234 research outputs found

    BioDiVinE: A Framework for Parallel Analysis of Biological Models

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    In this paper a novel tool BioDiVinEfor parallel analysis of biological models is presented. The tool allows analysis of biological models specified in terms of a set of chemical reactions. Chemical reactions are transformed into a system of multi-affine differential equations. BioDiVinE employs techniques for finite discrete abstraction of the continuous state space. At that level, parallel analysis algorithms based on model checking are provided. In the paper, the key tool features are described and their application is demonstrated by means of a case study

    Reachability in Biochemical Dynamical Systems by Quantitative Discrete Approximation (extended abstract)

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    In this paper, a novel computational technique for finite discrete approximation of continuous dynamical systems suitable for a significant class of biochemical dynamical systems is introduced. The method is parameterized in order to affect the imposed level of approximation provided that with increasing parameter value the approximation converges to the original continuous system. By employing this approximation technique, we present algorithms solving the reachability problem for biochemical dynamical systems. The presented method and algorithms are evaluated on several exemplary biological models and on a real case study.Comment: In Proceedings CompMod 2011, arXiv:1109.104

    Consequence of the tumor-associated conversion to cyclin D1b.

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    Clinical evidence suggests that cyclin D1b, a variant of cyclin D1, is associated with tumor progression and poor outcome. However, the underlying molecular basis was unknown. Here, novel models were created to generate a genetic switch from cyclin D1 to cyclin D1b. Extensive analyses uncovered overlapping but non-redundant functions of cyclin D1b compared to cyclin D1 on developmental phenotypes, and illustrated the importance of the transcriptional regulatory functions of cyclin D1b in vivo. Data obtained identify cyclin D1b as an oncogene, wherein cyclin D1b expression under the endogenous promoter induced cellular transformation and further cooperated with known oncogenes to promote tumor growth in vivo. Further molecular interrogation uncovered unexpected links between cyclin D1b and the DNA damage/PARP1 regulatory networks, which could be exploited to suppress cyclin D1b-driven tumors. Collectively, these data are the first to define the consequence of cyclin D1b expression on normal cellular function, present evidence for cyclin D1b as an oncogene, and provide pre-clinical evidence of effective methods to thwart growth of cells dependent upon this oncogenic variant

    Radio emission from Supernova Remnants

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    The explosion of a supernova releases almost instantaneously about 10^51 ergs of mechanic energy, changing irreversibly the physical and chemical properties of large regions in the galaxies. The stellar ejecta, the nebula resulting from the powerful shock waves, and sometimes a compact stellar remnant, constitute a supernova remnant (SNR). They can radiate their energy across the whole electromagnetic spectrum, but the great majority are radio sources. Almost 70 years after the first detection of radio emission coming from a SNR, great progress has been achieved in the comprehension of their physical characteristics and evolution. We review the present knowledge of different aspects of radio remnants, focusing on sources of the Milky Way and the Magellanic Clouds, where the SNRs can be spatially resolved. We present a brief overview of theoretical background, analyze morphology and polarization properties, and review and critical discuss different methods applied to determine the radio spectrum and distances. The consequences of the interaction between the SNR shocks and the surrounding medium are examined, including the question of whether SNRs can trigger the formation of new stars. Cases of multispectral comparison are presented. A section is devoted to reviewing recent results of radio SNRs in the Magellanic Clouds, with particular emphasis on the radio properties of SN 1987A, an ideal laboratory to investigate dynamical evolution of an SNR in near real time. The review concludes with a summary of issues on radio SNRs that deserve further study, and analyzing the prospects for future research with the latest generation radio telescopes.Comment: Revised version. 48 pages, 15 figure

    Evaluation of secretion prediction highlights differing approaches needed for oomycete and fungal effectors

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    © 2015 Sperschneider, Williams, Hane, Singh and Taylor. The steadily increasing number of sequenced fungal and oomycete genomes has enabled detailed studies of how these eukaryotic microbes infect plants and cause devastating losses in food crops. During infection, fungal and oomycete pathogens secrete effector molecules which manipulate host plant cell processes to the pathogen's advantage. Proteinaceous effectors are synthesized intracellularly and must be externalized to interact with host cells. Computational prediction of secreted proteins from genomic sequences is an important technique to narrow down the candidate effector repertoire for subsequent experimental validation. In this study, we benchmark secretion prediction tools on experimentally validated fungal and oomycete effectors. We observe that for a set of fungal SwissProt protein sequences, SignalP 4 and the neural network predictors of SignalP 3 (D-score) and SignalP 2 perform best. For effector prediction in particular, the use of a sensitive method can be desirable to obtain the most complete candidate effector set. We show that the neural network predictors of SignalP 2 and 3, as well as TargetP were the most sensitive tools for fungal effector secretion prediction, whereas the hidden Markov model predictors of SignalP 2 and 3 were the most sensitive tools for oomycete effectors. Thus, previous versions of SignalP retain value for oomycete effector prediction, as the current version, SignalP 4, was unable to reliably predict the signal peptide of the oomycete Crinkler effectors in the test set. Our assessment of subcellular localization predictors shows that cytoplasmic effectors are often predicted as not extracellular. This limits the reliability of secretion predictions that depend on these tools. We present our assessment with a view to informing future pathogenomics studies and suggest revised pipelines for secretion prediction to obtain optimal effector predictions in fungi and oomycetes

    TOPAZ1, a Novel Germ Cell-Specific Expressed Gene Conserved during Evolution across Vertebrates

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    BACKGROUND: We had previously reported that the Suppression Subtractive Hybridization (SSH) approach was relevant for the isolation of new mammalian genes involved in oogenesis and early follicle development. Some of these transcripts might be potential new oocyte and granulosa cell markers. We have now characterized one of them, named TOPAZ1 for the Testis and Ovary-specific PAZ domain gene. PRINCIPAL FINDINGS: Sheep and mouse TOPAZ1 mRNA have 4,803 bp and 4,962 bp open reading frames (20 exons), respectively, and encode putative TOPAZ1 proteins containing 1,600 and 1653 amino acids. They possess PAZ and CCCH domains. In sheep, TOPAZ1 mRNA is preferentially expressed in females during fetal life with a peak during prophase I of meiosis, and in males during adulthood. In the mouse, Topaz1 is a germ cell-specific gene. TOPAZ1 protein is highly conserved in vertebrates and specifically expressed in mouse and sheep gonads. It is localized in the cytoplasm of germ cells from the sheep fetal ovary and mouse adult testis. CONCLUSIONS: We have identified a novel PAZ-domain protein that is abundantly expressed in the gonads during germ cell meiosis. The expression pattern of TOPAZ1, and its high degree of conservation, suggests that it may play an important role in germ cell development. Further characterization of TOPAZ1 may elucidate the mechanisms involved in gametogenesis, and particularly in the RNA silencing process in the germ lin

    Pre-Micro RNA Signatures Delineate Stages of Endothelial Cell Transformation in Kaposi Sarcoma

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    MicroRNAs (miRNA) have emerged as key regulators of cell lineage differentiation and cancer. We used precursor miRNA profiling by a novel real-time QPCR method (i) to define progressive stages of endothelial cell transformation cumulating in Kaposi sarcoma (KS) and (ii) to identify specific miRNAs that serve as biomarkers for tumor progression. We were able to compare primary patient biopsies to well-established culture and mouse tumor models. Loss of mir-221 and gain of mir-15 expression demarked the transition from merely immortalized to fully tumorigenic endothelial cells. Mir-140 and Kaposi sarcoma–associated herpesvirus viral miRNAs increased linearly with the degree of transformation. Mir-24 emerged as a biomarker specific for KS

    Bypass Mechanisms of the Androgen Receptor Pathway in Therapy-Resistant Prostate Cancer Cell Models

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    Background: Prostate cancer is initially dependent on androgens for survival and growth, making hormonal therapy the cornerstone treatment for late-stage tumors. However, despite initial remission, the cancer will inevitably recur. The present study was designed to investigate how androgen-dependent prostate cancer cells eventually survive and resume growth under androgen-deprived and antiandrogen supplemented conditions. As model system, we used the androgen-responsive PC346C cell line and its therapy-resistant sublines: PC346DCC, PC346Flu1 and PC346Flu2. Methodology/Principal Findings: Microarray technology was used to analyze differences in gene expression between the androgen-responsive and therapy-resistant PC346 cell lines. Microarray analysis revealed 487 transcripts differentiallyexpressed between the androgen-responsive and the therapy-resistant cell lines. Most of these genes were common to all three therapy-resistant sublines and only a minority (,5%) was androgen-regulated. Pathway analysis revealed enrichment in functions involving cellular movement, cell growth and cell death, as well as association with cancer and reproductive system disease. PC346DCC expressed residual levels of androgen receptor (AR) and showed significant down-regulation of androgen-regulated genes (p-value = 10 27). Up-regulation of VAV3 and TWIST1 oncogenes and repression of the DKK3 tumor-suppressor was observed in PC346DCC, suggesting a potential AR bypass mechanism. Subsequent validation of these three genes in patient samples confirmed that expression was deregulated during prostate cancer progression
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