Renormalization of composite operators

The blocked composite operators are defined in the one-component Euclidean scalar field theory, and shown to generate a linear transformation of the operators, the operator mixing. This transformation allows us to introduce the parallel transport of the operators along the RG trajectory. The connection on this one-dimensional manifold governs the scale evolution of the operator mixing. It is shown that the solution of the eigenvalue problem of the connection gives the various scaling regimes and the relevant operators there. The relation to perturbative renormalization is also discussed in the framework of the $\phi^3$ theory in dimension $d=6$.Comment: 24 pages, revtex (accepted by Phys. Rev. D), changes in introduction and summar

Heavy quarkonium: progress, puzzles, and opportunities

A golden age for heavy quarkonium physics dawned a decade ago, initiated by the confluence of exciting advances in quantum chromodynamics (QCD) and an explosion of related experimental activity. The early years of this period were chronicled in the Quarkonium Working Group (QWG) CERN Yellow Report (YR) in 2004, which presented a comprehensive review of the status of the field at that time and provided specific recommendations for further progress. However, the broad spectrum of subsequent breakthroughs, surprises, and continuing puzzles could only be partially anticipated. Since the release of the YR, the BESII program concluded only to give birth to BESIII; the $B$-factories and CLEO-c flourished; quarkonium production and polarization measurements at HERA and the Tevatron matured; and heavy-ion collisions at RHIC have opened a window on the deconfinement regime. All these experiments leave legacies of quality, precision, and unsolved mysteries for quarkonium physics, and therefore beg for continuing investigations. The plethora of newly-found quarkonium-like states unleashed a flood of theoretical investigations into new forms of matter such as quark-gluon hybrids, mesonic molecules, and tetraquarks. Measurements of the spectroscopy, decays, production, and in-medium behavior of c\bar{c}, b\bar{b}, and b\bar{c} bound states have been shown to validate some theoretical approaches to QCD and highlight lack of quantitative success for others. The intriguing details of quarkonium suppression in heavy-ion collisions that have emerged from RHIC have elevated the importance of separating hot- and cold-nuclear-matter effects in quark-gluon plasma studies. This review systematically addresses all these matters and concludes by prioritizing directions for ongoing and future efforts.Comment: 182 pages, 112 figures. Editors: N. Brambilla, S. Eidelman, B. K. Heltsley, R. Vogt. Section Coordinators: G. T. Bodwin, E. Eichten, A. D. Frawley, A. B. Meyer, R. E. Mitchell, V. Papadimitriou, P. Petreczky, A. A. Petrov, P. Robbe, A. Vair

A search for resonances decaying into a Higgs boson and a new particle X in the XH → qqbb final state with the ATLAS detector

A search for heavy resonances decaying into a Higgs boson (H) and a new particle (X) is reported, utilizing 36.1 fb−1 of proton–proton collision data at collected during 2015 and 2016 with the ATLAS detector at the CERN Large Hadron Collider. The particle X is assumed to decay to a pair of light quarks, and the fully hadronic final state is analysed. The search considers the regime of high XH resonance masses, where the X and H bosons are both highly Lorentz-boosted and are each reconstructed using a single jet with large radius parameter. A two-dimensional phase space of XH mass versus X mass is scanned for evidence of a signal, over a range of XH resonance mass values between 1 TeV and 4 TeV, and for X particles with masses from 50 GeV to 1000 GeV. All search results are consistent with the expectations for the background due to Standard Model processes, and 95% CL upper limits are set, as a function of XH and X masses, on the production cross-section of the resonance

Computational modeling of miRNA-mediated gene regulation in consideration of miRNP binding information from AGO-bound CLIP-Seq data analysis.

As our knowledge of the eukaryotic genome structure and organization has evolved, a new family of small non-coding regulatory RNAs, called microRNAs (miRNAs), has emerged. 20 years after their first discovery, our comprehension of these molecules and their interactions is still limited yet. Bound to an Argonaute (AGO) containing ribonucleoprotein complex (miRNP), miRNAs were suggested to form a requisite post-transcriptional regulation layer controlling many cellular processes. Recent CLIP-Seq technologies allowed for the first time, the determination of miRNP target sites of a whole transcriptome with high specificity. This doctoral thesis aimed to quantitatively elucidate basic miRNP:target interaction paradigms, to examine how these are impacted by genetic variance, and finally, to develop a novel computational approach to qualitatively model global miRNA-mediated regulation by means of novel information extracted from available AGO-bound CLIP-Seq libraries

Large-scale modeling of condition-specific gene regulatory networks by information integration and inference.

Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η(2) (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research

The sufficient minimal set of miRNA seed types.

MOTIVATION: Pairing between the target sequence and the 6-8 nt long seed sequence of the miRNA presents the most important feature for miRNA target site prediction. Novel high-throughput technologies such as Argonaute HITS-CLIP afford meanwhile a detailed study of miRNA:mRNA duplices. These interaction maps enable a first discrimination between functional and non-functional target sites in a bulky fashion. Prediction algorithms apply different seed paradigms to identify miRNA target sites. Therefore, a quantitative assessment of miRNA target site prediction is of major interest. RESULTS: We identified a set of canonical seed types based on a transcriptome wide analysis of experimentally verified functional target sites. We confirmed the specificity of long seeds but we found that the majority of functional target sites are formed by less specific seeds of only 6 nt indicating a crucial role of this type. A substantial fraction of genuine target sites arenon-conserved. Moreover, the majority of functional sites remain uncovered by common prediction methods

Large scale analysis reveals novel insights in the characteristics of miRNA targeting.

MicroRNAs (miRNAs) have emerged as central post-transcriptional regulators of gene expression in higher eukaryotes. The about 23 nucleotides long RNA molecules regulate gene expression by binding preferably to the 3'untranslated region (3'UTR) of protein-coding messenger RNAs (mR-Nas). Generally, miRNA-mediated regulation represses protein synthesis either by inhibition of translation or by degradation of mRNAs [FBS08]. To understand the functional role of miRNAs it isessential to have knowledge of their regulatory targets. Although the number of experimentally validated miRNA targets is increasing, the majority of interactions are still unknown. Computational miRNA target prediction has emergedd to uncover unknown miRNA-mRNA interactions. Meanwhile several rules that reflect miRNA targeting have been suggested and subsequently adopted for computational target prediction [Bar09]. Of particular importance for target recognition are sites of length 6 to 8 nucleotides that pair to the 5' region of the miRNA, which is referred to as the miRNA seed [CZMD09]. Specificity of prediction is improved by considering further targeting features such as conservation of the target site, position of the site within the 3'UTR [GFJ+07] as well as the structural accessibility of the target region [KIU*07]. Although the accuracy of prediction methods was steadily growing the number of false positive predictions methods was steadily growing the number of false positive predictions is still very high. Consequently, the existing models of target recognition by miRNAs are still insufficient to describe the reality of miRNA-target interaction. Recently, a miRNA-mRNA interaction map has been published containing a set of verified target sites for 20 miRNAs in the transcriptome of the murine brain [CZMD09]. The large size of the map and the precise localization of miRNA target sites allowed us to study miRNA target recognition as well as the performance of target prediction methods in an unprecedent way

miR-92a regulates TGF-β1-induced WISP1 expression in pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is the most common and fatal form of idiopathic interstitial pneumonia. MicroRNAs (miRNAs), short, single-stranded RNAs that regulate protein expression in a post-transcriptional manner, have recently been demonstrated to contribute to IPF pathogenesis. We have previously identified WNT1-inducible signaling pathway protein 1 (WISP1) as a highly expressed pro-fibrotic mediator in IPF, but the underlying mechanisms resulting in increased WISP1 expression, remain elusive. Here, we investigated whether WISP1 is a target of miRNA regulation. We applied a novel supervised machine learning approach, which predicted miR-30a/d and miR-92a target sites in regions of the human WISP1 3'UTR preferentially bound by the miRNA ribonucleoprotein complex. Both miRNAs were decreased in IPF samples, whereas WISP1 protein was increased. We demonstrated further that transforming growth factor (TGF)-β1-induced WISP1 expression in primary lung fibroblasts in vitro and lung homogenates in vivo. Notably, miR-30a and miR-92a reversed TGF-β1-induced WISP1 mRNA expression in lung fibroblasts. Moreover, miR-92a inhibition increased WISP1 protein expression in lung fibroblasts. An inverse relationship for WISP1 and miR-92a was found in a TGF-β1 dependent lung fibrosis model in vivo. Finally, we found significantly increased WISP1 expression in primary IPF fibroblasts, which negatively correlated with miR-92a level ex vivo. Altogether, our findings indicate a regulatory role of miR-92a for WISP1 expression in pulmonary fibrosis