Ph.D. / This thesis is a theoretical treatise on a proposed new computer security system, based on a biological immune system. Modem day network-centric computing is fast approaching the density and complexity of biological organisms, making biological and computer analogies relevant and meaningful. The success of biological immune systems in protecting life over countless millennia is well known. It is therefore postulated that a highly effective defensive mechanism can be developed, to transparently enforce an acceptable level of security in very extensive and complex computer networks and systems. It can be done by building very basic, but specialized autonomous software agents, functioning in a hierarchical system, that follow basic rules that can be deduced from biological immune systems. The computer security model proposed in this thesis does not require radical new technologies and it is extremely simple. The complexity however, lies in the effective implementation of the model. Three building blocks support the computer immune model: Biology, software agent technology and nanotechnology. The main features of the model are: • Firstly, it allows computer systems to automatically and transparently protect themselves, by using mobile autonomous intelligent software agents in an artificial immune system, based on biological immune systems. • Secondly, it allows computer systems to be pro-active in protecting themselves by being able to discern between which components are part of themselves (trusted system), and which components are foreign and may thus be harmful. Although part of the model relies on specialist human collaboration and international security standards, the main thrust is the heuristic ability of the proposed computer immune system. It allows systems to learn to recognize and cope with previously unknown cyber-antigens, automatically share the information amongst the participating computer systems, and thus 'inoculate' them to render them immune to similar attacks.

It is well established that females are more immunocompetent than males as evidenced by higher humoral antibody titers, lowered susceptibility to infection, and more efficient graft rejection. Furthermore, females also exhibit a much higher incidence of autoimmune disease. These observations have led investigators to believe that the male hormonal environment may play a key role in the regulation of immune response. For this reason, this study is concerned with the expression of autoimmunity and of immune function in the mouse. This study included the New Zealand Black (NZB) mouse strain, as an animal model for human SLE, as well as normal DBA/2 and Balb/c strains. Animals were administered testosterone via subcutaneous implants in silastic tubing or by injection. Mice used were intact females, intact males and castrated males. Animals were otherwise untreated or had been exposed to a sublethal dose (400-550 rads) of irradiation. Target organ weight changes, immune capacity and peripheral blood picture changes were measured.

In combating variable pathogens, mammalian immune systems have evolved diverse families of ligands and receptors. Epitomizing this strategy are the polymorphic major histocompatibility complex class I genes (termed HLA class I in humans) that encode ligands for highly variable natural killer (NK) cell receptors (in humans, the killer cell immunoglobulin-like receptors or KIR). Technological advances are poised to allow sequencing of these polymorphic genes, the most variable in the human genome, at the highest possible accuracy and resolution. However, studies that correlate immunogenetic polymorphisms with functional changes are in their infancy and often limited to those variants that combine high ligand avidity and high frequency in Caucasians. As a result, there is a paucity of information regarding the true scope of functional human immunogenetic diversity. This not only restricts our understanding of the evolution and function of the human immune system, but also underserves non-Caucasian populations with respect to disease association studies and therapeutic advances. The work presented in this thesis details original research and methodological advances that begin to address these functional shortfalls, the goal being to improve our understanding of the relationship between immunogenetic diversity, protein structure and immune function.

Autonomous robots are expected to interact with their dynamic changing environment. This interactions requires certain level of behavior based Intelligence, which facilitates the dynamic adaptation of the robot behavior accordingly with his surrounding environment. Many researches have been done in biological information processing systems to model the behavior of an autonomous robot. The Artificial Immune System (AIS) provides new paradigm suitable for dynamic problem dealing with unknown environment rather than a static problem. The immune system has some features such as memory, tolerance, diversity and more features that can be used in engineering applications. The immune system has an important feature called meta-dynamics in which new species of antibodies are produced continuously from the bone marrow. If the B-Cell (robot) cannot deal with the current situation, new behaviors (antibodies) should be generated by the meta dynamics function. This behavior should be incorporated into the existing immune system to gain immunity against new environmental changes. We decided to use a feed forward Artificial Neural Network (ANN) to simulate this problem, and to build the AIS memory. Many researchers have tried to tackle different points in mimicking the biological immune system, but no one previously has proposed such an acquired memory. This contribution is made as a "proof of concept" to the field of biological immune system simulation as a start of further research efforts in this direction. Many applications can potentially use our designed Neuro-Immune Network (NIN), especially in the area of autonomous robotics. We demonstrated the use of the designed NIN to control a robot arm in an unknown environment. As the system encounters new cases, it will increase its ability to deal with old and new situations encountered. This novel technique can be applied to many robotics applications in industry, where autonomous robots are required to have adaptive behavior in response to their environmental changes. Regarding future work, the use of VLSI neural networks to enhance the speed of the system for real time applications can be investigated along with possible methods of design and implementation of a similar VLSI chip for the AIN. / Ph. D.

Certain tasks require multiple robots to cooperate in order to solve them. The main problem with multi-robot systems is that they are inherently complex and usually situated in a dynamic environment. Now, biological immune systems possess a natural distributed control and exhibit real-time adaptivity, properties that are required to solve problems in multi-robot systems. In this thesis, biological immune systems and their response to external elements to maintain an organism's health state are researched. The objective of this research is to propose immune-inspired approaches to cooperation, to establish an adaptive cooperation algorithm, and to determine the refinements that can be applied in relation to cooperation. Two immune-inspired models that are based on the immune network theory are proposed, namely the Immune Network T-cell-regulated---with Memory (INT-M) and the Immune Network T-cell-regulated---Cross-Reactive (INT-X) models. The INT-M model is further studied where the results have suggested that the model is feasible and suitable to be used, especially in the multi-robot cooperative shepherding domain. The Collecting task in the RoboShepherd scenario and the application of the INT-M algorithm for multi-robot cooperation are discussed. This scenario provides a highly dynamic and complex situation that has wide applicability in real-world problems. The underlying 'mechanism of cooperation' in the immune inspired model (INT-M) is verified to be adaptive in this chosen scenario. Several multi-robot cooperative shepherding factors are studied and refinements proposed, notably methods used for Shepherds' Approach, Shepherds' Formation and Steering Points' Distance. This study also recognises the importance of flock identification in relation to cooperative shepherding, and the Connected Components Labelling method to overcome the related problem is presented. Further work is suggested on the proposed INT-X model that was not implemented in this study, since it builds on top of the INT-M algorithm and its refinements. This study can also be extended to include other shepherding behaviours, further investigation of other useful features of biological immune systems, and the application of the proposed models to other cooperative tasks.

Background: Immunological events due to infection by the human immunodeficiency virus (HIV) perturb mitochondrial function which augments virus-induced metabolic imbalances. Organic acids, established biomarkers of mitochondrial dysfunction have not yet been studied as indicators of HIV-induced changes in this organelle. In this study, mass spectrometry (MS) was used to determine the organic acid profile and flow cytometry the corresponding immune changes in biofluids of clinically stable patients, with the aim of identifying HIV-influenced molecules which could potentially be developed into diagnostic and/or prognostic markers. Methodology and Results: Gas chromatography mass spectrometry (GC-MS) was used to determine HIV-induced mitochondrial dysfunction by means of organic acid profiling of sera, peripheral blood mononuclear cells (PBMCs) and urine. The Metabolomics Ion-based Data Extraction Algorithm (MET-IDEA) proved more suitable for data analysis than other software packages. The biofluids analyzed differed in the type of metabolites identified but provided related biological information. An overlap in the metabolic profiles of HIV seronegative (HIV-) and seropositive (HIV+) groups was observed. When cases in the advanced stage of the disease were included an improved separation between the groups was observed. Metabolites altered as a result of HIV infection were representative of disrupted mitochondrial metabolism, changes in lipid, sugar, energy and neurometabolism as well as oxidative stress. Metabolite detection was found to be influenced by viral load. Corresponding immune parameters were measured by detecting oxidative stress, apoptosis and cytokine changes. As expected, the HIV+ individuals experience constant oxidative stress. Significantly higher amounts of reactive oxygen species (ROS, p =0.004) were detected in infected sera. Apoptosis in the HIV+ cells was significantly higher than that occurring in the HIV- cells (p< 0.0001). When gating T cells, a greater percentage apoptosis was measured in the CD8 positive cell population (p=0.0269). Since the CD4 cells of the patient group were not depleted these cells were able to produce the soluble factor needed for apoptosis to occur in CD8 cells. In vitro stimulation of the infected PBMCs with viral peptides led to an increase in the percentage T cells which produced intracellular interferon gamma (IFN-γ). The T helper type 1 (Th1), Th2 and Th17 cytokine profile in aliquots of HIV and HIV+ sera measured using Cytometric Bead Array (CBA) technology and analyzed using multivariate statistics, correctly classified over 70 % of the cases as HIV- or HIV+. Interleukin (IL)-6 and IL-10 were found to be the key immune markers altered during HIV infection. Analyzing cytokines in this manner follows a cytokinomics approach. Conclusion: Organic acids detected agree with the oxidative, apoptotic and cytokine responses. The impact of HIV on the metabolic signature and immune system is detectable in the early asymptomatic phase of infection by using MS, flow cytometry and spectroscopy. The observed changes share a biochemical relationship and are supportive of the link between the metabolic and immune systems. The data was collected using different forms of spectroscopy and spectrometry and these approaches may therefore have a future in the management of HIV infection and the acquired immunodeficiency syndrome (AIDS). / Thesis (PhD)--University of Pretoria, 2012. / Biochemistry / unrestricted

The negative selection algorithm developed by Forrest et al. was inspired by the manner in which T-cell lymphocytes mature within the thymus before being released into the blood system. The resultant T-cell lymphocytes, which are then released into the blood, exhibit an interesting characteristic: they are only activated by non-self cells that invade the human body. The work presented in this thesis examines the current body of research on the negative selection theory and introduces a new affinity threshold function, called the feature-detection rule. The feature-detection rule utilises the inter-relationship between both adjacent and non-adjacent features within a particular problem domain to determine if an artificial lymphocyte is activated by a particular antigen. The performance of the feature-detection rule is contrasted with traditional affinity-matching functions currently employed within negative selection theory, most notably the r-chunks rule (which subsumes the r-contiguous bits rule) and the hamming-distance rule. The performance will be characterised by considering the detection rate, false-alarm rate, degree of generalisation and degree of overfitting. The thesis will show that the feature-detection rule is superior to the r-chunks rule and the hamming-distance rule, in that the feature-detection rule requires a much smaller number of detectors to achieve greater detection rates and less false-alarm rates. The thesis additionally refutes that the way in which permutation masks are currently applied within negative selection theory is incorrect and counterproductive, while placing the feature-detection rule within the spectrum of affinity-matching functions currently employed by artificial immune-system (AIS) researchers. / Dissertation (MSc)--University of Pretoria, 2009. / Computer Science / Unrestricted

The nervous system and immune system contact one another through two-way communication in order to establish and preserve homeostasis. The sympathetic neurotransmitter norepinephrine has an impact on how the immune system responds by affecting regional blood flow and activation of adrenergic receptors on leukocytes. Former studies showed that immune cells are capable of releasing nerve growth factor allowing for the establishment and continuation of sympathetic nerves in targeted tissues. From this gathered information, it was hypothesized that sympathetic nerves would prove to be less frequent in spleens from the immunodeficient R2G2 mouse strain (Envigo) when compared to 129P3/J (129) and C57BL/6 (C57) strains. R2G2 mice are an immunodeficient strain that lacks functional T, B, and natural killer cells. Ten to eleven week aged-matched male mice were measured by body weight, spleen weight, and temperature. Spleens were cut and fixed for histological investigation. Sympathetic nerves were labeled by immunostaining tyrosine hydroxylase (TH). Hematoxylin & eosin (H&E) was used to stain spleen sections in order to evaluate cytoarchitecture. Von Willebrand factor (VWF) was used to immunostain for megakaryocytes. R2G2 mice showed slightly higher temperatures and body weights but yielded a significantly smaller spleen weight (R2G2, 38.20 ± 1.48; 129, 65.08 ± 11.71; C57, 81.33 ± 8.38; P< 0.0001, ANOVA). TH stain revealed sympathetic innervation in all strains but location and morphology differed in R2G2 mice compared to controls. Control spleens had nerves which entered white pulp regions of the spleen and were closely related to leukocytes. Fiber profiles in the controls were filamentous with small acute bends. R2G2 differed by having (TH+) nerve fibers more associated with arteries and less localized in the surrounding parenchyma. The fibers were abnormally swollen and held a more granular shape instead of a filamentous shape. The H&E stain showed clear red and white pulp zones in the control spleens with 129 showing more distinct germinal centers than C57. R2G2 H&E sections showed cytoarchitecture with indistinct pulp areas. VWF staining revealed R2G2 mice had an abundant amount of megakaryocytes versus control mice megakaryocyte counts (R2G2, 11.28 ± 3.87 per 20X field; 129, 1.73 ± 0.70; C57, 1.42 ± 0.13; P< 0.0001, ANOVA) and extramedullary hematopoiesis was highly prominent. This evidence supports that leukocytes secrete neurotrophic factors or are vital to establishing normal growth of TH+ nerves toward the white pulp. Leukocytes may not be required for sympathetic innervation of blood vessels in the spleen, however, lack of leukocytes shows TH+ nerve fibers with abnormal morphology in severely immune threatened mice.

Influenza is one of the most common diseases worldwide, yet the vaccines against influenza are only 35% effective at protecting against infection. Creating a more effective vaccine requires an understanding of the foundation and the factors that contribute to a strong and protective adaptive immune response. T-bet [TBX21] is a transcription factor that plays an instrumental role in the orchestration of the type 1 immune response, which is the specialized response used by the immune system for a cell-mediated response against intracellular pathogens, such as influenza. It has yet to be explored in an influenza setting on the role T-bet in the production of antibodies. The aim of this study is to understand T-bet's role in production of antibody isotypes and identify whether expression of T-bet is more important for antibody production in T cells or B cells. We expected T-bet knockout (KO) mice to have IgG2a and that T-bet expression would be more important in T cells for antibody production. An enzyme-linked immunosorbent assay (ELISA) was used to measure the amount of virus-specific antibody in T-bet KO versus wild type (WT) mice infected with influenza. The results show that the T-bet KO and WT mice have relatively the same amount of IgG and IgG1, but the T-bet KO have a significantly lower level of IgG2a, confirming T-bet's importance for its production. To distinguish the importance of T-bet expression while T-bet expression in T cells was constant, a model was developed to allow us to control expression of T-bet in B cells. The results however were inconclusive, and the experiment will have to be repeated to make a firm conclusion on the roles of lymphocytes in the control of IgG isotypes. Overall, these results indicate that the manipulation of T-bet expression can be used as a vector to control IgG antibody levels, which holds potential for the improvement of vaccines.

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