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
The performance of a synergistic combination of electrocoagulation (EC) and electro-oxidation (EO) for oilfield wastewater treatment has been studied. The effect of operative variables such as current density, pH, and electrolyte concentration on the reduction of chemical oxygen demand (COD) was studied and optimized based on Response Surface Methodology (RSM). The results showed that the current density had the highest impact on the COD removal with a contribution of 64.07% while pH, NaCl addition and other interactions affects account for only 34.67%. The optimized operating parameters were a current density of 26.77 mA/cm2 and a pH of 7.6 with no addition of NaCl which results in a COD removal efficiency of 93.43% and a specific energy c
... Show MorePrediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
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The population is sets of vocabulary common in character or characters and it’s study subject or research . statistically , this sets is called study population (or abridgement population ) such as set of person or trees of special kind of fruits or animals or product any country for any commodity through infinite temporal period term ... etc.
The population maybe finite if we can enclose the number of its members such as the students of finite school grade . and maybe infinite if we can not enclose the number of it is members such as stars or aquatic creatures in the sea . when we study any character for population the statistical data is concentrate by two metho
... Show MoreIn this paper, the error distribution function is estimated for the single index model by the empirical distribution function and the kernel distribution function. Refined minimum average variance estimation (RMAVE) method is used for estimating single index model. We use simulation experiments to compare the two estimation methods for error distribution function with different sample sizes, the results show that the kernel distribution function is better than the empirical distribution function.
This study aims to numerically simulate the flow of the salt wedge by using computational fluid dynamics, CFD. The accuracy of the numerical simulation model was assessed against published laboratory data. Twelve CFD model runs were conducted under the same laboratory conditions. The results showed that the propagation of the salt wedge is inversely proportional to the applied freshwater discharge and the bed slope of the flume. The maximum propagation is obtained at the lowest discharge value and the minimum slope of the flume. The comparison between the published laboratory results and numerical simulation shows a good agreement. The range of the relative error varies between 0 and 16% with an average of 2% and a roo
... Show MoreThe main problem when dealing with fuzzy data variables is that it cannot be formed by a model that represents the data through the method of Fuzzy Least Squares Estimator (FLSE) which gives false estimates of the invalidity of the method in the case of the existence of the problem of multicollinearity. To overcome this problem, the Fuzzy Bridge Regression Estimator (FBRE) Method was relied upon to estimate a fuzzy linear regression model by triangular fuzzy numbers. Moreover, the detection of the problem of multicollinearity in the fuzzy data can be done by using Variance Inflation Factor when the inputs variable of the model crisp, output variable, and parameters are fuzzed. The results were compared usin
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