A Recommender System based on the Immune Network

Abstract-The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an artificial immune system (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by collaborative filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen - antibody interaction for matching and antibody - antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

A Recommender System based on Idiotypic Artificial Immune Networks

The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an Artificial Immune System (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by Collaborative Filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen-antibody interaction for matching and idiotypic antibody-antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

An immune inspired Network Intrusion Detection System utilising correlation

Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

The implementation of a novel, bio-inspired, robotic security system

The implementation of a robotic security solution generally requires one algorithm to route the robot around the environment and another algorithm to perform anomaly detection. Solutions to the routing problem require the robot to have a good estimate of its own pose. We present a novel security system that uses metrics generated by the localisation algorithm to perform adaptive anomaly detection. The localisation algorithm is a vision-based SLAM solution called RatSLAM, based on mechanisms within the hippocampus. The anomaly detection algorithm is based on the mechanisms used by the immune system to identify threats to the body. The system is explored using data gathered within an unmodified office environment. It is shown that the algorithm successfully reacts to the presence of people and objects in areas where they are not usually present and is tolerised against the presence of people in environments that are usually dynamic.

The macrophage-inducible C-type lectin, Mincle, is an essential component of the innate immune response to Candida albicans

The recognition of carbohydrate moieties by cells of the innate immune system is emerging as an essential element in antifungal immunity, but despite the number and diversity of lectins expressed by innate immune cells, few carbohydrate receptors have been characterized. Mincle, a C-type lectin, is expressed predominantly on macrophages, and is here shown to play a role in macrophage responses to the yeast Candida albicans. After exposure to the yeast in vitro, Mincle localized to the phagocytic cup, but it was not essential for phagocytosis. In the absence of Mincle, production of TNF-_ by macrophages was reduced, both in vivo and in vitro. In addition, mice lacking Mincle showed a significantly increased susceptibility to systemic candidiasis. Thus, Mincle plays a novel and nonredundant role in the induction of inflammatory signaling in response to C. albicans infection.

A human-simulated immune evolutionary computation approach

Premature convergence to local optimal solutions is one of the main difficulties when using evolutionary algorithms in real-world optimization problems. To prevent premature convergence and degeneration phenomenon, this paper proposes a new optimization computation approach, human-simulated immune evolutionary algorithm (HSIEA). Considering that the premature convergence problem is due to the lack of diversity in the population, the HSIEA employs the clonal selection principle of artificial immune system theory to preserve the diversity of solutions for the search process. Mathematical descriptions and procedures of the HSIEA are given, and four new evolutionary operators are formulated which are clone, variation, recombination, and selection. Two benchmark optimization functions are investigated to demonstrate the effectiveness of the proposed HSIEA.

Decentralized detector generation in cooperative intrusion detection system

We consider Cooperative Intrusion Detection System (CIDS) which is a distributed AIS-based (Artificial Immune System) IDS where nodes collaborate over a peer-to-peer overlay network. The AIS uses the negative selection algorithm for the selection of detectors (e.g., vectors of features such as CPU utilization, memory usage and network activity). For better detection performance, selection of all possible detectors for a node is desirable but it may not be feasible due to storage and computational overheads. Limiting the number of detectors on the other hand comes with the danger of missing attacks. We present a scheme for the controlled and decentralized division of detector sets where each IDS is assigned to a region of the feature space. We investigate the trade-off between scalability and robustness of detector sets. We address the problem of self-organization in CIDS so that each node generates a distinct set of the detectors to maximize the coverage of the feature space while pairs of nodes exchange their detector sets to provide a controlled level of redundancy. Our contribution is twofold. First, we use Symmetric Balanced Incomplete Block Design, Generalized Quadrangles and Ramanujan Expander Graph based deterministic techniques from combinatorial design theory and graph theory to decide how many and which detectors are exchanged between which pair of IDS nodes. Second, we use a classical epidemic model (SIR model) to show how properties from deterministic techniques can help us to reduce the attack spread rate.

Interrelations between acute and chronic exercise and the immune and endocrine systems

Interaction between the endocrine and immune system is necessary to regulate our health. However, under some conditions, stress hormones can overstimulate or suppress the immune system, resulting in harmful consequences (1). Stress is often considered negative, yet it is an intrinsic part of everyday life. Stress is not clearly defined; it is context-specific and depends on the nature of factors that challenge our body. Internal stimuli will elicit different stress reactions compared with external stimuli (1). Similarly, some stressors will induce responses that may benefit survival, whereas others will cause disturbances that may endanger our health. Stress also depends on how our bodies perceive and respond to stressful stimuli (1).

Targeting histone deacetylases for the treatment of immune, endocrine and metabolic disorders

The 'histone code' is a well-established hypothesis describing the idea that specific patterns of post-translational modifications to histones act like a molecular "code" recognised and used by non-histone proteins to regulate specific chromatin functions. One modification which has received significant attention is that of histone acetylation. The enzymes which regulate this modification are described as histone acetyltransferases or HATs, and histone deacetylases or HDACs. Due to their conserved catalytic domain HDACs have been actively targeted as a therapeutic target. The proinflammatory environment is increasingly being recognised as a critical element for both degenerative diseases and cancer. The present review will discuss the current knowledge surrounding the clinical potential & current development of histone deacetylases for the treatment of diseases for which a proinflammatory environment plays important roles, and the molecular mechanisms by which such inhibitors may play important functions in modulating the proinflammatory environment. © 2009 Bentham Science Publishers Ltd.

Innate and adaptive immunity at mucosal surfaces of the female reproductive tract : stratification and integration of immune protection against the transmission of sexually transmitted infections

This review examines the multiple levels of pre-existing immunity in the upper and lower female reproductive tract. In addition, we highlight the need for further research of innate and adaptive immune protection of mucosal surfaces in the female reproductive tract. Innate mechanisms include the mucus lining, a tight epithelial barrier and the secretion of antimicrobial peptides and cytokines by epithelial and innate immune cells. Stimulation of the innate immune system also serves to bridge the adaptive arm resulting in the generation of pathogen-specific humoral and cell-mediated immunity. Less understood are the multiple components that act in a coordinated way to provide a network of ongoing protection. Innate and adaptive immunity in the human female reproductive tract are influenced by the stage of menstrual cycle and are directly regulated by the sex steroid hormones, progesterone and estradiol. Furthermore, the effect of hormones on immunity is mediated both directly on immune and epithelial cells and indirectly by stimulating growth factor secretion from stromal cells. The goal of this review is to focus on the diverse aspects of the innate and adaptive immune systems that contribute to a unique network of protection throughout the female reproductive tract.

A cellular automata model to investigate immune cell–tumor cell interactions in growing tumors in two spatial dimensions

We develop a hybrid cellular automata model to describe the effect of the immune system and chemokines on a growing tumor. The hybrid cellular automata model consists of partial differential equations to model chemokine concentrations, and discrete cellular automata to model cell–cell interactions and changes. The computational implementation overlays these two components on the same spatial region. We present representative simulations of the model and show that increasing the number of immature dendritic cells (DCs) in the domain causes a decrease in the number of tumor cells. This result strongly supports the hypothesis that DCs can be used as a cancer treatment. Furthermore, we also use the hybrid cellular automata model to investigate the growth of a tumor in a number of computational “cancer patients.” Using these virtual patients, the model can explain that increasing the number of DCs in the domain causes longer “survival.” Not surprisingly, the model also reflects the fact that the parameter related to tumor division rate plays an important role in tumor metastasis.

Vaccination of koalas (Phascolarctos cinereus) with a recombinant chlamydial major outer membrane protein adjuvanted with poly I:C, a host defense peptide and polyphosphazine, elicits strong and long lasting cellular and humoral immune responses

Chlamydial infections are wide spread in koalas across their range and a solution to this debilitating disease has been sought for over a decade. Antibiotics are the currently accepted therapeutic measure, but are not an effective treatment due to the asymptomatic nature of some infections and a low efficacy rate. Thus, a vaccine would be an ideal way to address this infectious disease threat in the wild. Previous vaccine trials have used a three-dose regimen; however this is very difficult to apply in the field as it would require multiple capture events, which are stressful and invasive processes for the koala. In addition, it requires skilled koala handlers and a significant monetary investment. To overcome these challenges, in this study we utilized a polyphosphazine based poly I:C and a host defense peptide adjuvant combined with recombinant chlamydial major outer membrane protein (rMOMP) antigen to induce long lasting (54 weeks) cellular and humoral immunity in female koalas with a novel single immunizing dose. Immunized koalas produced a strong IgG response in plasma, as well as at mucosal sites. Moreover, they showed high levels of C. pecorum specific neutralizing antibodies in the plasma as well as vaginal and conjunctival secretions. Lastly, Chlamydia-specific lymphocyte proliferation responses were produced against both whole chlamydial elementary bodies and rMOMP protein, over the 12-month period. The results of this study suggest that a single dose rMOMP vaccine incorporating a poly I:C, host defense peptide and polyphosphazine adjuvant is able to stimulate both arms of the immune system in koalas, thereby providing an alternative to antibiotic treatment and/or a three-dose vaccine regime.

The koala immunological toolkit: Sequence identification and comparison of key markers of the koala (Phascolarctos cinereus) immune response

The koala (Phascolarctos cinereus) is an Australian marsupial that continues to experience significant population declines. Infectious diseases caused by pathogens such as Chlamydia are proposed to have a major role. Very few species-specific immunological reagents are available, severely hindering our ability to respond to the threat of infectious diseases in the koala. In this study, we utilise data from the sequencing of the koala transcriptome to identify key immunological markers of the koala adaptive immune response and cytokines known to be important in the host response to chlamydial infection in other species. This report describes the identification and preliminary sequence analysis of (1) T lymphocyte glycoprotein markers (CD4, CD8); (2) IL-4, a marker for the Th2 response; (3) cytokines such as IL-6, IL-12 and IL-1β, that have been shown to have a role in chlamydial clearance and pathology in other hosts; and (4) the sequences for the koala immunoglobulins, IgA, IgG, IgE and IgM. These sequences will enable the development of a range of immunological reagents for understanding the koala’s innate and adaptive immune responses, while also providing a resource that will enable continued investigations into the origin and evolution of the marsupial immune system.

Genetic associations and functional characterization of M1 aminopeptidases and immune-mediated diseases

Endosplasmic reticulum aminopeptidase 1 (ERAP1), endoplasmic reticulum aminopeptidase 2 (ERAP2) and puromycin-sensitive aminopeptidase (NPEPPS) are key zinc metallopeptidases that belong to the oxytocinase subfamily of M1 aminopeptidase family. NPEPPS catalyzes the processing of proteosome-derived peptide repertoire followed by trimming of antigenic peptides by ERAP1 and ERAP2 for presentation on major histocompatibility complex (MHC) Class I molecules. A series of genome-wide association studies have demonstrated associations of these aminopeptidases with a range of immune-mediated diseases such as ankylosing spondylitis, psoriasis, Behçet's disease, inflammatory bowel disease and type I diabetes, and significantly, genetic interaction between some aminopeptidases and HLA Class I loci with which these diseases are strongly associated. In this review, we highlight the current state of understanding of the genetic associations of this class of genes, their functional role in disease, and potential as therapeutic targets.

Identification of multiple risk variants for ankylosing spondylitis through high-density genotyping of immune-related loci

Ankylosing spondylitis is a common, highly heritable inflammatory arthritis affecting primarily the spine and pelvis. In addition to HLA-B*27 alleles, 12 loci have previously been identified that are associated with ankylosing spondylitis in populations of European ancestry, and 2 associated loci have been identified in Asians. In this study, we used the Illumina Immunochip microarray to perform a case-control association study involving 10,619 individuals with ankylosing spondylitis (cases) and 15,145 controls. We identified 13 new risk loci and 12 additional ankylosing spondylitis-associated haplotypes at 11 loci. Two ankylosing spondylitis-associated regions have now been identified encoding four aminopeptidases that are involved in peptide processing before major histocompatibility complex (MHC) class I presentation. Protective variants at two of these loci are associated both with reduced aminopeptidase function and with MHC class I cell surface expression.