Warpfield population synthesis: The physics of (extra-)Galactic star formation and feedback-driven cloud structure and emission from sub-to-kpc scales

We present a novel method to model galactic-scale star formation and emission of star clusters and a multiphase interstellar medium (ISM). We combine global parameters, including star formation rate and metallicity, with the 1D cloud evolution code warpfield to model the sources of feedback within a star-forming galaxy. Within individual star-forming regions, we include stellar evolution, stellar winds, radiation pressure, and supernovae, all coupled to the dynamical evolution of the 1D parental cloud in a highly non-linear fashion. Heating of the diffuse galactic gas and dust is calculated self-consistently with the age-, mass-, and density-dependent escape fractions of photons from these fully resolved local star-forming regions. We construct the interstellar radiation field, and we employ the multifrequency radiative transfer code polaris to produce synthetic emission maps for a one-to-one comparison with observations. We apply this to a cosmological simulation of a Milky-Way-like galaxy built-up in a high-resolution MHD simulation of cosmic structure formation. From this, we produce the multiscale/phase distribution of ISM density and temperature and present a synthesized all-sky H α map. We use a multipole expansion to show that the resulting maps reproduce all observed statistical emission characteristics. Next, we predict [S iii] 9530 Å, a key emission line that will be observed in several large forthcoming surveys. It suffers less extinction than other lines and provides information about star formation in very dense environments that are otherwise observationally inaccessible optically. Finally, we explore the effects of differential extinction, and discuss the consequences for the interpretation of H α emission at different viewing angles by an extragalactic observer

The radio spectral energy distribution and star-formation rate calibration in galaxies

We study the spectral energy distribution (SED) of the radio continuum (RC) emission from the Key Insight in Nearby Galaxies Emitting in Radio (KINGFISHER) sample of nearby galaxies to understand the energetics and origin of this emission. Effelsberg multi-wavelength observations at 1.4, 4.8, 8.4, and 10.5 GHz combined with archive data allow us, for the first time, to determine the mid-RC (1-10 GHz, MRC) bolometric luminosities and further present calibration relations versus the monochromatic radio luminosities. The 1-10 GHz radio SED is fitted using a Bayesian Markov Chain Monte Carlo technique leading to measurements for the nonthermal spectral index (S-nu similar to nu(-alpha nt)) and the thermal fraction (f(th)) with mean values of alpha(nt)= 0.97 +/- 0.16(0.79 +/- 0.15 for the total spectral index) and f(th) = (10 +/- 9)% at 1.4 GHz. The MRC luminosity changes over similar to 3 orders of magnitude in the sample, 4.3 x 10(2) L-circle dot < MRC < 3.9 x 10(5) L-circle dot. The thermal emission is responsible for similar to 23% of the MRC on average. We also compare the extinction-corrected diagnostics of the. star-formation rate (SFR) with the thermal and nonthermal radio tracers and derive the first star-formation calibration relations using the MRC radio luminosity. The nonthermal spectral index flattens with increasing SFR surface density, indicating the effect of the star-formation feedback on the cosmic-ray electron population in galaxies. Comparing the radio and IR SEDs, we find that the FIR-to-MRC ratio could decrease with SFR, due to the amplification of the magnetic fields in starforming regions. This particularly implies a decrease in the ratio at high redshifts, where mostly luminous/starforming galaxies are detected

DODO: an efficient orthologous genes assignment tool based on domain architectures. Domain based ortholog detection

<p>Abstract</p> <p>Background</p> <p>Orthologs are genes derived from the same ancestor gene loci after speciation events. Orthologous proteins usually have similar sequences and perform comparable biological functions. Therefore, ortholog identification is useful in annotations of newly sequenced genomes. With rapidly increasing number of sequenced genomes, constructing or updating ortholog relationship between all genomes requires lots of effort and computation time. In addition, elucidating ortholog relationships between distantly related genomes is challenging because of the lower sequence similarity. Therefore, an efficient ortholog detection method that can deal with large number of distantly related genomes is desired.</p> <p>Results</p> <p>An efficient ortholog detection pipeline DODO (DOmain based Detection of Orthologs) is created on the basis of domain architectures in this study. Supported by domain composition, which usually directly related with protein function, DODO could facilitate orthologs detection across distantly related genomes. DODO works in two main steps. Starting from domain information, it first assigns protein groups according to their domain architectures and further identifies orthologs within those groups with much reduced complexity. Here DODO is shown to detect orthologs between two genomes in considerably shorter period of time than traditional methods of reciprocal best hits and it is more significant when analyzed a large number of genomes. The output results of DODO are highly comparable with other known ortholog databases.</p> <p>Conclusions</p> <p>DODO provides a new efficient pipeline for detection of orthologs in a large number of genomes. In addition, a database established with DODO is also easier to maintain and could be updated relatively effortlessly. The pipeline of DODO could be downloaded from <url>http://140.109.42.19:16080/dodo_web/home.htm</url></p

Evaluation of Physicochemical and Antioxidant Properties of Peanut Protein Hydrolysate

Peanut protein and its hydrolysate were compared with a view to their use as food additives. The effects of pH, temperature and protein concentration on some of their key physicochemical properties were investigated. Compared with peanut protein, peanut peptides exhibited a significantly higher solubility and significantly lower turbidity at pH values 2–12 and temperature between 30 and 80°C. Peanut peptide showed better emulsifying capacity, foam capacity and foam stability, but had lower water holding and fat adsorption capacities over a wide range of protein concentrations (2–5 g/100 ml) than peanut protein isolate. In addition, peanut peptide exhibited in vitro antioxidant properties measured in terms of reducing power, scavenging of hydroxyl radical, and scavenging of DPPH radical. These results suggest that peanut peptide appeared to have better functional and antioxidant properties and hence has a good potential as a food additive

The Artelon CMC spacer compared with tendon interposition arthroplasty: A randomized, controlled, multicenter study of 109 patients with osteoarthritis followed for 1 year

Background and purpose The Artelon CMC spacer is designed for surgical treatment of osteoarthritis (OA) in the carpometacarpal joint of the thumb (CMC-I). Good results using this degradable device were previously presented in a pilot study. We now present results from a larger randomized, controlled, multicenter study

The Radio Spectral Energy Distribution and Star Formation Rate Calibration in Galaxies

We study the spectral energy distribution (SED) of the radio continuum (RC) emission from the Key Insight in Nearby Galaxies Emitting in Radio (KINGFISHER) sample of nearby galaxies to understand the energetics and origin of this emission. Effelsberg multi-wavelength observations at 1.4, 4.8, 8.4, and 10.5 GHz combined with archive data allow us, for the first time, to determine the mid-RC (1–10 GHz, MRC) bolometric luminosities and further present calibration relations versus the monochromatic radio luminosities. The 1–10 GHz radio SED is fitted using a Bayesian Markov Chain Monte Carlo technique leading to measurements for the nonthermal spectral index ($S_{\nu}$ ~ $\nu$$^ {-\alpha_{nt}}$) and the thermal fraction ($f_{\text{th}}$) with mean values of $\alpha_{nt}$ = 0.97 ± 0.16 (0.79 ± 0.15 for the total spectral index) and $f_{\text{th}}$ = (10 ± 9)% at 1.4 GHz. The MRC luminosity changes over ~3 orders of magnitude in the sample, 4.3 $\times$ 10$^2$ $L_\odot$ < MRC < 3.9 $\times$ 10$^5$ $L_\odot$. The thermal emission is responsible for ~23% of the MRC on average. We also compare the extinction-corrected diagnostics of the star-formation rate (SFR) with the thermal and nonthermal radio tracers and derive the first star-formation calibration relations using the MRC radio luminosity. The nonthermal spectral index flattens with increasing SFR surface density, indicating the effect of the star-formation feedback on the cosmic-ray electron population in galaxies. Comparing the radio and IR SEDs, we find that the FIR-to-MRC ratio could decrease with SFR, due to the amplification of the magnetic fields in star-forming regions. This particularly implies a decrease in the ratio at high redshifts, where mostly luminous/star-forming galaxies are detected.F.S.T. acknowledges support by the German Research Foundation DFG via the grant TA 801/1-1 and the Spanish Ministry of Economy and Competitiveness(MINECO) under grant number AYA2013-41243-P. R.B. acknowledges financial support from DFG Research Unit FOR1254. D.D.M acknowledges support from ERCStG 307215 (LODESTONE)

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Understanding Communication Signals during Mycobacterial Latency through Predicted Genome-Wide Protein Interactions and Boolean Modeling

About 90% of the people infected with Mycobacterium tuberculosis carry latent bacteria that are believed to get activated upon immune suppression. One of the fundamental challenges in the control of tuberculosis is therefore to understand molecular mechanisms involved in the onset of latency and/or reactivation. We have attempted to address this problem at the systems level by a combination of predicted functional protein∶protein interactions, integration of functional interactions with large scale gene expression studies, predicted transcription regulatory network and finally simulations with a Boolean model of the network. Initially a prediction for genome-wide protein functional linkages was obtained based on genome-context methods using a Support Vector Machine. This set of protein functional linkages along with gene expression data of the available models of latency was employed to identify proteins involved in mediating switch signals during dormancy. We show that genes that are up and down regulated during dormancy are not only coordinately regulated under dormancy-like conditions but also under a variety of other experimental conditions. Their synchronized regulation indicates that they form a tightly regulated gene cluster and might form a latency-regulon. Conservation of these genes across bacterial species suggests a unique evolutionary history that might be associated with M. tuberculosis dormancy. Finally, simulations with a Boolean model based on the regulatory network with logical relationships derived from gene expression data reveals a bistable switch suggesting alternating latent and actively growing states. Our analysis based on the interaction network therefore reveals a potential model of M. tuberculosis latency

An Improved, Bias-Reduced Probabilistic Functional Gene Network of Baker's Yeast, Saccharomyces cerevisiae

Background: Probabilistic functional gene networks are powerful theoretical frameworks for integrating heterogeneous functional genomics and proteomics data into objective models of cellular systems. Such networks provide syntheses of millions of discrete experimental observations, spanning DNA microarray experiments, physical protein interactions, genetic interactions, and comparative genomics; the resulting networks can then be easily applied to generate testable hypotheses regarding specific gene functions and associations. Methodology/Principal Findings: We report a significantly improved version (v. 2) of a probabilistic functional gene network [1] of the baker's yeast, Saccharomyces cerevisiae. We describe our optimization methods and illustrate their effects in three major areas: the reduction of functional bias in network training reference sets, the application of a probabilistic model for calculating confidences in pair-wise protein physical or genetic interactions, and the introduction of simple thresholds that eliminate many false positive mRNA co-expression relationships. Using the network, we predict and experimentally verify the function of the yeast RNA binding protein Puf6 in 60S ribosomal subunit biogenesis. Conclusions/Significance: YeastNet v. 2, constructed using these optimizations together with additional data, shows significant reduction in bias and improvements in precision and recall, in total covering 102,803 linkages among 5,483 yeast proteins (95% of the validated proteome). YeastNet is available from http://www.yeastnet.org.This work was supported by grants from the N.S.F. (IIS-0325116, EIA-0219061), N.I.H. (GM06779-01,GM076536-01), Welch (F-1515), and a Packard Fellowship (EMM). These agencies were not involved in the design and conduct of the study, in the collection, analysis, and interpretation of the data, or in the preparation, review, or approval of the manuscript.Cellular and Molecular Biolog