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.

An Immune Network Intrusion Detection System Utilising Correlation Context

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.

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.

An idiotypic immune network as a short-term learning architecture for mobile robots

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.

Artificial immune networks Copt-aiNet and Opt-aiNet applied to the reconfiguration problem of radial electrical distribution systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Computational immunology: The coming of age

The explosive growth in biotechnology combined with major advancesin information technology has the potential to radically transformimmunology in the postgenomics era. Not only do we now have readyaccess to vast quantities of existing data, but new data with relevanceto immunology are being accumulated at an exponential rate. Resourcesfor computational immunology include biological databases and methodsfor data extraction, comparison, analysis and interpretation. Publiclyaccessible biological databases of relevance to immunologists numberin the hundreds and are growing daily. The ability to efficientlyextract and analyse information from these databases is vital forefficient immunology research. Most importantly, a new generationof computational immunology tools enables modelling of peptide transportby the transporter associated with antigen processing (TAP), modellingof antibody binding sites, identification of allergenic motifs andmodelling of T-cell receptor serial triggering.

Mast cells and oral inflammation

Mast cells are mobile granule-containing secretory cells that are distributed preferentially about the microvascular endothelium in oral mucosa and dental pulp. The enzyme profile of mast cells in oral tissues resembles that of skin, with most mast cells expressing the serine proteases tryptase and chymase. Mast cells in oral tissues contain the pro-inflammatory cytokine tumour necrosis factor-alpha in their granules, and release of this promotes leukocyte infiltration during evolving inflammation in several conditions, including lichen planus, gingivitis, pulpitis, and periapical inflammation, through induction of endothelial-leukocyte adhesion molecules. Mast cell synthesis and release of other mediators exerts potent immunoregulatory effects on other cell types, while several T-lymphocyte-derived cytokines influence mast cell migration and mediator release. Mast cell proteases may contribute to alterations in basement membranes in inflammation in the oral cavity, such as the disruptions that allow cytotoxic lymphocytes to enter the epithelium in oral lichen planus. A close relationship exists among mast cells, neural elements, and laminin, and this explains the preferential distribution of mast cells in tissues. Mast cells are responsive to neuropeptides and, through their interaction with neural elements, form a neural immune network with Langerhans cells in mucosal tissues. This facilitates mast cell degranulation in response to a range of immunological and non-immunological stimuli. Because mast cells play a pivotal role in inflammation, therapies that target mast cell functions could have value in the treatment of chronic inflammatory disorders in the oral cavity.

Prevalencia de síntomas de fatiga crónica / encefalomielitis miálgica (SFC/EM) y su relación con factores ocupacionales en trabajadores en una empresa de vigilancia en Bogotá, Colombia, 2016

Antecedentes: El síndrome de fatiga crónica/encefalomielitis miálgica (SFC/EM), un trastorno debilitante y complejo que se caracteriza por un cansancio intenso, ha sido estudiado en población general, sin embargo, su exploración en población trabajadora ha sido limitada. Objetivo: Determinar la prevalencia de síntomas asociados a SFC/EM y su relación con factores ocupacionales en personal de una empresa de vigilancia en Bogotá, durante el año 2016. Materiales y métodos: Estudio de corte transversal en una empresa de vigilancia, utilizando como instrumento para la recolección de datos la historia clínica-ocupacional. En las variables cualitativas se obtuvieron frecuencias simples y porcentajes y en las variables cuantitativas medidas de tendencia central y de dispersión. Se determinaron asociaciones entre variables (Ji-cuadrado de Pearson o test exacto de Fisher, valores esperados <5), (mann-whitney.y un modelo de regresión logística incondicional (p<0.05)). Resultados: Se evaluaron 162 trabajadores, los síntomas de SFC/EM con mayor prevalencia fueron sueño no reparador (38,3%) y dolor muscular (30,2%). Se encontró asociación estadísticamente significativa entre fatiga severa y crónica por al menos 6 meses con alteración en sistema nervioso (p=0,016) y consumo de medicamentos (p=0,043), así mismo entre el sueño no reparador con el número de horas de sueño de 5 a 7 horas (p=0,002). Conclusión: En los vigilantes el síntoma de SFC/EM más prevalente fue sueño no reparador y este se asoció con el número de horas de sueño de 5 a 7 horas. Con el estudio se pudieron determinar los casos probables de SFC/EM los cuales se beneficiarían de una valoración médica integral para un diagnóstico oportuno.

Induction of an immune response through the idiotypic network with monoclonal anti-idiotype antibodies in the carcinoembryonic antigen system.

Anti-idiotype antibodies can mimic the conformational epitopes of the original antigen and act as antigen substitutes for vaccination and/or serological purposes. To investigate this possibility concerning the tumor marker carcinoembryonic antigen (CEA), BALB/c mice were immunized with the previously described anti-CEA monoclonal antibody (MAb) 5.D11 (AB1). After cell fusion, 15 stable cloned cell lines secreting anti-Ids (AB2) were obtained. Selected MAbs gave various degrees of inhibition (up to 100%) of the binding of 125I-labeled CEA to MAb 5.D11. Absence of reactivity of anti-Id MAbs with normal mouse IgG was first demonstrated by the fact that anti-Id MAbs were not absorbed by passage through a mouse IgG column, and second because they bound specifically to non-reduced MAb 5.D11 on Western blots. Anti-5.D11 MAbs did not inhibit binding to CEA of MAb 10.B9, another anti-CEA antibody obtained in the same fusion as 5.D11, or that of several anti-CEA MAbs reported in an international workshop, with the exception of two other anti-CEA MAbs, both directed against the GOLD IV epitope. When applied to an Id-anti-Id competitive radioimmunoassay, a sensitivity of 2 ng/ml of CEA was obtained, which is sufficient for monitoring circulating CEA in carcinoma patients. To verify that the anti-Id MAbs have the potential to be used as CEA vaccines, syngeneic BALB/c mice were immunized with these MAbs (AB2). Sera from immunized mice were demonstrated to contain AB3 antibodies recognizing the original antigen, CEA, both in enzyme immunoassay and by immunoperoxidase staining of human colon carcinoma. These results open the perspective of vaccination against colorectal carcinoma through the use of anti-idiotype antibodies as antigen substitutes.

B cells as a critical node in the microbiota-host immune system network.

Mutualism with our intestinal microbiota is a prerequisite for healthy existence. This requires physical separation of the majority of the microbiota from the host (by secreted antimicrobials, mucus, and the intestinal epithelium) and active immune control of the low numbers of microbes that overcome these physical and chemical barriers, even in healthy individuals. In this review, we address how B-cell responses to members of the intestinal microbiota form a robust network with mucus, epithelial integrity, follicular helper T cells, innate immunity, and gut-associated lymphoid tissues to maintain host-microbiota mutualism.

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.

Efficient discovery of immune response targets by cyclical refinement of QSAR models of peptide binding

Peptides that induce and recall T-cell responses are called T-cell epitopes. T-cell epitopes may be useful in a subunit vaccine against malaria. Computer models that simulate peptide binding to MHC are useful for selecting candidate T-cell epitopes since they minimize the number of experiments required for their identification. We applied a combination of computational and immunological strategies to select candidate T-cell epitopes. A total of 86 experimental binding assays were performed in three rounds of identification of HLA-All binding peptides from the six preerythrocytic malaria antigens. Thirty-six peptides were experimentally confirmed as binders. We show that the cyclical refinement of the ANN models results in a significant improvement of the efficiency of identifying potential T-cell epitopes. (C) 2001 by Elsevier Science Inc.

A Dynamical Modeling to Study the Adaptive Immune System and the Influence of Antibodies in the Immune Memory

Immunological systems have been an abundant inspiration to contemporary computer scientists. Problem solving strategies, stemming from known immune system phenomena, have been successfully applied to chall enging problems of modem computing. Simulation systems and mathematical modeling are also beginning use to answer more complex immunological questions as immune memory process and duration of vaccines, where the regulation mechanisms are not still known sufficiently (Lundegaard, Lund, Kesmir, Brunak, Nielsen, 2007). In this article we studied in machina a approach to simulate the process of antigenic mutation and its implications for the process of memory. Our results have suggested that the durability of the immune memory is affected by the process of antigenic mutation.and by populations of soluble antibodies in the blood. The results also strongly suggest that the decrease of the production of antibodies favors the global maintenance of immune memory.

Trapping of naive lymphocytes triggers rapid growth and remodeling of the fibroblast network in reactive murine lymph nodes.

Adaptive immunity is initiated in T-cell zones of secondary lymphoid organs. These zones are organized in a rigid 3D network of fibroblastic reticular cells (FRCs) that are a rich cytokine source. In response to lymph-borne antigens, draining lymph nodes (LNs) expand several folds in size, but the fate and role of the FRC network during immune response is not fully understood. Here we show that T-cell responses are accompanied by the rapid activation and growth of FRCs, leading to an expanded but similarly organized network of T-zone FRCs that maintains its vital function for lymphocyte trafficking and survival. In addition, new FRC-rich environments were observed in the expanded medullary cords. FRCs are activated within hours after the onset of inflammation in the periphery. Surprisingly, FRC expansion depends mainly on trapping of naïve lymphocytes that is induced by both migratory and resident dendritic cells. Inflammatory signals are not required as homeostatic T-cell proliferation was sufficient to trigger FRC expansion. Activated lymphocytes are also dispensable for this process, but can enhance the later growth phase. Thus, this study documents the surprising plasticity as well as the complex regulation of FRC networks allowing the rapid LN hyperplasia that is critical for mounting efficient adaptive immunity.