Background: Saliva is one of the most important etiological host factors in relation to dental caries. It affects the carious process by its organic and inorganic constituents; in addition to its physiological functions as (flow rate, pH and buffer capacity). The aims of this study were to determine the concentrations of major elements (calcium and phosphorus) and trace elements (ferrous iron, nickel, chromium and aluminum) in saliva among a group of adolescent girls, and to explore the relation of these elements, flow rate and pH with dental caries. Material & Methods: The study group consisted of 25 girls with an age of 13-15 years old. Dental caries was diagnosed by both clinical and radiographical examinations following the criteria of D1-4MFS index. Stimulated saliva was collected from patients between 9-11 Am under standarized conditions, and chemically analyzed to determine the concentration of calcium, nickel, chromium and aluminum by Atomic Absorption Spectrophotometer, while salivary phosphorus and ferrous iron were determined by using colorimetric method. The average salivary flow rate was measured from total volume, and salivary pH was determined using digital pH meter. All data were analyzed using SPSS version 19. Results: All elements measured in saliva in addition to P/Ca ratio recorded statistically non significant correlation with DMFS, except ferrous Fe ions which showed statistically significant correlation (r= 0.34, P=0.05). Salivary flow rate and pH correlated weakly and statistically not significant with DMFS There were weak and statistically not significant correlations between all elements measured in saliva and salivary flow rate and pH. Conclusions: It had been found that Fe, Ni, Al and Cr ions present in very small amounts in saliva in comparison to Ca and P ions. The presence of these elements in saliva may indicate their presence in food, water and air.
'Steganography is the science of hiding information in the cover media', a force in the context of information sec, IJSR, Call for Papers, Online Journal
Water quality sensors have recently received a lot of attention due to their impact on human health. Due to their distinct features, environmental sensors are based on carbon quantum dots (CQDs). In this study, CQDs were prepared using the electro-chemical method, where the structural and optical properties were studied. These quantum dots were used in the environmental sensor application after mixing them with three different materials: CQDs, Alq3 polymer and CQDs and Alq3 solutions using two different methods: drop casting and spin coating, and depositing them on silicon. The sensitivity of the water pollutants was studied for each case of the prepared samples after measuring the change in resistance of the samples at a temperature of
... Show MoreTanuma and Zubair formations are known as the most problematic intervals in Zubair Oilfield, and they cause wellbore instability due to possible shale-fluid interaction. It causes a vast loss of time dealing with various downhole problems (e.g., stuck pipe) which leads to an increase in overall well cost for the consequences (e.g., fishing and sidetrack). This paper aims to test shale samples with various laboratory tests for shale evaluation and drilling muds development. Shale's physical properties are described by using a stereomicroscope and the structures are observed with Scanning Electron Microscope. The shale reactivity and behavior are analyzed by using the cation exchange capacity testing and the capillary suction test is
... Show MoreIn information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare
... Show MoreBackground: Diabetes mellitus is one of the commonest chronic disorders worldwide with a rapid rise in prevalence. In Iraq its prevalence is high especially in elderly age group. Patients with type 2 diabetes mellitus have higher vulnerability for complications, whether microvascular or macrovascular. Ocular complications are common in diabetes mellitus, and comprise diabetic retinopathy, diabetic papillopathy, cataract, glaucoma, dry eye disease and diabetic keratopathy. Diabetic keratopathy involves endothelial and epithelial tissues of the cornea, leading to persistent epithelial defect, corneal erosion, or corneal ulcers.
Aim of the Study: To compare the mean corneal endothelial cell count between patients wi
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