Partially Composite Higgs in Supersymmetry

We propose a framework for natural breaking of electroweak symmetry in supersymmetric models, where elementary Higgs fields are semi-perturbatively coupled to a strong superconformal sector. The Higgs VEVs break conformal symmetry in the strong sector at the TeV scale, and the strong sector in turn gives important contributions to the Higgs potential, giving rise to a kind of Higgs bootstrap. A Higgs with mass 125\GeV can be accommodated without any fine tuning. A Higgsino mass of order the Higgs mass is also dynamically generated in these models. The masses in the strong sector generically violate custodial symmetry, and a good precision electroweak fit requires tuning of order $\sim 10$. The strong sector has an approximately supersymmetric spectrum of hadrons at the TeV scale that can be observed by looking for a peak in the $WZ$ invariant mass distribution, as well as final states containing multiple $W$, $Z$, and Higgs bosons. The models also generically predict large corrections (either enhancement or suppression) to the h \to \ga\ga width.Comment: 31 page

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

A general approach to simultaneous model fitting and variable elimination in response models for biological data with many more variables than observations

<p>Abstract</p> <p>Background</p> <p>With the advent of high throughput biotechnology data acquisition platforms such as micro arrays, SNP chips and mass spectrometers, data sets with many more variables than observations are now routinely being collected. Finding relationships between response variables of interest and variables in such data sets is an important problem akin to finding needles in a haystack. Whilst methods for a number of response types have been developed a general approach has been lacking.</p> <p>Results</p> <p>The major contribution of this paper is to present a unified methodology which allows many common (statistical) response models to be fitted to such data sets. The class of models includes virtually any model with a linear predictor in it, for example (but not limited to), multiclass logistic regression (classification), generalised linear models (regression) and survival models. A fast algorithm for finding sparse well fitting models is presented. The ideas are illustrated on real data sets with numbers of variables ranging from thousands to millions. R code implementing the ideas is available for download.</p> <p>Conclusion</p> <p>The method described in this paper enables existing work on response models when there are less variables than observations to be leveraged to the situation when there are many more variables than observations. It is a powerful approach to finding parsimonious models for such datasets. The method is capable of handling problems with millions of variables and a large variety of response types within the one framework. The method compares favourably to existing methods such as support vector machines and random forests, but has the advantage of not requiring separate variable selection steps. It is also works for data types which these methods were not designed to handle. The method usually produces very sparse models which make biological interpretation simpler and more focused.</p

Nasal gene expression differentiates COPD from controls and overlaps bronchial gene expression

© 2017 The Author(s). Background: Nasal gene expression profiling is a promising method to characterize COPD non-invasively. We aimed to identify a nasal gene expression profile to distinguish COPD patients from healthy controls. We investigated whether this COPD-associated gene expression profile in nasal epithelium is comparable with the profile observed in bronchial epithelium. Methods: Genome wide gene expression analysis was performed on nasal epithelial brushes of 31 severe COPD patients and 22 controls, all current smokers, using Affymetrix Human Gene 1.0 ST Arrays. We repeated the gene expression analysis on bronchial epithelial brushes in 2 independent cohorts of mild-to-moderate COPD patients and controls. Results: In nasal epithelium, 135 genes were significantly differentially expressed between severe COPD patients and controls, 21 being up- and 114 downregulated in COPD (false discovery rate < 0.01). Gene Set Enrichment Analysis (GSEA) showed significant concordant enrichment of COPD-associated nasal and bronchial gene expression in both independent cohorts (FDRGSEA < 0.001). Conclusion: We identified a nasal gene expression profile that differentiates severe COPD patients from controls. Of interest, part of the nasal gene expression changes in COPD mimics differentially expressed genes in the bronchus. These findings indicate that nasal gene expression profiling is potentially useful as a non-invasive biomarker in COPD. Trial registration:ClinicalTrials.govregistration number NCT01351792(registration date May 10, 2011), ClinicalTrials.govregistration number NCT00848406(registration date February 19, 2009), ClinicalTrials.govregistration number NCT00807469(registration date December 11, 2008)

Composite Higgs Boson Pair Production at the LHC

The measurement of the trilinear and quartic Higgs self-couplings is necessary for the reconstruction of the Higgs potential. This way the Higgs mechanism as the origin of electroweak symmetry breaking can be tested. The couplings are accessible in multi-Higgs production processes at the LHC. In this paper we investigate the prospects of measuring the trilinear Higgs coupling in composite Higgs models. In these models, the Higgs boson emerges as a pseudo-Goldstone boson of a strongly interacting sector, and the Higgs potential is generated by loops of the Standard Model (SM) gauge bosons and fermions. The Higgs self-couplings are modified compared to the SM and controlled by the compositeness parameter $\xi$ in addition to the Higgs boson mass. We construct areas of sensitivity to the trilinear Higgs coupling in the relevant parameter space for various final states

Electrochemical noise and impedance of Au electrode/electrolyte interfaces enabling extracellular detection of glioma cell populations

Microelectrode arrays (MEA) record extracellular local field potentials of cells adhered to the electrodes. A disadvantage is the limited signal-to-noise ratio. The state-of-the-art background noise level is about 10 mu Vpp. Furthermore, in MEAs low frequency events are filtered out. Here, we quantitatively analyze Au electrode/electrolyte interfaces with impedance spectroscopy and noise measurements. The equivalent circuit is the charge transfer resistance in parallel with a constant phase element that describes the double layer capacitance, in series with a spreading resistance. This equivalent circuit leads to a Maxwell-Wagner relaxation frequency, the value of which is determined as a function of electrode area and molarity of an aqueous KCl electrolyte solution. The electrochemical voltage and current noise is measured as a function of electrode area and frequency and follow unambiguously from the measured impedance. By using large area electrodes the noise floor can be as low as 0.3 mu Vpp. The resulting high sensitivity is demonstrated by the extracellular detection of C6 glioma cell populations. Their minute electrical activity can be clearly detected at a frequency below about 10 Hz, which shows that the methodology can be used to monitor slow cooperative biological signals in cell populations

The Social Higgs

Using published Higgs search data we investigate whether any evidence supports the possibility that the Higgs may be mixed with other neutral scalars. We combine the positive evidence for the Higgs at 125.5 GeV with search constraints at other masses to explore the viability of two simple models. The first Higgs 'friend' model is simply a neutral scalar mixed with the Higgs. In the second Higgs 'accomplice' model the new scalar has an enhanced coupling to photons due to couplings to additional charged fields. We find that the latter scenario allows improvement in fitting the data by accommodating enhanced diphoton rates and suppression in other channels for a Higgs mass of 125.5 GeV. Small excesses at other masses allow the additional scalar to further improve the fit to the data, particularly if it has mass in the vicinity of 210 GeV. Due to observed event rates at 125.5 GeV and strong limits in high mass Higgs searches, mixing angles greater than pi/4 are typically disfavored at the 95% confidence level, depending on the mass of the scalar.Comment: 11 pages, 4 figures. v2 references added, Higgs data update

The predominance of Human Immunodeficiency Virus type 1 (HIV-1) circulating recombinant form 02 (CRF02_AG) in West Central Africa may be related to its replicative fitness

BACKGROUND: CRF02_AG is the predominant HIV strain circulating in West and West Central Africa. The aim of this study was to test whether this predominance is associated with a higher in vitro replicative fitness relative to parental subtype A and G viruses. Primary HIV-1 isolates (10 CRF02_AG, 5 subtype A and 5 subtype G) were obtained from a well-described Cameroonian cohort. Growth competition experiments were carried out at equal multiplicity of infection in activated T cells and monocyte-derived dendritic cells (MO-DC) in parallel. RESULTS: Dual infection/competition experiments in activated T cells clearly indicated that CRF02_AG isolates had a significant replication advantage over the subtype A and subtype G viruses. The higher fitness of CRF02_AG was evident for isolates from patients with CD4+ T cell counts >200 cells/μL (non-AIDS) or CD4+ T cell counts <200 cells/μL (AIDS), and was independent of the co-receptor tropism. In MO-DC cultures, CRF02_AG isolates showed a slightly but not significantly higher replication advantage compared to subtype A or G isolates. CONCLUSION: We observed a higher ex vivo replicative fitness of CRF02_AG isolates compared to subtype A and G viruses from the same geographic region and showed that this was independent of the co-receptor tropism and irrespective of high or low CD4+ T cell count. This advantage in replicative fitness may contribute to the dominant spread of CRF02_AG over A and G subtypes in West and West Central Africa

An expression meta-analysis of predicted microRNA targets identifies a diagnostic signature for lung cancer

<p>Abstract</p> <p>Background</p> <p>Patients diagnosed with lung adenocarcinoma (AD) and squamous cell carcinoma (SCC), two major histologic subtypes of lung cancer, currently receive similar standard treatments, but resistance to adjuvant chemotherapy is prevalent. Identification of differentially expressed genes marking AD and SCC may prove to be of diagnostic value and help unravel molecular basis of their histogenesis and biologies, and deliver more effective and specific systemic therapy.</p> <p>Methods</p> <p>MiRNA target genes were predicted by union of miRanda, TargetScan, and PicTar, followed by screening for matched gene symbols in NCBI human sequences and Gene Ontology (GO) terms using the PANTHER database that was also used for analyzing the significance of biological processes and pathways within each ontology term. Microarray data were extracted from Gene Expression Omnibus repository, and tumor subtype prediction by gene expression used Prediction Analysis of Microarrays.</p> <p>Results</p> <p>Computationally predicted target genes of three microRNAs, miR-34b/34c/449, that were detected in human lung, testis, and fallopian tubes but not in other normal tissues, were filtered by representation of GO terms and their ability to classify lung cancer subtypes, followed by a meta-analysis of microarray data to classify AD and SCC. Expression of a minimal set of 17 predicted miR-34b/34c/449 target genes derived from the developmental process GO category was identified from a training set to classify 41 AD and 17 SCC, and correctly predicted in average 87% of 354 AD and 82% of 282 SCC specimens from total 9 independent published datasets. The accuracy of prediction still remains comparable when classifying 103 AD and 79 SCC samples from another 4 published datasets that have only 14 to 16 of the 17 genes available for prediction (84% and 85% for AD and SCC, respectively). Expression of this signature in two published datasets of epithelial cells obtained at bronchoscopy from cigarette smokers, if combined with cytopathology of the cells, yielded 89–90% sensitivity of lung cancer detection and 87–90% negative predictive value to non-cancer patients.</p> <p>Conclusion</p> <p>This study focuses on predicted targets of three lung-enriched miRNAs, compares their expression patterns in lung cancer by their GO terms, and identifies a minimal set of genes differentially expressed in AD and SCC, followed by validating this gene signature in multiple published datasets. Expression of this gene signature in bronchial epithelial cells of cigarette smokers also has a great sensitivity to predict the patients having lung cancer if combined with cytopathology of the cells.</p

The Role of Vaccine Coverage within Social Networks in Cholera Vaccine Efficacy

Traditional vaccine trial methods have an underlying assumption that the effect of a vaccine is the same throughout the trial area. There are, however, many spatial and behavioral factors that alter the rates of contact among infectious and susceptible individuals and result in different efficacies across a population. We reanalyzed data from a field trial in Bangladesh to ascertain whether there is evidence of indirect protection from cholera vaccines when vaccination rates are high in an individual's social network.We analyzed the first year of surveillance data from a placebo-controlled trial of B subunit-killed whole-cell and killed whole-cell-only oral cholera vaccines in children and adult women in Bangladesh. We calculated whether there was an inverse trend for the relation between the level of vaccine coverage in an individual's social network and the incidence of cholera in individual vaccine recipients or placebo recipients after controlling for potential confounding variables.Using bari-level social network ties, we found incidence rates of cholera among placebo recipients were inversely related to levels of vaccine coverage (5.28 cases per 1000 in the lowest quintile vs 3.27 cases per 1000 in the highest quintile; p = 0.037 for trend). Receipt of vaccine by an individual and the level of vaccine coverage of the individual's social network were independently related to a reduced risk of cholera.Findings indicate that progressively higher levels of vaccine coverage in bari-level social networks can lead to increasing levels of indirect protection of non-vaccinated individuals and could also lead to progressively higher levels of total protection of vaccine recipients