Apical periodontitis (AP) is the most prevalent chronic inflammatory disease of the teeth. Bone resorption dynamics in symptomatic and asymptomatic AP are still unrecognized. This study examined different inflammatory markers within gingival crevicular fluid, including matrix metalloproteinases 8 (MMP8), tissue inhibitors of metalloproteinases 1 (TIMP1), receptor activator of nuclear factor κB (RANK), its ligand (RANKL), and osteoprotegerin (OPG), to be used in comparing symptomatic apical periodontitis (SAP) and asymptomatic apical periodontitis (AAP) versus healthy teeth. Subjects with SAP, AAP, and a control group were recruited and GCF samples were collected by Periopaper strips. Clinical and radiographical measures were used for diagnosing AP. Levels of MMP8, TIMP, RANK, RANKL, and OPG were determined by ELISA and their abilities to discriminate between examined sites were evaluated by receiver operator characteristic (ROC) curves. All examined biomarkers were statistically significant higher (p < 0.05) in SAP than AAP and the control group, apart from RANK. Significant positive correlations (p < 0.05) were identified between all SAP and AAP biomarkers except TIMP1 and RANK in AAP teeth. TIMP1 and OPG exhibited the highest ability to distinguish between SAP and AAP with areas under the curve of 0.824 and 0.763 in comparing SAP and the control group, and 0.732 and 0.73 when comparing AAP and the control group, respectively. Additionally, TIMP1 and OPG showed the highest AUC of 0.778 and 0.747 when SAP and AAP were compared, respectively. This study concluded that GCF levels of TIMP1 and OPG can be used to differentiate between SAP, AAP, and healthy teeth.
During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreBackground: Obesity and dental caries are multifactorial diseases related to poor eating habits and show a close relationship with the sociodemographic characteristics of individuals presenting these diseases. This research aimed to investigate the severity of dental caries among group of obese boys aged 12 year in relation to salivary interleukin-6 (IL-6) and C-reactive protein (CRP) of unstimulated whole saliva in comparison with normal weighted boys of the same age. Materials and Methods: The study group included 40 obese boys, with an age of 12 year. The control group included 40 normal weighted boys of the same age. The total sample involved for nutritional status assessment using Body Mass Index specific for age and gender according t
... Show MoreThis paper deals with an analytical study of the flow of an incompressible generalized Burgers’ fluid (GBF) in an annular pipe. We discussed in this problem the flow induced by an impulsive pressure gradient and compare the results with flow due to a constant pressure gradient. Analytic solutions for velocity is earned by using discrete Laplace transform (DLT) of the sequential fractional derivatives (FD) and finite Hankel transform (FHT). The influences of different parameters are analyzed on a velocity distribution characteristics and a comparison between two cases is also presented, and discussed in details. Eventually, the figures are plotted to exhibit these effects.
It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological
... Show MoreAcute appendicitis is the most common surgical abdominal emergency. Its clinical diagnosis remains a challenge to surgeons, so different imaging options were introduced to improve diagnostic accuracy. Among these imaging modality choices, diagnostic medical sonography (DMS) is a simple, easily available, and cost effective clinical tool. The purpose of this study was to assess the accuracy of DMS, in the diagnosis of acute appendicitis compared to the histopathology report, as a gold standard. Between May 2015 and May 2016, 215 patients with suspected appendicitis were examined with DMS. The DMS findings were recorded as positive and negative for acute appendicitis and compared with the histopathological results, as a gold standard
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