Rheumatoid arthritis is a worldwide inflammatory chronic autoimmune disease with varying severity. Due to no definitive cure for this disease, current therapies aim to decrease the pain and slow further damage. The interleukin (IL)‐36 cytokine was little known for its role in rheumatoid arthritis; this research aimed to evaluate the serum IL36 levels in RA patients compared to healthy controls. This study included 80 patients with rheumatoid arthritis registered at the Rheumatology Clinic in Baghdad teaching hospital. The patients were divided into three groups based on the treatments received. Group 1 included patients treated with biological therapy (etanercept, adalimumab), Group2 patients with non-biological treatment (methotrexate hydroxychloroquine and prednisone), Group3 patients without any treatment and compared with Group 4 healthy control group. Patients is all groups were assessed for their serum IL-36 concentration; the mean IL-36 serum level was significantly higher in three groups of RA patients which include the group of patients treated with biological therapy (Enbrel (etanercept) and Humira (adalimumab) means were (1132.41±475.2,), and group of non-biological therapy patients (Methotrexate hydroxychloroquine and prednisone) (G2) means was 553.95±307, than patients' group without any treatment (G3) means was 1044.01±575.3 compared to the control (341.38±113.1) p-value> 0.00001. The patient's age and BMI were not significantly different between three groups of patient Rheumatoid arthritis. Parameters for this disease also were tested which include RF, CRP, ESR, anti-CCP and disease activity score-28 (DAS 28), there were significant differences when compared with the control group. IL-36 serum level was significantly higher in three groups of rheumatoid arthritis than those in controls, and when compared between three patients groups there was less concentration in the non-biological therapy treatment group means was 553.95±307 than in the rest of the patient groups,biology tratment, without any treatment, means were (1132.41±475.2, 1044.01±575.3) respectively. This study found that Rheumatoid arthritis patients' serum IL36 levels increased, where a non-biologic therapies reduced this cytokine. IL-36's pathogenic involvement in Rheumatoid arthritis needs more study. Keywords: Rheumatoid arthritis, IL-36, IL-1,C‐reactive protein, RF, ESR and anti-CCP.
The solution casting method was used to prepare a polyvinylpyrrolidone (PVP)/Multi-walled carbon nanotubes (MWCNTs) nanocomposite with Graphene (Gr). Field Effect Scanning Electron Microscope (FESEM) and Fourier Transformer Infrared (FTIR) were used to characterize the surface morphology and optical properties of samples. FESEM images revealed a uniform distribution of graphene within the PVP-MWCNT nanocomposite. The FTIR spectra confirmed the nanocomposite information is successful with apperaring the presence of primary distinct peaks belonging to vibration groups that describe the prepared samples.. Furthermore, found that the DC electrical conductivity of the prepared nanocomposites increases with increasing MWCNT concentratio
... Show MoreIn this study, three strengthening techniques, near-surface mounted NSM-CRFP, NSM-CFRP with externally bonding EB-CFRP, and hybrid CFRP with circularization were studied to increase the seismic performance of existing RC slender columns under lateral loads. Experimentally, 1:3 scale RC models were studied and subjected to both lateral static load and seismic excitation. In the dynamic test, a model was subjected to El Centro 1940 NS earthquake excitation by using a shaking table. According to the test results, the strengthening techniques showed a significant increase in load carrying capacity, of about 86.6%, and 46.6%, for circularization and NSM-CFRP respectively, of the reference unstrengthened columns. On the other hand, column
... Show MoreFour mixed ligand complexes were prepared from 1,10-phenanthroline (Phen), 5-chlorosalicylic acid (CSA), and anthranilic acid (Anthra) dissolved in aqueous ethanol at a ratio of (1:1:1:1) M: Phen:CSA: Anthra, M(II)= Cu, Zn, Cd, and Hg. The prepared compounds were analyzed by flame atomic absorption, FT-IR, UV-Vis, and spectroscopic methods, as well as conductivity measurements and magnetic properties. After analyzing the prepared compounds using the acquired data, the complexes formed by mixing ligands were concluded to adopt an octahedral geometry. That study has been conducted to test the inhibitory effectiveness of the complexes (1,10-Phenanthroline (Phen), 5-Chlorosalicylic acid (CSA), Na[Cu(Phen)(CSA)(Anthra), Na[Zn(Phen)(CSA
... Show MoreThe interactions of drug amoxicillin with maltose or galactose solutions with a variation of temperature have been discussed by taking in the volumetric and viscometric procedures. Physical properties [densities (ρ) and viscosities (η)] of amoxicillin (AMOX) aqueous solutions and aqueous solutions of two type saccharides (maltose and galactose 0.05m) have been measured at T = (298.15, 303.15 and 308.15) K under atmospheric pressure. The apparent molar volume (ϕv cm3mole-1) has been evaluated from density data and fitted to a Redlich-Mayer equation. The empirical parameters of the Mayer-Redlich equation and apparent molar volume at infinite dilution ذv were explicated in terms of interactions from type solute-solvent and solute
... Show MoreThe preparation of low cost activated carbon from date stones and microwave method by using K2CO3 as chemical activator were investigated.
The prepared activated carbon was used to remove fluoroquinolones antibiotics from aqueous solution. The characterizations of the activated carbon is represented by surface area, pore volume, ash content, moisture content, bulk density, and iodine number. The adsorbed fluoroquinolones antibiotics are Ciprofloxcin (CIP), Norfloxcin (NOR) and Levofloxcin (LEVO). Different variables as pH, initial concentrations and contact time were studied to show the efficieny of prepared activated carbon. The experimental adsorption data were analyzed by Lungmuir, Freundlich
... Show MoreTo accommodate utilities in buildings, different sizes of openings are provided in the web of reinforced concrete deep beams, which cause reductions in the beam strength and stiffness. This paper aims to investigate experimentally and numerically the effectiveness of using carbon fiber reinforced polymer (CFRP) strips, as a strengthening technique, to externally strengthen reinforced concrete continuous deep beams (RCCDBs) with large openings. The experimental work included testing three RCCDBs under five-point bending. A reference specimen was prepared without openings to explore the reductions in strength and stiffness after providing large openings. Openings were created symmetrically at the center of spans of the other specimens
... Show MoreDuring the last few years, the greener additives prepared from bio-raw materials with low-cost and multifunctional applications have attracted considerable attention in the field of lubricant industry. In the present work, copolymers derived from sunflower and linseed oils with decyl methacrylate were synthesized by a thermal method using benzoyl peroxide (BPO) as a radical initiator. Direct polymerization of fatty acid double bonds in the presence of a free radical initiator results in the development of environmentally friendly copolymeric additives (Co-1 and Co-2). Fourier Transform Infrared (FTIR) and Proton Nuclear Magnetic Resonance (1H-NMR) were used to characterize the resulting copolymers. Thermal decomposition of copolymers was de
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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