Background: The main purpose of this study is to find if there is any correlation between the level of C-reactive protein (CRP) in gingival crevicular fluid with its serum level in chronic periodontitis patients and to explore the differences between them according to the probing depth. Materials and methods: Forty seven male subjects enrolled in this study. Thirty males with chronic periodontitis considered as study group whom further subdivided according to probing depth into subgroup 1 with pocket depth ≤6mm, subgroup 2 with pocket depth >6mm. The other 17 subjects considered as controls. For all subjects, clinical examination where done for periodontal parameters plaque index (PLI), gingival index (GI), bleeding on probing (BOP), probing pocket depth (PPD) and clinical attachment level (CAL). The gingival crevicular fluid (GCF) were collected using filter paper size 30 from gingival sulcus of the controls and from (138) pocket site (75 sites > 6mm. and 63 ≤ 6mm.). The weight of the GCF was measured by reading the difference in the weight of filter paper before and after absorption of GCF. Crevicular level of CRP was measured calorimetrically. The serum level CRP was measured using latex test. Results: Highly significant difference in the weight of GCF, crevicular and serum level of CRP between chronic periodontitis and control groups. Subgroup 2 got higher scores of weight of GCF and positive record of crevicular and serum CRP compared with subgroup 1 with a non-significant difference. A highly significant difference in the number of sites with positive crevicular and serum CRP compared to the negative number between chronic periodontitis and control groups also between subgroup1 and subgroup 2. Weight of GCF gets a negative significant correlation with GI at control group and subgroup2. Serum level of CRP exhibits a negative significant correlation with PLI for chronic periodontitis and control group and positive significant correlation for GI at subgroup 1. The crevicular CRP get significant negative correlation with GI of subgroup 1. Conclusions: Crevicular fluid is very good marker for the degree of inflammation of the periodontal pocket. The crevicular level of CRP may be considered as a good tool for estimating the systemic effect and predictor for the effect of periodontitis on the general health and the correlation of crevicular with serum CRP aid to high light this effect.
Periodontitis is a chronic inflammation affecting the tooth-supporting periodontal tissues. It is diagnosed by measuring periodontal parameters. However, documenting this data takes effort and may not discover early periodontitis. Biomarkers may help diagnose and assess periodontitis. This study aimed to evaluate the potential diagnostic of the salivary tumor necrosis factor-α (TNF-α) and receptor-activator of nuclear factor ĸ-B-ligand (RANKL) in distinguishing between periodontitis and healthy periodontium.
The
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Equilibrium and rate of mixing of free flowing solid materials are found using gas fluidized bed. The solid materials were sand (size 0.7 mm), sugar (size0.7 mm) and 15% cast iron used as a tracer. The fluidizing gas was air with velocity ranged from 0.45-0.65 m/s while the mixing time was up to 10 minutes. The mixing index for each experiment was calculated by averaging the results of 10 samples taken from different radial and axial positions in fluidized QVF column 150 mm ID and 900 mm height.
The experimental results were used in solving a mathematical model of mixing rate and mixing index at an equilibrium proposed by Rose. The results show that mixing index increases with inc
... Show MoreThis study is qualitative, it illustrates H.G. Wells\\'s The Time Machine through the scientific and social framework of the Victorian Era. Wells\\'s portrayal of future societies examines the rapid technological progress and social changes of the 19th century. The analysis scrutinizes the division between the Eloi and the Morlocks, tracing the consequences of social division. To meet the objective of the study, Victorian frame of mind is utilized to examine the class struggle that is symbolized by the Eloi and the Morlocks. The analysis highlights the economic and social effects of industrialization and how Wells examines the capitalist system and its impact on human relationships and class division. The study also utilizes concepts from D
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Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the
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Community detection is an important and interesting topic for better understanding and analyzing complex network structures. Detecting hidden partitions in complex networks is proven to be an NP-hard problem that may not be accurately resolved using traditional methods. So it is solved using evolutionary computation methods and modeled in the literature as an optimization problem. In recent years, many researchers have directed their research efforts toward addressing the problem of community structure detection by developing different algorithms and making use of single-objective optimization methods. In this study, we have continued that research line by improving the Particle Swarm Optimization (PSO) algorithm using a
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
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In this work, the effect of aluminum (Al) dust particles on the DC discharge plasma properties in argon was investigated. A magnetron is placed behind the cathode at different pressures and with varying amounts of Al. The plasma temperature (Te) and density (ne) were calculated using the Boltzmann equation and Stark broadening phenomena, which are considered the most important plasma variables through which the other plasma parameters were calculated. The measurements showed that the emission intensity decreases with increasing pressure from 0.06 to 0.4 Torr, and it slightly decreases with the addition of the NPs. The calculations showed that the ne increased and Te decreased with pressure. Both Te and ne were reduced by increasing
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