Novel role for the innate immune receptor toll-like receptor 4 (TLR4) in the regulation of the wnt signaling pathway and photoreceptor apoptosis

Recent evidence has implicated innate immunity in regulating neuronal survival in the brain during stroke and other neurodegenerations. Photoreceptors are specialized light-detecting neurons in the retina that are essential for vision. In this study, we investigated the role of the innate immunity receptor TLR4 in photoreceptors. TLR4 activation by lipopolysaccharide (LPS) significantly reduced the survival of cultured mouse photoreceptors exposed to oxidative stress. With respect to mechanism, TLR4 suppressed Wnt signaling, decreased phosphorylation and activation of the Wnt receptor LRP6, and blocked the protective effect of the Wnt3a ligand. Paradoxically, TLR4 activation prior to oxidative injury protected photoreceptors, in a phenomenon known as preconditioning. Expression of TNFα and its receptors TNFR1 and TNFR2 decreased during preconditioning, and preconditioning was mimicked by TNFα antagonists, but was independent of Wnt signaling. Therefore, TLR4 is a novel regulator of photoreceptor survival that acts through the Wnt and TNFα pathways. © 2012 Yi et al

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

TRBP and eIF6 Homologue in Marsupenaeus japonicus Play Crucial Roles in Antiviral Response

Plants and invertebrates can suppress viral infection through RNA silencing, mediated by RNA-induced silencing complex (RISC). Trans-activation response RNA-binding protein (TRBP), consisting of three double-stranded RNA-binding domains, is a component of the RISC. In our previous paper, a TRBP homologue in Fenneropenaeus chinensis (Fc-TRBP) was reported to directly bind to eukaryotic initiation factor 6 (Fc-eIF6). In this study, we further characterized the function of TRBP and the involvement of TRBP and eIF6 in antiviral RNA interference (RNAi) pathway of shrimp. The double-stranded RNA binding domains (dsRBDs) B and C of the TRBP from Marsupenaeus japonicus (Mj-TRBP) were found to mediate the interaction of TRBP and eIF6. Gel-shift assays revealed that the N-terminal of Mj-TRBP dsRBD strongly binds to double-stranded RNA (dsRNA) and that the homodimer of the TRBP mediated by the C-terminal dsRBD increases the affinity to dsRNA. RNAi against either Mj-TRBP or Mj-eIF6 impairs the dsRNA-induced sequence-specific RNAi pathway and facilitates the proliferation of white spot syndrome virus (WSSV). These results further proved the important roles of TRBP and eIF6 in the antiviral response of shrimp

First Observation of τ→3πηντ\tau\to 3\pi\eta\nu_{\tau} and τ→f1πντ\tau\to f_{1}\pi\nu_{\tau} Decays

We have observed new channels for $\tau$ decays with an $\eta$ in the final state. We study 3-prong tau decays, using the $\eta\to\gamma\gamma$ and \eta\to 3\piz decay modes and 1-prong decays with two \piz's using the $\eta\to\gamma\gamma$ channel. The measured branching fractions are \B(\tau^{-}\to \pi^{-}\pi^{-}\pi^{+}\eta\nu_{\tau}) =(3.4^{+0.6}_{-0.5}\pm0.6)\times10^{-4} and \B(\tau^{-}\to \pi^{-}2\piz\eta\nu_{\tau} =(1.4\pm0.6\pm0.3)\times10^{-4}. We observe clear evidence for $f_1\to\eta\pi\pi$ substructure and measure \B(\tau^{-}\to f_1\pi^{-}\nu_{\tau})=(5.8^{+1.4}_{-1.3}\pm1.8)\times10^{-4}. We have also searched for $\eta'(958)$ production and obtain 90% CL upper limits \B(\tau^{-}\to \pi^{-}\eta'\nu_\tau)<7.4\times10^{-5} and \B(\tau^{-}\to \pi^{-}\piz\eta'\nu_\tau)<8.0\times10^{-5}.Comment: 11 page postscript file, postscript file also available through http://w4.lns.cornell.edu/public/CLN

Search for the Decays B^0 -> D^{(*)+} D^{(*)-}

Using the CLEO-II data set we have searched for the Cabibbo-suppressed decays B^0 -> D^{(*)+} D^{(*)-}. For the decay B^0 -> D^{*+} D^{*-}, we observe one candidate signal event, with an expected background of 0.022 +/- 0.011 events. This yield corresponds to a branching fraction of Br(B^0 -> D^{*+} D^{*-}) = (5.3^{+7.1}_{-3.7}(stat) +/- 1.0(syst)) x 10^{-4} and an upper limit of Br(B^0 -> D^{*+} D^{*-}) D^{*\pm} D^\mp and B^0 -> D^+ D^-, no significant excess of signal above the expected background level is seen, and we calculate the 90% CL upper limits on the branching fractions to be Br(B^0 -> D^{*\pm} D^\mp) D^+ D^-) < 1.2 x 10^{-3}.Comment: 12 page postscript file also available through http://w4.lns.cornell.edu/public/CLNS, submitted to Physical Review Letter

ΛΛˉ\Lambda\bar{\Lambda} Production in Two-Photon Interactions at CLEO

Using the CLEO detector at the Cornell $e^+e^-$ storage ring, CESR, we study the two-photon production of $\Lambda \bar{\Lambda}$, making the first observation of $\gamma \gamma \to \Lambda \bar{\Lambda}$. We present the cross-section for $\gamma \gamma \to \Lambda \bar{\Lambda}$ as a function of the $\gamma \gamma$ center of mass energy and compare it to that predicted by the quark-diquark model.Comment: 10 pages, postscript file also available through http://w4.lns.cornell.edu/public/CLN

A new pairwise kernel for biological network inference with support vector machines

International audienceBACKGROUND: Much recent work in bioinformatics has focused on the inference of various types of biological networks, representing gene regulation, metabolic processes, protein-protein interactions, etc. A common setting involves inferring network edges in a supervised fashion from a set of high-confidence edges, possibly characterized by multiple, heterogeneous data sets (protein sequence, gene expression, etc.). RESULTS: Here, we distinguish between two modes of inference in this setting: direct inference based upon similarities between nodes joined by an edge, and indirect inference based upon similarities between one pair of nodes and another pair of nodes. We propose a supervised approach for the direct case by translating it into a distance metric learning problem. A relaxation of the resulting convex optimization problem leads to the support vector machine (SVM) algorithm with a particular kernel for pairs, which we call the metric learning pairwise kernel. This new kernel for pairs can easily be used by most SVM implementations to solve problems of supervised classification and inference of pairwise relationships from heterogeneous data. We demonstrate, using several real biological networks and genomic datasets, that this approach often improves upon the state-of-the-art SVM for indirect inference with another pairwise kernel, and that the combination of both kernels always improves upon each individual kernel. CONCLUSION: The metric learning pairwise kernel is a new formulation to infer pairwise relationships with SVM, which provides state-of-the-art results for the inference of several biological networks from heterogeneous genomic data

Observation of the Decay Ds+→ωπ+D_{s}^{+}\to \omega\pi^{+}

Using e+e- annihilation data collected by the CLEO~II detector at CESR, we have observed the decay Ds+ to omega pi+. This final state may be produced through the annihilation decay of the Ds+, or through final state interactions. We find a branching ratio of [Gamma(Ds+ to omega pi+)/Gamma(Ds+ to eta pi+)]=0.16+-0.04+-0.03, where the first error is statistical and the second is systematic.Comment: 9 pages, postscript file also available through http://w4.lns.cornell.edu/public/CLN