Regulatory B Cell (B10 Cell) Expansion during Listeria Infection Governs Innate and Cellular Immune Responses in Mice

Pathogens use numerous methods to subvert host immune responses, including the modulation of host IL-10 production by diverse cell types. However, the B cell sources of IL-10 and their overall influence on innate and cellular immune responses have not been well characterized during infections. Using Listeria as a model pathogen, infection drove the acute expansion of a small subset of regulatory B cells (B10 cells) that potently suppress inflammation and autoimmunity through the production of IL-10. Unexpectedly, spleen bacteria loads were 92–97% lower in B10 cell-deficient CD19−/− mice, in mice depleted of mature B cells, and in mice treated with CD22 mAb to preferentially deplete B10 cells before infection. By contrast, the adoptive transfer of wild type B10 cells reduced bacterial clearance by 38-fold in CD19−/− mice through IL-10-dependent pathways. B10 cell depletion using CD22 mAb significantly enhanced macrophage phagocytosis of Listeria and their production of IFN-γ, TNF-α, and nitric oxide ex vivo. Accelerated bacteria clearance following B10 cell depletion significantly reduced Ag-specific CD4+ T cell proliferation and cytokine production, but did not alter CD8+ T cell responses. B10 cell regulatory function during innate immune responses was nonetheless dependent on cognate interactions with CD4+ T cells since B10 cells deficient in IL-10, MHC-II or IL-21 receptor expression did not influence Listeria clearance. Thus, Listeria manipulates immune responses through a strategy of immune evasion that involves the preferential expansion of endogenous B10 cells that regulate the magnitude and duration of both innate and cellular immune responses

Biomarkers detected in cord blood predict vaccine responses in young infants

Introduction Factors influencing vaccine immune priming in the first year of life involve both innate and adaptive immunity but there are gaps in understanding how these factors sustain vaccine antibody levels in healthy infants. The hypothesis was that bioprofiles associated with B cell survival best predict sustained vaccine IgG levels at one year. Methods Longitudinal study of plasma bioprofiles in 82 term, healthy infants, who received standard recommended immunizations in the United States, with changes in 15 plasma biomarker concentrations and B cell subsets associated with germinal center development monitored at birth, soon after completion of the initial vaccine series at 6 months, and prior to the 12-month vaccinations. Post vaccination antibody IgG levels to Bordetella pertussis, tetanus toxoid, and conjugated Haemophilus influenzae type B (HiB) were outcome measures. Results Using a least absolute shrinkage and selection operator (lasso) regression model, cord blood (CB) plasma IL-2, IL-17A, IL-31, and soluble CD14 (sCD14) were positively associated with pertussis IgG levels at 12 months, while CB plasma concentrations of APRIL and IL-33 were negatively associated. In contrast, CB concentrations of sCD14 and APRIL were positively associated with sustained tetanus IgG levels. A separate cross-sectional analysis of 18 mother/newborn pairs indicated that CB biomarkers were not due to transplacental transfer, but rather due to immune activation at the fetal/maternal interface. Elevated percentages of cord blood switched memory B cells were positively associated with 12-month HiB IgG levels. BAFF concentrations at 6 and 12 months were positively associated with pertussis and HiB IgG levels respectively. Discussion Sustained B cell immunity is highly influenced by early life immune dynamics beginning prior to birth. The findings provide important insights into how germinal center development shapes vaccine responses in healthy infants and provide a foundation for studies of conditions that impair infant immune development

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Search for supersymmetry in events with one lepton and multiple jets in proton-proton collisions at root s=13 TeV

Peer reviewe

Search for anomalous couplings in boosted WW/WZ -> l nu q(q)over-bar production in proton-proton collisions at root s=8TeV

Peer reviewe