Intravenous apoptotic spleen cell infusion induces a TGF-beta-dependent regulatory T-cell expansion.: Apoptosis and regulatory T cells

International audienceApoptotic leukocytes are endowed with immunomodulatory properties that can be used to enhance hematopoietic engraftment and prevent graft-versus-host disease (GvHD). This apoptotic cell-induced tolerogenic effect is mediated by host macrophages and not recipient dendritic cells or donor phagocytes present in the bone marrow graft as evidenced by selective cell depletion and trafficking experiments. Furthermore, apoptotic cell infusion is associated with TGF-beta-dependent donor CD4+CD25+ T-cell expansion. Such cells have a regulatory phenotype (CD62L(high) and intracellular CTLA-4+), express high levels of forkhead-box transcription factor p3 (Foxp3) mRNA and exert ex vivo suppressive activity through a cell-to-cell contact mechanism. In vivo CD25 depletion after apoptotic cell infusion prevents the apoptotic cell-induced beneficial effects on engraftment and GvHD occurrence. This highlights the role of regulatory T cells in the tolerogenic effect of apoptotic cell infusion. This novel association between apoptosis and regulatory T-cell expansion may also contribute to preventing deleterious autoimmune responses during normal turnover

Apoptotic cell-based therapies against transplant rejection: role of recipient’s dendritic cells

One of the ultimate goals in transplantation is to develop novel therapeutic methods for induction of donor-specific tolerance to reduce the side effects caused by the generalized immunosuppression associated to the currently used pharmacologic regimens. Interaction or phagocytosis of cells in early apoptosis exerts potent anti-inflammatory and immunosuppressive effects on antigen (Ag)-presenting cells (APC) like dendritic cells (DC) and macrophages. This observation led to the idea that apoptotic cell-based therapies could be employed to deliver donor-Ag in combination with regulatory signals to recipient’s APC as therapeutic approach to restrain the anti-donor response. This review describes the multiple mechanisms by which apoptotic cells down-modulate the immuno-stimulatory and pro-inflammatory functions of DC and macrophages, and the role of the interaction between apoptotic cells and APC in self-tolerance and in apoptotic cell-based therapies to prevent/treat allograft rejection and graft-versus-host disease in murine experimental systems and in humans. It also explores the role that in vivo-generated apoptotic cells could have in the beneficial effects of extracorporeal photopheresis, donor-specific transfusion, and tolerogenic DC-based therapies in transplantation

Towards Comprehensive Foundations of Computational Intelligence

Abstract. Although computational intelligence (CI) covers a vast variety of different methods it still lacks an integrative theory. Several proposals for CI foundations are discussed: computing and cognition as compression, meta-learning as search in the space of data models, (dis)similarity based methods providing a framework for such meta-learning, and a more general approach based on chains of transformations. Many useful transformations that extract information from features are discussed. Heterogeneous adaptive systems are presented as particular example of transformation-based systems, and the goal of learning is redefined to facilitate creation of simpler data models. The need to understand data structures leads to techniques for logical and prototype-based rule extraction, and to generation of multiple alternative models, while the need to increase predictive power of adaptive models leads to committees of competent models. Learning from partial observations is a natural extension towards reasoning based on perceptions, and an approach to intuitive solving of such problems is presented. Throughout the paper neurocognitive inspirations are frequently used and are especially important in modeling of the higher cognitive functions. Promising directions such as liquid and laminar computing are identified and many open problems presented.

Hybrid neural networks: An evolutionary approach with local search

Considering computational algorithms available in the literature, associated with supervised learning in feedforward neural networks, a wide range of distinct approaches can be identified. While the adjustment of the connection weights represents an omnipresent stage, the algorithms differ on three basic aspects: the technique chosen to determine the dimension of the multilayer neural network, the procedure adopted to specify the activation functions, and the kind of composition used to produce the output. Advanced learning algorithms should be developed to simultaneously treat all these aspects during learning, and an evolutionary learning algorithm with local search is proposed here. The essence of this approach is a synergy between genetic algorithms and conjugate gradient optimization, operating on a hybrid neural network architecture. As a consequence, the final neural network is automatically generated, and is characterized to be dedicated and computationally parsimonious.91577