Common bacterial blight CBB, caused by Xanthomonas axonopodis pv. phaseoli, is an important disease of common bean (Phaseolus vulgaris L.). Genetic resistance is the most economically-efficient, environmentally-friendly, and socially-acceptable approach to control plant diseases including CBB. To examine the main and interaction effects of the previously-identified CBB-resistance quantitative trait loci (QTL), a resistant inter-cross population of OAC Rex and HR45 was evaluated under artificial inoculation. While the QTL on chromosome B6 of HR45 accounted for 37 to 46 % of phenotypic variation in the field, the QTL on chromosome B4 of OAC Rex was only significant in more sensitive assays using image analysis under controlled condition using a select number of lines, accounting for 15% of the variation. Broad sense heritability estimates of CBB resistance and the QTL associated with BC420 were high for severity and the area under disease progress curve, promoting the continued use of this marker in selecting CBB resistant genotypes, which in combination with SU91 marker on B8 seem to provide high levels of resistance.

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Photochromic Molecular Flow Visualization is an in vitro, experimental technique that uses high speed image acquisition combined with an ultraviolet laser to capture instantaneous flow profiles. It is particularly adept at measuring near wall velocities which are necessary for accurate wall shear rate measurements. This thesis describes the implementation and validation of the technique at McGill. The system was used to investigate the wall shear rate patterns in an idealized 50% asymmetric stenosis model under steady flow for Reynolds numbers 206, 99 and 50. A large recirculation zone with flow reattachment was seen downstream of the stenosis with maximum shear values occurring slightly upstream of peak stenosis for Reynolds number 206. This information is vital to ongoing dynamic cell culture experiments aimed at understanding the progression of atherosclerosis.

This thesis focuses on super resolution STED optical imaging. STED provides a wealth of new informational content to the acquired images by using stimulated emission to surpass the diffraction limit in optical fluorescence microscopy. To further increase the informational content, a new method to perform multicolor STED imaging by exploiting differences in the photostability and excitation spectra of dyes is presented. In order to extract information from the images, computational algorithms which handle the new type of high resolution informational content are developed. We propose that multicolor super resolution imaging in combination with image analysis can reduce the amount of clinical samples required to perform accurate cancer diagnosis. To date, such diagnosis is based mainly on significant amounts of tissue samples extracted from the suspected tumor site. The sample extraction often requires anesthetics and can lead to complications such as hematoma, infections and even cancer cell ceding along the needle track. We show that by applying multicolor STED and image analysis, the information gained from single cells is greatly increased. We therefore propose that accurate diagnosis can be based on significantly less extracted tissue material, allowing for a more patient friendly sampling. This approach can also be applied when studying blood platelets, where we show how the high informational content can be used to identify platelet specific activational states. Since platelets are involved in many different types of diseases, such analysis could provide means of performing truly minimally invasive diagnostics based on a simple blood test. In addition, our data makes it possible to understand in finer detail the underlying mechanisms rendering cells metastasis competent. We combine the high resolution spatial information provided by STED with information regarding the adhesive forces of cells measured by TFM (Traction Force Microscopy) and the cell stiffness measured by AFM (Atomic Force Microscopy). Such comparisons provide a link between the specific highly resolved protein distributions and different cellular mechanics and functions. This thesis also includes STED imaging and analysis on the spatial organization of neuronal synaptic regulating proteins, implicating the speed with which neuronal signaling can be regulated. / <p>QC 20140207</p>

Rehabilitation of landfill sites is important for successful land utilization. Revegetation is one key element of the process since it can overcome aesthetic problems. The inimical challenges of landfill leachate and gas are largely responsible for the difficulties associated with the revegetation of completed sites. Many components of landfill leachate can be catabolized by microbial associations thereby reducing their impacts on the environment. The importance of research on interactions between pollutants, microorganisms and soil is its applicability in environmental risk assessment and impact studies of organic pollutants which enter the soil either accidentally or intentionally. The application of image analysis with microscopy techniques to landfill soil-pollution interactions provides a means to study surface microbiology directly and to investigate microbial cells under highly controlled conditions. This research focused on the development of a method to study the real time processes of attachment, establishment, growth and division of microbial cells/associations in site covering soils. Image analysis provides a powerful tool for differential quantification of microbial number, identification of morphotypes and their respective responses to microenvironment changes. This minimal disturbance technique of examining visually complex images utilizes the spatial distributions and metabolic sensitivities of microbial species. It was, therefore, used to examine hexanoic acid catabolizing species, both free-living and in a biofilm, with respect to obviating the threat of hexanoic acid to reclamation strategies. The three sources of inoculum (soil cover, soil from the landfill base liner and municipal refuse) were compared for their ability to provide associations which catabolized the substrate rapidly. During the enrichment programme the inocula were challenged with different concentrations of hexanoic acid, a common landfill intermediate. From the rates at which the substrate was catabolized conclusions were drawn on which concentration of hexanoate facilitated the fastest enrichment. The results of initial batch culture enrichments confirmed that the soil used contained microbial associations capable of catabolizing hexanoic acid at concentrations < 50mM, a key leachate component. Exposing the landfill top soil microorganisms to a progressive increase in hexanoic acid concentration ensured that catabolic populations developed which, in situ, should reduce the phytotoxic threat to plants subsequently grown on the landfill cover. The analysis of surface colonization was simplified by examining the initial growth on newly-exposed surfaces. The microbial associations generated complex images which were visually difficult to quantify. Nevertheless, the dimensional and morphological exclusions which were incorporated in the image analysis software permitted the quantification of selected components of the associations although morphology alone was inadequate to confirm identification. The effects of increasing the dilution rate and substrate concentration on the growth of surface-attached associations in Continuous Culture Microscopy Units (CCMUs) were examined. Of the five dilution rates examined the most extensive biofilm development (9.88 jum2) during the selected time period (72h) resulted at a dilution rate of 0.5h' (at 10mM hexanoic acid). The highest growth (608 microorganisms.field"1) was recorded in the presence of 50mM hexanoic acid (D = 0.5h"1). To ensure that the different morphotypes of the associations were able to multiply under the defined conditions a detailed investigation of the component morphotypes was made. Numerically, after 60h of open culture cultivation in the presence of 50mM hexanoic acid, rods were the predominant bacterial morphotypes (43.74 field'1) in the biofilms. Both rods and cocci were distributed throughout the CCMUs whereas the less numerous fungal hyphae (0.25 field'1) were concentrated near the effluent port. The specific growth rates of the surface-attached associations and the component morphotypes were determined by area (//m2) colonized and number of microorganisms.field"' and compared to aerobic planktonic landfill associations. From area determinations ( > 0.16 h'1) and the number of microorganisms.field"1 10mM hexanoic acid was found to support the highest specific growth rate ( > 0.05 h"1) of the surfaceattached association isolated from municipal refuse. With optical density determinations, the highest specific growth rate (0.01 h'1) was recorded with 25mM hexanoic acid. The surface-attached microbial associations component species determinations by area and number showed that the hyphae had the highest specific growth rate ( > 0.11 h"1). The surface-attached microbial association specific growth rate determinations from the discriminated phase (0.023 h'1), area colonized (0.023 h"1) and number of microorganisms (0.027 h"1) calculated from the results of the component species rather than the association should give more accurate results. The specific growth rate obtained differed depending on the method of determination. Any one of these may be the "correct" answer under the cultivation conditions. Depending on the state (thickness) of the association (free-living, monolayer or thick biofilm) the different monitoring methods may be employed to determine the growth. As a consequence of the results of this study, the kinetics of microbial colonization of surfaces in situ may be subjected to the same degree of mathematical analysis as the kinetics of homogeneous cultures. This type of analysis is needed if quantitative studies of microbial growth are to be extended to surfaces in various natural and artificial environments. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 1998.

The aim of this study is to compare remote sensing methods in the context of a vegetation mapping of an urban environment. The methods used was (1) a traditional per-pixel based method; maximum likelihood supervised classification (ENVI), (2) a standard object based method; example based feature extraction (ENVI) and (3) a newly developed method; Window Independent Contextual Segmentation (WICS) (Choros Cognition). A four-band SPOT5 image with a pixel size of 10x10m was used for the classifications. A validation data-set was created using a ortho corrected aerial image with a pixel size of 1x1m. Error matrices was created by cross-tabulating the classified images with the validation data-set. From the error matrices, overall accuracy and kappa coefficient was calculated. The object-based method performed best with a overall accuracy of 80% and a kappa value of 0.6, followed by the WICS method with an overall accuracy of 77% and a kappa value of 0.53, placing the supervised classification last with an overall accuracy of 71% and a kappa value of 0.38. The results of this study suggests object-based method and WICS to perform better than the supervised classification in an urban environment.

Histopathological classification and grading of biopsy specimens play an important role in early cancer detection and prognosis. Nottingham Grading System (NGS) is one of the standard grading procedures used in breast cancer assessment, where three parameters, Mitotic Count (MC), Nuclear Pleomorphism (NP), and Tubule Formation (TF) are used for prognostic information. The grading takes into account the deviations in cellular structures and appearance between tumour and normal cells, using measures such as density, size, colour, and regularity. Cell structures in tissue images are also known to exhibit multifractal characteristics. This research focused on the multifractal properties of several graded biopsy specimens and analysed the dependency and variation of the fractal parameters with respect to the scores pre-assigned by pathologists. The effectiveness of using multifractal techniques on breast cancer grading was measured with a set of quantitative evaluations for MC, NP, and TF criteria. The developed method for MC scoring has obtained 82.87% true positive rate on detecting mitotic cells. Furthermore, the overall positive classification rates for NP and TF analysis were 67.38% and 71.82%, respectively, while obtaining 30.26% of false classification rate for NP analysis and 27.17% for TF analysis. The results have shown that multifractal formalism is a feasible and novel method that could be used for automatic grading of biopsy sections.

The detailed structure of the myofibrillar material in fibres from different muscles has been studied. Specimens have been obtained from human muscles and from different muscles frequently examined in experimental studies. Both light- and electron microscopical techniques have been used. Of central importance has been the method, which makes it possible to prepare ultrathin sections of frozen tissue, i.e. cryo-ult- ramicrotomy. A number of techniques for image analysis have been applied in order to obtain objektive data from the micrographs. In Paper I the present knowledge about muscle fibre structure, cryo-- sectioning and image analysis is summarized and relevant methodological problems are discussed. Paper II describes the detailed structure of the C-zone of the A-band and shows, above all, that structures occur with different repeats along the long axis of the myofibril. Paper III describes the subcellular organization of different fibres in a homogeneous (based on enzyme histochemical mATPase) population, and shows that different structural characteristies can vary independently of each other. Paper IV describes the structural diversity of the myofibrillar M-band, and paper V the diversity of the myofilament fine structure in different fibres. The results show that there is a most sophisticated, and previosly unrealized, structural specialization both within the myofibrils and between myofibrils from different fibres and muscles, even if the fibres are of the same fibre type. The findings suggest that generally used models, showing the structural organization within myofibrils and myofilaments, are oversimplifications. The fibre population is more heterogeneously built up than the common systems for fibre type classification makes one to belive. / <p>Diss. (sammanfattning) Umeå : Umeå universitet, 1988, härtill 5 uppsatser.</p> / digitalisering@umu

Closely packed myosin filaments are an example of a disordered biological array responsible for the contraction of muscle. X-ray fiber diffraction data is used to study these biomolecular assemblies but the inherent disorder in muscle makes interpretation of the diffraction data difficult. Limited knowledge of the precise nature of the myosin lattice disorder and its effects on X-ray diffraction data is currently limiting advances in studies on muscle structure and function. This thesis covers theoretical and computational efforts to incorporate the myosin lattice disorder in X-ray diffraction analysis. An automated image analysis program is developed to rapidly and accurately quantitate the disorder from electron micrographs of muscle cross-sections. The observed disorder is modelled as an antiferromagnetic Ising model and the model verified using Monte Carlo simulations. Theory and methods are developed for efficient calculation of cylindrically averaged X-ray diffraction from two-dimensional lattices that incorporate this disorder.

Genitourinary cancer refers to the presence of tumours in the genital or urinary organs such as bladder, kidney and prostate. In 2008 the worldwide incidence of bladder cancer was 382,600 with a mortality of 150,282. Radiotherapy is one of the main treatment choices for genitourinary cancer where accurate delineation of the gross tumour volume (GTV) on computed tomography (CT) images is crucial for the success of this treatment. Limited CT resolution and contrast in soft tissue organs make this difficult and has led to significant inter- and intra- clinical variability in defining the extent of the GTV, especially at the junctions of different organs. In addition the introduction of new imaging techniques and modalities has significantly increased the number of the medical images that require contouring. More advanced image processing is required to help reduce contouring variability and assist in handling the increased volume of data. In this thesis image analysis methodologies were used to extract low-level features such as entropy, moment and correlation from radiotherapy planning CT images. These distinctive features were identified and used for defining the GTV and to implement a fully-automatic contouring system. The first key contribution is to demonstrate that second-order statistics from co-occurrence matrices (GTSDM) give higher accuracy in classifying soft tissue regions of interest (ROIs) into GTV and non-GTV. Loadings of the principal components (PCs) of the GTSDM features were found to be consistent over different patients. Exhaustive feature selection suggested that entropies and correlations produced consistently larger areas under receiver operating characteristic (AUROC) curves than first-order features. The second significant contribution is to demonstrate that in the bladder-prostate junction, where the largest inter-clinical variability is observed, the second-order principal entropy from stationery wavelet denoised CT images (DPE) increased the saliency of the bladder prostate junction. As a result thresholding of the DPE produced good agreement between gold standard clinical contours and those produced by this approach with Dice coefficients. The third contribution is to implement a fully automatic and reproducible system for bladder cancer GTV auto-contouring based on classifying second-order statistics. The Dice similarity coefficients (DSCs) were employed to evaluate the automatic contours. It was found that in the mid-range of the bladder the automatic contours are accurate, but in the inferior and superior ends of bladder automatic contours were more likely to have small DSCs with clinical contours, which reconcile with the fact of clinical variability in defining GTVs. A novel male bladder probability atlas was constructed based on the clinical contours and volume estimation from the classification results. Registration of the classification results with this probabilistic atlas consistently increases the DSCs of the inferior slices.