A Novel Intrusion Detection Model Based on Danger Theory

As the traditional negative selection, clonal selection algorithms predefine one part of antigens to be self (the training set) in intrusion detection applications, but in practice the self is difficult to define and can change over time. With the change of the self, error detection rate increases sharply. A recently developed hypothesis in immunology, the Danger Theory, states that our immune system responds to the presence of intruders through sensing molecules belonging to those invaders, plus signals generated by the host indicating danger and damage. Integrating the ldquoDanger Theoryrdquo, negative selection and immune memory, the paper proposes a novel artificial immune model for intrusion detection. The paper considers the coordination of DCs in the innate immune system and T cells in the adaptive immune system. At the same time the paper focuses on how to define ldquodanger signalsrdquo and considers whether to have a danger to the protected system as the basis of defining ldquoself-nonselfrdquo, in which the self is dynamically updated. The theory analysis shows that the dynamic self can improve the problem of error detection rate increasing sharply, and the dual detection method of DCs detecting the behaviors of antigens and T cells detecting the antigens can also significantly decrease error detection rate.

An Immune System Based Multi-robot Mobile Agent Network

A biological immune system comprises components that circulate within the body and defend it from attacks by pathogens. Its artificial counterpart has found applications in a wide spectrum of domains including Robotics. The cells in an immune system can be viewed to be analogous to mobile agents that migrate from one node (organ) to another. Mobility of such agents provides the framework for movement of components within a system. In this paper we describe the modeling of a mobile agent based robotic system that works on the principles of an artificial immune system. The mobile agents form the B-cell equivalents, generating rule-sets (antibodies) that help the robot to overcome a problem (antigen).

Artificial immune classifier with swarm learning

Artificial immune systems are computational systems inspired by the principles and processes of the natural immune system. The various applications of artificial immune systems have been used for pattern recognition and classification problems; however, these artificial immune systems have three major problems, which are growing of the memory cell population, eliminating of the useful memory cells in next the steps, and randomly using cloning and mutation operators. In this study, a new artificial immune classifier with swarm learning is proposed to solve these three problems. The proposed algorithm uses the swarm learning to evolve the antibody population. In each step, the antibodies that belong to the same class move to the same way according to their affinities. The size of the memory cell population does not grow during the training stage of the algorithm. Therefore, the method is faster than other artificial immune classifiers. The classifier was tested on two case studies. In the first case study, the algorithm was used to diagnose the faults of induction motors. In the second case study, five benchmark data sets were used to evaluate the performance of the algorithm. The results of second case studies show that the proposed method gives better results than two well-known artificial immune systems for real word data sets. The results were compared to other classification techniques, and the method is competitive to other classifiers.

Human immune system during sleep.

A joint function of tissues, organs and cells for the protection of body develops immune system. The human immune response against various infections during sleep, its mechanism, neuroimmune interactions, immunoregulatory effect of sleep along with sleep deprivation and role of cytokines in sleep deprivation were addressed. It is revealed that human immune system and sleep both are associated and influenced by each other. Sleep deprivation makes a living body susceptible to many infectious agents. In the result, immune system of human body is altered by releasing immunomodulators in the response of infections as reported by various researchers. Basic reasons and mechanisms of most of the poor sleep networks and release of proinflammatory modulators are still uncertain. The current situation requires improved sleep habits to make immune system efficient for a healthy life.

Data analysis using artificial immune systems, cluster analysis and Kohonen networks: some comparisons

Knowledge discovery in databases (KDD) is still a relatively new and expanding field. To aid the KDD process, data mining methods are used to extract previously unknown patterns and trends in vast amounts of data. There exist a number of data mining techniques, taking methods from the machine learning, statistical analysis and pattern recognition communities, to name a few. Each technique has something different to offer over other techniques and each is suitable for different purposes giving certain benefits in varying situations. This paper examines a novel data analysis technique that is inspired by the human immune system: the artificial immune system (AIS). Immune system principles act as inspiration, allowing the creation of a network of cells that in effect clusters similar patterns and trends together. It is inspired by but not a model of the human immune system. This clustering allows the human user to effectively identify areas of similarity from the training data set that would previously have been unobtainable.

Using an agent-based model to analyze the dynamic communication network of the immune response

The mucosal immune system in the oral cavity—an orchestra of T cell diversity

The mucosal immune system defends against a vast array of pathogens, yet it exhibits limited responses to commensal microorganisms under healthy conditions. The oral-pharyngeal cavity, the gateway for both the gastrointestinal and respiratory tracts, is composed of complex anatomical structures and is constantly challenged by antigens from air and food. The mucosal immune system of the oral-pharyngeal cavity must prevent pathogen entry while maintaining immune homeostasis, which is achieved via a range of mechanisms that are similar or different to those utilized by the gastrointestinal immune system. In this review, we summarize the features of the mucosal immune system, focusing on T cell subsets and their functions. We also discuss our current understanding of the oral-pharyngeal mucosal immune system.

Single-cell sequencing provides clues about the host interactions of segmented filamentous bacteria (SFB)

Segmented filamentous bacteria (SFB) are host-specific intestinal symbionts that comprise a distinct clade within the Clostridiaceae, designated Candidatus Arthromitus. SFB display a unique life cycle within the host, involving differentiation into multiple cell types. The latter include filaments that attach intimately to intestinal epithelial cells, and from which “holdfasts” and spores develop. SFB induce a multifaceted immune response, leading to host protection from intestinal pathogens. Cultivation resistance has hindered characterization of these enigmatic bacteria. In the present study, we isolated five SFB filaments from a mouse using a microfluidic device equipped with laser tweezers, generated genome sequences from each, and compared these sequences with each other, as well as to recently published SFB genome sequences. Based on the resulting analyses, SFB appear to be dependent on the host for a variety of essential nutrients. SFB have a relatively high abundance of predicted proteins devoted to cell cycle control and to envelope biogenesis, and have a group of SFB-specific autolysins and a dynamin-like protein. Among the five filament genomes, an average of 8.6% of predicted proteins were novel, including a family of secreted SFB-specific proteins. Four ADP-ribosyltransferase (ADPRT) sequence types, and a myosin-cross-reactive antigen (MCRA) protein were discovered; we hypothesize that they are involved in modulation of host responses. The presence of polymorphisms among mouse SFB genomes suggests the evolution of distinct SFB lineages. Overall, our results reveal several aspects of SFB adaptation to the mammalian intestinal tract.

Immune responses to myxoma virus.

Myxoma virus causes the systemic disease myxomatosis in the European rabbit (Oryctolagus cuniculus). Originating in the South American rabbit Sylvilagus brasiliensis, where it causes a relatively localized fibroma, myxoma virus is a classic example of a virus that has jumped species to produce an exotic disease and then coevolved with its new host. Like other poxviruses, myxoma virus encodes multiple proteins capable of downregulating the host innate and acquired immune responses. Other virus-encoded proteins enable replication in host lymphocytes and monocytes, for example, by inhibiting apoptosis. Detailed studies on these proteins have demonstrated novel methods of interactions with the host immune system and added substantially to the understanding of the interaction of large DNA viruses with their hosts. Despite the increasingly detailed molecular knowledge of myxoma virus, relatively little is known about the dynamics of the interaction of the virus with the integrated host-immune system during infection and, in particular, about the evolution of resistance to the virus in wild rabbits or the species barrier. This review will focus on the detailed molecular studies that have been done with myxoma virus and discuss the more limited knowledge of the pathogenesis of myxoma virus in rabbits and the ways that the consolidated immune responses may determine genetic resistance to myxomatosis.

Immunity in athletes.

It has become clear that the immune system responds to increased physical activity and may be given some of the credit for exercise-related reduction in illness. In contrast, it has repeatedly been shown that intense exercise causes immunosuppression. In essence the immune system is enhanced during moderate and severe exercise, and only intense long-duration exercise is followed by immunodepression. The latter include suppressed concentration of lymphocytes, suppressed natural killer and lymphokine activated killer cytotoxicity and secretory IgA in mucosa. Whether or not the "open window" in the immune system occurs is dependent on the intensity and duration of exercise. One reason for the "overtraining effect" seen in elite athletes could be that this window of opportunism for pathogens is longer and the degree of immunosuppression more pronounced. It is being hypothesized that severe immunodepression may occur if athletes does not allow the immune system to recover, but initiate a new bout of exercise while still immunodepressed. It has also been suggested that neutrophils serve as a last line of defence. The removal of this back-up system following extreme activity would be compatible with the propensity of "overtrained" individuals to develop upper respiratory tract infections.

Artificial immune algorithm for IIR filter design

Over the recent years, several studies have been carried out by the researchers to describe a general, flexible and powerful design method based on modern heuristic optimisation algorithms for infinite impulse response (IIR) digital filters since these algorithms have the ability of finding global optimal solution in a nonlinear search space. One of the modern heuristic algorithms is the artificial immune algorithm which implements a learning technique inspired by human immune system. However, the immune system has not attracted the same kind of interest from researchers as other heuristic algorithms. In this work, an artificial immune algorithm is described and applied to the design of IIR filters, and its performance is compared to that of genetic and touring ant colony optimisation algorithms.

Interplay Between Innate Immunity and the Plant Microbiota.

The innate immune system of plants recognizes microbial pathogens and terminates their growth. However, recent findings suggest that at least one layer of this system is also engaged in cooperative plant-microbe interactions and influences host colonization by beneficial microbial communities. This immune layer involves sensing of microbe-associated molecular patterns (MAMPs) by pattern recognition receptors (PRRs) that initiate quantitative immune responses to control host-microbial load, whereas diversification of MAMPs and PRRs emerges as a mechanism that locally sculpts microbial assemblages in plant populations. This suggests a more complex microbial management role of the innate immune system for controlled accommodation of beneficial microbes and in pathogen elimination. The finding that similar molecular strategies are deployed by symbionts and pathogens to dampen immune responses is consistent with this hypothesis but implies different selective pressures on the immune system due to contrasting outcomes on plant fitness. The reciprocal interplay between microbiota and the immune system likely plays a critical role in shaping beneficial plant-microbiota combinations and maintaining microbial homeostasis.

Cascading effects of stressors and inflammatory immune system activation: implications for major depressive disorder.

Activation of the inflammatory immune system provokes numerous neuroendocrine and neurotransmitter changes, many of which are similar to those provoked by physical or psychological stressors. These findings, among others, have led to the suggestion that the brain translates immune activation much as if it were a stressor. In this review, I provide synopses of the effects of traditional stressors on the release of corticotropin-releasing hormones at hypothalamic and extrahypothalamic sites, variations of serotonin and its receptors and changes of brain-derived neurotrophic factor (BDNF). These effects are similar to those elicited by activation of the inflammatory immune system, particularly the impact of the immune-signalling molecules interleukin-1 beta, interleukin-6, tumour necrosis factor-alpha and interferon-alpha on neuroendocrine, neurotransmitter and BDNF function. In addition, it is reported that stressors and cytokines may synergistically influence biological and behavioural processes and that these treatments may have long-term ramifications through the sensitization of processes associated with stress responses. Finally, I present an overview of the depressogenic actions of these cytokines in rodent models and in humans, and I provide provisional suggestions (and caveats) about the mechanisms by which cytokines and stressors might culminate in major depressive disorder.

A resource limited artificial immune system for data analysis

This paper presents a resource limited artificial immune system (RLAIS) for data analysis. The work presented here builds upon previous work on artificial immune systems (AIS) for data analysis. A population control mechanism, inspired by the natural immune system, has been introduced to control population growth and allow termination of the learning algorithm. The new algorithm is presented, along with the immunological metaphors used as inspiration. Results are presented for Fisher Iris data set, where very successful results are obtained in identifying clusters within the data set. It is argued that this new resource-based mechanism is a large step forward in making AISs a viable contender for effective unsupervised machine learning and allows for not just a one shot learning mechanism, but a continual learning model to be developed.

Interactions between the Neuroendocrine and Immune Systems: Common Hormones and Receptors

The studies reviewed here support a molecular basis for bidirectional communication between the immune and neuroendocrine systems. The main findings can be summarized as follows: First, cells of the immune system can synthesize biologically active neuroendocrine peptide hormones. Second, immune cells also possess receptors for many of these peptides. Third, these same neuroendocrine hormones can influence immune function; and fourth, lymphokines can influence neuroendocrine tissues. Although recent studies have begun to unravel the biochemistry of bidirectional communication between the immune and neuroendocrine systems, there are still missing parts in this puzzle. Among the important questions that must be resolved are the identification of factors that trigger the synthesis of neuroendocrine hormones by immune cells. Are these events operating similar to or in balance with pituitary cells? Drugs that interfere with either pathway may be useful. Second, it will be of value to understand the factors controlling neuroendocrine hormone receptor expression on immune cells. A better understanding of the spectrum of positive and negative regulatory events for both systems may determine the ultimate behavior of immune and neuroendocrine cells. In addition, since leukocytes can produce hormones and also have receptors for the same hormones (e.g., ACTH and GH), it is possible that these immunocytes may also influence their own function in an autocrine-like fashion. We have postulated that the immune system can serve as a sensory organ for external stimuli that cannot be detected by the nervous system (Blalock 1984). Thus, the immune system recognizes stimuli such as bacteria, viruses or tumors, whereas the nervous system detects classical sensory stimuli. The contribution of extrapituitary sites of hormone production and function may provide new clues to define psychological and/or pathological states in the pathophysiology of infectious diseases and tumors.

The mucus and mucins of the goblet cells and enterocytes provide the first defense line of the gastrointestinal tract and interact with the immune system

The gastrointestinal tract is covered by mucus that has different properties in the stomach, small intestine, and colon. The large highly glycosylated gel‐forming mucins MUC2 and MUC5AC are the major components of the mucus in the intestine and stomach, respectively. In the small intestine, mucus limits the number of bacteria that can reach the epithelium and the Peyer's patches. In the large intestine, the inner mucus layer separates the commensal bacteria from the host epithelium. The outer colonic mucus layer is the natural habitat for the commensal bacteria. The intestinal goblet cells secrete not only the MUC2 mucin but also a number of typical mucus components: CLCA1, FCGBP, AGR2, ZG16, and TFF3. The goblet cells have recently been shown to have a novel gate‐keeping role for the presentation of oral antigens to the immune system. Goblet cells deliver small intestinal luminal material to the lamina propria dendritic cells of the tolerogenic CD103+ type. In addition to the gel‐forming mucins, the transmembrane mucins MUC3, MUC12, and MUC17 form the enterocyte glycocalyx that can reach about a micrometer out from the brush border. The MUC17 mucin can shuttle from a surface to an intracellular vesicle localization, suggesting that enterocytes might control and report epithelial microbial challenge. There is communication not only from the epithelial cells to the immune system but also in the opposite direction. One example of this is IL10 that can affect and improve the properties of the inner colonic mucus layer. The mucus and epithelial cells of the gastrointestinal tract are the primary gate keepers and controllers of bacterial interactions with the host immune system, but our understanding of this relationship is still in its infancy.

Mechanisms involved in the evasion of the host defence by Pseudomonas aeruginosa.

Pseudomonas aeruginosa, an extracellular opportunistic pathogen, utilizes two major mechanisms to evade the host defence system. One of these mechanisms is the production of a large number of extracellular products, such as proteases, toxins, and lipases. The two proteases, alkaline protease and elastase, inhibit the function of the cells of the immune system (phagocytes, NK cells, T cells), inactivate several cytokines (IL-1, IL-2, IFN-r, TNF), cleave immunoglobulins and inactivate complement. Inhibition of the local immune response by bacterial proteases provides an environment for the colonization and establishment of chronic infection. The other mechanism by which P. aeruginosa evades the host defence system is the biofilm mode of growth of the bacteria in chronic infections. The biofilm-grown bacteria induce a low phagocyte response, and provide a barrier for the bacteria against antibodies, complement, and the cells of the immune system. Protection from the host defence system combined with increased antibiotic resistance of the bacteria in the biofilm are the major reasons for the persistence of P. aeruginosa in chronic infections.

The immune system, adaptation, and machine learning

Abstract The immune system is capable of learning, memory, and pattern recognition. By employing genetic operators on a time scale fast enough to observe experimentally, the immune system is able to recognize novel shapes without preprogramming. Here we describe a dynamical model for the immune system that is based on the network hypothesis of Jerne, and is simple enough to simulate on a computer. This model has a strong similarity to an approach to learning and artificial intelligence introduced by Holland, called the classifier system. We demonstrate that simple versions of the classifier system can be cast as a nonlinear dynamical system, and explore the analogy between the immune and classifier systems in detail. Through this comparison we hope to gain insight into the way they perform specific tasks, and to suggest new approaches that might be of value in learning systems.

Exercise and the immune system: regulation, integration, and adaptation.

Stress-induced immunological reactions to exercise have stimulated much research into stress immunology and neuroimmunology. It is suggested that exercise can be employed as a model of temporary immunosuppression that occurs after severe physical stress. The exercise-stress model can be easily manipulated experimentally and allows for the study of interactions between the nervous, the endocrine, and the immune systems. This review focuses on mechanisms underlying exercise-induced immune changes such as neuroendocrinological factors including catecholamines, growth hormone, cortisol, beta-endorphin, and sex steroids. The contribution of a metabolic link between skeletal muscles and the lymphoid system is also reviewed. The mechanisms of exercise-associated muscle damage and the initiation of the inflammatory cytokine cascade are discussed. Given that exercise modulates the immune system in healthy individuals, considerations of the clinical ramifications of exercise in the prevention of diseases for which the immune system has a role is of importance. Accordingly, drawing on the experimental, clinical, and epidemiological literature, we address the interactions between exercise and infectious diseases as well as exercise and neoplasia within the context of both aging and nutrition.

Innate and Adaptive Immunity Cooperate Flexibly to Maintain Host-Microbiota Mutualism

Maintaining Mutual Ignorance Our gut is colonized by trillions of bacteria that do not activate the immune system because of careful compartmentalization. Such compartmentalization means that our immune system is “ignorant” of these microbes and thus it has been proposed that loss of compartmentalization might result in an immune response to the colonizing bacteria. Microorganisms are sensed by cells that express pattern recognition receptors, such as Toll-like receptors, which recognize patterns specific to those microbes. Slack et al. (p. 617) show that Toll-like receptor–dependent signaling is required to maintain compartmentalization of bacteria to the gut of mice. In the absence of Toll-dependent signaling, intestinal bacteria disseminated throughout the body and the mice mounted a high-titer antibody response against them. This antibody response was of great functional importance because, despite the loss of systemic ignorance to intestinal microbes, the mice were tolerant of the bacteria. Thus, in the absence of innate immunity, the adaptive immune system can compensate so that host and bacterial mutualism can be maintained. Mouse immune systems interact to ensure tolerance to nonpathogenic bacteria in the gut. Commensal bacteria in the lower intestine of mammals are 10 times as numerous as the body’s cells. We investigated the relative importance of different immune mechanisms in limiting the spread of the intestinal microbiota. Here, we reveal a flexible continuum between innate and adaptive immune function in containing commensal microbes. Mice deficient in critical innate immune functions such as Toll-like receptor signaling or oxidative burst production spontaneously produce high-titer serum antibodies against their commensal microbiota. These antibody responses are functionally essential to maintain host-commensal mutualism in vivo in the face of innate immune deficiency. Spontaneous hyper-activation of adaptive immunity against the intestinal microbiota, secondary to innate immune deficiency, may clarify the underlying mechanisms of inflammatory diseases where immune dysfunction is implicated.