89 research outputs found

    The concentration of kynurenine in rat model of asthma.

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    Asthma is a chronic inflammatory disease that involves the immune system activation. Evidence is accumulating about the role of kynurenine pathway in the immune system regulation. The kynurenine pathway includes several metabolites of tryptophan, among others kynurenine (KYN). To study the immunological system regulation in asthma a simple and sensitive models of asthma are required. In the present study we induced rat model of asthma using ovalbumin (OVA) sensitization followed by challenge with OVA. The development of asthma has been confirmed by plasma total IgE measurement and the histological examination. The concentration of KYN has been determined in plasma, lungs and liver by high-performance liquid chromatography (HPLC). In OVA sensitized rats the concentration of total IgE was statistically significantly increased as compared to VEH sensitized control groups (437.6 +/- 97.7 kU/l vs 159.2 +/- 22.7 kU/l, respectively; p< 0.01). In asthmatic animals, the number of eosinophils, neutrophils and mast cells increased considerably, and epithelial lesion and the increase in airway epithelium goblet cells and edema of bronchial mucosa were present. We did not observe any significant changes in the concentration of KYN in plasma, lungs or liver between studied groups. In conclusion, the concentration of KYN remains unchanged in asthmatic animals as compared to control groups. Further studies using rat model of asthma are warranted to establish the role of kynurenine pathway regulation in asthma

    Effectiveness of soluble CTLA-4-Fc in the inhibition of bone marrow T-cell activation in context of indoleamine 2.3-dioxygenase (IDO) and CD4+Foxp3+ Treg induction

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    BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease with systemic inflammation finally resulting in damaged joints. One of the RA development models suggests bone marrow (BM) as a place of inflammation development further leading to disease progression. We aimed to investigate the potential of CTLA-4-Fc molecule in inducing tolerogenic milieu in BM measured as indoleamine 2,3-dioxygenase (IDO) expression, CD4 METHODS: Bone marrow mononuclear cells (BMMC) were stimulated by pro-inflammatory cytokines and CTLA-4-Fc. Next IDO expression, CD4 RESULTS: We found that CTLA-4-Fc and IFN-γ stimulation results in IDO production by BMMC. CTLA-4-Fc induced tryptophan catabolism can inhibit mitogen-induced CD4 CONCLUSION: This study sheds light on some immunosuppression aspects present or induced in BM. The potential of IDO-mediated pathways were confirmed in the periphery, what may represent the promising candidates for therapeutic strategies in RA

    Long-range angular correlations on the near and away side in p&#8211;Pb collisions at

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    Underlying Event measurements in pp collisions at s=0.9 \sqrt {s} = 0.9 and 7 TeV with the ALICE experiment at the LHC

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    Pointwise consistency of the hermite series density estimate

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    The Hermite series estimate of a density f [epsilon] Lp, p> 1, convergessin the mean square to f (x) for almost all x [epsilon] R, if N (n) --> [infinity] and N (n) / n2 --> ) as n --> [infinity], where N is the number of the Hermite functions in the estimate while n is the number of observations. Moreover, the mean square and weak consistency are equivalent. For m times differentiable densities, the mean squares convergence rate is O(n-(2m-1)/2m). Results for complete convergence are also given.density estimate nonparametric orthogonal series Hermite series

    Necessary and sufficient consistency conditions for a recursive kernel regression estimate

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    A recursive kernel estimate [summation operator]i = 1n YiK[+45 degree rule](x - Xi)hi)[+45 degree rule][summation operator]j = 1n K((x - Xj)[+45 degree rule]hj) of a regression m(x) = E{YX = x} calculated from independent observations (X1, Y1),..., (Xn, Yn) of a pair (X, Y) of random variables is examined. ForEY1 + [delta] 0, the estimate is weakly pointwise consistent for almost all ([mu]) x [set membership, variant] Rd, [mu] is the probability measure of X, if and only if[summation operator]i-1n hid I{hi > [var epsilon] } [+45 degree rule] [summation operator]j = 1n hjd --> 0 as n --> [infinity], all [var epsilon] > 0, and[summation operator]i = 1[infinity] hid = [infinity], d is the dimension of X. For EY1 + [delta] 0, the estimate is strongly pointwise consistent for almost all ([mu]) x [set membership, variant] Rd, if and only if the same conditions hold. ForEY1 + [delta] 0, weak and strong consistency are equivalent. Similar results are given for complete convergence.regression function nonparametric estimation kernel estimate recursive estimate consistency

    The Weighted Nearest Neighbor Estimate for Hammerstein System Identification

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    Hammerstein System Identification With the Nearest Neighbor Algorithm

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