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 objective of the study is to demonstrate the predictive ability is better between the logistic regression model and Linear Discriminant function using the original data first and then the Home vehicles to reduce the dimensions of the variables for data and socio-economic survey of the family to the province of Baghdad in 2012 and included a sample of 615 observation with 13 variable, 12 of them is an explanatory variable and the depended variable is number of workers and the unemployed.
Was conducted to compare the two methods above and it became clear by comparing the logistic regression model best of a Linear Discriminant function written
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A novel demountable shear connector for precast steel‐concrete composite bridges is presented. The connector uses high‐strength steel bolts, which are fastened to the top flange of the steel beam with the aid of a special locking nut configuration that prevents slip of bolts within their holes. Moreover, the connector promotes accelerated construction and overcomes typical construction tolerances issues of precast structures. Most importantly, the connector allows bridge disassembly, and therefore, can address different bridge deterioration scenarios with minimum disturbance to traffic flow, i.e. (i) precast deck panels can be rapidly uplifted and replaced; (ii) connectors can be rapidly removed and replaced; and (iii) steel beams can b
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Medicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
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Objectives: Small field of view gamma detection and imaging technologies for monitoring in vivo tracer uptake are rapidly expanding and being introduced for bed-side imaging and image guided surgical procedures. The Hybrid Gamma Camera (HGC) has been developed to enhance the localization of targeted radiopharmaceuticals during surgical procedures; for example in sentinel lymph node (SLN) biopsies and for bed-side imaging in procedures such as lacrimal drainage imaging and thyroid scanning. In this study, a prototype anthropomorphic head and neck phantom has been designed, constructed, and evaluated using representative modelled medical scenarios to study the capability of the HGC to detect SLNs and image small organs. Methods: An anthropom
... Show MoreIn this research, titanium dioxide nanoparticles (TiO2 NPs) were prepared through the sol-gel process at an acidic medium (pH3).TiO2 nanoparticles were prepared from titanium trichloride (TiCl3) as a precursor with Ammonium hydroxide (NH4OH) with 1:3 ratio at 50 °C. The resulting gel was dried at 70 °C to obtain the Nanocrystalline powder. The powder from the drying process was treated thermally at temperatures 500 °C and 700 °C. The crystalline structure, surface morphology, and particle size were studied by using X-ray diffraction (XRD), Atomic Force Microscopy (AFM), and Scanning Electron Microscope (SEM). The results showed (anatase) phase of titanium dioxide with the average grain size
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Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different
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Solubility problem of many of effective pharmaceutical molecules are still one of the major obstacle in theformulation of such molecules. Candesartan cilexetil (CC) is angiotensin II receptor antagonist with very low water solubility and this result in low and variable bioavailability. Self- emulsifying drug delivery system (SEDDS) showed promising result in overcoming solubility problem of many drug molecules. CC was prepared as SEDDS by using novel combination of two surfactants (tween 80 and cremophore EL) and tetraglycol as cosurfactant, in addition to the use of triacetin as oil. Different tests were performed in order to confirm the stability of the final product which includes thermodynamic study, determination of self-emulsificat
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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The reconciliation of tax reconciliation is one of the legal methods used by the financial authority in Iraq, which is done with the taxpayer
The research dealt with the weakness of tax revenues for many reasons, including tax evasion, which led to the search for ways to reduce evasion to increase the tax revenue, and settlement reconciliation one of these means .
The research proceeded from the premise that the use of a more broadly settled settlement would govern the tax evasion of taxpayers.
The researchers used a series of studies and previous research, books and other sources related to the subject of research, and this was done through the theoretical framework, and the practical aspect that included the fin
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