2,397 research outputs found

    MicroRNA-203 predicts human survival after resection of colorectal liver metastasis.

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    BackgroundResection of colorectal liver metastasis (CRLM) can be curative. Predicting which patients may benefit from resection, however, remains challenging. Some microRNAs (miRNAs) become deregulated in cancers and contribute to cancer progression. We hypothesized that miRNA expression can serve as a prognostic marker of survival after CRLM resection.ResultsMiR-203 was significantly overexpressed in tumors of short-term survivors compared to long-term survivors. R1/R2 margin status and high clinical risk score (CRS) were also significantly associated with short-term survival (both p = 0.001). After adjusting for these variables, higher miR-203 expression remained an independent predictor of shorter survival (p = 0.010). In the serum cohort, high CRS and KRAS mutation were significantly associated with short-term survival (p = 0.005 and p = 0.026, respectively). After adjusting for CRS and KRAS status, short-term survivors were found to have significantly higher miR-203 levels (p = 0.016 and p = 0.033, respectively).Materials and methodsWe employed next-generation sequencing of small-RNAs to profile miRNAs in solid tumors obtained from 38 patients who underwent hepatectomy for CRLM. To validate, quantitative reverse-transcription polymerase chain reaction (qRT-PCR) was performed on 91 tumor samples and 46 preoperative serum samples.ConclusionsAfter CRLM resection, short-term survivors exhibited significantly higher miR-203 levels relative to long-term survivors. MiR-203 may serve as a prognostic biomarker and its prognostic capacity warrants further investigation

    Emulating opportunistic networks with KauNet Triggers

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    In opportunistic networks the availability of an end-to-end path is no longer required. Instead opportunistic networks may take advantage of temporary connectivity opportunities. Opportunistic networks present a demanding environment for network emulation as the traditional emulation setup, where application/transport endpoints only send and receive packets from the network following a black box approach, is no longer applicable. Opportunistic networking protocols and applications additionally need to react to the dynamics of the underlying network beyond what is conveyed through the exchange of packets. In order to support IP-level emulation evaluations of applications and protocols that react to lower layer events, we have proposed the use of emulation triggers. Emulation triggers can emulate arbitrary cross-layer feedback and can be synchronized with other emulation effects. After introducing the design and implementation of triggers in the KauNet emulator, we describe the integration of triggers with the DTN2 reference implementation and illustrate how the functionality can be used to emulate a classical DTN data-mule scenario

    Protein disulfide-isomerase interacts with a substrate protein at all stages along its folding pathway

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    In contrast to molecular chaperones that couple protein folding to ATP hydrolysis, protein disulfide-isomerase (PDI) catalyzes protein folding coupled to formation of disulfide bonds (oxidative folding). However, we do not know how PDI distinguishes folded, partly-folded and unfolded protein substrates. As a model intermediate in an oxidative folding pathway, we prepared a two-disulfide mutant of basic pancreatic trypsin inhibitor (BPTI) and showed by NMR that it is partly-folded and highly dynamic. NMR studies show that it binds to PDI at the same site that binds peptide ligands, with rapid binding and dissociation kinetics; surface plasmon resonance shows its interaction with PDI has a Kd of ca. 10−5 M. For comparison, we characterized the interactions of PDI with native BPTI and fully-unfolded BPTI. Interestingly, PDI does bind native BPTI, but binding is quantitatively weaker than with partly-folded and unfolded BPTI. Hence PDI recognizes and binds substrates via permanently or transiently unfolded regions. This is the first study of PDI's interaction with a partly-folded protein, and the first to analyze this folding catalyst's changing interactions with substrates along an oxidative folding pathway. We have identified key features that make PDI an effective catalyst of oxidative protein folding – differential affinity, rapid ligand exchange and conformational flexibility

    Feasibility of intensity-modulated and image-guided radiotherapy for locally advanced esophageal cancer

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    BACKGROUND:In this study the feasibility of intensity-modulated radiotherapy (IMRT) and tomotherapy-based image-guided radiotherapy (IGRT) for locally advanced esophageal cancer was assessed.METHODS:A retrospective study of ten patients with locally advanced esophageal cancer who underwent concurrent chemotherapy with IMRT (1) and IGRT (9) was conducted. The gross tumor volume was treated to a median dose of 70Gy (62.4-75Gy).RESULTS:At a median follow-up of 14months (1-39 months), three patients developed local failures, six patients developed distant metastases, and complications occurred in two patients (1 tracheoesophageal fistula, 1 esophageal stricture requiring repeated dilatations). No patients developed grade 3-4 pneumonitis or cardiac complications.CONCLUSIONS:IMRT and IGRT may be effective for the treatment of locally advanced esophageal cancer with acceptable complications.This item is part of the UA Faculty Publications collection. For more information this item or other items in the UA Campus Repository, contact the University of Arizona Libraries at [email protected]

    PPCAS: Implementation of a Probabilistic Pairwise Model for Consistency-Based Multiple Alignment in Apache Spark

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    Large-scale data processing techniques, currently known as Big-Data, are used to manage the huge amount of data that are generated by sequencers. Although these techniques have significant advantages, few biological applications have adopted them. In the Bioinformatic scientific area, Multiple Sequence Alignment (MSA) tools are widely applied for evolution and phylogenetic analysis, homology and domain structure prediction. Highly-rated MSA tools, such as MAFFT, ProbCons and T-Coffee (TC), use the probabilistic consistency as a prior step to the progressive alignment stage in order to improve the final accuracy. In this paper, a novel approach named PPCAS (Probabilistic Pairwise model for Consistency-based multiple alignment in Apache Spark) is presented. PPCAS is based on the MapReduce processing paradigm in order to enable large datasets to be processed with the aim of improving the performance and scalability of the original algorithm.This work was supported by the MEyC-Spain [contract TIN2014-53234-C2-2-R]

    Focal Distribution of Hepatitis C Virus RNA in Infected Livers

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    Background: Hepatitis C virus (HCV) is a plus-strand RNA virus that replicates by amplification of genomic RNA from minus strands leading to accumulation of almost one thousand copies per cell under in vitro cell culture conditions. In contrast, HCV RNA copy numbers in livers of infected patients appear to be much lower, estimated at a few copies per cell. Methodology/Principal Findings: To gain insights into mechanisms that control HCV replication in vivo, we analyzed HCV RNA levels as well as expression of interferon beta (IFNb) and several interferon stimulated genes (ISGs) from whole liver sections and micro-dissected subpopulations of hepatocytes in biopsy samples from 21 HCV-infected patients. The results showed that intrahepatic HCV RNA levels range form less than one copy per hepatocyte to a maximum of about eight. A correlation existed between viral RNA levels and IFNb expression, but not between viral RNA and ISG levels. Also, IFNb expression did not correlate with ISGs levels. Replication of HCV RNA occurred in focal areas in the liver in the presence of a general induction of ISGs. Conclusion/Significance: The low average levels of HCV RNA in biopsy samples can be explained by focal distribution of infected hepatocytes. HCV replication directly induces IFNb, which then activates ISGs. The apparent lack of a correlation between levels of IFNb and ISG expression indicates that control of the innate immune response during HCV infection

    The Wor1-like Protein Fgp1 Regulates Pathogenicity, Toxin Synthesis and Reproduction in the Phytopathogenic Fungus Fusarium graminearum

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    WOR1 is a gene for a conserved fungal regulatory protein controlling the dimorphic switch and pathogenicity determents in Candida albicans and its ortholog in the plant pathogen Fusarium oxysporum, called SGE1, is required for pathogenicity and expression of key plant effector proteins. F. graminearum, an important pathogen of cereals, is not known to employ switching and no effector proteins from F. graminearum have been found to date that are required for infection. In this study, the potential role of the WOR1-like gene in pathogenesis was tested in this toxigenic fungus. Deletion of the WOR1 ortholog (called FGP1) in F. graminearum results in greatly reduced pathogenicity and loss of trichothecene toxin accumulation in infected wheat plants and in vitro. The loss of toxin accumulation alone may be sufficient to explain the loss of pathogenicity to wheat. Under toxin-inducing conditions, expression of genes for trichothecene biosynthesis and many other genes are not detected or detected at lower levels in Δfgp1 strains. FGP1 is also involved in the developmental processes of conidium formation and sexual reproduction and modulates a morphological change that accompanies mycotoxin production in vitro. The Wor1-like proteins in Fusarium species have highly conserved N-terminal regions and remarkably divergent C-termini. Interchanging the N- and C- terminal portions of proteins from F. oxysporum and F. graminearum resulted in partial to complete loss of function. Wor1-like proteins are conserved but have evolved to regulate pathogenicity in a range of fungi, likely by adaptations to the C-terminal portion of the protein

    A quantitative approach to study indirect effects among disease proteins in the human protein interaction network

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    <p>Abstract</p> <p>Background</p> <p>Systems biology makes it possible to study larger and more intricate systems than before, so it is now possible to look at the molecular basis of several diseases in parallel. Analyzing the interaction network of proteins in the cell can be the key to understand how complex processes lead to diseases. Novel tools in network analysis provide the possibility to quantify the key interacting proteins in large networks as well as proteins that connect them. Here we suggest a new method to study the relationships between topology and functionality of the protein-protein interaction network, by identifying key mediator proteins possibly maintaining indirect relationships among proteins causing various diseases.</p> <p>Results</p> <p>Based on the i2d and OMIM databases, we have constructed (i) a network of proteins causing five selected diseases (DP, disease proteins) plus their interacting partners (IP, non-disease proteins), the DPIP network and (ii) a protein network showing only these IPs and their interactions, the IP network. The five investigated diseases were (1) various cancers, (2) heart diseases, (3) obesity, (4) diabetes and (5) autism. We have quantified the number and strength of IP-mediated indirect effects between the five groups of disease proteins and hypothetically identified the most important mediator proteins linking heart disease to obesity or diabetes in the IP network. The results present the relationship between mediator role and centrality, as well as between mediator role and functional properties of these proteins.</p> <p>Conclusions</p> <p>We show that a protein which plays an important indirect mediator role between two diseases is not necessarily a hub in the PPI network. This may suggest that, even if hub proteins and disease proteins are trivially of great interest, mediators may also deserve more attention, especially if disease-disease associations are to be understood. Identifying the hubs may not be sufficient to understand particular pathways. We have found that the mediators between heart diseases and obesity, as well as heart diseases and diabetes are of relatively high functional importance in the cell. The mediator proteins suggested here should be experimentally tested as products of hypothetical disease-related proteins.</p
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