Background: Urinary tract infections (UTIs) and their complications such as Bladder cancer (Bl. C.) are a health growing problem worldwide. Objective: To shed light on this subject, present study was done to investigate relationship between recurrent urinary tract infection (RUTI) due to Escherichia coli (E. coli) and Bl. C.Type of study: Cross-sectional study. Methods: This study included 130 patients with RUTI, 50 patients with Bl. C. and 50 control of both sexes (aged 7-85 years) attending Al-Zahra Teaching Hospital in Al-Kut/Wassit governorate and Al-Harery Teaching Hospital of specialized surgeries/Baghdad. The patients were divided into two groups: the first group (n=130) included those who were suffering from recurrent UTI without bladder cancer and diagnosed clinically as having recurrent UTI. The second group(n=50) included those who had bladder cancer. One hundred and thirty morning midstream urine specimens were collected from recurrent urinary tract infection patients and 50 from healthy persons as a control and also 50 biopsy specimens collected from recurrent UTI with bladder cancer(after surgical operation to these patients) during beginning of October 2012 to end of March 2013. Results: Intracellular bacterial communities (ICBC) (namely Escherichia coli) was isolated from (68/130) 53% from patients with RUTI while (12/50) 24% isolated from patients with Bladder cancer In this study, other molecular technique called Repetitive extragenic palindromic (REP) were used for drawing the genetic map of bacteria to know the points of similarity and differences between isolated bacteria. A difference between bacteria in each group were found, but when comparing the genetic map of UPEC isolated from patients with Bl. C. with those isolated from patients with recurrent UTI high difference between them were seen. Conclusion: Detecting the intracellular bacterial communities (namely E. coli) in patients with recurrent UTI, with or without bladder cancer. Detecting similarity and difference in genetic map of UPEC isolated from RUTI and Bl. C. by Repetitive extragenic palindromic DNA (REP) technique, in which found high similarity between UPEC isolated from each group but difference from UPEC isolated from other group
The fingerprinting DNA method which depends on the unique pattern in this study was employed to detect the hydatid cyst of Echinococcus granulosus and to determine the genetic variation among their strains in different intermediate hosts (cows and sheep). The unique pattern represents the number of amplified bands and their molecular weights with specialized sequences to one sample which different from the other samples. Five hydatitd cysts samples from cows and sheep were collected, genetic analysis for isolated DNA was done using PCR technique and Random Amplified Polymorphic DNA reaction(RAPD) depending on (4) random primers, and the results showed:
... Show MoreSeveral toxigenic cyanobacteria produce the cyanotoxin (microcystin). Being a health and environmental hazard, screening of water sources for the presence of microcystin is increasingly becoming a recommended environmental procedure in many countries of the world. This study was conducted to assess the ability of freshwater cyanobacterial species Westiellopsis prolifica to produce microcystins in Iraqi freshwaters via using molecular and immunological tools. The toxigenicity of W. prolifica was compared via laboratory experiments with other dominant bloom-forming cyanobacteria isolated from the Tigris River: Microcystis aeruginosa, Chroococcus turigidus, Nostoc carneum, and Lyngbya sp. signifi
... Show MoreA survey statistician for cholera in Iraq for 1980 and until 2003 show that cholera is endemic in Iraq and that the highest number of casualties recorded in the years 1998-1999 and increasing spread of the disease during the wars in hot climates, wet a study bacteriological used where circles selective and tests Alkouhaoah examinations serological system
In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare
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