Direct damage controlled seismic design of plane steel degrading frames

A new method for seismic design of plane steel moment resisting framed structures is developed. This method is able to control damage at all levels of performance in a direct manner. More specifically, the method: (a) can determine damage in any member or the whole of a designed structure under any given seismic load, (b) can dimension a structure for a given seismic load and desired level of damage and (c) can determine the maximum seismic load a designed structure can sustain in order to exhibit a desired level of damage. In order to accomplish these things, an appropriate seismic damage index is used that takes into account the interaction between axial force and bending moment at a section, strength and stiffness degradation as well as low cycle fatigue. Then, damage scales are constructed on the basis of extensive parametric studies involving a large number of frames exhibiting cyclic strength and stiffness degradation and a large number of seismic motions and using the above damage index for damage determination. Some numerical examples are presented to illustrate the proposed method and demonstrate its advantages against other methods of seismic design. © 2014, Springer Science+Business Media Dordrecht

DIANA-microT Web server upgrade supports Fly and Worm miRNA target prediction and bibliographic miRNA to disease association

microRNAs (miRNAs) are small endogenous RNA molecules that are implicated in many biological processes through post-transcriptional regulation of gene expression. The DIANA-microT Web server provides a user-friendly interface for comprehensive computational analysis of miRNA targets in human and mouse. The server has now been extended to support predictions for two widely studied species: Drosophila melanogaster and Caenorhabditis elegans. In the updated version, the Web server enables the association of miRNAs to diseases through bibliographic analysis and provides insights for the potential involvement of miRNAs in biological processes. The nomenclature used to describe mature miRNAs along different miRBase versions has been extensively analyzed, and the naming history of each miRNA has been extracted. This enables the identification of miRNA publications regardless of possible nomenclature changes. User interaction has been further refined allowing users to save results that they wish to analyze further. A connection to the UCSC genome browser is now provided, enabling users to easily preview predicted binding sites in comparison to a wide array of genomic tracks, such as single nucleotide polymorphisms. The Web server is publicly accessible in www.microrna.gr/microT-v4

Resonant Amplification of Electroweak Baryogenesis at Preheating

We explore viable scenarios for parametric resonant amplification of electroweak (EW) gauge fields and Chern-Simons number during preheating, leading to baryogenesis at the electroweak (EW) scale. In this class of scenarios time-dependent classical EW gauge fields, essentially spatially-homogeneous on the horizon scales, carry Chern-Simons number which can be amplified by parametric resonance up to magnitudes at which unsuppressed topological transitions in the Higgs sector become possible. Baryon number non-conservation associated with the gauge sector and the highly non-equilibrium nature of preheating allow for efficient baryogenesis. The requisite large CP violation can arise either from the time dependence of a slowly varying Higgs field (spontaneous baryogenesis), or from a resonant amplification of CP violation induced in the gauge sector through loops. We identify several CP violating operators in the Standard Model and its minimal extensions that can facilitate efficient baryogenesis at preheating, and show how to overcome would-be exponential suppression of baryogenesis associated with tunneling barriers.Comment: 51 pages, 8 figues; minor corrections; references adde

DIANA-microT web server: elucidating microRNA functions through target prediction

Computational microRNA (miRNA) target prediction is one of the key means for deciphering the role of miRNAs in development and disease. Here, we present the DIANA-microT web server as the user interface to the DIANA-microT 3.0 miRNA target prediction algorithm. The web server provides extensive information for predicted miRNA:target gene interactions with a user-friendly interface, providing extensive connectivity to online biological resources. Target gene and miRNA functions may be elucidated through automated bibliographic searches and functional information is accessible through Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. The web server offers links to nomenclature, sequence and protein databases, and users are facilitated by being able to search for targeted genes using different nomenclatures or functional features, such as the genes possible involvement in biological pathways. The target prediction algorithm supports parameters calculated individually for each miRNA:target gene interaction and provides a signal-to-noise ratio and a precision score that helps in the evaluation of the significance of the predicted results. Using a set of miRNA targets recently identified through the pSILAC method, the performance of several computational target prediction programs was assessed. DIANA-microT 3.0 achieved there with 66% the highest ratio of correctly predicted targets over all predicted targets. The DIANA-microT web server is freely available at www.microrna.gr/microT

Representative transcript sets for evaluating a translational initiation sites predictor

<p>Abstract</p> <p>Background</p> <p>Translational initiation site (TIS) prediction is a very important and actively studied topic in bioinformatics. In order to complete a comparative analysis, it is desirable to have several benchmark data sets which can be used to test the effectiveness of different algorithms. An ideal benchmark data set should be reliable, representative and readily available. Preferably, proteins encoded by members of the data set should also be representative of the protein population actually expressed in cellular specimens.</p> <p>Results</p> <p>In this paper, we report a general algorithm for constructing a reliable sequence collection that only includes mRNA sequences whose corresponding protein products present an average profile of the general protein population of a given organism, with respect to three major structural parameters. Four representative transcript collections, each derived from a model organism, have been obtained following the algorithm we propose. Evaluation of these data sets shows that they are reasonable representations of the spectrum of proteins obtained from cellular proteomic studies. Six state-of-the-art predictors have been used to test the usefulness of the construction algorithm that we proposed. Comparative study which reports the predictors' performance on our data set as well as three other existing benchmark collections has demonstrated the actual merits of our data sets as benchmark testing collections.</p> <p>Conclusion</p> <p>The proposed data set construction algorithm has demonstrated its property of being a general and widely applicable scheme. Our comparison with published proteomic studies has shown that the expression of our data set of transcripts generates a polypeptide population that is representative of that obtained from evaluation of biological specimens. Our data set thus represents "real world" transcripts that will allow more accurate evaluation of algorithms dedicated to identification of TISs, as well as other translational regulatory motifs within mRNA sequences. The algorithm proposed by us aims at compiling a redundancy-free data set by removing redundant copies of homologous proteins. The existence of such data sets may be useful for conducting statistical analyses of protein sequence-structure relations. At the current stage, our approach's focus is to obtain an "average" protein data set for any particular organism without posing much selection bias. However, with the three major protein structural parameters deeply integrated into the scheme, it would be a trivial task to extend the current method for obtaining a more selective protein data set, which may facilitate the study of some particular protein structure.</p

HelexKids:a word frequency database for Greek and Cypriot primary school children

In this article, we introduce HelexKids, an online written-word database for Greek-speaking children in primary education (Grades 1 to 6). The database is organized on a grade-by-grade basis, and on a cumulative basis by combining Grade 1 with Grades 2 to 6. It provides values for Zipf, frequency per million, dispersion, estimated word frequency per million, standard word frequency, contextual diversity, orthographic Levenshtein distance, and lemma frequency. These values are derived from 116 textbooks used in primary education in Greece and Cyprus, producing a total of 68,692 different word types. HelexKids was developed to assist researchers in studying language development, educators in selecting age-appropriate items for teaching, as well as writers and authors of educational books for Greek/Cypriot children. The database is open access and can be searched online at www.helexkids.org

Differential impact of LPG-and PG-deficient Leishmania major mutants on the immune response of human dendritic cells

<div><p>Background</p><p><i>Leishmania major</i> infection induces robust interleukin-12 (IL12) production in human dendritic cells (hDC), ultimately resulting in Th1-mediated immunity and clinical resolution. The surface of <i>Leishmania</i> parasites is covered in a dense glycocalyx consisting of primarily lipophosphoglycan (LPG) and other phosphoglycan-containing molecules (PGs), making these glycoconjugates the likely pathogen-associated molecular patterns (PAMPS) responsible for IL12 induction.</p><p>Methodology/Principal Findings</p><p>Here we explored the role of parasite glycoconjugates on the hDC IL12 response by generating <i>L</i>. <i>major</i> Friedlin V1 mutants defective in LPG alone, (FV1 <i>lpg1-</i>), or generally deficient for all PGs, (FV1 <i>lpg2-</i>). Infection with metacyclic, infective stage, <i>L</i>. <i>major</i> or purified LPG induced high levels of <i>IL12B</i> subunit gene transcripts in hDCs, which was abrogated with FV1 <i>lpg1-</i> infections. In contrast, hDC infections with FV1 <i>lpg2-</i> displayed increased <i>IL12B</i> expression, suggesting other PG-related/<i>LPG2</i> dependent molecules may act to dampen the immune response. Global transcriptional profiling comparing WT, FV1 <i>lpg1-</i>, FV1 <i>lpg2-</i> infections revealed that FV1 <i>lpg1-</i> mutants entered hDCs in a silent fashion as indicated by repression of gene expression. Transcription factor binding site analysis suggests that LPG recognition by hDCs induces IL-12 in a signaling cascade resulting in Nuclear Factor κ B (NFκB) and Interferon Regulatory Factor (IRF) mediated transcription.</p><p>Conclusions/Significance</p><p>These data suggest that <i>L</i>. <i>major</i> LPG is a major PAMP recognized by hDC to induce IL12-mediated protective immunity and that there is a complex interplay between PG-baring <i>Leishmania</i> surface glycoconjugates that result in modulation of host cellular IL12.</p></div

Differentiating Protein-Coding and Noncoding RNA: Challenges and Ambiguities

The assumption that RNA can be readily classified into either protein-coding or non-protein–coding categories has pervaded biology for close to 50 years. Until recently, discrimination between these two categories was relatively straightforward: most transcripts were clearly identifiable as protein-coding messenger RNAs (mRNAs), and readily distinguished from the small number of well-characterized non-protein–coding RNAs (ncRNAs), such as transfer, ribosomal, and spliceosomal RNAs. Recent genome-wide studies have revealed the existence of thousands of noncoding transcripts, whose function and significance are unclear. The discovery of this hidden transcriptome and the implicit challenge it presents to our understanding of the expression and regulation of genetic information has made the need to distinguish between mRNAs and ncRNAs both more pressing and more complicated. In this Review, we consider the diverse strategies employed to discriminate between protein-coding and noncoding transcripts and the fundamental difficulties that are inherent in what may superficially appear to be a simple problem. Misannotations can also run in both directions: some ncRNAs may actually encode peptides, and some of those currently thought to do so may not. Moreover, recent studies have shown that some RNAs can function both as mRNAs and intrinsically as functional ncRNAs, which may be a relatively widespread phenomenon. We conclude that it is difficult to annotate an RNA unequivocally as protein-coding or noncoding, with overlapping protein-coding and noncoding transcripts further confounding this distinction. In addition, the finding that some transcripts can function both intrinsically at the RNA level and to encode proteins suggests a false dichotomy between mRNAs and ncRNAs. Therefore, the functionality of any transcript at the RNA level should not be discounted