The human immune system: Part 1

The immune system protects the human body against infectious and maligant disease. The concept of an immune system arose because of the observation that an attack of measles or mumps, two common childhood diseases, conferred an immunity on the individual, the immunity being specific to the disease. It was only much later that it was discovered that a system in the body conferred this immunity.

The human immune system Part 2: auto-immune disorders

For the immune system to function effectively, the body must be able to distinguish foreign antigens from self-antigens. However, the mechanisms which maintain this distinction may break down and result in auto-immune disease in which self-reacting antibodies and T-cells are produced. This article discusses first, the evidence for the existence of human auto-immune disease and second, the auto-immune diseases which have characteristic ocular symptoms.

The human immune system: Part 1

The immune system protects the human body against infectious and malignant disease. The concept of an immune system arose because of the observation that an attack of measles or mumps, two common childhood disease, conferred an immunity on the individual, the immunity being specific to the disease. It was only much later that it was discovered that a system in the body conferred this immunity. This article discusses the various components of the immune system, how they develop and their action in conferring immunity.

The human immune system: Part 2

For the immune system to function effectively, the body must be able to distinguish foreign antigens from self antigens. However, the mechanisms which maintain this distinction may break down and result in an auto-immune disease in which self-reacting antibodies and T-cells are produced. This article discusses first, the evidence for the existence of human auto-immune disease and second, the auto-immune diseases which have characteristic ocular symptoms.

The innate immune system and the clearance of apoptotic cells

Removal of unwanted, effete, or damaged cells through apoptosis, an active cell death culminating in phagocytic removal of cell corpses, is an important process throughout the immune system in development, control, and homeostasis. For example, neutrophil apoptosis is central to the resolution of acute inflammation, whereas autoreactive and virus-infected cells are similarly deleted. The AC removal process functions not only to remove cell corpses but further, to control inappropriate immune responses so that ACs are removed in an anti-inflammatory manner. Such "silent" clearance is mediated by the innate immune system via polarized monocyte/macrophage populations that use a range of PRRs and soluble molecules to promote binding and phagocytosis of ACs. Additionally, attractive signals are released from dying cells to recruit phagocytes to sites of death. Here, we review the molecular mechanisms associated with innate immune removal of and responses to ACs and outline how these may impact on tissue homeostasis and age-associated pathology (e.g., cardiovascular disease). Furthermore, we discuss how an aging innate immune system may contribute to the inflammatory consequences of aging and why the study of an aging immune system may be a useful path to advance characterization of mechanisms mediating effective AC clearance. © Society for Leukocyte Biology.

The immune system as drug target

The immune system is perhaps the largest yet most diffuse and distributed somatic system in vertebrates. It plays vital roles in fighting infection and in the homeostatic control of chronic disease. As such, the immune system in both pathological and healthy states is a prime target for therapeutic interventions by drugs-both small-molecule and biologic. Comprising both the innate and adaptive immune systems, human immunity is awash with potential unexploited molecular targets. Key examples include the pattern recognition receptors of the innate immune system and the major histocompatibility complex of the adaptive immune system. Moreover, the immune system is also the source of many current and, hopefully, future drugs, of which the prime example is the monoclonal antibody, the most exciting and profitable type of present-day drug moiety. This brief review explores the identity and synergies of the hierarchy of drug targets represented by the human immune system, with particular emphasis on the emerging paradigm of systems pharmacology. © the authors, publisher and licensee Libertas Academica Limited.

Functional study of ephrins and eph receptors in the immune system

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

An investigation of the molecular interactions between statins and bacterial pathogens, and their combined impact on the human immune system

Statins are a class of drug that inhibits cholesterol biosynthesis, and are used to treat patients with high serum cholesterol levels. They exert this function by competitively binding to the enzyme 3-hydroxy-3-methylglutaryl-CoenzymeA reductase (HMGR), which catalyses the formation of mevalonate, a rate-limiting step in cholesterol biosynthesis. In addition, statins have what are called “pleiotropic effects”, which include the reduction of inflammation, immunomodulation, and antimicrobial effects. Statins can also improve survival of patients with sepsis and pneumonia. Cystic fibrosis (CF) is the most common recessive inherited disease in the Caucasian population, which is characterised by factors including, but not limited to, excessive lung inflammation and increased susceptibility to infection. Therefore, the overall objective of this study was to examine the effects of statins on CFassociated bacterial pathogens and the host response. In this work, the prevalence of HMGR was examined in respiratory pathogens, and several CF-associated pathogens were found to possess homologues of this enzyme. HMGR homology was analysed in Staphylococcus aureus, Burkholderia cenocepacia and Streptococcus pneumoniae, and the HMGR of B. cenocepacia was found to have significant conservation to that of Pseudomonas mevalonii, which is the most widely-characterised bacterial HMGR. However, in silico analysis revealed that, unlike S. aureus and S. pneumoniae, B. cenocepacia did not possess homologues of other mevalonate pathway proteins, and that the HMGR of B. cenocepacia appeared to be involved in an alternative metabolic pathway. The effect of simvastatin was subsequently tested on the growth and virulence of S. aureus, B. cenocepacia and S. pneumoniae. Simvastatin inhibited the growth of all 3 species in a dose-dependent manner. In addition, statin treatment also attenuated biofilm formation of all 3 species, and reduced in vitro motility of S. aureus. Interestingly, simvastatin also increased the potency of the aminoglycoside antibiotic gentamicin against B. cenocepacia. The impact of statins was subsequently tested on the predominant CF-associated pathogen Pseudomonas aeruginosa, which does not possess a HMGR homologue. Mevastatin, lovastatin and simvastatin did not influence the growth of this species. However, sub-inhibitory statin concentrations reduced the swarming motility and biofilm formation of P. aeruginosa. The influence of statins was also examined on Type 3 toxin secretion, quorum sensing and chemotaxis, and no statin effect was observed on any of these phenotypes. Statins did not appear to have a characteristic effect on the P. aeruginosa transcriptome. However, a mutant library screen revealed that the effect of statins on P. aeruginosa biofilm was mediated through the PvrR regulator and the Cup fimbrial biosynthesis genes. Furthermore, proteomic analysis demonstrated that 6 proteins were reproducibly induced by simvastatin in the P. aeruginosa swarming cells. The effect of statins on the regulation of the host-P. aeruginosa immune response was also investigated. Statin treatment increased expression of the pro-inflammatory cytokines IL-8 and CCL20 in lung epithelial cells, but did not attenuate P. aeruginosa-mediated inflammatory gene induction. In fact, simvastatin and P. aeruginosa caused a synergistic effect on CCL20 expression. The expression of the transcriptional regulators KLF2 and KLF6 was also increased by statins and P. aeruginosa, with the induction of KLF6 by simvastatin proving to be a novel effect. Interestingly, both statins and P. aeruginosa were capable of inducing alternative splicing of KLF6. P. aeruginosa was found to induce KLF6 alternative splicing by way of the type 3 secreted toxin ExoS. In addition, a mechanistic role was elucidated for KLF6 in the lung, as it was determined that statin-mediated induction of this protein was responsible for the induction of the host response genes CCL20 and iNOS. Moreover, statin treatment caused a slight increase in infection-related cytotoxicity, and increased bacterial adhesion to cells. Taken together, these data demonstrate that statins can reduce the virulence of CFassociated bacterial pathogens and alter host response effectors. Furthermore, novel statin effectors were identified in both bacterial and host cells.

Functional study of ephrins and eph receptors in the immune system

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Partner selection for reverse logistics centres in green supply chains: a fuzzy artificial immune optimization approach

The design of reverse logistics networks has now emerged as a major issue for manufacturers, not only in developed countries where legislation and societal pressures are strong, but also in developing countries where the adoption of reverse logistics practices may offer a competitive advantage. This paper presents a new model for partner selection for reverse logistic centres in green supply chains. The model offers three advantages. Firstly, it enables economic, environment, and social factors to be considered simultaneously. Secondly, by integrating fuzzy set theory and artificial immune optimization technology, it enables both quantitative and qualitative criteria to be considered simultaneously throughout the whole decision-making process. Thirdly, it extends the flat criteria structure for partner selection evaluation for reverse logistics centres to the more suitable hierarchy structure. The applicability of the model is demonstrated by means of an empirical application based on data from a Chinese electronic equipment and instruments manufacturing company.

'Introducing Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomaly Detection'

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.

Applying Mathematical Models to Study the Role of the Immune System in Chronic Myelogenous Leukemia

Although tyrosine kinase inhibitors (TKIs) such as imatinib have transformed chronic myelogenous leukemia (CML) into a chronic condition, these therapies are not curative in the majority of cases. Most patients must continue TKI therapy indefinitely, a requirement that is both expensive and that compromises a patient's quality of life. While TKIs are known to reduce leukemic cells' proliferative capacity and to induce apoptosis, their effects on leukemic stem cells, the immune system, and the microenvironment are not fully understood. A more complete understanding of their global therapeutic effects would help us to identify any limitations of TKI monotherapy and to address these issues through novel combination therapies. Mathematical models are a complementary tool to experimental and clinical data that can provide valuable insights into the underlying mechanisms of TKI therapy. Previous modeling efforts have focused on CML patients who show biphasic and triphasic exponential declines in BCR-ABL ratio during therapy. However, our patient data indicates that many patients treated with TKIs show fluctuations in BCR-ABL ratio yet are able to achieve durable remissions. To investigate these fluctuations, we construct a mathematical model that integrates CML with a patient's autologous immune response to the disease. In our model, we define an immune window, which is an intermediate range of leukemic concentrations that lead to an effective immune response against CML. While small leukemic concentrations provide insufficient stimulus, large leukemic concentrations actively suppress a patient's immune system, thus limiting it's ability to respond. Our patient data and modeling results suggest that at diagnosis, a patient's high leukemic concentration is able to suppress their immune system. TKI therapy drives the leukemic population into the immune window, allowing the patient's immune cells to expand and eventually mount an efficient response against the residual CML. This response drives the leukemic population below the immune window, causing the immune population to contract and allowing the leukemia to partially recover. The leukemia eventually reenters the immune window, thus stimulating a sequence of weaker immune responses as the two populations approach equilibrium. We hypothesize that a patient's autologous immune response to CML may explain the fluctuations in BCR-ABL ratio that are regularly seen during TKI therapy. These fluctuations may serve as a signature of a patient's individual immune response to CML. By applying our modeling framework to patient data, we are able to construct an immune profile that can then be used to propose patient-specific combination therapies aimed at further reducing a patient's leukemic burden. Our characterization of a patient's anti-leukemia immune response may be especially valuable in the study of drug resistance, treatment cessation, and combination therapy.

Idiotypic Immune Networks in Mobile Robot Control

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.

Introducting Dendritic Cells as a Novel Immune-Inspired Algorithm for Anomaly Detection

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 imnological concepts.