Background: Non-host-adapted Salmonella serovar Typhimurium is a facultative intracellular bacterium, which invades and multiplies within mononuclear phagocytes in liver, spleen, lymph nodes and Peyer’s plaques. Salmonella infection is a crucial medical and veterinary problem globally. S. Typhimurium causes various clinical symptoms, from asymptomatic infection to typhoid-like syndromes in infants or highly susceptible animals, for instance mice. Objective: The present study was carried out to investigate the efficacy of anthrax protective antigen (PA)as a potent adjuvant mixed with killed Salmonella Typhimurium (S.T.) to enhance the immunization capacity of the last. Materials and Methods: Two groups of mice were immunized with either the mixture of S.T. and PA or S.T. alone, in addition to a control group immunized with phosphate buffered saline. Skin test and ELISA test were performed to evaluate cell-mediated and humoral immunity, respectively. Results: The mixture group showed the best results in cell-mediated immunity.Furthermore, ELISA reading 14 days from booster dose was higher in the mixture group than S.T. alone. The mixture revealed high Ab titres compared to control or S.T. cohort 53 days from the beginning of immunization.These results were verified by histopathological examination. Conclusions: Our findings suggest anthrax PA as a suitable and robust adjuvant for inactivated Salmonella Typhimurium vaccine in mice.
Genome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id
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A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network
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The current study is concerned with the analysis of spatial and temporal to death the elderly population in the city of Baghdad and at the level of administrative units Minor (districts and the areas) depending on the general population census of the province of Baghdad, data for 1997 and data from the Ministry of Health Department of Health and Vital Statistics for 2013.
The study showed differing age and quality of mortality rates at the level of administrative units of the study area, and notes the high mortality rates of elderly people of all age groups in 2013 compared to 1997, and this is due to security conditions after the USA occupation, and the accompanying conditions have affected the increase in mortality rates.
The tensions and crises and the psychological pressure as well as the rapid changes and great development which is taking place in the present time. And witnessing community of wars and conflicts that give rise to future concern among members of the community in general and students in particular, as it included the current research a number of chapters, the First chapter contains the research problem, the important goal, then set researcher terminology that has defined and contained in the title of research in the form (concern the future, artistic expression, middle school). The Second chapter included three sections, the first included the nature of adolescence and traits, characteristics and pr
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This research aims to present a proposed model for disclosure and documentation when performing the audit according to the joint audit method by using the questions and principles of the collective intelligence system, which leads to improving and enhancing the efficiency of the joint audit, and thus enhancing the confidence of the parties concerned in the outputs of the audit process. As the research problem can be formulated through the following question: “Does the proposed model for disclosure of the role of the collective intelligence system contribute to improving joint auditing?”
The proposed model is designed for the disclosure of joint auditing and the role
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Markov chains are an application of stochastic models in operation research, helping the analysis and optimization of processes with random events and transitions. The method that will be deployed to obtain the transient solution to a Markov chain problem is an important part of this process. The present paper introduces a novel Ordinary Differential Equation (ODE) approach to solve the Markov chain problem. The probability distribution of a continuous-time Markov chain with an infinitesimal generator at a given time is considered, which is a resulting solution of the Chapman-Kolmogorov differential equation. This study presents a one-step second-derivative method with better accuracy in solving the first-order Initial Value Problem
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