Swarming is one of the most important virulence factors used by bacteria to invade new sites. This study aimed to test the effects of gentamicin on swarming motility of Pseudomonas aeruginosa, both phenotypically and molecularly. The present results revealed that 11/25 isolates had gentamicin MIC of 1024 µg/ml.  However, gentamicin at sub-minimal inhibitory concentration significantly (P< 0.05) reduced the diameter of swarming in all P. aeruginosa isolates. Noticeably the mean and median swarming diameter before treatment with gentamicin 5.557 and 5.816 cm respectively had significantly (P < 0.001) reduced to 0.871 and 0.766 cm respectively. At the molecular level, amrZ (a global regulator of multiple genes) and

 Background: Prelabour rupture of membranes is a problem that faces the obstetricians. It has many maternal and fetal sequale and its etiology and management still controversial.
Objective: To test the absolute nucleated red blood cells counts at birth in infants who are born after prelabour rupture of membranes.
Methods: A prospective study conducted in AL-Kadhymia Teaching Hospital. Hundred pregnant women were included in this study. Fifty pregnant women who had prelabour rupture of membranes considered as group (1), other fifty pregnant women with intact membranes considered as group (2) through a period of one year. Nucleated red blood cell counts of venous cord blood obtained within one hour of life from 50 infants who we

      Compounds from tin oxide doped with gallium oxide and cerium oxide were synthesized. Thin films from (SnO2:Ga2O3,CeO2) with different doping ratios were prepared on glass and single crystal silicon as substrates with the use of the pulsed laser deposition technique. The results of FTIR spectrums analysis was presented. Varies heterojunctions were fabricated from (SnO2:Ga2O3,CeO2 /Cu2S/c-pSi) heterojunctions solar cell which are formed from two layers: the first was Cu2S and the second was layer from tin oxide doped with two oxides named gallium oxide and cerium oxide with different doping ratios (0, 0.03, 0.05, and 0.07). The heterojuntion (SnO2:5%Ga2O3 /Cu2S/c-pSi photovoltaic structure exhibits open circuit voltage (Voc

Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

Background: Breast cancer still a major cause of disability and mortality among women throughout the world. Lack of awareness and early detection programs in developing countries is a main reason for escalating the mortality.

Objectives: to assess level of awareness about breast cancer among university female students in Baghdad focusing on knowledge of breast cancer risk factors, warning symptoms and signs and knowledge about the screening method specially breast self-examination.

Methods: A cross-sectional study conducted over two months from first of march through April 2015 and included (240) female students in non- medical colleges at Al-Rusafa and A

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p