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.
Field experiment conducted to measure vibrations on three axes longitudinal X, lateral Y and vertical Z on steering wheel, platform tractor and vertical vibration in seat tractor and seat effective amplitude transmissibility (SEAT) factor during operation tillage in silt clay loam soil with depth 18 cm in Baghdad. Split – split plot design under randomized complete block design with three replications least significant design 5 % used. Three factor were used in this experiment included two types of plows included chisel and disc plows which represented main plot, three tires inflation pressure was second factor included 1.1 ,1.8 and 2.7 bar, and three forward speeds of the tillage was third factor included 2.35 , 4.25 and 6.50 km/hr. Resu
... Show MoreFlow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel
... Show MoreIn this study, an efficient photocatalyst for dissociation of water was prepared and studied. The chromium oxide (Cr2O3) with Titanium dioxide (TiO2) nanofibers (Cr2O3-TNFs) nanocomposite with (chitosan extract) were synthesized using ecologically friendly methods such as ultrasonic and hydrothermal techniques; such TiO2 exhibits nanofibers (TNFs) shape struct
... Show MoreIn this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.
Reservoir characterization is an important component of hydrocarbon exploration and production, which requires the integration of different disciplines for accurate subsurface modeling. This comprehensive research paper delves into the complex interplay of rock materials, rock formation techniques, and geological modeling techniques for improving reservoir quality. The research plays an important role dominated by petrophysical factors such as porosity, shale volume, water content, and permeability—as important indicators of reservoir properties, fluid behavior, and hydrocarbon potential. It examines various rock cataloging techniques, focusing on rock aggregation techniques and self-organizing maps (SOMs) to identify specific and
... Show MoreIn our article, three iterative methods are performed to solve the nonlinear differential equations that represent the straight and radial fins affected by thermal conductivity. The iterative methods are the Daftardar-Jafari method namely (DJM), Temimi-Ansari method namely (TAM) and Banach contraction method namely (BCM) to get the approximate solutions. For comparison purposes, the numerical solutions were further achieved by using the fourth Runge-Kutta (RK4) method, Euler method and previous analytical methods that available in the literature. Moreover, the convergence of the proposed methods was discussed and proved. In addition, the maximum error remainder values are also evaluated which indicates that the propo
... Show MoreSemi-parametric models analysis is one of the most interesting subjects in recent studies due to give an efficient model estimation. The problem when the response variable has one of two values either 0 ( no response) or one – with response which is called the logistic regression model.
We compare two methods Bayesian and . Then the results were compared using MSe criteria.
A simulation had been used to study the empirical behavior for the Logistic model , with different sample sizes and variances. The results using represent that the Bayesian method is better than the at small samples sizes.
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