Radiative Transfer for Exoplanet Atmospheres

Remote sensing of the atmospheres of distant worlds motivates a firm understanding of radiative transfer. In this review, we provide a pedagogical cookbook that describes the principal ingredients needed to perform a radiative transfer calculation and predict the spectrum of an exoplanet atmosphere, including solving the radiative transfer equation, calculating opacities (and chemistry), iterating for radiative equilibrium (or not), and adapting the output of the calculations to the astronomical observations. A review of the state of the art is performed, focusing on selected milestone papers. Outstanding issues, including the need to understand aerosols or clouds and elucidating the assumptions and caveats behind inversion methods, are discussed. A checklist is provided to assist referees/reviewers in their scrutiny of works involving radiative transfer. A table summarizing the methodology employed by past studies is provided.Comment: 7 pages, no figures, 1 table. Filled in missing information in references, main text unchange

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Measurement of the t¯tZ and t¯tW cross sections in proton-proton collisions at √s=13 TeV with the ATLAS detector

A measurement of the associated production of a top-quark pair (t¯t) with a vector boson (W, Z) in proton-proton collisions at a center-of-mass energy of 13 TeV is presented, using 36.1  fb−1 of integrated luminosity collected by the ATLAS detector at the Large Hadron Collider. Events are selected in channels with two same- or opposite-sign leptons (electrons or muons), three leptons or four leptons, and each channel is further divided into multiple regions to maximize the sensitivity of the measurement. The t¯tZ and t¯tW production cross sections are simultaneously measured using a combined fit to all regions. The best-fit values of the production cross sections are σt¯tZ=0.95±0.08stat±0.10syst pb and σt¯tW=0.87±0.13stat±0.14syst pb in agreement with the Standard Model predictions. The measurement of the t¯tZ cross section is used to set constraints on effective field theory operators which modify the t¯tZ vertex

Myelin Proteomics: Molecular Anatomy of an Insulating Sheath

Fast-transmitting vertebrate axons are electrically insulated with multiple layers of nonconductive plasma membrane of glial cell origin, termed myelin. The myelin membrane is dominated by lipids, and its protein composition has historically been viewed to be of very low complexity. In this review, we discuss an updated reference compendium of 342 proteins associated with central nervous system myelin that represents a valuable resource for analyzing myelin biogenesis and white matter homeostasis. Cataloging the myelin proteome has been made possible by technical advances in the separation and mass spectrometric detection of proteins, also referred to as proteomics. This led to the identification of a large number of novel myelin-associated proteins, many of which represent low abundant components involved in catalytic activities, the cytoskeleton, vesicular trafficking, or cell adhesion. By mass spectrometry-based quantification, proteolipid protein and myelin basic protein constitute 17% and 8% of total myelin protein, respectively, suggesting that their abundance was previously overestimated. As the biochemical profile of myelin-associated proteins is highly reproducible, differential proteome analyses can be applied to material isolated from patients or animal models of myelin-related diseases such as multiple sclerosis and leukodystrophies

Immunoglobulin Genomics in the Guinea Pig (Cavia porcellus)

In science, the guinea pig is known as one of the gold standards for modeling human disease. It is especially important as a molecular and cellular biology model for studying the human immune system, as its immunological genes are more similar to human genes than are those of mice. The utility of the guinea pig as a model organism can be further enhanced by further characterization of the genes encoding components of the immune system. Here, we report the genomic organization of the guinea pig immunoglobulin (Ig) heavy and light chain genes. The guinea pig IgH locus is located in genomic scaffolds 54 and 75, and spans approximately 6,480 kb. 507 VH segments (94 potentially functional genes and 413 pseudogenes), 41 DH segments, six JH segments, four constant region genes (μ, γ, ε, and α), and one reverse δ remnant fragment were identified within the two scaffolds. Many VH pseudogenes were found within the guinea pig, and likely constituted a potential donor pool for gene conversion during evolution. The Igκ locus mapped to a 4,029 kb region of scaffold 37 and 24 is composed of 349 Vκ (111 potentially functional genes and 238 pseudogenes), three Jκ and one Cκ genes. The Igλ locus spans 1,642 kb in scaffold 4 and consists of 142 Vλ (58 potentially functional genes and 84 pseudogenes) and 11 Jλ -Cλ clusters. Phylogenetic analysis suggested the guinea pig’s large germline VH gene segments appear to form limited gene families. Therefore, this species may generate antibody diversity via a gene conversion-like mechanism associated with its pseudogene reserves

Experimental Microbial Evolution of Extremophiles

Experimental microbial evolutions (EME) involves studying closely a microbial population after it has been through a large number of generations under controlled conditions (Kussell 2013). Adaptive laboratory evolution (ALE) selects for fitness under experimentally imposed conditions (Bennett and Hughes 2009; Dragosits and Mattanovich 2013). However, experimental evolution studies focusing on the contributions of genetic drift and natural mutation rates to evolution are conducted under non-selective conditions to avoid changes imposed by selection (Hindré et al. 2012). To understand the application of experimental evolutionary methods to extremophiles it is essential to consider the recent growth in this field over the last decade using model non-extremophilic microorganisms. This growth reflects both a greater appreciation of the power of experimental evolution for testing evolutionary hypotheses and, especially recently, the new power of genomic methods for analyzing changes in experimentally evolved lineages. Since many crucial processes are driven by microorganisms in nature, it is essential to understand and appreciate how microbial communities function, particularly with relevance to selection. However, many theories developed to understand microbial ecological patterns focus on the distribution and the structure of diversity within a microbial population comprised of single species (Prosser et al. 2007). Therefore an understanding of the concept of species is needed. A common definition of species using a genetic concept is a group of interbreeding individuals that is isolated from other such groups by barriers of recombination (Prosser et al. 2007). An alternative ecological species concept defines a species as set of individuals that can be considered identical in all relevant ecological traits (Cohan 2001). This is particularly important because of the abundance and deep phylogenetic complexity of microbial communities. Cohan postulated that “bacteria occupy discrete niches and that periodic selection will purge genetic variation within each niche without preventing divergence between the inhabitants of different niches”. The importance of gene exchange mechanisms likely in bacteria and archaea and therefore extremophiles, arises from the fact that their genomes are divided into two distinct parts, the core genome and the accessory genome (Cohan 2001). The core genome consists of genes that are crucial for the functioning of an organism and the accessory genome consists of genes that are capable of adapting to the changing ecosystem through gain and loss of function. Strains that belong to the same species can differ in the composition of accessory genes and therefore their capability to adapt to changing ecosystems (Cohan 2001; Tettelin et al. 2005; Gill et al. 2005). Additional ecological diversity exists in plasmids, transposons and pathogenicity islands as they can be easily shared in a favorable environment but still be absent in the same species found elsewhere (Wertz et al. 2003). This poses a major challenge for studying ALE and community microbial ecology indicating a continued need to develop a fitting theory that connects the fluid nature of microbial communities to their ecology (Wertz et al. 2003; Coleman et al. 2006). Understanding the nature and contribution of different processes that determine the frequencies of genes in any population is the biggest concern in population and evolutionary genetics (Prosser et al. 2007) and it is critical for an understanding of experimental evolution

Complete Genome Sequence of the N2-Fixing Broad Host Range Endophyte Klebsiella pneumoniae 342 and Virulence Predictions Verified in Mice

We report here the sequencing and analysis of the genome of the nitrogen-fixing endophyte, Klebsiella pneumoniae 342. Although K. pneumoniae 342 is a member of the enteric bacteria, it serves as a model for studies of endophytic, plant-bacterial associations due to its efficient colonization of plant tissues (including maize and wheat, two of the most important crops in the world), while maintaining a mutualistic relationship that encompasses supplying organic nitrogen to the host plant. Genomic analysis examined K. pneumoniae 342 for the presence of previously identified genes from other bacteria involved in colonization of, or growth in, plants. From this set, approximately one-third were identified in K. pneumoniae 342, suggesting additional factors most likely contribute to its endophytic lifestyle. Comparative genome analyses were used to provide new insights into this question. Results included the identification of metabolic pathways and other features devoted to processing plant-derived cellulosic and aromatic compounds, and a robust complement of transport genes (15.4%), one of the highest percentages in bacterial genomes sequenced. Although virulence and antibiotic resistance genes were predicted, experiments conducted using mouse models showed pathogenicity to be attenuated in this strain. Comparative genomic analyses with the presumed human pathogen K. pneumoniae MGH78578 revealed that MGH78578 apparently cannot fix nitrogen, and the distribution of genes essential to surface attachment, secretion, transport, and regulation and signaling varied between each genome, which may indicate critical divergences between the strains that influence their preferred host ranges and lifestyles (endophytic plant associations for K. pneumoniae 342 and presumably human pathogenesis for MGH78578). Little genome information is available concerning endophytic bacteria. The K. pneumoniae 342 genome will drive new research into this less-understood, but important category of bacterial-plant host relationships, which could ultimately enhance growth and nutrition of important agricultural crops and development of plant-derived products and biofuels

Production of dust by massive stars at high redshift

The large amounts of dust detected in sub-millimeter galaxies and quasars at high redshift pose a challenge to galaxy formation models and theories of cosmic dust formation. At z > 6 only stars of relatively high mass (> 3 Msun) are sufficiently short-lived to be potential stellar sources of dust. This review is devoted to identifying and quantifying the most important stellar channels of rapid dust formation. We ascertain the dust production efficiency of stars in the mass range 3-40 Msun using both observed and theoretical dust yields of evolved massive stars and supernovae (SNe) and provide analytical expressions for the dust production efficiencies in various scenarios. We also address the strong sensitivity of the total dust productivity to the initial mass function. From simple considerations, we find that, in the early Universe, high-mass (> 3 Msun) asymptotic giant branch stars can only be dominant dust producers if SNe generate <~ 3 x 10^-3 Msun of dust whereas SNe prevail if they are more efficient. We address the challenges in inferring dust masses and star-formation rates from observations of high-redshift galaxies. We conclude that significant SN dust production at high redshift is likely required to reproduce current dust mass estimates, possibly coupled with rapid dust grain growth in the interstellar medium.Comment: 72 pages, 9 figures, 5 tables; to be published in The Astronomy and Astrophysics Revie

Performance and calibration of quark/gluon-jet taggers using 140 fb⁻¹ of pp collisions at √s=13 TeV with the ATLAS detector

The identification of jets originating from quarks and gluons, often referred to as quark/gluon tagging, plays an important role in various analyses performed at the Large Hadron Collider, as Standard Model measurements and searches for new particles decaying to quarks often rely on suppressing a large gluon-induced background. This paper describes the measurement of the efficiencies of quark/gluon taggers developed within the ATLAS Collaboration, using √s=13 TeV proton–proton collision data with an integrated luminosity of 140 fb-1 collected by the ATLAS experiment. Two taggers with high performances in rejecting jets from gluon over jets from quarks are studied: one tagger is based on requirements on the number of inner-detector tracks associated with the jet, and the other combines several jet substructure observables using a boosted decision tree. A method is established to determine the quark/gluon fraction in data, by using quark/gluon-enriched subsamples defined by the jet pseudorapidity. Differences in tagging efficiency between data and simulation are provided for jets with transverse momentum between 500 GeV and 2 TeV and for multiple tagger working points