On a Subposet of the Tamari Lattice

We explore some of the properties of a subposet of the Tamari lattice introduced by Pallo, which we call the comb poset. We show that three binary functions that are not well-behaved in the Tamari lattice are remarkably well-behaved within an interval of the comb poset: rotation distance, meets and joins, and the common parse words function for a pair of trees. We relate this poset to a partial order on the symmetric group studied by Edelman.Comment: 21 page

Resummation of transverse energy in vector boson and Higgs boson production at hadron colliders

We compute the resummed hadronic transverse energy (E_T) distribution due to initial-state QCD radiation in vector boson and Higgs boson production at hadron colliders. The resummed exponent, parton distributions and coefficient functions are treated consistently to next-to-leading order. The results are matched to fixed-order calculations at large E_T and compared with parton-shower Monte Carlo predictions at Tevatron and LHC energies.Comment: 24 pages, 15 figure

A Formalism for the Systematic Treatment of Rapidity Logarithms in Quantum Field Theory

Many observables in QCD rely upon the resummation of perturbation theory to retain predictive power. Resummation follows after one factorizes the cross section into the rele- vant modes. The class of observables which are sensitive to soft recoil effects are particularly challenging to factorize and resum since they involve rapidity logarithms. In this paper we will present a formalism which allows one to factorize and resum the perturbative series for such observables in a systematic fashion through the notion of a "rapidity renormalization group". That is, a Collin-Soper like equation is realized as a renormalization group equation, but has a more universal applicability to observables beyond the traditional transverse momentum dependent parton distribution functions (TMDPDFs) and the Sudakov form factor. This formalism has the feature that it allows one to track the (non-standard) scheme dependence which is inherent in any scenario where one performs a resummation of rapidity divergences. We present a pedagogical introduction to the formalism by applying it to the well-known massive Sudakov form factor. The formalism is then used to study observables of current interest. A factorization theorem for the transverse momentum distribution of Higgs production is presented along with the result for the resummed cross section at NLL. Our formalism allows one to define gauge invariant TMDPDFs which are independent of both the hard scattering amplitude and the soft function, i.e. they are uni- versal. We present details of the factorization and resummation of the jet broadening cross section including a renormalization in pT space. We furthermore show how to regulate and renormalize exclusive processes which are plagued by endpoint singularities in such a way as to allow for a consistent resummation.Comment: Typos in Appendix C corrected, as well as a typo in eq. 5.6

A self-organized model for cell-differentiation based on variations of molecular decay rates

Systemic properties of living cells are the result of molecular dynamics governed by so-called genetic regulatory networks (GRN). These networks capture all possible features of cells and are responsible for the immense levels of adaptation characteristic to living systems. At any point in time only small subsets of these networks are active. Any active subset of the GRN leads to the expression of particular sets of molecules (expression modes). The subsets of active networks change over time, leading to the observed complex dynamics of expression patterns. Understanding of this dynamics becomes increasingly important in systems biology and medicine. While the importance of transcription rates and catalytic interactions has been widely recognized in modeling genetic regulatory systems, the understanding of the role of degradation of biochemical agents (mRNA, protein) in regulatory dynamics remains limited. Recent experimental data suggests that there exists a functional relation between mRNA and protein decay rates and expression modes. In this paper we propose a model for the dynamics of successions of sequences of active subnetworks of the GRN. The model is able to reproduce key characteristics of molecular dynamics, including homeostasis, multi-stability, periodic dynamics, alternating activity, differentiability, and self-organized critical dynamics. Moreover the model allows to naturally understand the mechanism behind the relation between decay rates and expression modes. The model explains recent experimental observations that decay-rates (or turnovers) vary between differentiated tissue-classes at a general systemic level and highlights the role of intracellular decay rate control mechanisms in cell differentiation.Comment: 16 pages, 5 figure

Lung adenocarcinoma originates from retrovirus infection of proliferating type 2 pneumocytes during pulmonary post-natal development or tissue repair

Jaagsiekte sheep retrovirus (JSRV) is a unique oncogenic virus with distinctive biological properties. JSRV is the only virus causing a naturally occurring lung cancer (ovine pulmonary adenocarcinoma, OPA) and possessing a major structural protein that functions as a dominant oncoprotein. Lung cancer is the major cause of death among cancer patients. OPA can be an extremely useful animal model in order to identify the cells originating lung adenocarcinoma and to study the early events of pulmonary carcinogenesis. In this study, we demonstrated that lung adenocarcinoma in sheep originates from infection and transformation of proliferating type 2 pneumocytes (termed here lung alveolar proliferating cells, LAPCs). We excluded that OPA originates from a bronchioalveolar stem cell, or from mature post-mitotic type 2 pneumocytes or from either proliferating or non-proliferating Clara cells. We show that young animals possess abundant LAPCs and are highly susceptible to JSRV infection and transformation. On the contrary, healthy adult sheep, which are normally resistant to experimental OPA induction, exhibit a relatively low number of LAPCs and are resistant to JSRV infection of the respiratory epithelium. Importantly, induction of lung injury increased dramatically the number of LAPCs in adult sheep and rendered these animals fully susceptible to JSRV infection and transformation. Furthermore, we show that JSRV preferentially infects actively dividing cell in vitro. Overall, our study provides unique insights into pulmonary biology and carcinogenesis and suggests that JSRV and its host have reached an evolutionary equilibrium in which productive infection (and transformation) can occur only in cells that are scarce for most of the lifespan of the sheep. Our data also indicate that, at least in this model, inflammation can predispose to retroviral infection and cancer

Composite Higgs Search at the LHC

The Higgs boson production cross-sections and decay rates depend, within the Standard Model (SM), on a single unknown parameter, the Higgs mass. In composite Higgs models where the Higgs boson emerges as a pseudo-Goldstone boson from a strongly-interacting sector, additional parameters control the Higgs properties which then deviate from the SM ones. These deviations modify the LEP and Tevatron exclusion bounds and significantly affect the searches for the Higgs boson at the LHC. In some cases, all the Higgs couplings are reduced, which results in deterioration of the Higgs searches but the deviations of the Higgs couplings can also allow for an enhancement of the gluon-fusion production channel, leading to higher statistical significances. The search in the H to gamma gamma channel can also be substantially improved due to an enhancement of the branching fraction for the decay of the Higgs boson into a pair of photons.Comment: 32 pages, 16 figure

Natural computation meta-heuristics for the in silico optimization of microbial strains

<p>Abstract</p> <p>Background</p> <p>One of the greatest challenges in Metabolic Engineering is to develop quantitative models and algorithms to identify a set of genetic manipulations that will result in a microbial strain with a desirable metabolic phenotype which typically means having a high yield/productivity. This challenge is not only due to the inherent complexity of the metabolic and regulatory networks, but also to the lack of appropriate modelling and optimization tools. To this end, Evolutionary Algorithms (EAs) have been proposed for <it>in silico </it>metabolic engineering, for example, to identify sets of gene deletions towards maximization of a desired physiological objective function. In this approach, each mutant strain is evaluated by resorting to the simulation of its phenotype using the Flux-Balance Analysis (FBA) approach, together with the premise that microorganisms have maximized their growth along natural evolution.</p> <p>Results</p> <p>This work reports on improved EAs, as well as novel Simulated Annealing (SA) algorithms to address the task of <it>in silico </it>metabolic engineering. Both approaches use a variable size set-based representation, thereby allowing the automatic finding of the best number of gene deletions necessary for achieving a given productivity goal. The work presents extensive computational experiments, involving four case studies that consider the production of succinic and lactic acid as the targets, by using <it>S. cerevisiae </it>and <it>E. coli </it>as model organisms. The proposed algorithms are able to reach optimal/near-optimal solutions regarding the production of the desired compounds and presenting low variability among the several runs.</p> <p>Conclusion</p> <p>The results show that the proposed SA and EA both perform well in the optimization task. A comparison between them is favourable to the SA in terms of consistency in obtaining optimal solutions and faster convergence. In both cases, the use of variable size representations allows the automatic discovery of the approximate number of gene deletions, without compromising the optimality of the solutions.</p

Immune response CC chemokines CCL2 and CCL5 are associated with pulmonary sarcoidosis

Abstract Background Pulmonary sarcoidosis involves an intense leukocyte infiltration of the lung with the formation of non-necrotizing granulomas. CC chemokines (chemokine (C-C motif) ligand 2 (CCL2)-CCL5) are chemoattractants of mononuclear cells and act through seven transmembrane G-coupled receptors. Previous studies have demonstrated conflicting results with regard to the associations of these chemokines with sarcoidosis. In an effort to clarify previous discrepancies, we performed the largest observational study to date of CC chemokines in bronchoalveolar lavage fluid (BALF) from patients with pulmonary sarcoidosis. Results BALF chemokine levels from 72 patients affected by pulmonary sarcoidosis were analyzed by enzyme-linked immunosorbent assay (ELISA) and compared to 8 healthy volunteers. BALF CCL3 and CCL4 levels from pulmonary sarcoidosis patients were not increased compared to controls. However, CCL2 and CCL5 levels were elevated, and subgroup analysis showed higher levels of both chemokines in all stages of pulmonary sarcoidosis. CCL2, CCL5, CC chemokine receptor type 1 (CCR1), CCR2 and CCR3 were expressed from mononuclear cells forming the lung granulomas, while CCR5 was only found on mast cells. Conclusions These data suggest that CCL2 and CCL5 are important mediators in recruiting CCR1, CCR2, and CCR3 expressing mononuclear cells as well as CCR5-expressing mast cells during all stages of pulmonary sarcoidosis