124 research outputs found

    The RNA-binding protein HuR contributes to neuroinflammation by promoting C-C chemokine receptor 6 (CCR6) expression on Th17 cells.

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    In both multiple sclerosis and experimental autoimmune encephalomyelitis (EAE), the C-C chemokine receptor 6 (CCR6) is critical for pathogenic T helper 17 (Th17) cell migration to the central nervous system (CNS). Whereas many cytokines and their receptors are potently regulated via post-transcriptional mechanisms in response to various stimuli, how CCR6 expression is post-transcriptionally regulated in Th17 cells is unknown. Here, using RNA-binding protein HuR conditional knock-out (KO) and wild-type (WT) mice, we present evidence that HuR post-transcriptionally regulates CCR6 expression by binding to and stabilizing Ccr6 mRNA and by promoting CCR6 translation. We also found that HuR down-regulates several microRNA expressions, which could target the 3\u27-UTR of Ccr6 mRNA for decay. Accordingly, knock-out of HuR reduced CCR6 expression on Th17 cells and impaired their migration to CNS compared with the response of WT Th17 cells and thereby ameliorated EAE. Together, these findings highlight how HuR contributes to Th17 cell-mediated autoimmune neuroinflammation and support the notion that targeting HuR might be a potential therapeutic intervention for managing autoimmune disorders of the CNS

    Efficient Online Timed Pattern Matching by Automata-Based Skipping

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    The timed pattern matching problem is an actively studied topic because of its relevance in monitoring of real-time systems. There one is given a log ww and a specification A\mathcal{A} (given by a timed word and a timed automaton in this paper), and one wishes to return the set of intervals for which the log ww, when restricted to the interval, satisfies the specification A\mathcal{A}. In our previous work we presented an efficient timed pattern matching algorithm: it adopts a skipping mechanism inspired by the classic Boyer--Moore (BM) string matching algorithm. In this work we tackle the problem of online timed pattern matching, towards embedded applications where it is vital to process a vast amount of incoming data in a timely manner. Specifically, we start with the Franek-Jennings-Smyth (FJS) string matching algorithm---a recent variant of the BM algorithm---and extend it to timed pattern matching. Our experiments indicate the efficiency of our FJS-type algorithm in online and offline timed pattern matching

    Pattern Matching in Link Streams: a Token-based Approach

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    International audienceLink streams model the dynamics of interactions in complex distributed systems as sequences of links (interactions) occurring at a given time. Detecting patterns in such sequences is crucial for many applications but it raises several challenges. In particular, there is no generic approach for the specification and detection of link stream patterns in a way similar to regular expressions and automata for text patterns. To address this, we propose a novel automata framework integrating both timed constraints and finite memory together with a recognition algorithm. The algorithm uses structures similar to tokens in high-level Petri nets and includes non-determinism and concurrency. We illustrate the use of our framework in real-world cases and evaluate its practical performances

    Quantitative Regular Expressions for Arrhythmia Detection Algorithms

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    Motivated by the problem of verifying the correctness of arrhythmia-detection algorithms, we present a formalization of these algorithms in the language of Quantitative Regular Expressions. QREs are a flexible formal language for specifying complex numerical queries over data streams, with provable runtime and memory consumption guarantees. The medical-device algorithms of interest include peak detection (where a peak in a cardiac signal indicates a heartbeat) and various discriminators, each of which uses a feature of the cardiac signal to distinguish fatal from non-fatal arrhythmias. Expressing these algorithms' desired output in current temporal logics, and implementing them via monitor synthesis, is cumbersome, error-prone, computationally expensive, and sometimes infeasible. In contrast, we show that a range of peak detectors (in both the time and wavelet domains) and various discriminators at the heart of today's arrhythmia-detection devices are easily expressible in QREs. The fact that one formalism (QREs) is used to describe the desired end-to-end operation of an arrhythmia detector opens the way to formal analysis and rigorous testing of these detectors' correctness and performance. Such analysis could alleviate the regulatory burden on device developers when modifying their algorithms. The performance of the peak-detection QREs is demonstrated by running them on real patient data, on which they yield results on par with those provided by a cardiologist.Comment: CMSB 2017: 15th Conference on Computational Methods for Systems Biolog

    Transcriptomic-wide discovery of direct and indirect HuR RNA targets in activated CD4+ T cells

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    Due to poor correlation between steady state mRNA levels and protein product, purely transcriptomic profiling methods may miss genes posttranscriptionally regulated by RNA binding proteins (RBPs) and microRNAs (miRNAs). RNA immunoprecipitation (RIP) methods developed to identify in vivo targets of RBPs have greatly elucidated those mRNAs which may be regulated via transcript stability and translation. The RBP HuR (ELAVL1) and family members are major stabilizers of mRNA. Many labs have identified HuR mRNA targets; however, many of these analyses have been performed in cell lines and oftentimes are not independent biological replicates. Little is known about how HuR target mRNAs behave in conditional knock-out models. In the present work, we performed HuR RIP-Seq and RNA-Seq to investigate HuR direct and indirect targets using a novel conditional knock-out model of HuR genetic ablation during CD4+ T activation and Th2 differentiation. Using independent biological replicates, we generated a high coverage RIP-Seq data set (>160 million reads) that was analyzed using bioinformatics methods specifically designed to find direct mRNA targets in RIP-Seq data. Simultaneously, another set of independent biological replicates were sequenced by RNA-Seq (>425 million reads) to identify indirect HuR targets. These direct and indirect targets were combined to determine canonical pathways in CD4+ T cell activation and differentiation for which HuR plays an important role. We show that HuR may regulate genes in multiple canonical pathways involved in T cell activation especially the CD28 family signaling pathway. These data provide insights into potential HuR-regulated genes during T cell activation and immune mechanisms

    LNCS

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    We provide a procedure for detecting the sub-segments of an incrementally observed Boolean signal ω that match a given temporal pattern ϕ. As a pattern specification language, we use timed regular expressions, a formalism well-suited for expressing properties of concurrent asynchronous behaviors embedded in metric time. We construct a timed automaton accepting the timed language denoted by ϕ and modify it slightly for the purpose of matching. We then apply zone-based reachability computation to this automaton while it reads ω, and retrieve all the matching segments from the results. Since the procedure is automaton based, it can be applied to patterns specified by other formalisms such as timed temporal logics reducible to timed automata or directly encoded as timed automata. The procedure has been implemented and its performance on synthetic examples is demonstrated

    Elevated expression of artemis in human fibroblast cells is associated with cellular radiosensitivity and increased apoptosis

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    Copyright @ 2012 Nature Publishing GroupThis article has been made available through the Brunel Open Access Publishing Fund.Background: The objective of this study was to determine the molecular mechanism(s) responsible for cellular radiosensitivity in two human fibroblast cell lines 84BR and 175BR derived from two cancer patients. Methods: Clonogenic assays were performed following exposure to increasing doses of gamma radiation to confirm radiosensitivity. Îł-H2AX foci assays were used to determine the efficiency of DNA double strand break (DSB) repair in cells. Quantitative-PCR (Q-PCR) established the expression levels of key DNA DSB repair proteins. Imaging flow cytometry using Annexin V-FITC was used to compare artemis expression and apoptosis in cells. Results: Clonogenic cellular hypersensitivity in the 84BR and 175BR cell lines was associated with a defect in DNA DSB repair measured by the Îł-H2AX foci assay. Q-PCR analysis and imaging flow cytometry revealed a two-fold overexpression of the artemis DNA repair gene which was associated with an increased level of apoptosis in the cells before and after radiation exposure. Over-expression of normal artemis protein in a normal immortalised fibroblast cell line NB1-Tert resulted in increased radiosensitivity and apoptosis. Conclusion: We conclude elevated expression of artemis is associated with higher levels of DNA DSB, radiosensitivity and elevated apoptosis in two radio-hypersensitive cell lines. These data reveal a potentially novel mechanism responsible for radiosensitivity and show that increased artemis expression in cells can result in either radiation resistance or enhanced sensitivity.This work was supported in part by The Vidal Sassoon Foundation USA. This article is made available through the Brunel Open Access Publishing Fund

    LNCS

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    We solve the offline monitoring problem for timed propositional temporal logic (TPTL), interpreted over dense-time Boolean signals. The variant of TPTL we consider extends linear temporal logic (LTL) with clock variables and reset quantifiers, providing a mechanism to specify real-time constraints. We first describe a general monitoring algorithm based on an exhaustive computation of the set of satisfying clock assignments as a finite union of zones. We then propose a specialized monitoring algorithm for the one-variable case using a partition of the time domain based on the notion of region equivalence, whose complexity is linear in the length of the signal, thereby generalizing a known result regarding the monitoring of metric temporal logic (MTL). The region and zone representations of time constraints are known from timed automata verification and can also be used in the discrete-time case. Our prototype implementation appears to outperform previous discrete-time implementations of TPTL monitoring

    Moving Beyond Mimicry: Developing Hybrid Spaces in Indian Business Schools

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    This article analyses the identity work of Indian management educators and scholars as they seek to establish, maintain and revise a sense of self in the context of business school globalization. We show how globalization, combined with the historical legacy of colonialism, renders Indian scholars precarious in their interactions with Western business schools. Based on a qualitative interview study, we explore how Indian business school scholars perform their identities in the context of neo-colonial relations, which are characterised by the dominance of English language and a pressure to conform to research norms set by globally-ranked journals. Drawing on postcolonial theory, our argument focuses on mimicry as a distinctive form of identity work that involves maintaining difference between Western and non-Western identities by 'Othering' Indian scholars, while simultaneously seeking to transform them. We draw attention to ambivalence within participants' accounts, which we suggest arises because the authority of Western scholarship relies on maintaining non-Western scholars in a position of alterity or 'not quite-ness'. We suggest that hybridity offers an opportunity to disrupt and question current practices of business school globalization and facilitate scholarly engagement that reflects more diverse philosophical positions and worldviews

    Screening and diagnostic breast MRI: how do they impact surgical treatment? Insights from the MIPA study

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    Objectives: To report mastectomy and reoperation rates in women who had breast MRI for screening (S-MRI subgroup) or diagnostic (D-MRI subgroup) purposes, using multivariable analysis for investigating the role of MRI referral/nonreferral and other covariates in driving surgical outcomes. Methods: The MIPA observational study enrolled women aged 18–80 years with newly diagnosed breast cancer destined to have surgery as the primary treatment, in 27 centres worldwide. Mastectomy and reoperation rates were compared using non-parametric tests and multivariable analysis. Results: A total of 5828 patients entered analysis, 2763 (47.4%) did not undergo MRI (noMRI subgroup) and 3065 underwent MRI (52.6%); of the latter, 2441/3065 (79.7%) underwent MRI with preoperative intent (P-MRI subgroup), 510/3065 (16.6%) D-MRI, and 114/3065 S-MRI (3.7%). The reoperation rate was 10.5% for S-MRI, 8.2% for D-MRI, and 8.5% for P-MRI, while it was 11.7% for noMRI (p ≤ 0.023 for comparisons with D-MRI and P-MRI). The overall mastectomy rate (first-line mastectomy plus conversions from conserving surgery to mastectomy) was 39.5% for S-MRI, 36.2% for P-MRI, 24.1% for D-MRI, and 18.0% for noMRI. At multivariable analysis, using noMRI as reference, the odds ratios for overall mastectomy were 2.4 (p < 0.001) for S-MRI, 1.0 (p = 0.957) for D-MRI, and 1.9 (p < 0.001) for P-MRI. Conclusions: Patients from the D-MRI subgroup had the lowest overall mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). This analysis offers an insight into how the initial indication for MRI affects the subsequent surgical treatment of breast cancer. Key Points: • Of 3065 breast MRI examinations, 79.7% were performed with preoperative intent (P-MRI), 16.6% were diagnostic (D-MRI), and 3.7% were screening (S-MRI) examinations. • The D-MRI subgroup had the lowest mastectomy rate (24.1%) among MRI subgroups and the lowest reoperation rate (8.2%) together with P-MRI (8.5%). • The S-MRI subgroup had the highest mastectomy rate (39.5%) which aligns with higher-than-average risk in this subgroup, with a reoperation rate (10.5%) not significantly different to that of all other subgroups
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