Background: Tumor necrosis factor-alpha (TNF-α) and interleukins play important roles in the pathogenesis of rheumatoid arthritis (RA). Genetic research has been employed to find many of the missing connections between genetic risk variations and causal genetic components. Objective: The goal of this study is to look at the genetic variations of TNF-α and interleukins in Iraqi RA patients and see how they relate to disease severity or response to biological therapy. Method: Using specific keywords, the authors conducted a systematic and comprehensive search to identify relevant Iraqi studies examining the genetic variations of TNF-α and interleukins in Iraqi RA patients and how they relate to disease severity or response to biological therapy. Results: Thirteen studies have looked at TNF-α and interleukin genetic polymorphisms in Iraqi RA patients. Only the IL-2, IL-4, IL-6, IL-17, and IL-23 receptor gene polymorphisms were explored for interleukins; however, the results of studies indicate no association between genetic polymorphism and the severity of RA. Very few researchers examine the correlation between genetic variation and TNF-α inhibitor responsiveness. Numerous studies have been conducted to investigate the genetic variations of the TNF-α promoter. The -308 G/A region in the promotor region was the most studied location.
In this work pyrazolin derivatives were prepared from the diazonium chloride salt of 4-aminobenzoic acid. Azo compounds were prepared from the reaction of an ethanolic solution of sodium acetate and calculated amount of active methylene compound namely, acetyl acetone to obtain the corresponding hydrazono derivative (1). Cyclocondensation reaction of compounds (1) with hydrazine hydrate and phenyl hydrazine in boiling ethanol affording the corresponding pyrazoline-5-one derivatives of 4-aminobenzoic acid (2,3). Then compound (3) was reacted with thionyl chloride to give the corresponding acid chloride derivative(4), followed by conversion into the corresponding acid hydrazide derivative (5) carboxylic acid thiosemicarbazide (11), esters
... Show MoreSolid‐waste management, particularly of aluminum (Al), is a challenge that is being confronted around the world. Therefore, it is valuable to explore methods that can minimize the exploitation of natural assets, such as recycling. In this study, using hazardous Al waste as the main electrodes in the electrocoagulation (EC) process for dye removal from wastewater was discussed. The EC process is considered to be one of the most efficient, promising, and cost‐effective ways of handling various toxic effluents. The effect of current density (10, 20, and 30 mA/cm2), electrolyte concentration (1 and 2 g/L), and initial concentration of Brilliant Blue dye (15 and 30 mg/L) on
Generalized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used
... Show MoreComposite materials are widely used in the engineered assets as aerospace structures, marine and air navigation owing to their high strength/weight ratios. Detection and identification of damage in the composite structures are considered as an important part of monitoring and repairing of structural systems during the service to avoid instantaneous failure. Effective cost and reliability are essential during the process of detecting. The Lamb wave method is an effective and sensitive technique to tiny damage and can be applied for structural health monitoring using low energy sensors; it can provide good information about the condition of the structure during its operation by analyzing the propagation of the wave in the
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Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate
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