Urinary tract infection is a bacterial infection that often affects the bladder and thus the urinary system. E. coli is one of the leading uropathogenic bacteria that cause urinary tract infections. Uropathogenic E. coli is highly effective and successful in causing urinary tract infections through biofilm formation and urothelial cell invasion mechanisms. Other organisms that cause urinary tract infections include members of the Enterobacteriaceae family, streptococci and staphylococci species and perch. In addition, K.penumoniae is another important gram-negative bacterium that causes urinary tract infections. With the PCR technique, unseen bacterial species can be detected using standard clinical microbiology methods. In this study, the

Background: Molar Incisor hypomineralisation (MIH) is one of the biggest challenges with great clinical interest. Currently, the etiology of MIH remains unclear. There is no previous study concerning school children aged 7 – 9 years in Al-Najaf governorate in order to estimate the prevalence and severity of molar incisor hypomineralisation and the possible associated risk factors. This study aimed to estimate the prevalence, severity and the possible associated etiological factors of molar incisor hypomineralisation and also to study the correlation between body mass index and molar incisor hypomineralisation. Material and Methods: Across sectional study conducted at Al-Najaf Governorate. A total of 600 children were enrolled those

This study is concerned with the recent changes that occurred in the last three years (2017-2019) in the marshes region in southern Iraq as a result of the changes in the global climate, the study included all the water bodies in the five governorates that are located in the southern regions of Iraq (Wasit, Maysan, Dhi-Qar, Qadisiyah and Basrah), which represent the marshes lands in Iraq. Scenes of the Landsat 8 satellite are used to create a mosaic to cover the five governorates within a time window with the slightest difference between the date of the scene capture, not to exceed 8 days. The results of calculating the changes in water areas were obtained using the classifier support vector machine, where high accuracy ratios were recorded