Abstract Candida albicans is a commensal fungal pathogen that grows in yeast and hyphal forms in the human gut. C. albicans causes mucosal and cutaneous diseases that can result in significant mortality following systematic infections and it also exhibits drug resistance. Zebrafish have been an excellent model to investigate C. albicans infections because of their transparency and the availability of many transgenic lines. However, there is a limitation in using zebrafish as a model because the fish embryos cannot survive at 37°C therefore it is not suitable for studying Candida infections at physiological relevant human body temperature. In this thesis, the normal embryonic development of Arabian killifish (A. dispar) is investigated, revealing that embryogenesis was divided into 32 stages based on diagnostic patterns of development. A. dispar can also found to tolerate a wide range of temperatures and salinities. This suggests that A. dispar could be developed as a novel model to investigate host-pathogen interactions. The tolerance of A. dispar to high temperatures may in part be attributable to brown pigment cells with a highly fluorescent character that may have developed to allow the fish to adapt to live within extreme environmental conditions with strong sunlight and a wide range of temperatures (Chapter 3). In terms of Candida infections, this study examined A. dispar as a model to test C. albicans pathogenicity. The survival of A. dispar embryos following Candida infection showed a dose dependent relationship. We also found that A. dispar can survive longer than zebrafish after infection. Furthermore, C. albicans cells were observed to undergo a transition from yeast to hyphae at 37°C. An investigation of the ability of mutant strains of C. albicans with defects in cell wall mannosylation revealed a significant impact on virulence, host mortality, and the fishes’ immune response. The present study found that although the deletion of O- and N-mannan from the cell wall of C. albicans, affected fungal burden (attenuation), and the survival of the infected embryos per se was significantly decreased in the infections of the mutant strains compared to the WT. This data confirms the importance of the mannosylation state of the cell wall in triggering an immune recognition event (Chapter 4). A. dispar is also shown to be suitable for studying the effectiveness of 3 | P a g e antifungals. Fluconazole treatment of infected embryos and eggs promoted greater rates of survival at high doses, alongside a significant reduction of C. albicans CFUs (Chapter 4). When looking at the Candida-host interaction, we directly observed phagocytosed yeast cells within macrophages. Various detection methods were used to follow macrophages and neutrophils including Western blotting, immunostaining and histological staining (Sudan black and FITC-tyramide) allowing the monitoring of the time course of the immune cells. A biphasic response of macrophages was detected by L-plastin Western blotting, suggesting activation of two different type of macrophage: activated macrophage (M1) and alternative macrophage (M2). We also assayed reactive oxygen species (ROS) within infected embryos using a fluorescent probe (H2DCFDA), revealing the accumulation of the fluorescent probe at the sites of infection. Quantitative and qualitative analyses of the oxidative and immune response using the H2DCFDA and qPCR were also accomplished within A. dispar embryos after infection with both the WT and mutant strains of Candida albicans (WT, pmr1∆, mnt1-mnt2∆, and och1∆). The results confirmed that the mutant strains did not activate a host oxidative stress response nor immune cell accumulation when compared to WT, suggesting that the immune response is less activated against these mutants. Finally, a new transgenic line of A. dispar fish was developed using Betaactin-DsR-LoxP-GFP. The new transgenic A. dispar is suggested to be an ideal model for real time observation of host-pathogen interactions and for investigation of molecular functions of the immune response. Overall these results improve our understanding of the use of a new transparent fish model to study fungal pathogenesis and demonstrates the potential advantages of using this species in future studies of bacterial, fungal and viral pathogens at a physiologically relevant temperature for human infection. Such a model could lead us to investigate in more depth the key interactions between pathogens and their host and permit the screening and development of new antifungal therapies (that might target the pathogens directly or target the host immune system). View full metadata
Abstract
In this study, we compare between the autoregressive approximations (Yule-Walker equations, Least Squares , Least Squares ( forward- backword ) and Burg’s (Geometric and Harmonic ) methods, to determine the optimal approximation to the time series generated from the first - order moving Average non-invertible process, and fractionally - integrated noise process, with several values for d (d=0.15,0.25,0.35,0.45) for different sample sizes (small,median,large)for two processes . We depend on figure of merit function which proposed by author Shibata in 1980, to determine the theoretical optimal order according to min
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The result of a developed mathematical model for predicting the design
parameters of the fiber Raman amplifier (FRA) are demonstrated. The amplification
parameters are tested at different pump power with different fiber length. Recently,
the FRA employed in optical communication system to increase the repeater distance
as will as the capacity of the communication systems. The output results show, that
high Raman gain can be achieved by high pumping power, long effective area that
need to be small for high Raman gain. High-stimulated Raman gain coefficient is
recommended for high Raman amplifier gain, the low attenuation of the pump and the
transmitted signal in the fiber lead to high Raman gain.
A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
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Physically based modeling approach has been widely developed in recent years for the simulation of dam failure process due to the lack of field data. This paper provides and describes a physically-based model depending on dimensional analysis and hydraulic simulation methods for estimating the maximum water level and the wave propagation time from breaching of field test dams. The field physical model has been constructed in Dabbah city to represent the collapse of the Roseires dam in Sudan. Five cases of a dam failure were studied to simulate water flood conditions by changing initial water height in the reservoir (0.8, 1.0, 1.2, 1.4 and 1.5 m respectively).The physical model working under five cases, case 5 had the greatest influence of t
... Show MoreIn this paper, a discussion of the principles of stereoscopy is presented, and the phases
of 3D image production of which is based on the Waterfall model. Also, the results are based
on one of the 3D technology which is Anaglyph and it's known to be of two colors (red and
cyan).
A 3D anaglyph image and visualization technologies will appear as a threedimensional
by using a classes (red/cyan) as considered part of other technologies used and
implemented for production of 3D videos (movies). And by using model to produce a
software to process anaglyph video, comes very important; for that, our proposed work is
implemented an anaglyph in Waterfall model to produced a 3D image which extracted from a
video.
Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur
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A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twenty four samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
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