Pseudomonas aeruginosa has variety of virulence factors that contribute to its pathogenicity. Therefore, rapid detection with high accuracy and specificity is very important in the control of this pathogenic bacterium. To evaluate the accuracy and specificity of Polymerase Chain Reaction (PCR) assay, ETA and gyrB genes were targeted to detect pathogenic strains of P. aeruginosa. Seventy swab samples were taken from patients with infected wounds and burns in two hospitals in Erbil and Koya cities in Iraq. The isolates were traditionally identified using phenotypic methods, and DNA was extracted from the positive samples, to apply PCR using the species specific primers targeting ETA, the gene encoding for exotoxin A, and gyrB gene. The results of this study indicate that 100% of P. aeruginosa isolates harbored the gyrB gene, whereas 74% of these isolates harbored ETA gene. However, the specificity of PCR for detection of P. aeruginosa based on the both genes was 100%, since no amplified product obtained using DNA extracted from other bacterial species. Hence by considering the importance of rapid detection of this bacterium due to the presence of problems in biochemical methods, PCR targeting multiple virulence genes is suggested in identification of pathogenic strains of P. aeruginosa isolated from some infections which should speed diagnosis of an antimicrobial therapy.
This study was conducted to evaluate the efficacy of 6 isolates of Pseudomonas fluorescens and Trichoderma harzianum and there combination against Fusarium tomato wilt disease caused by Fusarium oxysporum F.sp. Lycopersisi under green house condition .The isolates of bacteria (B3) and Trichoderma (T1) were found to be highly effective in reducing the disease incidence to 13.3% , 21% respectively , compared to control treatment (40%).Furthermore, disease severity was reduced to 28 and 30% respectively in comparison to control (90%) .Colonization of the roots (cfu /g fresh root weight )by the two isolates whether alon or together was extremely high . The combination treatment had a high ability in reducing disease incidenece and sev
... Show MoreAbstractThe objective of the present study was measured of several oxidative stresses and liver function parameters in workers occupationally exposed to cement dust in Kufa Cement Factory, in order to test the hypothesis that cement dust exposure may perturb these parameters. Assessment of oxidative stress and liver function parameters were performed in 63 workers occupationally, in different departments of Kufa Cement Factory, exposed to cement dust (range of the exposure time was 5-38 years) and 36 matched unexposed controls. The study results illustrated an increasing in the oxidative stress parameters, moreover; liver function parameters showed abnormal results in the exposed workers compared to the unexposed. An increase in theses para
... Show MoreRecently, young people have shown a desire to keep cats as pets, despite being threatened with health problems including toxoplasmosis. Therefore, the current study was aimed to detect toxoplasmosis infections among of volunteers students as well as spreading health awareness among students and knowledge about the importance of this disease. Prevalence rate and effects of liver functions were tested by measured levels of Aspartate aminotransferase (AST) and Alanine aminotransferase (ALT) enzymes while the OnSiteToxo IgG/IgM combo rapid test was used in the diagnosis of the disease. The blood samples were collected from 76 volunteers (35 male and 41 female). The results showed that, the total percentage of infections was 27.6% and all infect
... Show MoreThe aim of this study was the discrimination of Salmonella isolated from chicken and their feed and drinking water for the epidemiological control of salmonellosis. Totally, 289 samples, including 217 chicken cloaca swabs, 46 water, and 26 feed samples were collected from five different farms in Karbala governorate, Iraq. Conventional bacteriology tests, API 20E, Vitek 2, and serology were used for bacterial identification. Random amplified polymorphic DNA (RAPD)-polymerase chain reaction (PCR) was applied to analyze the genetic relationships among Salmonella isolates. The isolation rate of Salmonella spp. was 21.1% (61/289). While the water samples constituted the highest rate (30.4%), a rate of
... Show MoreOne of the main causes for concern is the widespread presence of pharmaceuticals in the environment, which may be harmful to living things. They are often referred to as emerging chemical pollutants in water bodies because they are either still unregulated or undergoing regulation. Pharmaceutical pollution of the environment may have detrimental effects on ecosystem viability, human health, and water quality. In this study, the amount of remaining pharmaceutical compounds in environmental waters was determined using a straightforward review. Pharmaceutical production and consumption have increased due to medical advancements, leading to concerns about their environmental impact and potential harm to living things due to their increa
... Show MoreClinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision b
Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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