Background: Oxidative stress is a deleterious process that can be an important mediator of damage to cell structures and consequently various disease states. Exposure to free radicals from a variety of sources has led organisms to produce a series of defense mechanisms. The antioxidant ceruloplasmin is a copper-containing ferroxidase that can oxidize ferrous iron (Fe2+) to its nontoxic ferric (Fe3+) form. Ferrous iron (Fe2+) is extremely damaging because of its ability to generate toxic free radicals. Oral lichen planus (OLP) is a chronic inflammatory oral mucosal disease of unknown etiology. Previous studies reported that reactive oxygen species may be involved in the pathogenesis of lichen planus. The aim of this study was to estimate the role of oxidative stress in pathogenesis of OLP through the study of serum and saliva ceruloplasmin as a marker of antioxidant status. Methods: Forty eight patients with histologically confirmed OLP by oral pathologist were included in this study. The sample group was split up in to two groups according to the clinical presentation of the lesions, 21 patients with reticular formation and 27 patients with erosive form together with 32 healthy looking volunteers that were age-matched with the patients. Serum and saliva ceruloplasmin activity was determined by oxidation of P-Phenylenediamine to give a blue - violet color that measured spectrophotometricaly at 525 NM. Results: Statistically, there was a substantial increase in serum and saliva ceruloplasmin levels of OLP patients group as compared to controls (p<0.01) and there was no statistically significant differences in serum and saliva ceruloplasmin when compared between reticular and erosive forms (p>0.05). The study showed that there was no statistically significant correlation between serum and saliva ceruloplasmin levels in OLP patients group (r=-0.029, p>0.05). Conclusion: Oxidative status play a role in the pathogenesis of oral lichen planus represented by increased serum and saliva ceruloplasmin levels.
2-amino-4-(4-chloro phenyl)-1,3-thiazole (1) was synthesized by refluxing thiourea with para-chloro phenacyl bromide in absolute methanol. The condensation of amine compound (1) with phenylisothiocyanate in the presence of pyridine will produce 1-(4-(4-chlorophenyl)thiazol-2-yl)-3-phenylthiourea(2), which is upon treatment with 2,4 dinitrophenyl hydrazine by conventional method, afforded 1- ( 4 - ( 4 – chlorophenyl ) thiazol – 2 – yl ) – 3 - phenylhydrazonamide,N' - ( 2 , 4 -dinitrophenyl) ,(3).The characterization of the titled compounds were performed utilizing FTIR spectroscopy, 1HNMR and CHNS elemental analysis, and by me
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Objectives This work presents laser coating of grade 1 pure titanium (Ti) dental implant surface with sintered biological apatite beta-tricalcium phosphate (β-TCP), which has a chemical composition close to bone. Materials and methods Pulsed Nd:YAG laser of single pulse capability up to 70 J/10 ms and pulse peak power of 8 kW was used to implement the task. Laser pulse peak power, pulse duration, repetition rate and scanning speed were modulated to achieve the most homogenous, cohesive and highly adherent coat layer. Scanning electron microscopy (SEM), energy dispersive X-ray microscopy (EDX), optical microscopy and nanoindentation analyses were conducted to characterise and evaluate the microstructure, phases, modulus of elasticity
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In this study, a new adsorbent derived from sunflower husk powder and coated in CuO nanoparticles (CSFH) was investigated to evaluate the simultaneous adsorption of Levofloxacin (LEV), Meropenem (MER), and Tetracycline (TEC) from an aqueous solution. Significant improvements in the adsorption capacity of the sunflower husk were identified after the powder particles had been coated in CuO nanoparticles. Kinetic data were correlated using a pseudo-second-order model, and was successful for the three antibiotics. Moreover, high compatibility was identified between the LEV, MER, and TEC, isotherm data, and the Langmuir model, which produced a better fit to suit the isotherm curves. In addition, the spontaneous and exothermic nature of the adso
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This study includes design and synthesis of new non-steroidal anti-inflammatory agents (NSAIDs) with expected cyclooxygenase-2 (COX-2) selective inhibition to achieve better activity and low gastric side effects. Two series of compounds have been designed and synthesized as potential NSAIDs,these are: Salicylamide derivatives (compounds 3,4,5 ) and Diflunisal derivatives (compounds 10&11). In vivo acute anti-inflammatory effect of one of the synthesized agents (compound 3) was evaluated in the rat using egg-white induced paw edema model of inflammation. Preliminary pharmacological study revealed that compound 3 exhibited less anti-inflammatory effect compared to that of aspirin after
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Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction informati
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
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