Background: Ulcerative colitis disease is a chronic inflammatory condition that affects the gastrointestinal tract. In regulation of this inflammatory process, Interleukin-6, C-reactive proteins and albumin have a major role. Overproduction of IL-6 by immunocompetent cells contributes to activate the liver to produce CRP, transudation of plasma albumin and development of the inflammatory condition. Elevated levels of IL-6 in saliva could be expected, because the saliva-producing cells are part of the digestive system. The purpose of this study was to assess salivary IL-6, CRP and albumin in ulcerative colitis patients in relation to oral findings. Materials and methods: Forty eight saliva specimens collected from three groups of subjects (sixteen newly diagnosed UC patients, sixteen UC patients on medication and sixteen healthy subjects). The specimens were centrifuged and stored at -20°C then three ELISA kits were used for estimating the three variables. Results: There was a significant elevation of salivary IL-6, CRP and albumin level in both newly diagnosed and on medication groups in comparison to healthy persons. There was a significant elevation differences of salivary IL-6, CRP and albumin level between newly diagnosed and on medication groups. The prevalence of aphthus ulcer was highly significant in the newly diagnosed group in comparison to the other groups. Twenty five percent of patients on medication complain from candidiasis and only one patients with tempromandibular joints problem (hard clicking). Conclusions: Salivary IL-6, CRP and albumin are elevated simultaneously in UC patients, in both newly diagnosed and on medication groups, but the mean of variables in second group was lower than in the newly diagnosed group. There are no correlation between salivary IL-6, CRP and albumin with oral findings.
In this article, a numerical method integrated with statistical data simulation technique is introduced to solve a nonlinear system of ordinary differential equations with multiple random variable coefficients. The utilization of Monte Carlo simulation with central divided difference formula of finite difference (FD) method is repeated n times to simulate values of the variable coefficients as random sampling instead being limited as real values with respect to time. The mean of the n final solutions via this integrated technique, named in short as mean Monte Carlo finite difference (MMCFD) method, represents the final solution of the system. This method is proposed for the first time to calculate the numerical solution obtained fo
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The main goal of this paper is to introduce the higher derivatives multivalent harmonic function class, which is defined by the general linear operator. As a result, geometric properties such as coefficient estimation, convex combination, extreme point, distortion theorem and convolution property are obtained. Finally, we show that this class is invariant under the Bernandi-Libera-Livingston integral for harmonic functions.
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Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the
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This research has come out with that, function-based responsibility accounting system has harmful side – effects preventing it of achieving its controlling objective, that is, goal congruence, which are due to its un integrated measures, its focus on measuring measurable behaviors while neglecting behaviors that are hardly measured, and its dependence on standard operating procedures.
In addition, the system hypotheses and measures are designed to fit previous business environment, not the current environment.
The research has also concluded that the suggestive model, that is, activity-based responsibility accounting is designed to get ride of harmful side – effects of functi
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Metasurface polarizers are essential optical components in modern integrated optics and play a vital role in many optical applications including Quantum Key Distribution systems in quantum cryptography. However, inverse design of metasurface polarizers with high efficiency depends on the proper prediction of structural dimensions based on required optical response. Deep learning neural networks can efficiently help in the inverse design process, minimizing both time and simulation resources requirements, while better results can be achieved compared to traditional optimization methods. Hereby, utilizing the COMSOL Multiphysics Surrogate model and deep neural networks to design a metasurface grating structure with high extinction rat
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