72 research outputs found

    Smooth-muscle-derived WNT5A augments allergen-induced airway remodelling and Th2 type inflammation

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    Asthma is a heterogeneous disease characterized by chronic inflammation and structural changes in the airways. The airway smooth muscle (ASM) is responsible for airway narrowing and an important source of inflammatory mediators. We and others have previously shown that WNT5A mRNA and protein expression is higher in the ASM of asthmatics compared to healthy controls. Here, we aimed to characterize the functional role of (smooth muscle-derived) WNT5A in asthma. We generated a tet-ON smooth-muscle-specific WNT5A transgenic mouse model, enabling in vivo characterization of smooth-muscle-derived WNT5A in response to ovalbumin. Smooth muscle specific WNT5A overexpression showed a clear trend towards enhanced actin (α-SMA) expression in the ASM in ovalbumin challenged animals, but had no effect on collagen content. WNT5A overexpression in ASM also significantly enhanced the production of the Th2-cytokines IL4 and IL5 in lung tissue after ovalbumin exposure. In line with this, WNT5A increased mucus production, and enhanced eosinophilic infiltration and serum IgE production in ovalbumin-treated animals. In addition, CD4+ T cells of asthma patients and healthy controls were stimulated with WNT5A and changes in gene transcription assessed by RNA-seq. WNT5A promoted expression of 234 genes in human CD4+ T cells, among which the Th2 cytokine IL31 was among the top 5 upregulated genes. IL31 was also upregulated in response to smooth muscle-specific WNT5A overexpression in the mouse. In conclusion, smooth-muscle derived WNT5A augments Th2 type inflammation and remodelling. Our findings imply a pro-inflammatory role for smooth muscle-derived WNT5A in asthma, resulting in increased airway wall inflammation and remodelling

    Smooth-muscle-derived WNT5A augments allergen-induced airway remodelling and Th2 type inflammation

    Get PDF
    Asthma is a heterogeneous disease characterized by chronic inflammation and structural changes in the airways. The airway smooth muscle (ASM) is responsible for airway narrowing and an important source of inflammatory mediators. We and others have previously shown that WNT5A mRNA and protein expression is higher in the ASM of asthmatics compared to healthy controls. Here, we aimed to characterize the functional role of (smooth muscle-derived) WNT5A in asthma. We generated a tet-ON smooth-muscle-specific WNT5A transgenic mouse model, enabling in vivo characterization of smooth-muscle-derived WNT5A in response to ovalbumin. Smooth muscle specific WNT5A overexpression showed a clear trend towards enhanced actin (α-SMA) expression in the ASM in ovalbumin challenged animals, but had no effect on collagen content. WNT5A overexpression in ASM also significantly enhanced the production of the Th2-cytokines IL4 and IL5 in lung tissue after ovalbumin exposure. In line with this, WNT5A increased mucus production, and enhanced eosinophilic infiltration and serum IgE production in ovalbumin-treated animals. In addition, CD4+ T cells of asthma patients and healthy controls were stimulated with WNT5A and changes in gene transcription assessed by RNA-seq. WNT5A promoted expression of 234 genes in human CD4+ T cells, among which the Th2 cytokine IL31 was among the top 5 upregulated genes. IL31 was also upregulated in response to smooth muscle-specific WNT5A overexpression in the mouse. In conclusion, smooth-muscle derived WNT5A augments Th2 type inflammation and remodelling. Our findings imply a pro-inflammatory role for smooth muscle-derived WNT5A in asthma, resulting in increased airway wall inflammation and remodelling

    Anti-Inflammatory Role of the cAMP Effectors Epac and PKA: Implications in Chronic Obstructive Pulmonary Disease

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    Cigarette smoke-induced release of pro-inflammatory cytokines including interleukin-8 (IL-8) from inflammatory as well as structural cells in the airways, including airway smooth muscle (ASM) cells, may contribute to the development of chronic obstructive pulmonary disease (COPD). Despite the wide use of pharmacological treatment aimed at increasing intracellular levels of the endogenous suppressor cyclic AMP (cAMP), little is known about its exact mechanism of action. We report here that next to the β2-agonist fenoterol, direct and specific activation of either exchange protein directly activated by cAMP (Epac) or protein kinase A (PKA) reduced cigarette smoke extract (CSE)-induced IL-8 mRNA expression and protein release by human ASM cells. CSE-induced IκBα-degradation and p65 nuclear translocation, processes that were primarily reversed by Epac activation. Further, CSE increased extracellular signal-regulated kinase (ERK) phosphorylation, which was selectively reduced by PKA activation. CSE decreased Epac1 expression, but did not affect Epac2 and PKA expression. Importantly, Epac1 expression was also reduced in lung tissue from COPD patients. In conclusion, Epac and PKA decrease CSE-induced IL-8 release by human ASM cells via inhibition of NF-κB and ERK, respectively, pointing at these cAMP effectors as potential targets for anti-inflammatory therapy in COPD. However, cigarette smoke exposure may reduce anti-inflammatory effects of cAMP elevating agents via down-regulation of Epac1

    Pharmacological treatment options for mast cell activation disease

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    Alternating linear scheme in a bayesian framework for low-rank tensor approximation

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    Multiway data often naturally occurs in a tensorial format which can be approximately represented by a low-rank tensor decomposition. This is useful because complexity can be significantly reduced and the treatment of large-scale data sets can be facilitated. In this paper, we find a low-rank representation for a given tensor by solving a Bayesian inference problem. This is achieved by dividing the overall inference problem into subproblems where we sequentially infer the posterior distribution of one tensor decomposition component at a time. This leads to a probabilistic interpretation of the well-known iterative algorithm alternating linear scheme (ALS). In this way, the consideration of measurement noise is enabled, as well as the incorporation of application-specific prior knowledge and the uncertainty quantification of the low-rank tensor estimate. To compute the low-rank tensor estimate from the posterior distributions of the tensor decomposition components, we present an algorithm that performs the unscented transform in tensor train format.Team Manon KokTeam Kim Batselie
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