139 research outputs found

    Why We Follow Narcissistic Leaders

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    A recent study aimed to understand narcissistic leaders and who is most likely to follow them. The results revealed a few patterns. If you are someone who is always looking out for others, empathizes with others, and seeks harmony and consensus in your team (known as agreeable followers), you are more likely to be susceptible to following a narcissistic leader. If you are someone who gets anxious and worried easily or likes to get started on work projects early on to prevent anxiety as a deadline draws closer (known as neurotic followers), you probably prefer engaging with narcissistic leaders

    Rhesus macaque MHC class I molecules show differential subcellular localizations

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    The MHC class I gene family of rhesus macaques is characterised by considerable gene duplications. While a HLA-C-orthologous gene is absent, the Mamu-A and in particular the Mamu-B genes have expanded, giving rise to plastic haplotypes with differential gene content. Although some of the rhesus macaque MHC class I genes are known to be associated with susceptibility/resistance to infectious diseases, the functional significance of duplicated Mamu-A and Mamu-B genes and the expression pattern of their encoded proteins are largely unknown. Here, we present data of the subcellular localization of AcGFP-tagged Mamu-A and Mamu-B molecules. We found strong cell surface and low intracellular expression for Mamu-A1, Mamu-A2 and Mamu-A3-encoded molecules as well as for Mamu-B*01704, Mamu-B*02101, Mamu-B*04801, Mamu-B*06002 and Mamu-B*13401. In contrast, weak cell surface and strong intracellular expression was seen for Mamu-A4*1403, Mamu-B*01202, Mamu-B*02804, Mamu-B*03002, Mamu-B*05704, Mamu-I*010201 and Mamu-I*0121. The different expression patterns were assigned to the antigen-binding α1 and α2 domains, suggesting failure of peptide binding is responsible for retaining ‘intracellular’ Mamu class I molecules in the endoplasmic reticulum. These findings indicate a diverse functional role of the duplicated rhesus macaque MHC class I genes

    Human NK Cells Differ More in Their KIR2DL1-Dependent Thresholds for HLA-Cw6-Mediated Inhibition than in Their Maximal Killing Capacity

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    In this study we have addressed the question of how activation and inhibition of human NK cells is regulated by the expression level of MHC class I protein on target cells. Using target cell transfectants sorted to stably express different levels of the MHC class I protein HLA-Cw6, we show that induction of degranulation and that of IFN-γ secretion are not correlated. In contrast, the inhibition of these two processes by MHC class-I occurs at the same level of class I MHC protein. Primary human NK cell clones were found to differ in the amount of target MHC class I protein required for their inhibition, rather than in their maximum killing capacity. Importantly, we show that KIR2DL1 expression determines the thresholds (in terms of MHC I protein levels) required for NK cell inhibition, while the expression of other receptors such as LIR1 is less important. Furthermore, using mathematical models to explore the dynamics of target cell killing, we found that the observed delay in target cell killing is exhibited by a model in which NK cells require some activation or priming, such that each cell can lyse a target cell only after being activated by a first encounter with the same or a different target cell, but not by models which lack this feature

    Transcription factor Spi-B binds unique sequences present in the tandem repeat promoter/enhancer of JC virus and supports viral activity

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    Progressive multifocal leukoencephalopathy (PML) is an often fatal demyelinating disease caused by lytic infection of oligodendrocytes with JC virus (JCV). The development of PML in non-immunosuppressed individuals is a growing concern with reports of mortality in patients treated with mAb therapies. JCV can persist in the kidneys, lymphoid tissue and bone marrow. JCV gene expression is restricted by non-coding viral regulatory region sequence variation and cellular transcription factors. Because JCV latency has been associated with cells undergoing haematopoietic development, transcription factors previously reported as lymphoid specific may regulate JCV gene expression. This study demonstrates that one such transcription factor, Spi-B, binds to sequences present in the JCV promoter/enhancer and may affect early virus gene expression in cells obtained from human brain tissue. We identified four potential Spi-B-binding sites present in the promoter/enhancer elements of JCV sequences from PML variants and the non-pathogenic archetype. Spi-B sites present in the promoter/enhancers of PML variants alone bound protein expressed in JCV susceptible brain and lymphoid-derived cell lines by electromobility shift assays. Expression of exogenous Spi-B in semi- and non-permissive cells increased early viral gene expression. Strikingly, mutation of the Spi-B core in a binding site unique to the Mad-4 variant was sufficient to abrogate viral activity in progenitor-derived astrocytes. These results suggest that Spi-B could regulate JCV gene expression in susceptible cells, and may play an important role in JCV activity in the immune and nervous systems

    Proteomic Analysis of S-Acylated Proteins in Human B Cells Reveals Palmitoylation of the Immune Regulators CD20 and CD23

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    S-palmitoylation is a reversible post-translational modification important for controlling the membrane targeting and function of numerous membrane proteins with diverse roles in signalling, scaffolding, and trafficking. We sought to identify novel palmitoylated proteins in B lymphocytes using acyl-biotin exchange chemistry, coupled with differential analysis by liquid-chromatography tandem mass spectrometry. In total, we identified 57 novel palmitoylated protein candidates from human EBV-transformed lymphoid cells. Two of them, namely CD20 and CD23 (low affinity immunoglobulin epsilon Fc receptor), are immune regulators that are effective/potential therapeutic targets for haematological malignancies, autoimmune diseases and allergic disorders. Palmitoylation of CD20 and CD23 was confirmed by heterologous expression of alanine mutants coupled with bioorthogonal metabolic labeling. This study demonstrates a new subset of palmitoylated proteins in B cells, illustrating the ubiquitous role of protein palmitoylation in immune regulation

    Blimp1 Activation by AP-1 in Human Lung Cancer Cells Promotes a Migratory Phenotype and Is Inhibited by the Lysyl Oxidase Propeptide

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    B lymphocyte-induced maturation protein 1 (Blimp1) is a master regulator of B cell differentiation, and controls migration of primordial germ cells. Recently we observed aberrant Blimp1 expression in breast cancer cells resulting from an NF-κB RelB to Ras signaling pathway. In order to address the question of whether the unexpected expression of Blimp1 is seen in other epithelial-derived tumors, we selected lung cancers as they are frequently driven by Ras signaling. Blimp1 was detected in all five lung cancer cell lines examined and shown to promote lung cancer cell migration and invasion. Interrogation of microarray datasets demonstrated elevated BLIMP1 RNA expression in lung adenocarcinoma, pancreatic ductal carcinomas, head and neck tumors as well as in glioblastomas. Involvement of Ras and its downstream kinase c-Raf was confirmed using mutant and siRNA strategies. We next addressed the issue of mechanism of Blimp1 activation in lung cancer. Using knockdown and ectopic expression, the role of the Activator Protein (AP)-1 family of transcription factors was demonstrated. Further, chromatin immunoprecipitation assays confirmed binding to identified AP-1 elements in the BLIMP1 promoter of ectopically expressed c-Jun and of endogenous AP-1 subunits following serum stimulation. The propeptide domain of lysyl oxidase (LOX-PP) was identified as a tumor suppressor, with ability to reduce Ras signaling in lung cancer cells. LOX-PP reduced expression of Blimp1 by binding to c-Raf and inhibiting activation of AP-1, thereby attenuating the migratory phenotype of lung cancer cells. Thus, Blimp1 is a mediator of Ras/Raf/AP-1 signaling that promotes cell migration, and is repressed by LOX-PP in lung cancer

    Expression and prognostic relevance of activated extracellular-regulated kinases (ERK1/2) in breast cancer

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    Extracellular-regulated kinases (ERK1, ERK2) play important roles in the malignant behaviour of breast cancer cells in vitro. In our present study, 148 clinical breast cancer samples (120 cases with follow-up data) were studied for the expression of ERK1, ERK2 and their phosphorylated forms p-ERK1 and p-ERK2 by immunoblotting, and p-ERK1/2 expression in corresponding paraffin sections was analysed by immunohistochemistry. The results were correlated with established clinical and histological prognostic parameters, follow-up data and expression of seven cell-cycle regulatory proteins as well as MMP1, MMP9, PAI-1 and AP-1 transcription factors, which had been analysed before. High p-ERK1 expression as determined by immunoblots correlated significantly with a low frequency of recurrences and infrequent fatal outcome (P=0.007 and 0.008) and was an independent indicator of long relapse-free and overall survival in multivariate analysis. By immunohistochemistry, strong p-ERK staining in tumour cells was associated with early stages (P=0.020), negative nodal status (P=0.003) and long recurrence-free survival (P=0.017). In contrast, expression of the unphosphorylated kinases ERK1 and ERK2 was not associated with clinical and histological prognostic parameters, except a positive correlation with oestrogen receptor status. Comparison with the expression of formerly analysed cell-cycle- and invasion-associated proteins corroborates our conclusion that activation of ERK1 and ERK2 is not associated with enhanced proliferation and invasion of mammary carcinomas

    ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

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    <p>Abstract</p> <p>Background</p> <p>Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability.</p> <p>Methods</p> <p>Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications <it>in silico </it>using simulated datasets.</p> <p>Results</p> <p>We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage.</p> <p>Conclusions</p> <p>We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and modelling gene-gene interactions that influence a complex human trait.</p
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