Background: Orthodontic force is considered to stimulate cells in the periodontium to release many mediators such as cytokines which play a responsible role for periodontal and alveolar bone remodeling, bone resorption and new bone deposition. Aim of this study was carried out to estimate changes of the (interleukin-one beta, tumor necrosis factor – alpha and C-reactive protein) levels in unstimulated whole saliva during the leveling stage of orthodontic tooth movement. Materials and methods: The sample consisted of thirty adult patients (12 males and 18 females) with ages ranges (19-23) years. Each sample had Class I and Class II malocclusion dental classification and required bilateral extraction of their maxillary first premolars, underwent a session of professional oral hygiene and received oral hygiene instructions before and during the period of study, one month later fixed orthodontic appliance were placed in the upper arch by using 0.014 nickel titanium arch wire. The unstimulated whole saliva was taken from each sample immediately before placement of the appliance (baseline), and at (after1hour, after one week and after two week) following placement of the fixed orthodontic appliance. In addition the plaque index and gingival index were recorded during the interval periods of this study to assess oral cleanliness. The interleukin – one beta and tumor necrosis factor-alpha were determined by enzyme linked immunosorbent assay, while the C-reactive protein was determined by latex agglutination. Results: The results of the present study found the mean value of both salivary (interleukin-one beta and tumor necrosis factor -alpha) were highest at (after1hour) followed by at (after one week) then at (after two week) than the baseline with highly statistical significant differences (P< 0.01) among males, females and total samples, in addition there were no statistical significant differences between males and females (P>0.05). While the mean values of C-reactive protein were higher at (after 1hour) only with highly significant differences (P< 0.01) among females and total samples while only significant difference (P<0.05) for males, in addition there were no statistical significant differences between males and females. Regarding the correlation between salivary (interleukin – one beta and tumor necrosis factor -alpha), there were positive correlation between them at all periods of study. Moreover there were positive correlation between salivary (interleukin – one beta and tumor necrosis factor -alpha) and salivary C-reactive protein. On the other hand there were no association between the salivary (interleukin – one beta and tumor necrosis factor -alpha and C-reactive protein) and clinical parameter (plaque index and gingival index). Conclusion: From this clinical study we conclude that orthodontic force induces increasing the levels of (interleukin – one beta, tumor necrosis factor -alpha, C-reactive protein) in unstimulated whole saliva during orthodontic tooth movement.
This study is unique in this field. It represents a mix of three branches of technology: photometry, spectroscopy, and image processing. The work treats the image by treating each pixel in the image based on its color, where the color means a specific wavelength on the RGB line; therefore, any image will have many wavelengths from all its pixels. The results of the study are specific and identify the elements on the nucleus’s surface of a comet, not only the details but also their mapping on the nucleus. The work considered 12 elements in two comets (Temple 1 and 67P/Churyumoy-Gerasimenko). The elements have strong emission lines in the visible range, which were recognized by our MATLAB program in the treatment of the image. The percen
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Social media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq
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Background: Male infertility is a global concern and it tends to increase due to miscellaneous factors, such as environmental toxins and genetic and lifestyle choices. The aryl hydrocarbon receptor (AHR) has recently attracted attention due to its involvement in male infertility mechanisms and impact on sperm production and function. AHR, a versatile receptor expressed in various tissues, including the testes, regulates the genes involved in spermatogenesis. AHR activation is associated with cell cycle regulation and chromatin condensation during spermatogenesis. Objectives: This study aimed to investigate the influence of AHR activation on blood-testis barrier (BTB) integrity, focusing on the role of tight junction protein-1 (TJP1)
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.
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This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio
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