174 research outputs found

    International Business Cycle Spillovers

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    We apply Diebold-Yilmaz spillover index methodology to monthly industrial production indices to study business cycle interdependence among G-6 industrialized countries since 1958. The business cycle spillover index fluctuates substantially over time, increasing especially after the 1973-75, 1981-82 and 2001 U.S. recessions. The band within which the spillover index fluctuates has widened since the start of the globalization process in the early 1990s. Our most important result, however, concerns the current state of the world economy: In a matter of four months from September to December 2008, the business cycle spillover index recorded the sharpest increase ever, reaching a record level as of December 2008 (See http://data.economicresearchforum.org/erf/bcspill.aspx?lang=en for updates of the spillover plot). Focusing on directional spillover measures, we show that in the current episode the shocks are mostly originating from the United States and spreading to other industrialized countries. We also show that, throughout the period of analysis, the U.S. (1980s and 2000s) and Japan (1970s and 2000s) have been the major transmitters of shocks among the industrialized countries

    Microbial ligand costimulation drives neutrophilic steroid-refractory asthma

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    Funding: The authors thank the Wellcome Trust (102705) and the Universities of Aberdeen and Cape Town for funding. This research was also supported, in part, by National Institutes of Health GM53522 and GM083016 to DLW. KF and BNL are funded by the Fonds Wetenschappelijk Onderzoek, BNL is the recipient of an European Research Commission consolidator grant and participates in the European Union FP7 programs EUBIOPRED and MedALL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

    The Near-Earth Object Surveyor Mission

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    The Near-Earth Object (NEO) Surveyor mission is a NASA observatory designed to discover and characterize near-Earth asteroids and comets. The mission's primary objective is to find the majority of objects large enough to cause severe regional impact damage (>>140 m in effective spherical diameter) within its five-year baseline survey. Operating at the Sun-Earth L1 Lagrange point, the mission will survey to within 45 degrees of the Sun in an effort to find the objects in the most Earth-like orbits. The survey cadence is optimized to provide observational arcs long enough to reliably distinguish near-Earth objects from more distant small bodies that cannot pose an impact hazard. Over the course of its survey, NEO Surveyor will discover ∼\sim200,000 - 300,000 new NEOs down to sizes as small as ∼\sim10 m and thousands of comets, significantly improving our understanding of the probability of an Earth impact over the next century.Comment: accepted to PS

    MTar: a computational microRNA target prediction architecture for human transcriptome

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    <p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in important cell functions, there is a growing interest in identifying the relationship between miRNAs and their target mRNAs. So, there is now a imperative need to develop a computational method by which we can identify the target mRNAs of existing miRNAs. Here, we proposed an efficient machine learning model to unravel the relationship between miRNAs and their target mRNAs.</p> <p>Results</p> <p>We present a novel computational architecture MTar for miRNA target prediction which reports 94.5% sensitivity and 90.5% specificity. We identified 16 positional, thermodynamic and structural parameters from the wet lab proven miRNA:mRNA pairs and MTar makes use of these parameters for miRNA target identification. It incorporates an Artificial Neural Network (ANN) verifier which is trained by wet lab proven microRNA targets. A number of hitherto unknown targets of many miRNA families were located using MTar. The method identifies all three potential miRNA targets (5' seed-only, 5' dominant, and 3' canonical) whereas the existing solutions focus on 5' complementarities alone.</p> <p>Conclusion</p> <p>MTar, an ANN based architecture for identifying functional regulatory miRNA-mRNA interaction using predicted miRNA targets. The area of target prediction has received a new momentum with the function of a thermodynamic model incorporating target accessibility. This model incorporates sixteen structural, thermodynamic and positional features of residues in miRNA: mRNA pairs were employed to select target candidates. So our novel machine learning architecture, MTar is found to be more comprehensive than the existing methods in predicting miRNA targets, especially human transcritome.</p

    The MicroRNA-200 Family Is Upregulated in Endometrial Carcinoma

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    BACKGROUND: MicroRNAs (miRNAs, miRs) are small non-coding RNAs that negatively regulate gene expression at the post-transcriptional level. MicroRNAs are dysregulated in cancer and may play essential roles in tumorigenesis. Additionally, miRNAs have been shown to have prognostic and diagnostic value in certain types of cancer. The objective of this study was to identify dysregulated miRNAs in endometrioid endometrial adenocarcinoma (EEC) and the precursor lesion, complex atypical hyperplasia (CAH). METHODOLOGY: We compared the expression profiles of 723 human miRNAs from 14 cases of EEC, 10 cases of CAH, and 10 normal proliferative endometria controls using Agilent Human miRNA arrays following RNA extraction from formalin-fixed paraffin-embedded (FFPE) tissues. The expression of 4 dysregulated miRNAs was validated using real time reverse transcription-PCR. RESULTS: Forty-three miRNAs were dysregulated in EEC and CAH compared to normal controls (p<0.05). The entire miR-200 family (miR-200a/b/c, miR-141, and miR-429) was up-regulated in cases of EEC. CONCLUSIONS: This information contributes to the candidate miRNA expression profile that has been generated for EEC and shows that certain miRNAs are dysregulated in the precursor lesion, CAH. These miRNAs in particular may play important roles in tumorigenesis. Examination of miRNAs that are consistently dysregulated in various studies of EEC, like the miR-200 family, will aid in the understanding of the role that miRNAs play in tumorigenesis in this tumour type

    MicroRNAs in cell proliferation, cell death, and tumorigenesis

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    MicroRNAs (miRNAs) are a recently discovered class of ∼18–24 nucleotide RNA molecules that negatively regulate target mRNAs. All studied multicellular eukaryotes utilise miRNAs to regulate basic cellular functions including proliferation, differentiation, and death. It is now apparent that abnormal miRNA expression is a common feature of human malignancies. In this review, we will discuss how miRNAs influence tumorigenesis by acting as oncogenes and tumour suppressors
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