Immune-inspired adaptive information filtering

Adaptive information filtering is a challenging research problem. It requires the adaptation of a representation of a user’s multiple interests to various changes in them. We investigate the application of an immune-inspired approach to this problem. Nootropia, is a user profiling model that has many properties in common with computational models of the immune system that have been based on Franscisco Varela’s work. In this paper we concentrate on Nootropia’s evaluation. We define an evaluation methodology that uses virtual user’s to simulate various interest changes. The results show that Nootropia exhibits the desirable adaptive behaviour.

Nootropia : a user profiling model based on a self-organising term network

Artificial Immune Systems are well suited to the problem of using a profile representation of an individual’s or a group’s interests to evaluate documents. Nootropia is a user profiling model that exhibits similarities to models of the immune system that have been developed in the context of autopoietic theory. It uses a self-organising term network that can represent a user’s multiple interests and can adapt to both short-term variations and substantial changes in them. This allows Nootropia to drift, constantly following changes in the user’s multiple interests, and, thus, to become structurally coupled to the user.

Optimizing amino acid groupings for GPCR classification

MOTIVATION: There is much interest in reducing the complexity inherent in the representation of the 20 standard amino acids within bioinformatics algorithms by developing a so-called reduced alphabet. Although there is no universally applicable residue grouping, there are numerous physiochemical criteria upon which one can base groupings. Local descriptors are a form of alignment-free analysis, the efficiency of which is dependent upon the correct selection of amino acid groupings. RESULTS: Within the context of G-protein coupled receptor (GPCR) classification, an optimization algorithm was developed, which was able to identify the most efficient grouping when used to generate local descriptors. The algorithm was inspired by the relatively new computational intelligence paradigm of artificial immune systems. A number of amino acid groupings produced by this algorithm were evaluated with respect to their ability to generate local descriptors capable of providing an accurate classification algorithm for GPCRs.

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.

Mediators of gram-positive septic shock

Septic shock can occur as a result of Gram-negative or Gram-positive infection and involves a complex interaction between bacterial factors and the host immune system producing a systemic inflammatory state that may progress to multiple organ failure and death. Gram-positive bacteria are increasingly becoming more prevalent especially Staphylococcus epidermidis in association with indwelling devices. Lipopolysaccaride (LPS) is the key Gram-negative component involved in this process, but it is not clear which components of Gram-positive bacteria are responsible for progression of this often fatal disease. The aim of this thesis was to investigate the effect of bacterial components on the immune systems. Lipid S, a short chain form of lipoteichoic acid (LTA) found to be excreted from bacteria during growth in culture medium was examined along with other Gram-positive cell wall components: LTA, peptidoglycan (PG) and wall teichoic acids (WTA) and LPS from Gram-negative bacteria. Lipid S, LTA, PG and LPS but not WTA all stimulated murine macrophages and cell lines to produce significant amounts of NO, TNF-a, IL-6 and IL-1 and would induce fever and tissue damage seen in inflammatory diseases. Lipid S proved to be the most potent out of the Gram-positive samples tested. IgG antibodies in patients serum were found to bind to and cross react with lipid S and LTA. Anti-inflammatory antibiotics, platelet activating factor (PAF), PAF receptor antagonists and monoclonal antibodies (mAbs) directed to LTA, CD14 and toll-like receptors were utilised to modulate cytokine and NO production. In cell culture the anti-LTA and the anti-CD14 mAbs failed to markedly attenuate the production of NO, TNF-a, IL-6 or IL-1, the anti-TLR4 antibody did greatly inhibit the ability of LPS to stimulate cytokine production but not lipid S. The tetracyclines proved to be the most effective compounds, many were active at low concentrations and showed efficacy to inhibit both lipid S and LPS stimulated macrophages to produce NO.

Ecological studies on river pollution control

This collection of papers records a series of studies, carried out over a period of some 50 years, on two aspects of river pollution control - the prevention of pollution by sewage biological filtration and the monitoring of river pollution by biological surveillance. The earlier studies were carried out to develop methods of controlling flies which bred in the filters and caused serious nuisance and possible public health hazard, when they dispersed to surrounding villages. Although the application of insecticides proved effective as an alleviate measure, because it resulted in only a temporary disturbance of the ecological balance, it was considered ecologically unsound as a long-term solution. Subsequent investigations showed that the fly populations in filters were largely determined by the amount of food available to the grazing larval stage in the form of filter film. It was also established that the winter deterioration in filter performance was due to the excessive accumulation of film. Subsequent investigations were therefore carried out to determine the factors responsible for the accumulation of film in different types of filter. Methods of filtration which were considered to control film accumulation by increasing the flushing action of the sewage, were found to control fungal film by creating nutrient limiting conditions. In some filters increasing the hydraulic flushing reduced the grazing fauna population in the surface layers and resulted in an increase in film. The results of these investigations were successfully applied in modifying filters and in the design of a Double Filtration process. These studies on biological filters lead to the conclusion that they should be designed and operated as ecological systems and not merely as hydraulic ones. Studies on the effects of sewage effluents on Birmingham streams confirmed the findings of earlier workers justifying their claim for using biological methods for detecting and assessing river pollution. Further ecological studies showed the sensitivity of benthic riffle communities to organic pollution. Using experimental channels and laboratory studies the different environmental conditions associated with organic pollution were investigated. The degree and duration of the oxygen depletion during the dark hours were found to be a critical factor. The relative tolerance of different taxa to other pollutants, such as ammonia, differed. Although colonisation samplers proved of value in sampling difficult sites, the invertebrate data generated were not suitable for processing as any of the commonly used biotic indexes. Several of the papers, which were written by request for presentation at conferences etc., presented the biological viewpoint on river pollution and water quality issues at the time and advocated the use of biological methods. The information and experiences gained in these investigations was used as the "domain expert" in the development of artificial intelligence systems for use in the biological surveillance of river water quality.

Immunoinformatics:predicting immunogenicity in silico

This volume both engages the reader and provides a sound foundation for the use of immunoinformatics techniques in immunology and vaccinology. It addresses databases, HLA supertypes, MCH binding, and other properties of immune systems. The book contains chapters written by leaders in the field and provides a firm background for anyone working in immunoinformatics in one easy-to-use, insightful volume.

Knowledge based improvement:simulation and artificial intelligence for identifying and improving human decision-making in an operations systems

The performance of most operations systems is significantly affected by the interaction of human decision-makers. A methodology, based on the use of visual interactive simulation (VIS) and artificial intelligence (AI), is described that aims to identify and improve human decision-making in operations systems. The methodology, known as 'knowledge-based improvement' (KBI), elicits knowledge from a decision-maker via a VIS and then uses AI methods to represent decision-making. By linking the VIS and AI representation, it is possible to predict the performance of the operations system under different decision-making strategies and to search for improved strategies. The KBI methodology is applied to the decision-making surrounding unplanned maintenance operations at a Ford Motor Company engine assembly plant.

Administration routes affect the quality of immune responses:a cross-sectional evaluation of particulate antigen-delivery systems

Particulate delivery systems such as liposomes and polymeric nano- and microparticles are attracting great interest for developing new vaccines. Materials and formulation properties essential for this purpose have been extensively studied, but relatively little is known about the influence of the administration route of such delivery systems on the type and strength of immune response elicited. Thus, the present study aimed at elucidating the influence on the immune response when of immunising mice by different routes, such as the subcutaneous, intradermal, intramuscular, and intralymphatic routes with ovalbumin-loaded liposomes, N-trimethyl chitosan (TMC) nanoparticles, and poly(lactide-co-glycolide) (PLGA) microparticles, all with and without specifically selected immune-response modifiers. The results showed that the route of administration caused only minor differences in inducing an antibody response of the IgG1 subclass, and any such differences were abolished upon booster immunisation with the various adjuvanted and non-adjuvanted delivery systems. In contrast, the administration route strongly affected both the kinetics and magnitude of the IgG2a response. A single intralymphatic administration of all evaluated delivery systems induced a robust IgG2a response, whereas subcutaneous administration failed to elicit a substantial IgG2a response even after boosting, except with the adjuvanted nanoparticles. The intradermal and intramuscular routes generated intermediate IgG2a titers. The benefit of the intralymphatic administration route for eliciting a Th1-type response was confirmed in terms of IFN-gamma production of isolated and re-stimulated splenocytes from animals previously immunised with adjuvanted and non-adjuvanted liposomes as well as with adjuvanted microparticles. Altogether the results show that the IgG2a associated with Th1-type immune responses are sensitive to the route of administration, whereas IgG1 response associated with Th2-type immune responses were relatively insensitive to the administration route of the particulate delivery systems. The route of administration should therefore be considered when planning and interpreting pre-clinical research or development on vaccine delivery systems.

Effect of incorporating cholesterol into DDA:TDB liposomal adjuvants on Bilayer properties, biodistribution, and immune responses

Cholesterol is an abundant component of mammalian cell membranes and has been extensively studied as an artificial membrane stabilizer in a wide range of phospholipid liposome systems. In this study, the aim was to investigate the role of cholesterol in cationic liposomal adjuvant system based on dimethyldioctadecylammonium (DDA) and trehalose 6,6'-dibehenate (TDB) which has been shown as a strong adjuvant system for vaccines against a wide range of diseases. Packaging of cholesterol within DDA:TDB liposomes was investigated using differential scanning calorimetery and surface pressure-area isotherms of lipid monolayers; incorporation of cholesterol into liposomal membranes promoted the formation of a liquid-condensed monolayer and removed the main phase transition temperature of the system, resulting in an increased bilayer fluidity and reduced antigen retention in vitro. In vivo biodistribution studies found that this increase in membrane fluidity did not alter deposition of liposomes and antigen at the site of injection. In terms of immune responses, early (12 days after immunization) IgG responses were reduced by inclusion of cholesterol; thereafter there were no differences in antibody (IgG, IgG1, IgG2b) responses promoted by DDA:TDB liposomes with and without cholesterol. However, significantly higher levels of IFN-gamma were induced by DDA:TDB liposomes, and liposome uptake by macrophages in vitro was also shown to be higher for DDA:TDB liposomes compared to their cholesterol-containing counterparts, suggesting that small changes in bilayer mechanics can impact both cellular interactions and immune responses. © 2013 American Chemical Society.

Effect of incorporating cholesterol into DDA:TDB liposomal adjuvants on Bilayer properties, biodistribution, and immune responses

Cholesterol is an abundant component of mammalian cell membranes and has been extensively studied as an artificial membrane stabilizer in a wide range of phospholipid liposome systems. In this study, the aim was to investigate the role of cholesterol in cationic liposomal adjuvant system based on dimethyldioctadecylammonium (DDA) and trehalose 6,6'-dibehenate (TDB) which has been shown as a strong adjuvant system for vaccines against a wide range of diseases. Packaging of cholesterol within DDA:TDB liposomes was investigated using differential scanning calorimetery and surface pressure-area isotherms of lipid monolayers; incorporation of cholesterol into liposomal membranes promoted the formation of a liquid-condensed monolayer and removed the main phase transition temperature of the system, resulting in an increased bilayer fluidity and reduced antigen retention in vitro. In vivo biodistribution studies found that this increase in membrane fluidity did not alter deposition of liposomes and antigen at the site of injection. In terms of immune responses, early (12 days after immunization) IgG responses were reduced by inclusion of cholesterol; thereafter there were no differences in antibody (IgG, IgG1, IgG2b) responses promoted by DDA:TDB liposomes with and without cholesterol. However, significantly higher levels of IFN-gamma were induced by DDA:TDB liposomes, and liposome uptake by macrophages in vitro was also shown to be higher for DDA:TDB liposomes compared to their cholesterol-containing counterparts, suggesting that small changes in bilayer mechanics can impact both cellular interactions and immune responses. © 2013 American Chemical Society.

A novel approach to modelling and exploiting uncertainty in stochastic control systems

We consider an inversion-based neurocontroller for solving control problems of uncertain nonlinear systems. Classical approaches do not use uncertainty information in the neural network models. In this paper we show how we can exploit knowledge of this uncertainty to our advantage by developing a novel robust inverse control method. Simulations on a nonlinear uncertain second order system illustrate the approach.