Variations in the 6.2 μ\mum emission profile in starburst-dominated galaxies: a signature of polycyclic aromatic nitrogen heterocycles (PANHs)?

Analyses of the polycyclic aromatic hydrocarbon (PAH) feature profiles, especially the 6.2 $\mu$m feature, could indicate the presence of nitrogen incorporated in their aromatic rings. In this work, 155 predominantly starburst-dominated galaxies (including HII regions and Seyferts, for example), extracted from the Spitzer/IRS ATLAS project (Hern\'an-Caballero & Hatziminaoglou 2011), have their 6.2 $\mu$m profiles fitted allowing their separation into the Peeters' A, B and C classes (Peeters et al. 2002). 67% of these galaxies were classified as class A, 31% were as class B and 2% as class C. Currently class A sources, corresponding to a central wavelength near 6.22 $\mu$m, seem only to be explained by polycyclic aromatic nitrogen heterocycles (PANH, Hudgins et al. 2005), whereas class B may represent a mix between PAHs and PANHs emissions or different PANH structures or ionization states. Therefore, these spectra suggest a significant presence of PANHs in the interstellar medium (ISM) of these galaxies that could be related to their starburst-dominated emission. These results also suggest that PANHs constitute another reservoir of nitrogen in the Universe, in addition to the nitrogen in the gas phase and ices of the ISM

Comment on "Ab initio calculations of the lattice parameter and elastic stiffness coefficients of bcc Fe with solutes" Comp. Mat. Sci. v.126 pp.503-513 (2017)

In a recent paper, the authors propose to separately calculate the volumetric and chemical contributions to the elastic stiffness coefficients of systems containing solutes, as it is "computationally more efficient". We show that this is not the case and further that their methodology and hence their results are incorrect. There is no short cut for performing the desired calculations, if done rigorously, as we show in our 2012 work

Prevalent genes encoding carbohydrate-active enzymes.

<p>Prevalent genes encoding carbohydrate-active enzymes.</p

Abundance profiling of specific gene groups using precomputed gut metagenomes yields novel biological hypotheses

<div><p>The gut microbiota is essentially a multifunctional bioreactor within a human being. The exploration of its enormous metabolic potential provides insights into the mechanisms underlying microbial ecology and interactions with the host. The data obtained using “shotgun” metagenomics capture information about the whole spectrum of microbial functions. However, each new study presenting new sequencing data tends to extract only a little of the information concerning the metabolic potential and often omits specific functions. A meta-analysis of the available data with an emphasis on biomedically relevant gene groups can unveil new global trends in the gut microbiota. As a step toward the reuse of metagenomic data, we developed a method for the quantitative profiling of user-defined groups of genes in human gut metagenomes. This method is based on the quick analysis of a gene coverage matrix obtained by pre-mapping the metagenomic reads to a global gut microbial catalogue. The method was applied to profile the abundance of several gene groups related to antibiotic resistance, phages, biosynthesis clusters and carbohydrate degradation in 784 metagenomes from healthy populations worldwide and patients with inflammatory bowel diseases and obesity. We discovered country-wise functional specifics in gut resistome and virome compositions. The most distinct features of the disease microbiota were found for Crohn’s disease, followed by ulcerative colitis and obesity. Profiling of the genes belonging to crAssphage showed that its abundance varied across the world populations and was not associated with clinical status. We demonstrated temporal resilience of crAssphage and the influence of the sample preparation protocol on its detected abundance. Our approach offers a convenient method to add value to accumulated “shotgun” metagenomic data by helping researchers state and assess novel biological hypotheses.</p></div

Prevalence of the detected RiPP synthesis clusters in the metagenomes of healthy populations.

<p>The cluster names (along X axis) are indicated as in the original article [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0176154#pone.0176154.ref007" target="_blank">7</a>]. For each cluster, there are 5 colored bars indicating the prevalence of the cluster for each of the groups.</p

Methods comparison table.

<p>Methods comparison table.</p

Relative abundance of crAssphage reads in groups.

<p>Colored points represent distinct samples in different groups, with group statistics represented by faded boxplots in the background. Samples where no crAssphage genes were detected are not shown.</p

Distribution of discrepancy ratio for each gene set.

<p>Distribution of discrepancy ratio for each gene set.</p

Distribution of the metagenomes by the abundance of the genes associated with starch degradation.

<p>On the PCA plot, for each sample, the color shows the most abundant taxon. The color legend represents the three major taxa (the <i>Bacteroidaceae</i> and <i>Prevotellaceae</i> families and the <i>Clostridiales</i> order). The latter taxon was taken at a higher level of phylogenetic hierarchy because it includes multiple starch-degrading families (i.e., <i>Eubacteriaceae</i> and <i>Ruminococcaceae</i>), which together contribute to the observed gradient without a clear single driver. The percent of total variance explained by each of the first two principal components is included in the respective axes labels.</p

The most prevalent antibiotic resistance gene types in gut metagenomes.

<p>Colored bars show the prevalence for the healthy populations of the world. The dotted black line corresponds to fraction in patients with ulcerative colitis only and the solid black line corresponds to fraction in patients with Crohn’s disease only.</p