en] BACKGROUND: Hypoxia is known to modify skeletal muscle biological functions and muscle regeneration. However, the mechanisms underlying the effects of hypoxia on human myoblast differentiation remain unclear. The hypoxic response pathway is of particular interest in patients with hereditary muscular dystrophies since many present respiratory impairment and muscle regeneration defects. For example, an altered hypoxia response characterizes the muscles of patients with facioscapulohumeral dystrophy (FSHD). METHODS: We examined the impact of hypoxia on the differentiation of human immortalized myoblasts (LHCN-M2) cultured in normoxia (PO2: 21%) or hypoxia (PO2: 1%). Cells were grown in proliferation (myoblasts) or differentiation medium for 2 (myocytes) or 4 days (myotubes). We evaluated proliferation rate by EdU incorporation, used myogenin-positive nuclei as a differentiation marker for myocytes, and determined the fusion index and myosin heavy chain-positive area in myotubes. The contribution of HIF1α was studied by gain (CoCl2) and loss (siRNAs) of function experiments. We further examined hypoxia in LHCN-M2-iDUX4 myoblasts with inducible expression of DUX4, the transcription factor underlying FSHD pathology. RESULTS: We found that the hypoxic response did not impact myoblast proliferation but activated precocious myogenic differentiation and that HIF1α was critical for this process. Hypoxia also enhanced the late differentiation of human myocytes, but in an HIF1α-independent manner. Interestingly, the impact of hypoxia on muscle cell proliferation was influenced by dexamethasone. In the FSHD pathological context, DUX4 suppressed HIF1α-mediated precocious muscle differentiation. CONCLUSION: Hypoxia stimulates myogenic differentiation in healthy myoblasts, with HIF1α-dependent early steps. In FSHD, DUX4-HIF1α interplay indicates a novel mechanism by which DUX4 could interfere with HIF1α function in the myogenic program and therefore with FSHD muscle performance and regeneration

The DUX4-HIF1α Axis in Murine and Human Muscle Cells: A Link More Complex Than Expected

peer reviewedFacioScapuloHumeral Dystrophy (FSHD) is one of the most frequent inherited muscle disorders, and is linked to the inappropriate expression of the DUX4 transcription factor in adult muscles. The deregulated molecular network causing FSHD skeletal muscle dysfunction and pathology is still not well understood. It has been shown that the hypoxia response factor HIF1α is critically disturbed in FSHD and has a major role in DUX4 induced cell death. In this study, we further explore the relationship between DUX4 and HIF1α. We found that the DUX4 and HIF1α link differed according to the stage of myogenic differentiation and was conserved between human and mouse muscle. Finally, we found that HIF1α knock-down in an FSHD mouse model exacerbated DUX4-mediated muscle damages. Our data indicate that the suggested role of HIF1α in DUX4 toxicity is complex and that targeting HIF1α might be challenging in the context of FSHD therapeutic approaches

Ontologies, agents and the grid—an overview

semantic information processing. One of the important claims that permeate current view of information management is that ontological demarcation of data and semantic information processing are going to allow to infuse “intelligence ” into information systems. Separately, it is claimed that software agents, combined with ontologies will be the foundation of Web 4.0. In our work we are developing an agent-team-based resource management and brokering infrastructure for computational Grids. The proposed meta-level middleware is to utilize both software agents and ontologies. In this context, the aim of this chapter is twofold. First, we present an overview of found efforts to develop ontologies to be used in Grid and agent-Grid computing. Second, we analyze which one of them, if any, should be the base ontology for the system under development. References 1 hal-00834412, version 1- 17 Jun 2013 One of the important claims that permeate current view of information managemen