Factorization and NNLL Resummation for Higgs Production with a Jet Veto

Using methods of effective field theory, we derive the first all-order factorization theorem for the Higgs-boson production cross section with a jet veto, imposed by means of a standard sequential recombination jet algorithm. Like in the case of small-q_T resummation in Drell-Yan and Higgs production, the factorization is affected by a collinear anomaly. Our analysis provides the basis for a systematic resummation of large logarithms log(m_H/p_T^veto) beyond leading-logarithmic order. Specifically, we present predictions for the resummed jet-veto cross section and efficiency at next-to-next-to-leading logarithmic order. Our results have important implications for Higgs-boson searches at the LHC, where a jet veto is required to suppress background events.Comment: 28 pages, 5 figures; v2: published version; note added in proo

NLL+NNLO predictions for jet-veto efficiencies in Higgs-boson and Drell-Yan production

Using the technology of the CAESAR approach to resummation, we examine the jet-veto efficiency in Higgs-boson and Drell-Yan production at hadron colliders and show that at next-to-leading logarithmic (NLL) accuracy the resummation reduces to just a Sudakov form factor. Matching with NNLO calculations results in stable predictions for the case of Drell-Yan production, but reveals substantial uncertainties in gluon-fusion Higgs production, connected in part with the poor behaviour of the perturbative series for the total cross section. We compare our results to those from POWHEG with and without reweighting by HqT, as used experimentally, and observe acceptable agreement. In an appendix we derive the part of the NNLL resummation corrections associated with the radius dependence of the jet algorithm.Comment: 30 pages, 8 figures; v2 as published in JHE

Jet-veto in bottom-quark induced Higgs production at next-to-next-to-leading order

We present results for associated Higgs+n-jet production in bottom quark annihilation, for n=0 and n>=1 at NNLO and NLO accuracy, respectively. We consider both the cases with and without b-tagging. Numerical results are presented for parameters relevant for experiments at the LHC.Comment: 27 pages, 13 figures, 8 table

Factorization and resummation of s-channel single top quark production

In this paper we study the factorization and resummation of s-channel single top quark production in the Standard Model at both the Tevatron and the LHC. We show that the production cross section in the threshold limit can be factorized into a convolution of hard function, soft function and jet function via soft-collinear-effective-theory (SCET), and resummation can be performed using renormalization group equation in the momentum space resummation formalism. We find that in general, the resummation effects enhance the Next-to-Leading-Order (NLO) cross sections by about $3$ at both the Tevatron and the LHC, and significantly reduce the factorization scale dependence of the total cross section at the Tevatron, while at the LHC we find that the factorization scale dependence has not been improved, compared with the NLO results.Comment: 29 pages, 7 figures; version published in JHE

GPVI (Glycoprotein VI) Interaction With Fibrinogen Is Mediated by Avidity and the Fibrinogen αC-Region

Objective: GPVI (glycoprotein VI) is a key molecular player in collagen-induced platelet signaling and aggregation. Recent evidence indicates that it also plays important role in platelet aggregation and thrombus growth through interaction with fibrin(ogen). However, there are discrepancies in the literature regarding whether the monomeric or dimeric form of GPVI binds to fibrinogen at high affinity. The mechanisms of interaction are also not clear, including which region of fibrinogen is responsible for GPVI binding. We aimed to gain further understanding of the mechanisms of interaction at molecular level and to identify the regions on fibrinogen important for GPVI binding. Approach and Results: Using multiple surface- and solution-based protein-protein interaction methods, we observe that dimeric GPVI binds to fibrinogen with much higher affinity and has a slower dissociation rate constant than the monomer due to avidity effects. Moreover, our data show that the highest affinity interaction of GPVI is with the αC-region of fibrinogen. We further show that GPVI interacts with immobilized fibrinogen and fibrin variants at a similar level, including a nonpolymerizing fibrin variant, suggesting that GPVI binding is independent of fibrin polymerization. Conclusions: Based on the above findings, we conclude that the higher affinity of dimeric GPVI over the monomer for fibrinogen interaction is achieved by avidity. The αC-region of fibrinogen appears essential for GPVI binding. We propose that fibrin polymerization into fibers during coagulation will cluster GPVI through its αC-region, leading to downstream signaling, further activation of platelets, and potentially stimulating clot growth

Stable Isotopic Evidence for Methane Seeps in Neoproterozoic Postglacial Cap Carbonates

The Earth's most severe glaciations are thought to have occurred about 600 million years ago, in the late Neoproterozoic era. A puzzling feature of glacial deposits from this interval is that they are overlain by 1–5-m-thick 'cap carbonates' (particulate deep-water marine carbonate rocks) associated with a prominent negative carbon isotope excursion. Cap carbonates have been controversially ascribed to the aftermath of almost complete shutdown of the ocean ecosystems for millions of years during such ice ages—the 'snowball Earth' hypothesis. Conversely, it has also been suggested that these carbonate rocks were the result of destabilization of methane hydrates during deglaciation and concomitant flooding of continental shelves and interior basins. The most compelling criticism of the latter 'methane hydrate' hypothesis has been the apparent lack of extreme isotopic variation in cap carbonates inferred locally to be associated with methane seeps. Here we report carbon isotopic and petrographic data from a Neoproterozoic postglacial cap carbonate in south China that provide direct evidence for methane-influenced processes during deglaciation. This evidence lends strong support to the hypothesis that methane hydrate destabilization contributed to the enigmatic cap carbonate deposition and strongly negative carbon isotopic anomalies following Neoproterozoic ice ages. This explanation requires less extreme environmental disturbance than that implied by the snowball Earth hypothesis

Crystal Structure of the RNA Recognition Motif of Yeast Translation Initiation Factor eIF3b Reveals Differences to Human eIF3b

BACKGROUND: The multi-subunit eukaryotic initiation factor3 (eIF3) plays a central role in the initiation step of protein synthesis in eukaryotes. One of its large subunits, eIF3b, serves as a scaffold within eIF3 as it interacts with several other subunits. It harbors an RNA Recognition Motif (RRM), which is shown to be a non-canonical RRM in human as it is not capable to interact with oligonucleotides, but rather interacts with eIF3j, a sub-stoichiometric subunit of eIF3. PRINCIPAL FINDING: We have analyzed the high-resolution crystal structure of the eIF3b RRM domain from yeast. It exhibits the same fold as its human ortholog, with similar charge distribution on the surface interacting with the eIF3j in human. Thermodynamic analysis of the interaction between yeast eIF3b-RRM and eIF3j revealed the same range of enthalpy change and dissociation constant as for the human proteins, providing another line of evidence for the same mode of interaction between eIF3b and eIF3j in both organisms. However, analysis of the surface charge distribution of the putative RNA-binding β-sheet suggested that in contrast to its human ortholog, it potentially could bind oligonucleotides. Three-dimensional positioning of the so called "RNP1" motif in this domain is similar to other canonical RRMs, suggesting that this domain might indeed be a canonical RRM, conferring oligonucleotide binding capability to eIF3 in yeast. Interaction studies with yeast total RNA extract confirmed the proposed RNA binding activity of yeast eIF3b-RRM. CONCLUSION: We showed that yeast eIF3b-RRM interacts with eIF3j in a manner similar to its human ortholog. However, it shows similarities in the oligonucleotide binding surface to canonical RRMs and interacts with yeast total RNA. The proposed RNA binding activity of eIF3b-RRM may help eIF3 to either bind to the ribosome or recruit the mRNA to the 43S pre-initiation complex

Accuracy and quality assessment of 454 GS-FLX Titanium pyrosequencing

<p>Abstract</p> <p>Background</p> <p>The rapid evolution of 454 GS-FLX sequencing technology has not been accompanied by a reassessment of the quality and accuracy of the sequences obtained. Current strategies for decision-making and error-correction are based on an initial analysis by Huse <it>et al. </it>in 2007, for the older GS20 system based on experimental sequences. We analyze here the quality of 454 sequencing data and identify factors playing a role in sequencing error, through the use of an extensive dataset for Roche control DNA fragments.</p> <p>Results</p> <p>We obtained a mean error rate for 454 sequences of 1.07%. More importantly, the error rate is not randomly distributed; it occasionally rose to more than 50% in certain positions, and its distribution was linked to several experimental variables. The main factors related to error are the presence of homopolymers, position in the sequence, size of the sequence and spatial localization in PT plates for insertion and deletion errors. These factors can be described by considering seven variables. No single variable can account for the error rate distribution, but most of the variation is explained by the combination of all seven variables.</p> <p>Conclusions</p> <p>The pattern identified here calls for the use of internal controls and error-correcting base callers, to correct for errors, when available (e.g. when sequencing amplicons). For shotgun libraries, the use of both sequencing primers and deep coverage, combined with the use of random sequencing primer sites should partly compensate for even high error rates, although it may prove more difficult than previous thought to distinguish between low-frequency alleles and errors.</p

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