101 research outputs found
The interplay of microscopic and mesoscopic structure in complex networks
Not all nodes in a network are created equal. Differences and similarities
exist at both individual node and group levels. Disentangling single node from
group properties is crucial for network modeling and structural inference.
Based on unbiased generative probabilistic exponential random graph models and
employing distributive message passing techniques, we present an efficient
algorithm that allows one to separate the contributions of individual nodes and
groups of nodes to the network structure. This leads to improved detection
accuracy of latent class structure in real world data sets compared to models
that focus on group structure alone. Furthermore, the inclusion of hitherto
neglected group specific effects in models used to assess the statistical
significance of small subgraph (motif) distributions in networks may be
sufficient to explain most of the observed statistics. We show the predictive
power of such generative models in forecasting putative gene-disease
associations in the Online Mendelian Inheritance in Man (OMIM) database. The
approach is suitable for both directed and undirected uni-partite as well as
for bipartite networks
Choosing the right bar: a complex problem
Inputs to the central complex, the navigation center of Drosophila, are strongly modulated by the visual stimulus history. These history effects carry forward to bias turning behavior when flies choose between two visual stimuli
Effects of in vitro metabolism of a broccoli leachate, glucosinolates and S-methylcysteine sulphoxide on the human faecal microbiome
Purpose: Brassica are an important food source worldwide and are characterised by the presence of compounds called glucosinolates. Studies indicate that the glucosinolate derived bioactive metabolite sulphoraphane can elicit chemoprotective benefits on human cells. Glucosinolates can be metabolised in vivo by members of the human gut microbiome, although the prevalence of this activity is unclear. Brassica and Allium plants also contain S-methylcysteine sulphoxide (SMCSO), that may provide additional health benefits but its metabolism by gut bacteria is not fully understood. Methods: We examined the effects of a broccoli leachate (BL) on the composition and function of human faecal microbiomes of five different participants under in vitro conditions. Bacterial isolates from these communities were then tested for their ability to metabolise glucosinolates and SMCSO. Results: Microbial communities cultured in vitro in BL media were observed to have enhanced growth of lactic acid bacteria, such as lactobacilli, with a corresponding increase in the levels of lactate and short-chain fatty acids. Members of Escherichia isolated from these faecal communities were found to bioconvert glucosinolates and SMCSO to their reduced analogues. Conclusion: This study uses a broccoli leachate to investigate the bacterial-mediated bioconversion of glucosinolates and SMCSO, which may lead to further products with additional health benefits to the host. We believe that this is the first study that shows the reduction of the dietary compound S-methylcysteine sulphoxide by bacteria isolated from human faeces
Transcriptomic Coordination in the Human Metabolic Network Reveals Links between n-3 Fat Intake, Adipose Tissue Gene Expression and Metabolic Health
Understanding the molecular link between diet and health is a key goal in nutritional systems biology. As an alternative to pathway analysis, we have developed a joint multivariate and network-based approach to analysis of a dataset of habitual dietary records, adipose tissue transcriptomics and comprehensive plasma marker profiles from human volunteers with the Metabolic Syndrome. With this approach we identified prominent co-expressed sub-networks in the global metabolic network, which showed correlated expression with habitual n-3 PUFA intake and urinary levels of the oxidative stress marker 8-iso-PGF2α. These sub-networks illustrated inherent cross-talk between distinct metabolic pathways, such as between triglyceride metabolism and production of lipid signalling molecules. In a parallel promoter analysis, we identified several adipogenic transcription factors as potential transcriptional regulators associated with habitual n-3 PUFA intake. Our results illustrate advantages of network-based analysis, and generate novel hypotheses on the transcriptomic link between habitual n-3 PUFA intake, adipose tissue function and oxidative stress
Why Are Computational Neuroscience and Systems Biology So Separate?
Despite similar computational approaches, there is surprisingly little interaction between the computational neuroscience and the systems biology research communities. In this review I reconstruct the history of the two disciplines and show that this may explain why they grew up apart. The separation is a pity, as both fields can learn quite a bit from each other. Several examples are given, covering sociological, software technical, and methodological aspects. Systems biology is a better organized community which is very effective at sharing resources, while computational neuroscience has more experience in multiscale modeling and the analysis of information processing by biological systems. Finally, I speculate about how the relationship between the two fields may evolve in the near future
Observational Constraints on the Common Envelope Phase
The common envelope phase was first proposed more than forty years ago to
explain the origins of evolved, close binaries like cataclysmic variables. It
is now believed that the phase plays a critical role in the formation of a wide
variety of other phenomena ranging from type Ia supernovae through to binary
black holes, while common envelope mergers are likely responsible for a range
of enigmatic transients and supernova imposters. Yet, despite its clear
importance, the common envelope phase is still rather poorly understood. Here,
we outline some of the basic principles involved, the remaining questions as
well as some of the recent observational hints from common envelope phenomena -
namely planetary nebulae and luminous red novae - which may lead to answering
these open questions.Comment: 29 pages, 8 figures. To appear in the book "Reviews in Frontiers of
Modern Astrophysics: From Space Debris to Cosmology" (eds. Kabath, Jones and
Skarka; publisher Springer Nature) funded by the European Union Erasmus+
Strategic Partnership grant "Per Aspera Ad Astra Simul"
2017-1-CZ01-KA203-03556
MAGIC and Fermi-LAT gamma-ray results on unassociated HAWC sources
The HAWC Collaboration released the 2HWC catalogue of TeV sources, in which 19 show no association with any known high-energy (HE; E greater than or similar to 10 GeV) or very-high-energy (VHE; E greater than or similar to 300 GeV) sources. This catalogue motivated follow-up studies by both the Major Atmospheric Gamma-ray Imaging Cherenkov (MAGIC) and Fermi-LAT (Large Area Telescope) observatories with the aim of investigating gamma-ray emission over a broad energy band. In this paper, we report the results from the first joint work between High Altitude Water Cherenkov (HAWC), MAGIC, and Fermi-LAT on three unassociated HAWC sources: 2HWC J2006+341, 2HWC J1907+084*, and 2HWC J1852+013*. Although no significant detection was found in the HE and VHE regimes, this investigation shows that a minimum 1 degrees extension (at 95 per cent confidence level) and harder spectrum in the GeV than the one extrapolated from HAWC results are required in the case of 2HWC J1852+013*, whilst a simply minimum extension of 0.16 degrees (at 95 per cent confidence level) can already explain the scenario proposed by HAWC for the remaining sources. Moreover, the hypothesis that these sources are pulsar wind nebulae is also investigated in detail
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