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The Effect of TNF-Alpha Gene Polymorphisms At -376 G/A, -806 C/T, and -1031 T/C on The Likelihood of Becoming a Non-Responder to Etanercept in A Sample of Iraqi Rheumatoid Arthritis Patients
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Tumor necrosis factor-alpha (TNF-α) antagonists’ therapy are expensive and has a non-responsive rate between 30% to 40% in rheumatoid arthritis patients. Genetic variation plays a vital role in the responsiveness to this type of therapy.The aim of this study is to investigate if the presence of genetic polymorphism in the TNF-α gene promoter region at locations -376 G/A (rs1800750), -806 C/T (rs4248158), and -1031 T/C (rs1799964) affects rheumatoid arthritis patient's tendency to be a non-responder to etanercept.

Eighty RA patients on etanercept (ETN) for at least six months were recruited from the Rheumatology Unit at Baghdad Teaching Hospital. Based on The European League Against Rheumatism response (EULAR) criteria, patients were divided into two groups: responders and non-responders. After polymerase chain reaction amplification of their DNA, the amplified DNA was sequenced by Sanger method to determine the polymorphisms at the positions -376G/A, -806 C/T, and -1031T/C.

The results of this study found that equally Phi correlation and binary logistic regression analysis revealed a non-significant association for all genotypes in the three polymorphic sites with the tendency for being non-responder. Moreover, there was no significant difference in TNF-α mean level or the change in disease activity score for 28 joints (DAS28) after six months of etanercept therapy between all genotypes for each polymorphic site.

The present study concludes that there was no correlation between the polymorphisms in the TNF-α promoter region at -376G/A, -806 C/T, and -1031T/C with the tendency for being non-responder to ETN.

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Multi-Objective Genetic Algorithm-Based Technique for Achieving Low-Power VLSI Circuit Partition
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     Minimizing the power consumption of electronic systems is one of the most critical concerns in the design of integrated circuits for very large-scale integration (VLSI). Despite the reality that VLSI design is known for its compact size, low power, low price, excellent dependability, and high functionality, the design stage remains difficult to improve in terms of time and power. Several optimization algorithms have been designed to tackle the present issues in VLSI design. This study discusses a bi-objective optimization technique for circuit partitioning based on a genetic algorithm. The motivation for the proposed research is derived from the basic concept that, if some portions of a circuit's system are deactivated during th

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Publication Date
Thu May 18 2023
Journal Name
Journal Of Engineering
Genetic Algorithm Optimization Model for Central Marches Restoration Flows with Different Water Quality Scenarios
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A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and

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