Electroweak and QCD corrections to Higgs-boson production in vector-boson fusion at the LHC

Radiative corrections of strong and electroweak interactions are presented at next-to-leading order for Higgs-boson production in the weak-boson-fusion channel at the LHC. The calculation includes all weak-boson fusion and quark-antiquark annihilation diagrams as well as all related interferences. The electroweak corrections, which also include real corrections from incoming photons and leading heavy-Higgs-boson effects at two-loop order, are of the same size as the QCD corrections, viz. typically at the level of 5-10% for a Higgs-boson mass up to \sim 700 GeV. In general, they do not simply rescale differential distributions, but induce distortions at the level of 10%. The discussed corrections have been implemented in a flexible Monte Carlo event generator.Comment: 6 pages, LaTeX, 4 postscript figures, to appear in the proceedings of the "8th International Symposium on Radiative Corrections (RADCOR07)", Florence, Italy, October 1-5, 200

Strong and electroweak NLO corrections to Higgs-boson production in vector-boson fusion at the LHC

We present results on the strong and electroweak NLO corrections to the production of a Higgs boson plus two hard jets via weak interactions at the LHC. The calculation includes all weak-boson fusion and quark-antiquark annihilation diagrams as well as all related interferences. We discuss corrections of different origin (QCD corrections of vector-boson-fusion type and interferences, electroweak corrections induced by quark or photonic initial states, heavy-Higgs-boson effects, etc.) and give some new results for distributions for a Higgs-boson mass of 200 GeV. The electroweak corrections are of the same size as the QCD corrections, viz. typically at the level of 5-10% for a Higgs-boson mass up to \sim 700 GeV. In general, they do not simply rescale differential distributions, but induce distortions at the level of 10%. The discussed corrections have been implemented in a flexible Monte Carlo event generator.Comment: 6 pages, LaTeX, 6 postscript figures, to appear in proceedings of the "9th Workshop on Elementary Particle Theory: Loops and Legs in Quantum Field Theory", Sondershausen, Germany, April 20-25, 200

Efficient surveillance for healthcare-associated infections spreading between hospitals

Early detection of new or novel variants of nosocomial pathogens is a public health priority. We show that, for healthcare-associated infections that spread between hospitals as a result of patient movements, it is possible to design an effective surveillance system based on a relatively small number of sentinel hospitals. We apply recently developed mathematical models to patient admission data from the national healthcare systems of England and The Netherlands. Relatively short detection times are achieved once 10-20% hospitals are recruited as sentinels and only modest reductions are seen as more hospitals are recruited thereafter. Using a heuristic optimization approach to sentinel selection, the same expected time to detection can be achieved by recruiting approximately half as many hospitals. Our study provides a robust evidence base to underpin the design of an efficient sentinel hospital surveillance system for novel nosocomial pathogens, delivering early detection times for reduced expenditure and effort

Gluon-induced W-boson pair production at the LHC

Pair production of W bosons constitutes an important background to Higgs boson and new physics searches at the Large Hadron Collider LHC. We have calculated the loop-induced gluon-fusion process gg -> W*W* -> leptons, including intermediate light and heavy quarks and allowing for arbitrary invariant masses of the W bosons. While formally of next-to-next-to-leading order, the gg -> W*W* -> leptons process is enhanced by the large gluon flux at the LHC and by experimental Higgs search cuts, and increases the next-to-leading order WW background estimate for Higgs searches by about 30%. We have extended our previous calculation to include the contribution from the intermediate top-bottom massive quark loop and the Higgs signal process. We provide updated results for cross sections and differential distributions and study the interference between the different gluon scattering contributions. We describe important analytical and numerical aspects of our calculation and present the public GG2WW event generator.Comment: 20 pages, 4 figure

Small regulatory RNA-induced growth rate heterogeneity of Bacillus subtilis

Isogenic bacterial populations can consist of cells displaying heterogeneous physiological traits. Small regulatory RNAs (sRNAs) could affect this heterogeneity since they act by fine-tuning mRNA or protein levels to coordinate the appropriate cellular behavior. Here we show that the sRNA RnaC/S1022 from the Gram-positive bacterium Bacillus subtilis can suppress exponential growth by modulation of the transcriptional regulator AbrB. Specifically, the post-transcriptional abrB-RnaC/S1022 interaction allows B. subtilis to increase the cell-to-cell variation in AbrB protein levels, despite strong negative autoregulation of the abrB promoter. This behavior is consistent with existing mathematical models of sRNA action, thus suggesting that induction of protein expression noise could be a new general aspect of sRNA regulation. Importantly, we show that the sRNA-induced diversity in AbrB levels generates heterogeneity in growth rates during the exponential growth phase. Based on these findings, we hypothesize that the resulting subpopulations of fast- and slow-growing B. subtilis cells reflect a bet-hedging strategy for enhanced survival of unfavorable conditions

Analyse van patiëntstromen : De basis voor regionale bestrijding van gevaarlijke infecties

Antibiotic resistance is a worldwide threat to health care as it impairs the effective treatment of bacterial infections. Measures against the spread of resistance are mainly focused on individual health care institutions as these are viewed as the main source of resistance. However, health care institutions are not completely independent in their control of the prevalence of resistance, as movement of patients between hospitals and care institutions can induce movement of resistant micro-organisms. In other words, antibiotic resistance follows the flow of patients. Mapping this flow of patients results in a network that includes all health care institutions, and has a distinctive modular structure. Patients are moved primarily within regions, much less so between regions. We argue that the structure of this health care network should be used to design efficient and effective control strategies. To this end, we advocate (a) regional coordination of control measures, (b) differentiation of investment in infection prevention according to the network position of the institution, an

Analyse van patiëntstromen : De basis voor regionale bestrijding van gevaarlijke infecties

Antibiotic resistance is a worldwide threat to health care as it impairs the effective treatment of bacterial infections. Measures against the spread of resistance are mainly focused on individual health care institutions as these are viewed as the main source of resistance. However, health care institutions are not completely independent in their control of the prevalence of resistance, as movement of patients between hospitals and care institutions can induce movement of resistant micro-organisms. In other words, antibiotic resistance follows the flow of patients. Mapping this flow of patients results in a network that includes all health care institutions, and has a distinctive modular structure. Patients are moved primarily within regions, much less so between regions. We argue that the structure of this health care network should be used to design efficient and effective control strategies. To this end, we advocate (a) regional coordination of control measures, (b) differentiation of investment in infection prevention according to the network position of the institution, an

RnaC/S1022 is condition-dependently expressed.

<p>Promoter activity of the P_RnaC/S1022-<i>gfp</i> and P_<i>hag</i>-<i>gfp</i> fusions in cells grown on LB (A), M9G (B), and M9S (C). Promoter activities were computed by subtraction of GFP level from the previous time-point as described by Botella et al. [<a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1005046#pgen.1005046.ref038" target="_blank">38</a>]. The experiment was performed three times in triplicate. Average data from triplicate measurements of one representative experiment are shown. The grey line indicates mean data and the black line a smoothed version of this mean. One in two time-points were plotted for the growth curve as open circles for the P_<i>hag</i>-<i>gfp</i> strain and closed circles for the P_RnaC/S1022-<i>gfp</i> strain. D) Representative FC results for P_RnaC/S1022-<i>gfp</i> expression in mid-exponentially growing cells with or without a <i>sigD</i> deletion. The cells were grown in M9G. Wt, <i>B</i>. <i>subtilis</i> 168 not expressing GFP.</p

RnaC/S1022 induces protein expression noise of AbrB-GFP.

<p>A) Representative FC data for the translational AbrB-GFP fusion expressed from a single copy of the respective gene fusion integrated into the <i>B</i>. <i>subtilis</i> chromosome. All strains were grown on M9G. The left panel shows histograms for, from left to right, the AbrB-GFP-producing strain with two chromosomal RnaC/S1022 copies, the AbrB-GFP-producing parental strain with one chromosomal RnaC/S1022 copy, and the AbrB-GFP-producing strain with the ΔRnaC/S1022 mutation. The right panel shows data for the same strains with an additional Δ<i>spo0A</i> mutation. Please note the increase in the width of the distribution with increasing RnaC/S1022 gene dosage. B) Quantification of AbrB-GFP noise (left panel) and mean expression data (right panel) from three independent experiments with cells grown on M9G. Shaded areas indicate the noise increase (ΔCV%) from 0 to 2 sRNA copies in the <i>spo0A</i>-proficient background (wt) and the Δ<i>spo0A</i> mutant background. Statistical significance of the comparisons of data obtained for <i>spo0A</i>-proficient or -deficient strains containing 0 to 2 sRNA copies are indicated with asterisks in the legend (* p-value <0.05; ** p-value <0.01; ANOVA with Tukey HSD test). Error bars represent the standard deviation. C) Quantification of P_<i>abrB</i>-<i>gfp</i> noise (left panel) and mean P_<i>abrB</i>-<i>gfp</i> activity data (right panel) from three independent experiments with cells grown on M9G. Statistical significance of the comparisons of data obtained for <i>spo0A</i>-proficient or -deficient strains containing 0 to 2 sRNA copies are indicated with asterisks in the legend (* p-value <0.05; n.s. means not significant; ANOVA with Tukey HSD test). Error bars represent the standard deviation.</p