Varied Immune Response to FVIII: Presence of Proteolytic Antibodies Directed to Factor VIII in Different Human Pathologies

The versatility of antibodies is demonstrated by the various functions that they mediate such as neutralization, agglutination, fixation of the complement and its activation, and activation of effector cells. In addition to this plethora of functions, antibodies are capable of expressing enzymatic activity. Antibodies with catalytic function are a result of the productive interplay between the highly evolved machinery of the immune system and the chemical framework used to induce them (antigens). Catalytic antibodies are immunoglobulins with an ability to catalyze the reactions involving the antigen for which they are specific. Catalytic immunoglobulins of the IgM and IgG isotypes have been detected in the serum of healthy donors. In addition, catalytic immunoglobulins of the IgA isotype have been detected in the milk of healthy mothers. Conversely, antigen-specific hydrolytic antibodies have been reported in a number of inflammatory, autoimmune, and neoplastic disorders. The pathophysiological occurrence and relevance of catalytic antibodies remains a debated issue. Through the description of the hydrolysis of coagulation factor VIII as model target antigen, we propose that catalytic antibodies directed to the coagulation factor VIII may play a beneficial or a deleterious role depending on the immuno-inflammatory condition under which they occur.

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.

Symposium: Food pricing and affordability of ‘healthy’ versus ‘less healthy’ diets: An international approach to monitoring and surveillance

Symposium co-ordinated by The International Network for Food and Obesity/NCDs Research, Monitoring and Action Support (INFORMAS) Purpose Global monitoring of the price and affordability of foods, meals and diets is urgently needed. There are major methodological challenges in developing robust, cost-effective, standardized, and policy relevant tools, pertinent to nutrition, obesity, and diet-related non-communicable diseases and their inequalities. There is increasing pressure to take into account environmental sustainability. Changes in price differentials and affordability need to be comparable between and within countries and over time. Robust tools could provide baseline data for monitoring and evaluating structural, economic and social policies at the country/regional and household levels. INFORMAS offers one framework for consideration.

Unmanned Aerial Vehicles (UAVs) and artificial intelligence revolutionizing wildlife monitoring and conservation

Surveying threatened and invasive species to obtain accurate population estimates is an important but challenging task that requires a considerable investment in time and resources. Estimates using existing ground-based monitoring techniques, such as camera traps and surveys performed on foot, are known to be resource intensive, potentially inaccurate and imprecise, and difficult to validate. Recent developments in unmanned aerial vehicles (UAV), artificial intelligence and miniaturized thermal imaging systems represent a new opportunity for wildlife experts to inexpensively survey relatively large areas. The system presented in this paper includes thermal image acquisition as well as a video processing pipeline to perform object detection, classification and tracking of wildlife in forest or open areas. The system is tested on thermal video data from ground based and test flight footage, and is found to be able to detect all the target wildlife located in the surveyed area. The system is flexible in that the user can readily define the types of objects to classify and the object characteristics that should be considered during classification.

Enhancement of immune response by the proteinaceous crystal of Bacillus thuringiensis Var thuringiensis

The proteinaceous crystal of Bacillus thuringiensis Var thuringiensis was found to enhance humoral immune response in rats and guinea pigs immunised with sheep red blood cells. The enhancement was due to the increased levels of both 19S and 7S antibodies in the sera of the treated animals. A novel synthesis of 7S haemolytic antibodies was observed in case of crystal treated animals.

Incorporating the interrelationship between primary and support processes in monitoring and optimising longwall coal mining efficiency

This thesis increased the researchers understanding of the relationship between operations and maintenance in underground longwall coal mines, using data from a Queensland underground coal mine. The thesis explores various relationships between recorded variables. Issues with human recorded data was uncovered, and results emphasised the significance of variables associated with conveyor operation to explain production.

Causes and consequences of variation in nestling immune function

Defence against pathogens is a vital need of all living organisms that has led to the evolution of complex immune mechanisms. However, although immunocompetence the ability to resist pathogens and control infection has in recent decades become a focus for research in evolutionary ecology, the variation in immune function observed in natural populations is relatively little understood. This thesis examines sources of this variation (environmental, genetic and maternal effects) during the nestling stage and its fitness consequences in wild populations of passerines: the blue tit (Cyanistes caeruleus) and the collared flycatcher (Ficedula albicollis). A developing organism may face a dilemma as to whether to allocate limited resources to growth or to immune defences. The optimal level of investment in immunity is shaped inherently by specific requirements of the environment. If the probability of contracting infection is low, maintaining high growth rates even at the expense of immune function may be advantageous for nestlings, as body mass is usually a good predictor of post-fledging survival. In experiments with blue tits and haematophagous hen fleas (Ceratophyllus gallinae) using two methods, methionine supplementation (to manipulate nestlings resource allocation to cellular immune function) and food supplementation (to increase resource availability), I confirmed that there is a trade-off between growth and immunity and that the abundance of ectoparasites is an environmental factor affecting allocation of resources to immune function. A cross-fostering experiment also revealed that environmental heterogeneity in terms of abundance of ectoparasites may contribute to maintaining additive genetic variation in immunity and other traits. Animal model analysis of extensive data collected from the population of collared flycatchers on Gotland (Sweden) allowed examination of the narrow-sense heritability of PHA-response the most commonly used index of cellular immunocompetence in avian studies. PHA-response is not heritable in this population, but is subject to a non-heritable origin (presumably maternal) effect. However, experimental manipulation of yolk androgen levels indicates that the mechanism of the maternal effect in PHA-response is not in ovo deposition of androgens. The relationship between PHA-response and recruitment was studied for over 1300 collared flycatcher nestlings. Multivariate selection analysis shows that it is body mass, not PHA-response, that is under direct selection. PHA-response appears to be related to recruitment because of its positive relationship with body mass. These results imply that either PHA-response fails to capture the immune mechanisms that are relevant for defence against pathogens encountered by fledglings or that the selection pressure from parasites is not as strong as commonly assumed.

Immune response to insulin and changes in the gut immune system in children with or at risk for type 1 diabetes

Type 1 diabetes (T1D) is considered to be an autoimmune disease. The cause of T1D is the destruction of insulin-producing β-cells in the pancreatic islets. The autoimmune nature of T1D is characterized by the presence of autoreactive T-cells and autoantibodies against β-cell molecules. Insulin is the only β-cell-specific autoantigen associated with T1D but the insulin autoantibodies (IAAs) are difficult to measure with proper sensitivity. T-cell assays for detection of autoreactive T-cells, such as insulin-specific T-cells, have also proven to be difficult to perform. The genetic risk of T1D is associated with the HLA gene region but the environmental factors also play an important role. The most studied environmental risk factors of T1D are enteroviruses and cow's milk which both affect the immune system through the gut. One hypothesis is that the insulin-specific immune response develops against bovine insulin in cow's milk during early infancy and later spreads to include human insulin. The aims of this study were to determine whether the separation of immunoglobulin (Ig)G from plasma would improve the sensitivity of the IAA assay and how insulin treatment affects the cellular immune response to insulin in newly diagnosed patients. Furthermore, the effect of insulin concentration in mother's breast milk on the development of antibodies to dietary insulin in the child was examined. Small intestinal biopsies were also obtained from children with T1D to characterize any immunological changes associated with T1D in the gut. The isolation of the IgG fraction from the plasma of T1D patients negative for plasma IAA led to detectable IAA levels that exceeded those in the control children. Thus the isolation of IgG may improve the sensitivity of the IAA assay. The effect of insulin treatment on insulin-specific T-cells was studied by culturing peripheral blood mononuclear cells with insulin. The insulin stimulation induced increased expression of regulatory T-cell markers, such as Foxp3, in those patients treated with insulin than in patients examined before initiating insulin treatment. This finding suggests that insulin treatment in patients with T1D stimulates regulatory T-cells in vivo and this may partly explain the difficulties in measuring autoantigen-specific T-cell responses in recently diagnosed patients. The stimulation of regulatory T-cells by insulin treatment may also explain the remission period often seen after initiating insulin treatment. In the third study we showed that insulin concentration in mother's breast milk correlates inversely with the levels of bovine insulin-specific antibodies in those infants who were exposed to cow's milk proteins in their diet, suggesting that human insulin in breast milk induces tolerance to dietary bovine insulin. However, in infants who later developed T1D-associated autoantibodies, the insulin concentration in their mother's breast milk was increased. This finding may indicate that in those children prone to β-cell autoimmunity, breast milk insulin does not promote tolerance to insulin. In the small intestinal biopsies the presence of several immunological markers were quantified with the RT-PCR. From these markers the expression of the interleukin (IL)-18 cytokine was significantly increased in the gut in patients with T1D compared with children with celiac disease or control children. The increased IL-18 expression lends further support for the hypothesis that the gut immune system is involved in the pathogenesis of T1D.

Microbe-induced Innate Immune Responses in Human Dendritic Cells

Two types of antigen-presenting cells (APCs), macrophages and dendritic cells (DCs), function at the interface of innate and adaptive immunity. Through recognition of conserved microbial patterns, they are able to detect the invading pathogens. This leads to activation of signal transduction pathways that in turn induce gene expression of various molecules required for immune responses and eventually pathogen clearance. Cytokines are among the genes induced upon detection of microbes. They play an important role in regulating host immune responses during microbial infection. Chemotactic cytokines, chemokines, are involved in migratory events of immune cells. Cytokines also promote the differentiation of distinct T cell responses. Because of the multiple roles of cytokines in the immune system, the cytokine network needs to be tightly regulated. In this work, the induction of innate immune responses was studied using human primary macrophages or DCs as cell models. Salmonella enterica serovar Typhimurium served as a model for an intracellular bacterium, whereas Sendai virus was used in virus experiments. The starting point of this study was that DCs of mouse origin had recently been characterized as host cells for Salmonella. However, only little was known about the immune responses initiated in Salmonella-infected human DCs. Thus, cellular responses of macrophages and DCs, in particular the pattern of cytokine production, to Salmonella infection were compared. Salmonella-induced macrophages and DCs were found to produce multiple cytokines including interferon (IFN) -gamma, which is conventionally produced by T and natural killer (NK) cells. Both macrophages and DCs also promoted the intracellular survival of the bacterium. Phenotypic maturation of DCs as characterized by upregulation of costimulatory and human leukocyte antigen (HLA) molecules, and production of CCL19 chemokine, were also detected upon infection with Salmonella. Another focus of this PhD work was to unravel the regulatory events controlling the expression of cytokine genes encoding for CCL19 and type III IFNs, which are central to DC biology. We found that the promoters of CCL19 and type III IFNs contain similar regulatory elements that bind nuclear factor kappaB (NF-kappaB) and interferon regulatory factors (IRFs), which could mediate transcriptional activation of the genes. The regulation of type III IFNs in virus infection resembled that of type I IFNs a cytokine class traditionally regarded as antiviral. The induction of type I and type III IFNs was also observed in response to bacterial infection. Taken together, this work identifies new details about the interaction of Salmonella with its phagocytic host cells of human origin. In addition, studies provide information on the regulatory events controlling the expression of CCL19 and the most recently identified IFN family genes, type III IFN genes.

Dynamics of Finnish starlings in 1951-2005 : from monitoring to population modelling

Farmland bird species have been declining in Europe. Many declines have coincided with general intensification of farming practices. In Finland, replacement of mixed farming, including rotational pastures, with specialized cultivation has been one of the most drastic changes from the 1960s to the 1990s. This kind of habitat deterioration limits the persistence of populations, as has been previously indicated from local populations. Integrated population monitoring, which gathers species-specific information of population size and demography, can be used to assess the response of a population to environment changes also at a large spatial scale. I targeted my analysis at the Finnish starling (Sturnus vulgaris). Starlings are common breeders in farmland habitats, but severe declines of local populations have been reported from Finland in the 1970s and 1980s and later from other parts of Europe. Habitat deterioration (replacement of pasture and grassland habitats with specialized cultivation areas) limits reproductive success of the species. I analysed regional population data in order to exemplify the importance of agricultural change to bird population dynamics. I used nestling ringing and nest-card data from 1951 to 2005 in order to quantify population trends and per capita reproductive success within several geographical regions (south/north and west/east aspects). I used matrix modelling, acknowledging age-specific survival and fecundity parameters and density-dependence, to model population dynamics. Finnish starlings declined by 80% from the end of the 1960s up to the end of the 1980s. The observed patterns and the model indicated that the population decline was due to the decline of the carrying capacity of farmland habitats. The decline was most severe in north Finland where populations largely become extinct. However, habitat deterioration was most severe in the southern breeding areas. The deteriorations in habitat quality decreased reproduction, which finally caused the decline. I suggest that poorly-productive northern populations have been partly maintained by immigration from the highly-productive southern populations. As the southern populations declined, ceasing emigration caused the population extinction in north. This phenomenon was explained with source sink population dynamics, which I structured and verified on the basis of a spatially explicit simulation model. I found that southern Finnish starling population exhibits ten-year cyclic regularity, a phenomenon that can be explained with delayed density-dependence in reproduction.

Functional genes and gene array analysis as tools for monitoring hydrocarbon biodegradation

Bioremediation, which is the exploitation of the intrinsic ability of environmental microbes to degrade and remove harmful compounds from nature, is considered to be an environmentally sustainable and cost-effective means for environmental clean-up. However, a comprehensive understanding of the biodegradation potential of microbial communities and their response to decontamination measures is required for the effective management of bioremediation processes. In this thesis, the potential to use hydrocarbon-degradative genes as indicators of aerobic hydrocarbon biodegradation was investigated. Small-scale functional gene macro- and microarrays targeting aliphatic, monoaromatic and low molecular weight polyaromatic hydrocarbon biodegradation were developed in order to simultaneously monitor the biodegradation of mixtures of hydrocarbons. The validity of the array analysis in monitoring hydrocarbon biodegradation was evaluated in microcosm studies and field-scale bioremediation processes by comparing the hybridization signal intensities to hydrocarbon mineralization, real-time polymerase chain reaction (PCR), dot blot hybridization and both chemical and microbiological monitoring data. The results obtained by real-time PCR, dot blot hybridization and gene array analysis were in good agreement with hydrocarbon biodegradation in laboratory-scale microcosms. Mineralization of several hydrocarbons could be monitored simultaneously using gene array analysis. In the field-scale bioremediation processes, the detection and enumeration of hydrocarbon-degradative genes provided important additional information for process optimization and design. In creosote-contaminated groundwater, gene array analysis demonstrated that the aerobic biodegradation potential that was present at the site, but restrained under the oxygen-limited conditions, could be successfully stimulated with aeration and nutrient infiltration. During ex situ bioremediation of diesel oil- and lubrication oil-contaminated soil, the functional gene array analysis revealed inefficient hydrocarbon biodegradation, caused by poor aeration during composting. The functional gene array specifically detected upper and lower biodegradation pathways required for complete mineralization of hydrocarbons. Bacteria representing 1 % of the microbial community could be detected without prior PCR amplification. Molecular biological monitoring methods based on functional genes provide powerful tools for the development of more efficient remediation processes. The parallel detection of several functional genes using functional gene array analysis is an especially promising tool for monitoring the biodegradation of mixtures of hydrocarbons.

Time reversal technique for health monitoring of metallic structure using Lamb waves

Time reversal active sensing using Lamb waves is investigated for health monitoring of a metallic structure. Experiments were conducted on an aluminum plate to study the time reversal behavior of A(0) and S-0 Lamb wave modes under narrow band and broad band pulse excitation. Damage in the form of a notch was introduced in the plate to study the changes in the characteristics of the time reversed Lamb wave modes experimentally. Time-frequency analysis of the time reversed signal was carried out to extract the damage information. A measure of damage based on wavelet transform was derived to quantify the hidden damage information in the time reversed signal. It has been shown that time reversal can be used to achieve temporal recompression of Lamb waves under broadband signal excitation. Further, the broad band excitation can also improve the resolution of the technique in detecting closely located defects. This is demonstrated by picking up the reflection of waves from the edge of the plate, from a defect close to the edge of the plate and from defects located near to each other. This study shows the effectiveness of Lamb wave time reversal for temporal recompression of dispersive Lamb waves for damage detection in health monitoring applications. (C) 2009 Elsevier B.V. All rights reserved.

Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques

In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.