MRSA is one of the major pathogens in hospitals and the community, which have the ability to produce biofilm as a virulence factor, the impact of chalcone on biofilm formation, the synergism effect of chalcone and antibiotic in both in vitro and in vivo experiments, the gene expression of virulence genes (srtA, fnbA, fnbB) before and after treatment of it on MRSA biofilm cells in vitro, all these were the prime aims of this study. Chalcone at MBIC (20 μg/ml), significantly reduced the biofilm formation to 21.45% and at sub MBIC (15 μg/ml) to 36.58 %. While, Chalcone at MIC(5 μg/ml) reduced MRSA planktonic cells to 49.61%. Susceptibility of MRSA isolates against eight antibiotics showed that all isolates were sensitive to vancomycin and none of the isolates developed susceptibility to erythromycin. The combinatorial effect of chalcone at 5 μg/ml and vancomycin at MIC of (1 μg/ml) on MRSA planktonic cells was reduced it from 70 to 23.3% , and in combination with erythromycin at 32 μg/ml, was decreased from 53.1% to 22% and the effect of chalcone at sub MBIC (15 μg/ml) when combined with vancomycin was reducing the biofilm formation from 87% to 27.6 and with erythromycin from 55.1% to 23.8%. Combinatorial phenotypic effect of the antibiotics and chalcone (at sub MBIC), in vitro came in line with the result of in vivo experiment and the results showed decrease in the expression of fnbA, fnbB and srtA genes in tested isolates in the presence of chalcone at sub MBIC. In our study, we demonstrated that chalcone exhibited significant effect in biofilm formation of MRSA strains, which can be considered as promising antimicrobial agents that can be used for prevention of MRSA adherence or as adjunct to antibiotics in conventional therapy.
The Present research aimed at identifying:
1- The level of environmental stress among preparatory students
2- The level of self-rebellion among preparatory students
3- The correlation between the two variables of research (environmental stress and self-rebellion) and the extent to which the independent variable contributes to the variable of the middle school students.
The current research has determined the students of the fifth stage of the preparatory stage and all the branches in the departments of education in Baghdad province the morning study for the academic
... Show MoreThe seasonal behavior of the light curve for selected star SS UMI and EXDRA during outburst cycle is studied. This behavior describes maximum temperature of outburst in dwarf nova. The raw data has been mathematically modeled by fitting Gaussian function based on the full width of the half maximum and the maximum value of the Gaussian. The results of this modeling describe the value of temperature of the dwarf novae star system leading to identify the type of elements that each dwarf nova consisted of.
In this study, a different design of passive air Solar Chimney(SC)was tested by installing it in the south wall of insulated test room in Baghdad city. The SC was designed from vertical and inclined parts connected serially together, the vertical SC (first part) has a single pass and Thermal Energy Storage Box Collector (TESB (refined paraffin wax as Phase Change Material(PCM)-Copper Foam Matrix(CFM))), while the inclined SC was designed in single pass, double passes and double pass with TESB (semi refined paraffin wax with copper foam matrix) with selective working angle ((30o, 45o and 60o). A computational model was employed and solved by Finite Volume Method (FVM) to simulate the air i
... Show MoreAdverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD
... Show MoreTraffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c
... Show MoreThe research aimed: 1. Definition of family climate for the university students. 2. Definition of statistical significance of differences in family climate variable depending on the sex (males - females) and specialization (Scientific - humanity). 3. Definition of academic adjustment for university students. 4. Definition of correlation between climate and academic adjustment. The research sample formed of (300) male and female students by (150) male of scientific and humanitarian specialization and (150) female of scientific and humanitarian specialization randomly selected from the research community. To achieve the objectives of the research the researcher prepared a tool to measure family climate. And adopted the measure (Azzam 2010)
... Show More This study includes Estimating scale parameter, location parameter and reliability function for Extreme Value (EXV) distribution by two methods, namely: -
- Maximum Likelihood Method (MLE).
- Probability Weighted Moments Method (PWM).
Used simulations to generate the required samples to estimate the parameters and reliability function of different sizes(n=10,25,50,100) , and give real values for the parameters are and , replicate the simulation experiments (RP=1000)
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