It was aimed to understand the interleukin-4 (IL-4) role in etio-pathogenesis of rheumatoid arthritis (RA). Two approaches were adopted. In the first one, a quantitative expression of IL4 gene was assessed by reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and such findings were correlated with some demographic, clinical and laboratory parameters, which included gender, duration of disease, disease activity score (DAS-28), rheumatoid factors (RFs), C-reactive protein (CRP) and anti-cyclic citrullinated peptide (ACCP) antibodies. In the second approach, a single nucleotide polymorphism (SNP) of IL4 gene (rs2243250) was inspected by DNA sequencing using specific primers. Fifty-one Iraqi RA patients (22 males and 29 females) were enrolled in the study. They were under therapy, which was a single weekly subcutaneous dose of 25 mg of etanercept (Enbrel) for a period of 3-5 years. The results of gene expression (2-??Ct) revealed an increased expression of IL4 mRNA (Mean ± SEM: 8.247 ± 2.442), especially female patients compared to male patients (11.545 ± 3.928 vs. 3.537 ± 1.530; p = 0.03). The expression was also subjected to variations that were related to clinical and laboratory findings. With respect to IL4 gene SNP, allele and genotype frequencies showed no significant differences between RA patients and controls. In addition, the SNP genotypes had no effect on IL4 gene expression. In conclusion, an up-regulation of IL4 gene expression was observed in RA patients, and it was more pronounced in female than male patients by approximately four folds, while no association between the IL4 SNP alleles or genotypes and RA was observed.
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreFour metal compounds mixed ligand of azo dye ligand (L) and metformin.(Met) were produced at aquatic ethanol for (1:1:1) (M:L:Met). The prepared compounds were identified by utilizing atomic absorption flame, FT.IR and UV–Vis spectrum manners as well as conductivity mensuration. These compounds was assayed of the gained datum the octahedral geometry was proposed into whole prepared complexes.Also in this research was studied represented examining the antibacterial and antifungal impact of the azo dye ligand (L), metformin.(Met) and (Co,Ni, Cu and Cd complexes) on four types of pathogenic, clinically isolated bacteria that are resistant to antibiotic, like Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, Klebsiella pneu
... Show MorePoly-ether-ether-ketone (PEEK) was introduced in dentistry as an alternative to metal alloys.
To assess the effectiveness of PEEK-fixed retainers in preserving the stability of mandibular anterior and participant satisfaction as compared to the Dead-soft coaxial fixed retainer (DSC).
A single-centre, two-arm parallel groups
In order to select the optimal tracking of fast time variation of multipath fast time variation Rayleigh fading channel, this paper focuses on the recursive least-squares (RLS) and Extended recursive least-squares (E-RLS) algorithms and reaches the conclusion that E-RLS is more feasible according to the comparison output of the simulation program from tracking performance and mean square error over five fast time variation of Rayleigh fading channels and more than one time (send/receive) reach to 100 times to make sure from efficiency of these algorithms.