3,223 research outputs found

    THE ROLE OF ADAPTOR PROTEIN GADS IN CD8+ T CELL-MEDIATED IMMUNITY

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    CD8+ T cells are the branch of the adaptive immune system responsible for recognizing and killing tumor cells or cells infected with intracellular pathogens, such as Listeria monocytogenes (LM). However, when CD8+ T cells target our own tissues, they can cause autoimmune diseases, such as type I diabetes, rheumatoid arthritis. For CD8+ T cells to fulfill these functions, the T cell receptors (TCRs) on CD8+ T cells must recognize pathogens or antigens presented on the surface of target cells. TCR ligation triggers multiple signaling pathways that lead to the activation and proliferation of CD8+ T cells. The goal of our research is to define the TCR-proximal signaling events that regulate CD8+ T cell-mediated immunity. To accomplish this goal, we are focusing on an adaptor protein Gads, which is critical for optimal TCR-mediated calcium mobilization. We reported the first analysis of the function of Gads in peripheral naĂ¯ve CD8+ T cells. To examine the function of Gads in CD8+ T cell mediated immune responses, we crossed Gads-/- mice with mice expressing an MHC class I-restricted transgenic TCR recognizing ovalbumin (OVA). The transgenic mice are called ovalbumin-specific T cell receptor-major histocompatibility complex class I restricted (OT-I) mice. We investigated the effect of Gads on the proliferation of CD8+ T cells following stimulation with peptide antigen in vivo and in vitro. We stimulated splenocytes from Gads+/+ OT-I and Gads-/- OT-I mice with the peptide agonist. The experiments revealed that Gads is required for optimal proliferation of CD8+ T cells. The regulation of Gads is most evident at the early time points of proliferation. Then we demonstrated that Gads-/- CD8+ T cells have impaired TCR-mediated exit from G0 phase of the cell cycle. In addition, Gads-/- CD8+ T cells have delayed expression of c-myc and the activation markers CD69 and CD25, upon stimulation with peptide antigen. Next, we investigated how Gads affects CD8+ T cell-mediated immunity in the context of infection with LM. We adoptively transferred naĂ¯ve CD8+ T cells from Gads+/+ OT-I mice and/or Gads-/- OT-I mice into congenic wild-type hosts. Then the recipient mice were infected with recombinant LM expressing ovalbumin (rLM-OVA). The CD8+ T cells from OT-I mice recognize and respond to the ovalbumin provided by this strain of LM. By using this system, we investigated how Gads regulates the activation of antigen-specific CD8+ T cells as well as the expansion and memory phases of CD8+ T cell-mediated immune responses following infection with rLM-OVA. We also examined the recall response of CD8+ T cells after the secondary encounter with the same pathogen. Our data demonstrated that Gads regulates the expression of activation markers CD69 and CD25 of antigen-specific CD8+ T cells but Gads is not required for the onset of accumulation of antigen-specific CD8+ T cells following infection. However, Gads is critical to sustain the expansion of CD8+ T cell-mediated immune response following infection. Although the differentiation of naĂ¯ve CD8+ T cells into memory cells is independent of Gads, Gads is required for an optimal recall response. Our data indicating that Gads regulates the initiation of proliferation of CD8+ T cells upon TCR ligation by peptide antigen seemed to contradict with our in vivo infection data showing that Gads is not required for the initiation of expansion of CD8+ T cell population. In order to explain the "discrepancy", we hypothesized that the homotypic interactions among CD8+ T cells compensate for Gads deficiency at the initial stage of accumulation of antigen-specific CD8+ T cells upon infection. Our data indicated that the need for Gads in cell cycle progression of CD8+ T cells when total splenocytes were stimulated could be overcome by stimulating purified CD8+ T cells. These data suggested that the homotypic interactions among CD8+ T cells facilitate the TCR signaling so as to compensate for Gads deficiency in promoting cell cycle entry and proliferation. To conclude, the role of Gads in TCR-mediated activation and proliferation of CD8+ T cells is dependent on the interactions of CD8+ T cells and their partners. Interestingly, if CD8+ T cells interact with non-CD8+ T cells, Gads regulates the kinetics of cell cycle entry; however, if CD8+ T cells interact with other CD8+ T cells, Gads is dispensable for cell cycle entry of CD8+ T cells. Overall, these studies will help us better understand how TCR-proximal signaling regulates the activation of CD8+ T cells

    Online Updating of Statistical Inference in the Big Data Setting

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    We present statistical methods for big data arising from online analytical processing, where large amounts of data arrive in streams and require fast analysis without storage/access to the historical data. In particular, we develop iterative estimating algorithms and statistical inferences for linear models and estimating equations that update as new data arrive. These algorithms are computationally efficient, minimally storage-intensive, and allow for possible rank deficiencies in the subset design matrices due to rare-event covariates. Within the linear model setting, the proposed online-updating framework leads to predictive residual tests that can be used to assess the goodness-of-fit of the hypothesized model. We also propose a new online-updating estimator under the estimating equation setting. Theoretical properties of the goodness-of-fit tests and proposed estimators are examined in detail. In simulation studies and real data applications, our estimator compares favorably with competing approaches under the estimating equation setting.Comment: Submitted to Technometric

    A intelligent particle swarm optimization for short-term traffic flow forecasting using on-road sensor systems

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    On-road sensor systems installed on freeways are used to capture traffic flow data for short-term traffic flow predictors for traffic management, in order to reduce traffic congestion and improve vehicular mobility. This paper intends to tackle the impractical time-invariant assumptions which underlie the methods currently used to develop short-term traffic flow predictors: i) the characteristics of current data captured by on-road sensors are assumed to be time-invariant with respect to those of the historical data, which is used to developed short-term traffic flow predictors; and ii) the configuration of the on-road sensor systems is assumed to be time-invariant. In fact, both assumptions are impractical in the real world, as the current traffic flow characteristics can be very different from the historical ones, and also the on-road sensor systems are time-varying in nature due to damaged sensors or component wear. Therefore, misleading forecasting results are likely to be produced when short-term traffic flow predictors are designed using these two time-invariant assumptions. To tackle these time-invariant assumptions, an intelligent particle swarm optimization algorithm, namely IPSO, is proposed to develop short-term traffic flow predictors by integrating the mechanisms of particle swarm optimization, neural network and fuzzy inference system, in order to adapt to the time-varying traffic flow characteristics and the time-varying configurations of the on-road sensor systems. The proposed IPSO was applied to forecast traffic flow conditions on a section of freeway in Western Australia, whose traffic flow information can be captured on-line by the on-road sensor system. These results clearly demonstrate the effectiveness of using the proposed IPSO for real-time traffic flow forecasting based on traffic flow data captured by on-road sensor systems
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