Type IIn supernovae at z ~ 2 from archival data

Supernovae have been confirmed to redshift z ~ 1.7 for type Ia (thermonuclear detonation of a white dwarf) and to z ~ 0.7 for type II (collapse of the core of the star). The subclass type IIn supernovae are luminous core-collapse explosions of massive stars and, unlike other types, are very bright in the ultraviolet, which should enable them to be found optically at redshifts z ~ 2 and higher. In addition, the interaction of the ejecta with circumstellar material creates strong, long-lived emission lines that allow spectroscopic confirmation of many events of this type at z ~ 2 for 3 - 5 years after explosion. Here we report three spectroscopically confirmed type IIn supernovae, at redshifts z = 0.808, 2.013 and 2.357, detected in archival data using a method designed to exploit these properties at z ~ 2. Type IIn supernovae directly probe the formation of massive stars at high redshift. The number found to date is consistent with the expectations of a locally measured stellar initial mass function, but not with an evolving initial mass function proposed to explain independent observations at low and high redshift.Comment: 8 pages, 2 figures, includes supplementary informatio

Chromosome studies in Orchidaceae from Argentina

The center of diversity of Argentinean orchids is in the northeast region of the country. Chromosome numbers and karyotype features of 43 species belonging to 28 genera are presented here. Five chromosome records are the first ones at the genus level; these taxa are Aspidogyne kuckzinskii (2n = 42), Eurystyles actinosophila (2n = 56), Skeptrostachys paraguayensis (2n = 46), Stigmatosema polyaden (2n = 40) and Zygostates alleniana (2n = 54). In addition, a chromosome number is presented for the first time for 15 species: Corymborkis flava (2n = 56), Cyclopogon callophyllus (2n = 28), C. oliganthus (2n = 64), Cyrtopodium hatschbachii (2n = 46), C. palmifrons (2n = 46), Galeandra beyrichii (2n = 54), Habenaria bractescens (2n = 44), Oncidium edwallii (2n = 42), O. fimbriatum (2n = 56), O. pubes (2n = 84), O. riograndense (2n = 56), Pelexia ekmanii (2n = 46), P. lindmanii (2n = 46) and Warrea warreana (2n = 48). For Oncidium longicornu (2n = 42), O. divaricatum (2n = 56) and Sarcoglottis fasciculata (2n = 46+1B?, 46+3B?), a new cytotype was found. Chromosome data support phylogenetic relationships proposed by previous cytological, morphologic and molecular analyses, and in all the cases cover some gaps in the South American literature on orchid chromosomes

Effective transcription factor binding site prediction using a combination of optimization, a genetic algorithm and discriminant analysis to capture distant interactions

<p>Abstract</p> <p>Background</p> <p>Reliable transcription factor binding site (TFBS) prediction methods are essential for computer annotation of large amount of genome sequence data. However, current methods to predict TFBSs are hampered by the high false-positive rates that occur when only sequence conservation at the core binding-sites is considered.</p> <p>Results</p> <p>To improve this situation, we have quantified the performance of several Position Weight Matrix (PWM) algorithms, using exhaustive approaches to find their optimal length and position. We applied these approaches to bio-medically important TFBSs involved in the regulation of cell growth and proliferation as well as in inflammatory, immune, and antiviral responses (NF-κB, ISGF3, IRF1, STAT1), obesity and lipid metabolism (PPAR, SREBP, HNF4), regulation of the steroidogenic (SF-1) and cell cycle (E2F) genes expression. We have also gained extra specificity using a method, entitled SiteGA, which takes into account structural interactions within TFBS core and flanking regions, using a genetic algorithm (GA) with a discriminant function of locally positioned dinucleotide (LPD) frequencies.</p> <p>To ensure a higher confidence in our approach, we applied resampling-jackknife and bootstrap tests for the comparison, it appears that, optimized PWM and SiteGA have shown similar recognition performances. Then we applied SiteGA and optimized PWMs (both separately and together) to sequences in the Eukaryotic Promoter Database (EPD). The resulting SiteGA recognition models can now be used to search sequences for BSs using the web tool, SiteGA.</p> <p>Analysis of dependencies between close and distant LPDs revealed by SiteGA models has shown that the most significant correlations are between close LPDs, and are generally located in the core (footprint) region. A greater number of less significant correlations are mainly between distant LPDs, which spanned both core and flanking regions. When SiteGA and optimized PWM models were applied together, this substantially reduced false positives at least at higher stringencies.</p> <p>Conclusion</p> <p>Based on this analysis, SiteGA adds substantial specificity even to optimized PWMs and may be considered for large-scale genome analysis. It adds to the range of techniques available for TFBS prediction, and EPD analysis has led to a list of genes which appear to be regulated by the above TFs.</p

A Novel Secretion Pathway of Salmonella enterica Acts as an Antivirulence Modulator during Salmonellosis

Salmonella spp. are Gram-negative enteropathogenic bacteria that infect a variety of vertebrate hosts. Like any other living organism, protein secretion is a fundamental process essential for various aspects of Salmonella biology. Herein we report the identification and characterization of a horizontally acquired, autonomous and previously unreported secretion pathway. In Salmonella enterica serovar Typhimurium, this novel secretion pathway is encoded by STM1669 and STM1668, designated zirT and zirS, respectively. We show that ZirT is localized to the bacterial outer membrane, expected to adopt a compact β-barrel conformation, and functions as a translocator for ZirS. ZirS is an exoprotein, which is secreted into the extracellular environment in a ZirT-dependent manner. The ZirTS secretion pathway was found to share several important features with two-partner secretion (TPS) systems and members of the intimin/invasin family of adhesions. We show that zirTS expression is affected by zinc; and that in vivo, induction of zirT occurs distinctively in Salmonella colonizing the small intestine, but not in systemic sites. Additionally, strong expression of zirT takes place in Salmonella shed in fecal pellets during acute and persistent infections of mice. Inactivation of ZirTS results in a hypervirulence phenotype of Salmonella during oral infection of mice. Cumulatively, these results indicate that the ZirTS pathway plays a unique role as an antivirulence modulator during systemic disease and is involved in fine-tuning a host–pathogen balance during salmonellosis

Chest wall syndrome among primary care patients: a cohort study

BACKGROUND: The epidemiology of chest pain differs strongly between outpatient and emergency settings. In general practice, the most frequent cause is the chest wall pain. However, there is a lack of information about the characteristics of this syndrome. The aims of the study are to describe the clinical aspects of chest wall syndrome (CWS). METHODS: Prospective, observational, cohort study of patients attending 58 private practices over a five-week period from March to May 2001 with undifferentiated chest pain. During a one-year follow-up, questionnaires including detailed history and physical exam, were filled out at initial consultation, 3 and 12 months. The outcomes were: clinical characteristics associated with the CWS diagnosis and clinical evolution of the syndrome. RESULTS: Among 24 620 consultations, we observed 672 cases of chest pain and 300 (44.6%) patients had a diagnosis of chest wall syndrome. It affected all ages with a sex ratio of 1:1. History and sensibility to palpation were the keys for diagnosis. Pain was generally moderate, well localised, continuous or intermittent over a number of hours to days or weeks, and amplified by position or movement. The pain however, may be acute. Eighty-eight patients were affected at several painful sites, and 210 patients at a single site, most frequently in the midline or a left-sided site. Pain was a cause of anxiety and cardiac concern, especially when acute. CWS coexisted with coronary disease in 19 and neoplasm in 6. Outcome at one year was favourable even though CWS recurred in half of patients. CONCLUSION: CWS is common and benign, but leads to anxiety and recurred frequently. Because the majority of chest wall pain is left-sided, the possibility of coexistence with coronary disease needs careful consideration

Nrf2 protects against pulmonary fibrosis by regulating the lung oxidant level and Th1/Th2 balance

<p>Abstract</p> <p>Background</p> <p>Pulmonary fibrosis is a progressive and lethal disorder. Although the precise mechanisms of pulmonary fibrosis are not fully understood, oxidant/antioxidant and Th1/Th2 balances may play an important role in many of the processes of inflammation and fibrosis. The transcription factor Nrf2 acts as a critical regulator for various inflammatory and immune responses by controlling oxidative stress. We therefore investigated the protective role of Nrf2 against the development of pulmonary fibrosis.</p> <p>Methods</p> <p>To generate pulmonary fibrosis, both wild-type C57BL/6 mice and Nrf2-deficient mice of the same background were administered bleomycin intratracheally.</p> <p>Results</p> <p>The survival of Nrf2-deficient mice after bleomycin administration was significantly lower than that of wild-type mice. The degree of bleomycin-induced initial pulmonary inflammation and pulmonary fibrosis was much more severe in Nrf2-deficient mice than in wild-type mice. The expression of antioxidant enzymes and phase II detoxifying enzymes was significantly reduced in the lungs of Nrf2-deficient mice, concomitant with an elevation of lung 8-isoprostane level, compared with wild-type mice. The expression of Th2 cytokines, such as interleukin-4 and interleukin-13, was significantly elevated in the lungs of Nrf2-deficient mice with an increase in the number of Th2 cells that express GATA-binding protein 3.</p> <p>Conclusions</p> <p>The results indicated that Nrf2 protects against the development of pulmonary fibrosis by regulating the cellular redox level and lung Th1/Th2 balance. Thus, Nrf2 might be an important genetic factor in the determination of susceptibility to pulmonary fibrosis.</p

Unifying generative and discriminative learning principles

<p>Abstract</p> <p>Background</p> <p>The recognition of functional binding sites in genomic DNA remains one of the fundamental challenges of genome research. During the last decades, a plethora of different and well-adapted models has been developed, but only little attention has been payed to the development of different and similarly well-adapted learning principles. Only recently it was noticed that discriminative learning principles can be superior over generative ones in diverse bioinformatics applications, too.</p> <p>Results</p> <p>Here, we propose a generalization of generative and discriminative learning principles containing the maximum likelihood, maximum a posteriori, maximum conditional likelihood, maximum supervised posterior, generative-discriminative trade-off, and penalized generative-discriminative trade-off learning principles as special cases, and we illustrate its efficacy for the recognition of vertebrate transcription factor binding sites.</p> <p>Conclusions</p> <p>We find that the proposed learning principle helps to improve the recognition of transcription factor binding sites, enabling better computational approaches for extracting as much information as possible from valuable wet-lab data. We make all implementations available in the open-source library Jstacs so that this learning principle can be easily applied to other classification problems in the field of genome and epigenome analysis.</p

Apples and oranges: avoiding different priors in Bayesian DNA sequence analysis

<p>Abstract</p> <p>Background</p> <p>One of the challenges of bioinformatics remains the recognition of short signal sequences in genomic DNA such as donor or acceptor splice sites, splicing enhancers or silencers, translation initiation sites, transcription start sites, transcription factor binding sites, nucleosome binding sites, miRNA binding sites, or insulator binding sites. During the last decade, a wealth of algorithms for the recognition of such DNA sequences has been developed and compared with the goal of improving their performance and to deepen our understanding of the underlying cellular processes. Most of these algorithms are based on statistical models belonging to the family of Markov random fields such as position weight matrix models, weight array matrix models, Markov models of higher order, or moral Bayesian networks. While in many comparative studies different learning principles or different statistical models have been compared, the influence of choosing different prior distributions for the model parameters when using different learning principles has been overlooked, and possibly lead to questionable conclusions.</p> <p>Results</p> <p>With the goal of allowing direct comparisons of different learning principles for models from the family of Markov random fields based on the <it>same a-priori information</it>, we derive a generalization of the commonly-used product-Dirichlet prior. We find that the derived prior behaves like a Gaussian prior close to the maximum and like a Laplace prior in the far tails. In two case studies, we illustrate the utility of the derived prior for a direct comparison of different learning principles with different models for the recognition of binding sites of the transcription factor Sp1 and human donor splice sites.</p> <p>Conclusions</p> <p>We find that comparisons of different learning principles using the same a-priori information can lead to conclusions different from those of previous studies in which the effect resulting from different priors has been neglected. We implement the derived prior is implemented in the open-source library Jstacs to enable an easy application to comparative studies of different learning principles in the field of sequence analysis.</p