Host Selection of the giant willow aphid (Tuberolachnus salignus)

The giant willow aphid [Tuberolachnus salignus (Gmelin)] has recently become noteworthy as a potential pest species due to the increased uptake of willow, its host-plant, for use in growing biomass for energy production. In this paper we describe host selection studies of T. salignus on short rotation coppice (SRC) willow varieties in laboratory bioassays and field experiments. In laboratory olfactometry tests, T. salignus was significantly attracted to certain SRC willow varieties, but not to others. Field trials during 2007 and 2008 showed that T. salignus infestation levels varied significantly on different SRC willow varieties and that levels are highest on the varieties to which they are most strongly attracted in the laboratory bioassays

Multi-membership gene regulation in pathway based microarray analysis

This article is available through the Brunel Open Access Publishing Fund. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. Results: We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. Conclusions: We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes.The work was sponsored by the studentship scheme of the School of Information Systems, Computing and Mathematics, Brunel Universit

High Expression Levels of Total IGF-1R and Sensitivity of NSCLC Cells In Vitro to an Anti-IGF-1R Antibody (R1507)

© 2009 Gong et al

HLA-DR Alpha 2 Mediates Negative Signalling via Binding to Tirc7 Leading to Anti-Inflammatory and Apoptotic Effects in Lymphocytes In Vitro and In Vivo

Classically, HLA-DR expressed on antigen presenting cells (APC) initiates lymphocyte activation via presentation of peptides to TCR bearing CD4+ T-Cells. Here we demonstrate that HLA-DR alpha 2 domain (sHLA-DRα2) also induces negative signals by engaging TIRC7 on lymphocytes. This interaction inhibits proliferation and induces apoptosis in CD4+ and CD8+ T-cells via activation of the intrinsic pathway. Proliferation inhibition is associated with SHP-1 recruitment by TIRC7, decreased phosphorylation of STAT4, TCR-ζ chain & ZAP70, and inhibition of IFN-γ and FasL expression. HLA-DRα2 and TIRC7 co-localize at the APC-T cell interaction site. Triggering HLA-DR - TIRC7 pathway demonstrates that sHLA-DRα2 treatment inhibits proinflammatory-inflammatory cytokine expression in APC & T cells after lipopolysaccaride (LPS) stimulation in vitro and induces apoptosis in vivo. These results suggest a novel antiproliferative role for HLA-DR mediated via TIRC7, revise the notion of an exclusive stimulatory interaction of HLA-DR with CD4+ T cells and highlights a novel physiologically relevant regulatory pathway

Allergen Uptake, Activation, and IL-23 Production by Pulmonary Myeloid DCs Drives Airway Hyperresponsiveness in Asthma-Susceptible Mice

Maladaptive, Th2-polarized inflammatory responses are integral to the pathogenesis of allergic asthma. As regulators of T cell activation, dendritic cells (DCs) are important mediators of allergic asthma, yet the precise signals which render endogenous DCs “pro-asthmatic”, and the extent to which these signals are regulated by the pulmonary environment and host genetics, remains unclear. Comparative phenotypic and functional analysis of pulmonary DC populations in mice susceptible (A/J), or resistant (C3H) to experimental asthma, revealed that susceptibility to airway hyperresponsiveness is associated with preferential myeloid DC (mDC) allergen uptake, and production of Th17-skewing cytokines (IL-6, IL-23), whereas resistance is associated with increased allergen uptake by plasmacytoid DCs. Surprisingly, adoptive transfer of syngeneic HDM-pulsed bone marrow derived mDCs (BMDCs) to the lungs of C3H mice markedly enhanced lung IL-17A production, and rendered them susceptible to allergen-driven airway hyperresponsiveness. Characterization of these BMDCs revealed levels of antigen uptake, and Th17 promoting cytokine production similar to that observed in pulmonary mDCs from susceptible A/J mice. Collectively these data demonstrate that the lung environment present in asthma-resistant mice promotes robust pDC allergen uptake, activation, and limits Th17-skewing cytokine production responsible for driving pathologic T cell responses central to the development of allergen-induced airway hyperresponsiveness

IL-13 expression by blood T cells and not eosinophils is increased in asthma compared to non-asthmatic eosinophilic bronchitis

<p>Abstract</p> <p>Background</p> <p>In asthma interleukin (IL)-13 is increased in the airway compared with non-asthmatic eosinophilic bronchitis. Whether this differential expression is specific to the airway or is more generalised is uncertain.</p> <p>Methods</p> <p>We sought to examine IL-13 expression in peripheral blood T-cells and eosinophils in asthma and non-asthmatic eosinophilic bronchitis. Peripheral blood CD3+ cell and eosinophil intracellular IL-13 expression from subjects with asthma, non-asthmatic eosinophilic bronchitis and healthy controls was assessed. The effect of priming by asthmatic serum on the release of IL-13 by peripheral blood mononuclear cells from healthy subjects was examined and the serum from these subjects was analysed for a range of chemokines and cytokines.</p> <p>Results</p> <p>The median (IQR)% intracellular IL-13 expression by CD3+ cells was increased in asthma [5.3 (2.7–9.8)%; n = 12] compared to non-asthmatic eosinophilic bronchitis [1.1 (0.5–3)%; n = 7] and healthy controls [1.7 (0.2–3%); n = 9] (p = 0.02), but was not significantly different in eosinophils across the groups. IL-13 released from healthy peripheral blood mononuclear cells (n = 10) was increased by asthmatic serum [117 (47.8–198)pg/ml] compared to control [78.5 (42.6–128)pg/ml; p = 0.02), but was not affected by non-asthmatic serum.</p> <p>Conclusion</p> <p>Our findings support the view that IL-13 expression is increased in peripheral blood-derived T cells in asthma and that asthmatic serum up-regulates IL-13 release from healthy peripheral blood mononuclear cells.</p

Exploring men's and women's experiences of depression and engagement with health professionals: more similarities than differences? A qualitative interview study

<p>Abstract</p> <p>Background</p> <p>It is argued that the ways in which women express emotional distress mean that they are more likely to be diagnosed with depression, while men's relative lack of articulacy means their depression is hidden. This may have consequences for communicating with health professionals. The purpose of this analysis was to explore how men and women with depression articulate their emotional distress, and examine whether there are gender differences or similarities in the strategies that respondents found useful when engaging with health professionals.</p> <p>Methods</p> <p>In-depth qualitative interviews with 22 women and 16 men in the UK who identified themselves as having had depression, recruited through general practitioners, psychiatrists and support groups.</p> <p>Results</p> <p>We found gender similarities and gender differences in our sample. Both men and women found it difficult to recognise and articulate mental health problems and this had consequences for their ability to communicate with health professionals. Key gender differences noted were that men tended to value skills which helped them to talk while women valued listening skills in health professionals, and that men emphasised the importance of getting practical results from talking therapies in their narratives, as opposed to other forms of therapy which they conceptualised as 'just talking'. We also found diversity among women and among men; some respondents valued a close personal relationship with health professionals, while others felt that this personal relationship was a barrier to communication and preferred 'talking to a stranger'.</p> <p>Conclusion</p> <p>Our findings suggest that there is not a straightforward relationship between gender and engagement with health professionals for people with depression. Health professionals need to be sensitive to patients who have difficulties in expressing emotional distress and critical of gender stereotypes which suggest that women invariably find it easy to express emotional distress and men invariably find it difficult. In addition it is important to recognise that, for a minority of patients, a personal relationship with health professionals can act as a barrier to the disclosure of emotional distress.</p

Classification of microarray data using gene networks

BACKGROUND: Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) and their biological significance is often difficult. Currently, the standard approach is to map a posteriori the results onto gene networks in order to elucidate the functions perturbed at the level of pathways. However, integrating a priori knowledge of the gene networks could help in the statistical analysis of gene expression data and in their biological interpretation. RESULTS: We propose a method to integrate a priori the knowledge of a gene network in the analysis of gene expression data. The approach is based on the spectral decomposition of gene expression profiles with respect to the eigenfunctions of the graph, resulting in an attenuation of the high-frequency components of the expression profiles with respect to the topology of the graph. We show how to derive unsupervised and supervised classification algorithms of expression profiles, resulting in classifiers with biological relevance. We illustrate the method with the analysis of a set of expression profiles from irradiated and non-irradiated yeast strains. CONCLUSION: Including a priori knowledge of a gene network for the analysis of gene expression data leads to good classification performance and improved interpretability of the results

A genetic algorithm-Bayesian network approach for the analysis of metabolomics and spectroscopic data: application to the rapid detection of Bacillus spores and identification of Bacillus species

Background The rapid identification of Bacillus spores and bacterial identification are paramount because of their implications in food poisoning, pathogenesis and their use as potential biowarfare agents. Many automated analytical techniques such as Curie-point pyrolysis mass spectrometry (Py-MS) have been used to identify bacterial spores giving use to large amounts of analytical data. This high number of features makes interpretation of the data extremely difficult We analysed Py-MS data from 36 different strains of aerobic endospore-forming bacteria encompassing seven different species. These bacteria were grown axenically on nutrient agar and vegetative biomass and spores were analyzed by Curie-point Py-MS. Results We develop a novel genetic algorithm-Bayesian network algorithm that accurately identifies sand selects a small subset of key relevant mass spectra (biomarkers) to be further analysed. Once identified, this subset of relevant biomarkers was then used to identify Bacillus spores successfully and to identify Bacillus species via a Bayesian network model specifically built for this reduced set of features. Conclusions This final compact Bayesian network classification model is parsimonious, computationally fast to run and its graphical visualization allows easy interpretation of the probabilistic relationships among selected biomarkers. In addition, we compare the features selected by the genetic algorithm-Bayesian network approach with the features selected by partial least squares-discriminant analysis (PLS-DA). The classification accuracy results show that the set of features selected by the GA-BN is far superior to PLS-DA