The role of ground motion duration and pulse effects in the collapse of ductile systems

The seismic collapse capacity of ductile single‐degree‐of‐freedom systems vulnerable to P‐Δ effects is investigated by examining the respective influence of ground motion duration and acceleration pulses. The main objective is to provide simple relationships for predicting the duration‐dependent collapse capacity of modern ductile systems. A novel procedure is proposed for modifying spectrally equivalent records, such that they are also equivalent in terms of pulses. The effect of duration is firstly assessed, without accounting for pulses, by assembling 101 pairs of long and short records with equivalent spectral response. The systems considered exhibit a trilinear backbone curve with an elastic, hardening and negative stiffness segment. The parameters investigated include the period, negative stiffness slope, ductility and strain hardening, for both bilinear and pinching hysteretic models. Incremental dynamic analysis is employed to determine collapse capacities and derive design collapse capacity spectra. It is shown that up to 60% reduction in collapse capacity can occur due to duration effects for flexible bilinear systems subjected to low levels of P‐Δ. A comparative evaluation of intensity measures that account for spectral shape, duration or pulses, is also presented. The influence of pulses, quantified through incremental velocity, is then explicitly considered to modify the long records, such that their pulse distribution matches that of their short spectrally equivalent counterparts. The results show the need to account for pulse effects in order to achieve unbiased estimation of the role of duration in flexible ductile systems, as it can influence the duration‐induced reduction in collapse capacity by more than 20%

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

Using Biotic Interaction Networks for Prediction in Biodiversity and Emerging Diseases

Networks offer a powerful tool for understanding and visualizing inter-species ecological and evolutionary interactions. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for this methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease - Leishmaniasis. This data mining methodology allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases

Regulation of the let-7a-3 Promoter by NF-κB

Changes in microRNA expression have been linked to a wide array of pathological states. However, little is known about the regulation of microRNA expression. The let-7 microRNA is a tumor suppressor that inhibits cellular proliferation and promotes differentiation, and is frequently lost in tumors. We investigated the transcriptional regulation of two let-7 family members, let-7a-3 and let-7b, which form a microRNA cluster and are located 864 bp apart on chromosome 22q13.31. Previous reports present conflicting data on the role of the NF-κB transcription factor in regulating let-7. We cloned three fragments upstream of the let-7a-3/let-7b miRNA genomic region into a plasmid containing a luciferase reporter gene. Ectopic expression of subunits of NF-κB (p50 or p65/RelA) significantly increased luciferase activity in HeLa, 293, 293T and 3T3 cells, indicating that the let-7a-3/let-7b promoter is highly responsive to NF-κB. Mutation of a putative NF-κB binding site at bp −833 reduced basal promoter activity and decreased promoter activity in the presence of p50 or p65 overexpression. Mutation of a second putative binding site, at bp −947 also decreased promoter activity basally and in response to p65 induction, indicating that both sites contribute to NF-κB responsiveness. While the levels of the endogenous primary let-7a and let-7b transcript were induced in response to NF-κB overexpression in 293T cells, the levels of fully processed, mature let-7a and let-7b miRNAs did not increase. Instead, levels of Lin-28B, a protein that blocks let-7 maturation, were induced by NF-κB. Increased Lin-28B levels could contribute to the lack of an increase in mature let-7a and let-7b. Our results suggest that the final biological outcome of NF-κB activation on let-7 expression may vary depending upon the cellular context. We discuss our results in the context of NF-κB activity in repressing self-renewal and promoting differentiation

existing buildings the new italian provisions for probabilistic seismic assessment

In Europe, the reference document for the seismic assessment of buildings is the Eurocode 8-Part3, whose first draft goes back to 1996 and, for what concerns its safety format, has strong similarities with FEMA 276. Extended use of this document, especially in Italy after the 2009 L'Aquila earthquake has shown its inadequacy to provide consistent and univocal results. This situation has motivated the National Research Council of Italy to produce a document of a level higher than the one in force, characterized by a fully probabilistic structure allowing to account for all types of uncertainties and providing measures of performance in terms of mean rates of exceedance for a selected number of Limit States (LS). The document, which covers both reinforced concrete and masonry buildings, offers three alternative approaches to risk assessment, all of them belonging to the present consolidated state of knowledge in the area. These approaches include, in decreasing order of accuracy: (a) Incremental dynamic analysis on the complete structural model, (b) Incremental dynamic analysis on equivalent SDOF oscillator(s), (c) Non-linear static analysis. In all three approaches relevant uncertainties are distinguished in two classes: those amenable of description as continuous random variables and those requiring the set-up of different structural models. The first ones are taken into account by sampling a number of realizations from their respective distributions and by associating each realization with one of the records used for evaluating the structural response, the latter by having recourse to a logic tree. Exceedance of each of the three considered Limit States: Light or Severe damage and Collapse, is signaled by a scalar indicator Y, expressing the global state of the structure as a function of that of its members, taking a value of one when the Limit State is reached. For the first two LS's, which relate to functionality and to economic considerations, the formulation of Y is such as to leave to the owner the choice of the acceptable level of damage, while for the Collapse LS the formulation is obviously unique. An application to a real school building completes the paper

R-gene variation across Arabidopsis lyrata subspecies: effects of population structure, selection and mating system.

BACKGROUND: Examining allelic variation of R-genes in closely related perennial species of Arabidopsis thaliana is critical to understanding how population structure and ecology interact with selection to shape the evolution of innate immunity in plants. We finely sampled natural populations of Arabidopsis lyrata from the Great Lakes region of North America (A. l. lyrata) and broadly sampled six European countries (A. l. petraea) to investigate allelic variation of two R-genes (RPM1 and WRR4) and neutral genetic markers (Restriction Associated DNA sequences and microsatellites) in relation to mating system, phylogeographic structure and subspecies divergence. RESULTS: Fine-scale sampling of populations revealed strong effects of mating system and population structure on patterns of polymorphism for both neutral loci and R-genes, with no strong evidence for selection. Broad geographic sampling revealed evidence of balancing selection maintaining polymorphism in R-genes, with elevated heterozygosity and diversity compared to neutral expectations and sharing of alleles among diverged subspecies. Codon-based tests detected both positive and purifying selection for both R-genes, as commonly found for animal immune genes. CONCLUSIONS: Our results highlight that combining fine and broad-scale sampling strategies can reveal the multiple factors influencing polymorphism and divergence at potentially adaptive genes such as R-genes

Identification and analysis of miRNAs in human breast cancer and teratoma samples using deep sequencing

<p>Abstract</p> <p>Background</p> <p>MiRNAs play important roles in cellular control and in various disease states such as cancers, where they may serve as markers or possibly even therapeutics. Identifying the whole repertoire of miRNAs and understanding their expression patterns is therefore an important goal.</p> <p>Methods</p> <p>Here we describe the analysis of 454 pyrosequencing of small RNA from four different tissues: Breast cancer, normal adjacent breast, and two teratoma cell lines. We developed a pipeline for identifying new miRNAs, emphasizing extracting and retaining as much data as possible from even noisy sequencing data. We investigated differential expression of miRNAs in the breast cancer and normal adjacent breast samples, and systematically examined the mature sequence end variability of miRNA compared to non-miRNA loci.</p> <p>Results</p> <p>We identified five novel miRNAs, as well as two putative alternative precursors for known miRNAs. Several miRNAs were differentially expressed between the breast cancer and normal breast samples. The end variability was shown to be significantly different between miRNA and non-miRNA loci.</p> <p>Conclusion</p> <p>Pyrosequencing of small RNAs, together with a computational pipeline, can be used to identify miRNAs in tumor and other tissues. Measures of miRNA end variability may in the future be incorporated into the discovery pipeline as a discriminatory feature. Breast cancer samples show a distinct miRNA expression profile compared to normal adjacent breast.</p

The Silkworm (Bombyx mori) microRNAs and Their Expressions in Multiple Developmental Stages

BACKGROUND: MicroRNAs (miRNAs) play crucial roles in various physiological processes through post-transcriptional regulation of gene expressions and are involved in development, metabolism, and many other important molecular mechanisms and cellular processes. The Bombyx mori genome sequence provides opportunities for a thorough survey for miRNAs as well as comparative analyses with other sequenced insect species. METHODOLOGY/PRINCIPAL FINDINGS: We identified 114 non-redundant conserved miRNAs and 148 novel putative miRNAs from the B. mori genome with an elaborate computational protocol. We also sequenced 6,720 clones from 14 developmental stage-specific small RNA libraries in which we identified 35 unique miRNAs containing 21 conserved miRNAs (including 17 predicted miRNAs) and 14 novel miRNAs (including 11 predicted novel miRNAs). Among the 114 conserved miRNAs, we found six pairs of clusters evolutionarily conserved cross insect lineages. Our observations on length heterogeneity at 5' and/or 3' ends of nine miRNAs between cloned and predicted sequences, and three mature forms deriving from the same arm of putative pre-miRNAs suggest a mechanism by which miRNAs gain new functions. Analyzing development-related miRNAs expression at 14 developmental stages based on clone-sampling and stem-loop RT PCR, we discovered an unusual abundance of 33 sequences representing 12 different miRNAs and sharply fluctuated expression of miRNAs at larva-molting stage. The potential functions of several stage-biased miRNAs were also analyzed in combination with predicted target genes and silkworm's phenotypic traits; our results indicated that miRNAs may play key regulatory roles in specific developmental stages in the silkworm, such as ecdysis. CONCLUSIONS/SIGNIFICANCE: Taking a combined approach, we identified 118 conserved miRNAs and 151 novel miRNA candidates from the B. mori genome sequence. Our expression analyses by sampling miRNAs and real-time PCR over multiple developmental stages allowed us to pinpoint molting stages as hotspots of miRNA expression both in sorts and quantities. Based on the analysis of target genes, we hypothesized that miRNAs regulate development through a particular emphasis on complex stages rather than general regulatory mechanisms

Stoichiometric representation of geneproteinreaction associations leverages constraint-based analysis from reaction to gene-level phenotype prediction

Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models.DM was supported by the Portuguese Foundationfor Science and Technologythrough a post-doc fellowship (ref: SFRH/BPD/111519/ 2015). This study was supported by the PortugueseFoundationfor Science and Technology (FCT) under the scope of the strategic fundingof UID/BIO/04469/2013 unitand COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) fundedby EuropeanRegional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. This project has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under grant agreementNo 686070. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Selective Release of MicroRNA Species from Normal and Malignant Mammary Epithelial Cells

MicroRNAs (miRNAs) in body fluids are candidate diagnostics for a variety of conditions and diseases, including breast cancer. One premise for using extracellular miRNAs to diagnose disease is the notion that the abundance of the miRNAs in body fluids reflects their abundance in the abnormal cells causing the disease. As a result, the search for such diagnostics in body fluids has focused on miRNAs that are abundant in the cells of origin. Here we report that released miRNAs do not necessarily reflect the abundance of miRNA in the cell of origin. We find that release of miRNAs from cells into blood, milk and ductal fluids is selective and that the selection of released miRNAs may correlate with malignancy. In particular, the bulk of miR-451 and miR-1246 produced by malignant mammary epithelial cells was released, but the majority of these miRNAs produced by non-malignant mammary epithelial cells was retained. Our findings suggest the existence of a cellular selection mechanism for miRNA release and indicate that the extracellular and cellular miRNA profiles differ. This selective release of miRNAs is an important consideration for the identification of circulating miRNAs as biomarkers of disease