A 3D model for carbon monoxide molecular line emission as a potential cosmic microwave background polarization contaminant

We present a model for simulating Carbon Monoxide (CO) rotational line emission in molecular clouds, taking account of their 3D spatial distribution in galaxies with different geometrical properties. The model implemented is based on recent results in the literature and has been designed for performing Monte-Carlo simulations of this emission. We compare the simulations produced with this model and calibrate them, both on the map level and on the power spectrum level, using the second release of data from the Planck satellite for the Galactic plane, where the signal-to-noise ratio is highest. We use the calibrated model to extrapolate the CO power spectrum at low Galactic latitudes where no high sensitivity observations are available yet. We then forecast the level of unresolved polarized emission from CO molecular clouds which could contaminate the power spectrum of Cosmic Microwave Background (CMB) polarization B-modes away from the Galactic plane. Assuming realistic levels of the polarization fraction, we show that the level of contamination is equivalent to a cosmological signal with r 720.02. The Monte-Carlo MOlecular Line Emission (MCMole3D) Python package, which implements this model, is being made publicly available

MINE: Module Identification in Networks

<p>Abstract</p> <p>Background</p> <p>Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks.</p> <p>Results</p> <p>MINE outperforms MCODE, CFinder, NEMO, SPICi, and MCL in identifying non-exclusive, high modularity clusters when applied to the <it>C. elegans </it>protein-protein interaction network. The algorithm generally achieves superior geometric accuracy and modularity for annotated functional categories. In comparison with the most closely related algorithm, MCODE, the top clusters identified by MINE are consistently of higher density and MINE is less likely to designate overlapping modules as a single unit. MINE offers a high level of granularity with a small number of adjustable parameters, enabling users to fine-tune cluster results for input networks with differing topological properties.</p> <p>Conclusions</p> <p>MINE was created in response to the challenge of discovering high quality modules of gene products within highly interconnected biological networks. The algorithm allows a high degree of flexibility and user-customisation of results with few adjustable parameters. MINE outperforms several popular clustering algorithms in identifying modules with high modularity and obtains good overall recall and precision of functional annotations in protein-protein interaction networks from both <it>S. cerevisiae </it>and <it>C. elegans</it>.</p

Planck 2013 results. XXII. Constraints on inflation

We analyse the implications of the Planck data for cosmic inflation. The Planck nominal mission temperature anisotropy measurements, combined with the WMAP large-angle polarization, constrain the scalar spectral index to be ns = 0:9603 _ 0:0073, ruling out exact scale invariance at over 5_: Planck establishes an upper bound on the tensor-to-scalar ratio of r < 0:11 (95% CL). The Planck data thus shrink the space of allowed standard inflationary models, preferring potentials with V00 < 0. Exponential potential models, the simplest hybrid inflationary models, and monomial potential models of degree n _ 2 do not provide a good fit to the data. Planck does not find statistically significant running of the scalar spectral index, obtaining dns=dln k = 0:0134 _ 0:0090. We verify these conclusions through a numerical analysis, which makes no slowroll approximation, and carry out a Bayesian parameter estimation and model-selection analysis for a number of inflationary models including monomial, natural, and hilltop potentials. For each model, we present the Planck constraints on the parameters of the potential and explore several possibilities for the post-inflationary entropy generation epoch, thus obtaining nontrivial data-driven constraints. We also present a direct reconstruction of the observable range of the inflaton potential. Unless a quartic term is allowed in the potential, we find results consistent with second-order slow-roll predictions. We also investigate whether the primordial power spectrum contains any features. We find that models with a parameterized oscillatory feature improve the fit by __2 e_ _ 10; however, Bayesian evidence does not prefer these models. We constrain several single-field inflation models with generalized Lagrangians by combining power spectrum data with Planck bounds on fNL. Planck constrains with unprecedented accuracy the amplitude and possible correlation (with the adiabatic mode) of non-decaying isocurvature fluctuations. The fractional primordial contributions of cold dark matter (CDM) isocurvature modes of the types expected in the curvaton and axion scenarios have upper bounds of 0.25% and 3.9% (95% CL), respectively. In models with arbitrarily correlated CDM or neutrino isocurvature modes, an anticorrelated isocurvature component can improve the _2 e_ by approximately 4 as a result of slightly lowering the theoretical prediction for the ` <_ 40 multipoles relative to the higher multipoles. Nonetheless, the data are consistent with adiabatic initial conditions

Boosting hot electron flux and catalytic activity at metal-oxide interfaces of PtCo bimetallic nanoparticles

Despite numerous studies, the origin of the enhanced catalytic performance of bimetallic nanoparticles (NPs) remains elusive because of the ever-changing surface structures, compositions, and oxidation states of NPs under reaction conditions. An effective strategy for obtaining critical clues for the phenomenon is real-time quantitative detection of hot electrons induced by a chemical reaction on the catalysts. Here, we investigate hot electrons excited on PtCo bimetallic NPs during H-2 oxidation by measuring the chemicurrent on a catalytic nanodiode while changing the Pt composition of the NPs. We reveal that the presence of a CoO/Pt interface enables efficient transport of electrons and higher catalytic activity for PtCo NPs. These results are consistent with theoretical calculations suggesting that lower activation energy and higher exothermicity are required for the reaction at the CoO/Pt interface

Controlling Activity and Selectivity Using Water in the Au-Catalysed Preferential Oxidation of CO in H\u3csub\u3e2\u3c/sub\u3e

Industrial hydrogen production through methane steam reforming exceeds 50 million tons annually and accounts for 2–5% of global energy consumption. The hydrogen product, even after processing by the water–gas shift, still typically contains ∼1% CO, which must be removed for many applications. Methanation (CO + 3H2 → CH4 + H2O) is an effective solution to this problem, but consumes 5–15% of the generated hydrogen. The preferential oxidation (PROX) of CO with O2 in hydrogen represents a more-efficient solution. Supported gold nanoparticles, with their high CO-oxidation activity and notoriously low hydrogenation activity, have long been examined as PROX catalysts, but have shown disappointingly low activity and selectivity. Here we show that, under the proper conditions, a commercial Au/Al2O3 catalyst can remove CO to below 10 ppm and still maintain an O2-to-CO2 selectivity of 80–90%. The key to maximizing the catalyst activity and selectivity is to carefully control the feed-flow rate and maintain one to two monolayers of water (a key CO-oxidation co-catalyst) on the catalyst surface

DDX5 plays essential transcriptional and post-transcriptional roles in the maintenance and function of spermatogonia

Mammalian spermatogenesis is sustained by mitotic germ cells with self-renewal potential known as undifferentiated spermatogonia. Maintenance of undifferentiated spermatogonia and spermatogenesis is dependent on tightly co-ordinated transcriptional and post-transcriptional mechanisms. The RNA helicase DDX5 is expressed by spermatogonia but roles in spermatogenesis are unexplored. Using an inducible knockout mouse model, we characterise an essential role for DDX5 in spermatogonial maintenance and show that Ddx5 is indispensable for male fertility. We demonstrate that DDX5 regulates appropriate splicing of key genes necessary for spermatogenesis. Moreover, DDX5 regulates expression of cell cycle genes in undifferentiated spermatogonia post-transcriptionally and is required for cell proliferation and survival. DDX5 can also act as a transcriptional co-activator and we demonstrate that DDX5 interacts with PLZF, a transcription factor required for germline maintenance, to co-regulate select target genes. Combined, our data reveal a critical multifunctional role for DDX5 in regulating gene expression programmes and activity of undifferentiated spermatogonia

Microprocessor mediates transcriptional termination of long noncoding RNA transcripts hosting microRNAs

MicroRNA (miRNA) play a major role in the post-transcriptional regulation of gene expression. Mammalian miRNA biogenesis begins with co-transcriptional cleavage of RNA polymerase II (Pol II) transcripts by the Microprocessor complex. While most miRNA are located within introns of protein coding genes, a substantial minority of miRNA originate from long non coding (lnc) RNA where transcript processing is largely uncharacterized. Here, by detailed characterization of liver-specific lnc-pri-miR-122 and genome-wide analysis, we show that most lnc-pri-miRNA do not use the canonical cleavage and polyadenylation (CPA) pathway but instead use Microprocessor cleavage to terminate transcription. Microprocessor inactivation leads to extensive transcriptional readthrough of lnc-pri-miRNA and transcriptional interference with downstream genes. Consequently we define a novel RNase III-mediated, polyadenylation-independent mechanism of Pol II transcription termination in mammalian cells

Fetuin-A Induces Cytokine Expression and Suppresses Adiponectin Production

BACKGROUND: The secreted liver protein fetuin-A (AHSG) is up-regulated in hepatic steatosis and the metabolic syndrome. These states are strongly associated with low-grade inflammation and hypoadiponectinemia. We, therefore, hypothesized that fetuin-A may play a role in the regulation of cytokine expression, the modulation of adipose tissue expression and plasma concentration of the insulin-sensitizing and atheroprotective adipokine adiponectin. METHODOLOGY AND PRINCIPAL FINDINGS: Human monocytic THP1 cells and human in vitro differenttiated adipocytes as well as C57BL/6 mice were treated with fetuin-A. mRNA expression of the genes encoding inflammatory cytokines and the adipokine adiponectin (ADIPOQ) was assessed by real-time RT-PCR. In 122 subjects, plasma levels of fetuin-A, adiponectin and, in a subgroup, the multimeric forms of adiponectin were determined. Fetuin-A treatment induced TNF and IL1B mRNA expression in THP1 cells (p<0.05). Treatment of mice with fetuin-A, analogously, resulted in a marked increase in adipose tissue Tnf mRNA as well as Il6 expression (27- and 174-fold, respectively). These effects were accompanied by a decrease in adipose tissue Adipoq mRNA expression and lower circulating adiponectin levels (p<0.05, both). Furthermore, fetuin-A repressed ADIPOQ mRNA expression of human in vitro differentiated adipocytes (p<0.02) and induced inflammatory cytokine expression. In humans in plasma, fetuin-A correlated positively with high-sensitivity C-reactive protein, a marker of subclinical inflammation (r = 0.26, p = 0.01), and negatively with total- (r = -0.28, p = 0.02) and, particularly, high molecular weight adiponectin (r = -0.36, p = 0.01). CONCLUSIONS AND SIGNIFICANCE: We provide novel evidence that the secreted liver protein fetuin-A induces low-grade inflammation and represses adiponectin production in animals and in humans. These data suggest an important role of fatty liver in the pathophysiology of insulin resistance and atherosclerosis