919 resultados para IMMUNE SYSTEM
Resumo:
ABSTRACT Artificial immune system can be used to generate schedules in changing environments and it has been proven to be more robust than schedules developed using a genetic algorithm. Good schedules can be produced especially when the number of the antigens is increased. However, an increase in the range of the antigens had somehow affected the fitness of the immune system. In this research, we are trying to improve the result of the system by rescheduling the same problem using the same method while at the same time maintaining the robustness of the schedules.
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Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems.
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It has previously been shown that a recommender based on immune system idiotypic principles can outperform one based on correlation alone. This paper reports the results of work in progress, where we undertake some investigations into the nature of this beneficial effect. The initial findings are that the immune system recommender tends to produce different neighbourhoods, and that the superior performance of this recommender is due partly to the different neighbourhoods, and partly to the way that the idiotypic effect is used to weight each neighbour's recommendations.
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Abstract. Dendritic cells are antigen presenting cells that provide a vital link between the innate and adaptive immune system. Research into this family of cells has revealed that they perform the role of coordinating T-cell based immune responses, both reactive and for generating tolerance. We have derived an algorithm based on the functionality of these cells, and have used the signals and differentiation pathways to build a control mechanism for an artificial immune system. We present our algorithmic details in addition to some preliminary results, where the algorithm was applied for the purpose of anomaly detection. We hope that this algorithm will eventually become the key component within a large, distributed immune system, based on sound immunological concepts.
Resumo:
Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems. Notes: Uwe Aickelin, Department of Computing, University of Bradford, Bradford, BD7 1DP
On The Effects of Idiotypic Interactions for Recommendation Communities in Artificial Immune Systems
Resumo:
It has previously been shown that a recommender based on immune system idiotypic principles can outperform one based on correlation alone. This paper reports the results of work in progress, where we undertake some investigations into the nature of this beneficial effect. The initial findings are that the immune system recommender tends to produce different neighbourhoods, and that the superior performance of this recommender is due partly to the different neighbourhoods, and partly to the way that the idiotypic effect is used to weight each neighbour’s recommendations.
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Jerne's idiotypic network theory postulates that the immune response involves inter-antibody stimulation and suppression as well as matching to antigens. The theory has proved the most popular Artificial Immune System (AIS) model for incorporation into behavior-based robotics but guidelines for implementing idiotypic selection are scarce. Furthermore, the direct effects of employing the technique have not been demonstrated in the form of a comparison with non-idiotypic systems. This paper aims to address these issues. A method for integrating an idiotypic AIS network with a Reinforcement Learning based control system (RL) is described and the mechanisms underlying antibody stimulation and suppression are explained in detail. Some hypotheses that account for the network advantage are put forward and tested using three systems with increasing idiotypic complexity. The basic RL, a simplified hybrid AIS-RL that implements idiotypic selection independently of derived concentration levels and a full hybrid AIS-RL scheme are examined. The test bed takes the form of a simulated Pioneer robot that is required to navigate through maze worlds detecting and tracking door markers.
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The transition period is associated with the peak incidence of production problems, metabolic disorders and infectious diseases in dairy cows (Drackley, 1999). During this time the cow’s immune system seems to be weakened; it is apparent that metabolic challenges associated with the onset of lactation are factors capable of affecting immune function. However, the reasons for this state are not entirely clear (Goff, 2006). The negative energy balance associated with parturition leads to extensive mobilization of fatty acids stored in adipose tissue, thus, causing marked elevations in blood non-esterified fatty acids (NEFA) and B-hydroxybutyrate (BHBA) concentrations (Drackley et al., 2001). Prepartal level of dietary energy can potentially affect adipose tissue deposition and, thus, the amount of NEFA released into blood and available for metabolism in liver (Drackley et al., 2005). The current feeding practices for pregnant non-lactating cows has been called into question because increasing amounts of moderate-to-high energy diets (i.e. those more similar to lactation diets in the content of energy) during the last 3 wk postpartum have largely failed to overcome peripartal health problems, excessive body condition loss after calving, or declining fertility (Beever, 2006). Current prepartal feeding practices can lead to elevated intakes of energy, which can increase fat deposition in the viscera and upon parturition lead to compromised liver metabolism (Beever, 2006, Drackley et al., 2005). Our general hypothesis was that overfeeding dietary energy during the dry period, accompanied by the metabolic challenges associated with the onset of lactation would render the cow’s immune function less responsive early postpartum. The chapters in this dissertation evaluated neutrophil function, metabolic and inflammation indices and gene expression affected by the plane of dietary energy prepartum and an early post-partum inflammatory challenge in dairy cows. The diet effect in this experiment was transcendental during the transition period and potentially during the entire lactation. Changes in energy balance were observed and provided a good model to study the challenges associated with the onset of lactation. Overall the LPS model provided a consistent response representing an inflammation incident; however the changes in metabolic indices were sudden and hard to detect in most of the cases during the days following the challenge. In general overfeeding dietary energy during the dry period resulted in a less responsive immune function during the early postpartum. In other words, controlling the dietary energy prepartum has more benefits for the dairy cow during transition.
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Type 1diabetes (T1D) is an autoimmune disease, which is influenced by a variety of environmental factors including diet and microbes. These factors affect the homeostasis and the immune system of the gut. This thesis explored the altered regulation of the immune system and the development of diabetes in non-obese diabetic (NOD) mice. Inflammation in the entire intestine of diabetes-prone NOD mice was studied using a novel ex-vivo imaging system of reactive oxygen and nitrogen species (RONS), in relation to two feeding regimens. In parallel, gut barrier integrity and intestinal T-cell activation were assessed. Extra-intestinal manifestations of inflammation and decreased barrier integrity were sought for by studying peritoneal leukocytes. In addition, the role of pectin and xylan as dietary factors involved in diabetes development in NOD mice was explored. NOD mice showed expression of RONS especially in the distal small intestine, which coincided with T-cell activation and increased permeability to macromolecules. The introduction of a casein hydrolysate (hydrolysed milk protein) diet reduced these phenomena, altered the gut microbiota and reduced the incidence of T1D. Extra-intestinally, macrophages appeared in large numbers in the peritoneum of NOD mice after weaning. Peritoneal macrophages (PM) expressed high levels of interleukin-1 receptor associated kinase M (IRAK-M), which was indicative of exposure to ligands of toll-like receptor 4 (TLR-4) such as bacterial lipopolysaccharide (LPS). Intraperitoneal LPS injections activated T cells in the pancreatic lymph nodes (PaLN) and thus, therefore potentially could activate islet-specific T cells. Addition of pectin and xylan to an otherwise diabetes-retarding semisynthetic diet affected microbial colonization of newly-weaned NOD mice, disturbed gut homeostasis and promoted diabetes development. These results help us to understand how diet and microbiota impact the regulation of the gut immune system in a way that might promote T1D in NOD mice.
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Background: The role of the immune system in insulin resistance associated with type 2 diabetes has been suggested. Objectives: We assessed the profile of Th1/Th2 cytokines along with the frequencies of immune cells in insulin-treated type 2 diabetic patients (T2DP). Methods: 45 T2D patients and 43 age-matched healthy subjects were selected. Serum concentrations of T-helper type 1 (Th1) and Th2 cytokines and the frequencies of innate and adaptive immunity cells were assessed. Results: T2DP were hyperglycemic and showed high level of insulin, normal levels of triglycerides and total-cholesterol and without any change in HDL-cholesterol.Compared to healthy subjects, T2DP exhibited significant decreased frequencies of neutrophils, without any change in monocytes, eosinophils and natural killer cells. The percentages of total lymphocytes (CD3+) and CD8+-T-cells decreased whereas those of regulatory T-cells increased without any change in CD4+ T-cells in T2DP. Interestingly, the frequencies of effector CD4+-T and B-cells increased in T2DP. Serum concentrations of IL-2, IFN-γ and IL-4 decreased while IL-10 significantly enhanced in T2DP, suggesting a differentiation of CD4+T helper cells towards IL-10-producing- Teff-cells in these patients. Conclusion: Insulin-treated type 2 diabetes is associated with anti-inflammatory profile consistent with differentiation of CD4+-Th-cells towards IL-10-producing-Teff-cells, concomitant with increased frequencies of Treg and B-cells, and this may probably offer prevention against certain infections or autoimmune/inflammatory diseases.
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A combined Short-Term Learning (STL) and Long-Term Learning (LTL) approach to solving mobile robot navigation problems is presented and tested in both real and simulated environments. The LTL consists of rapid simulations that use a Genetic Algorithm to derive diverse sets of behaviours. These sets are then transferred to an idiotypic Artificial Immune System (AIS), which forms the STL phase, and the system is said to be seeded. The combined LTL-STL approach is compared with using STL only, and with using a handdesigned controller. In addition, the STL phase is tested when the idiotypic mechanism is turned off. The results provide substantial evidence that the best option is the seeded idiotypic system, i.e. the architecture that merges LTL with an idiotypic AIS for the STL. They also show that structurally different environments can be used for the two phases without compromising transferability.
Resumo:
The human immune system has numerous properties that make it ripe for exploitation in the computational domain, such as robustness and fault tolerance, and many different algorithms, collectively termed Artificial Immune Systems (AIS), have been inspired by it. Two generations of AIS are currently in use, with the first generation relying on simplified immune models and the second generation utilising interdisciplinary collaboration to develop a deeper understanding of the immune system and hence produce more complex models. Both generations of algorithms have been successfully applied to a variety of problems, including anomaly detection, pattern recognition, optimisation and robotics. In this chapter an overview of AIS is presented, its evolution is discussed, and it is shown that the diversification of the field is linked to the diversity of the immune system itself, leading to a number of algorithms as opposed to one archetypal system. Two case studies are also presented to help provide insight into the mechanisms of AIS; these are the idiotypic network approach and the Dendritic Cell Algorithm.
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The study of immune system aging, i.e. immunosenescence, is a relatively new research topic. It deals with understanding the processes of immuno-degradation that indicate signs of functionality loss possibly leading to death. Even though it is not possible to prevent immunosenescence, there is great benefit in comprehending its causes, which may help to reverse some of the damage done and thus improve life expectancy. One of the main factors influencing the process of immunosenescence is the number and phenotypical variety of naive T cells in an individual. This work presents a review of immunosenescence, proposes system dynamics modelling of the processes involving the maintenance of the naive T cell repertoire and presents some preliminary results.
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Interaction between the complement system and carbon nanotubes (CNTs) can modify their intended biomedical applications. Pristine and derivatised CNTs can activate complement primarily via the classical pathway which enhances uptake of CNTs and suppresses pro-inflammatory response by immune cells. Here, we report that the interaction of C1q, the classical pathway recognition molecule, with CNTs involves charge pattern and classical pathway activation that is partly inhibited by factor H, a complement regulator. C1q and its globular modules, but not factor H, enhanced uptake of CNTs by macrophages and modulated the pro-inflammatory immune response. Thus, soluble complement factors can interact differentially with CNTs and alter the immune response even without complement activation. Coating CNTs with recombinant C1q globular heads offers a novel way of controlling classical pathway activation in nanotherapeutics. Surprisingly, the globular heads also enhance clearance by phagocytes and down-regulate inflammation, suggesting unexpected complexity in receptor interaction. From the Clinical Editor: Carbon nanotubes (CNTs) maybe useful in the clinical setting as targeting drug carriers. However, it is also well known that they can interact and activate the complement system, which may have a negative impact on the applicability of CNTs. In this study, the authors functionalized multi-walled CNT (MWNT), and investigated the interaction with the complement pathway. These studies are important so as to gain further understanding of the underlying mechanism in preparation for future use of CNTs in the clinical setting.
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Solar ultraviolet (UV) radiation causes a range of skin disorders as well as affecting vision and the immune system. It also inhibits development of plants and animals. UV radiation monitoring is used routinely in some locations in order to alert the population to harmful solar radiation levels. There is ongoing research to develop UV-selective-sensors [1–3]. A personal, inexpensive and simple UV-selective-sensor would be desirable to measure UV intensity exposure. A prototype of such a detector has been developed and evaluated in our laboratory. It comprises a sealed two-electrode photoelectrochemical cell (PEC) based on nanocrystalline TiO2. This abundant semiconducting oxide, which is innocuous and very sta-ble, is the subject of intense study at present due to its application in dye sensitized solar cells (DSSC) [4]. Since TiO2 has a wide band gap (EG = 3.0 eV for rutile and EG = 3.2 eV for anatase), it is inher-ently UV-selective, so that UV filters are not required. This further reduces the cost of the proposed photodetector in comparison with conventional silicon detectors. The PEC is a semiconductor–electrolyte device that generates a photovoltage when it is illuminated and a corresponding photocur-rent if the external circuit is closed. The device does not require external bias, and the short circuit current is generally a linear function of illumination intensity. This greatly simplifies the elec-trical circuit needed when using the PEC as a photodetector. DSSC technology, which is based on a PEC containing nanocrystalline TiO2 sensitized with a ruthenium dye, holds out the promise of solar cells that are significantly cheaper than traditional silicon solar cells. The UV-sensor proposed in this paper relies on the cre-ation of electron–hole pairs in the TiO2 by UV radiation, so that it would be even cheaper than a DSSC since no sensitizer dye is needed. Although TiO2 has been reported as a suitable material for UV sensing [3], to the best of our knowledge, the PEC configuration described in the present paper is a new approach. In the present study, a novel double-layer TiO2 structure has been investigated. Fabrication is based on a simple and inexpensive technique for nanostructured TiO2 deposition using microwave-activated chemical bath deposition (MW-CBD) that has been reported recently [5]. The highly transparent TiO2 (anatase) films obtained are densely packed, and they adhere very well to the transparent oxide (TCO) substrate [6]. These compact layers have been studied as contacting layers in double-layer TiO2 structures for DSSC since improvement of electron extraction at the TiO2–TCO interface is expected [7]. Here we compare devices incorporating a single mesoporous nanocrystalline TiO2 structure with devices based on a double structure in which a MW-CBD film is situated between the TCO and the mesoporous nanocrystalline TiO2 layer. Besides improving electron extraction, this film could also help to block recombination of electrons transferred to the TCO with oxidized species in the electrolyte, as has been reported in the case of DSSC for compact TiO2 films obtained by other deposition tech-niques [8,9]. The two types of UV-selective sensors were characterized in detail. The current voltage characteristics, spectral response, inten-sity dependence of short circuit current and response times were measured and analyzed in order to evaluate the potential of sealed mesoporous TiO2-based photoelectrochemical cells (PEC) as low cost personal UV-photodetectors.