Pseudomonas aeruginosa produces an extracellular biofilm matrix that consists of nucleic acids, exopolysaccharides, lipid vesicles, and proteins. Alginate, Psl and Pel are three exopolysaccharides that constitute the main components in biofilm matrix, with many biological functions attributed to them, especially concerning the protection of the bacterial cell from antimicrobial agents and immune responses. A total of 25 gentamicin-resistant P. aeruginosa selected isolates were enrolled in this study. Biofilm development was observed in 96% of the isolates. In addition, the present results clarified the presence of pelA and pslA in all the studied isolates. The expression of these genes was very low. Even though all biof

     Pseudomonas aeruginosa produces an extracellular biofilm matrix that consists of nucleic acids, exopolysaccharides, lipid vesicles, and proteins. Alginate, Psl and Pel are three exopolysaccharides that constitute the main components in biofilm matrix, with many biological functions attributed to them, especially concerning the protection of the bacterial cell from antimicrobial agents and immune responses. A total of 25 gentamicin-resistant P. aeruginosa selected isolates were enrolled in this study. Biofilm development was observed in 96% of the isolates. In addition, the present results clarified the presence of pelA and pslA in all the studied isolates. The expression of

Fifteen local isolates of Pseudomonas were obtained from several sources such as soil, water and some high-fat foods (Meat, olives, coconuts, etc.). The ability of isolates to produce lipase was measured by the size of clear zone on Tween 20 solid medium and by measuring the enzymatic activity and specific activity. Isolate M3 (as named in this study) was found to be the most efficient for the production of the lipase with enzymatic activity reached 56.6 U/ml and specific activity of 305.94 U/mg. This isolate was identified through genetic analysis of the 16S rRNA gene. and it was shown that the isolate M3 belongs to Pseudomonas aeruginosa with 99% similarity. The DNA of isolate M3 was extracted and lipase gene was amplified through PCR tec

Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust  M method after their development through the use of sequential  approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate

Background: Acute appendicitis is the most common abdominal surgical emergency. The diagnosis of this condition is still essentially clinical and there is difficulty in the clinical diagnosis, especially among elderly, children and patients with a typical presentation, so early and accurate diagnosis of acute appendicitis is important to avoid its complications.Objectives: To evaluate the degree of accuracy of Alvarado scoring system in the diagnosis of acute appendicitis.Method: Two hundred patients were admitted to the Alkindy Teaching Hospital from January 2011 to april 2014- presented with symptoms and signs suggestive of acute appendicitis. After examination and investigations all patients were given a score according to Alvarado sc

Background: Widal test and blood culture together must be depended to diagnosis of typhoid fever.

Breast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we

The current research tackles the self-efficacy and its relation to the cognitive assessment for the daily disturbances for the University of Baghdad students. Two criteria have been adopted to achieve the objectives of the research. The sample of this study consists of 200 male and female students who were chosen randomly. The data were analyzed statistically, revealing that the university students owned their own self-efficacy as well as a cognitive assessment for the daily disturbances and they recognized them as self-threatening. The results also indicated the existence of a prediction activity in the field of the cognitive assessment to the daily disturbances selection. In light of the acquired results, the study recommends the neces

Pseudomonas aeruginosa is a common and major opportunistic human pathogen, its causes many and dangersinfectious diseases due to death in some timesex: cystic fibrosis , wounds inflammation , burns inflammation , urinary tract infection , other many infections otitis external , Endocarditis , nosocomial infection and also causes other blood infections (Bacteremia). thereforebecomes founding fast and exact identification of P. aeruginosafrom samples culture very important.However, identification of this species may be problematic due to the marked phenotypic variabilitydemonstrated by samples isolates and the presence of other closely related species. To facilitate species identification, we used 16S ribosomal DNA(rRNA) sequence data