Background: This study evaluate the immunohistochemical expression profile of transforming growth factor beta-1 in inflamed gingival tissue of patients with gingivitis and chronic periodontitis compared to healthy subjects and, determine the correlation between this cytokine and the clinical periodontal parameters, intensity of inflammation and chronic periodontitis severity. Materials and methods: Gingival tissue specimens were taken from 23 chronic periodontitis patients, 20 gingivitis patients and 20 periodontally healthy subjects. The periodontal status was evaluated by dichotomous measurements of the clinical periodontal parameters (PLI, GI, BOP, PPD, CAL). The gingival specimens were fixed immediately in 10% formalin and processed routinely into paraffin blocks for further immunohistochemical analysis. Results: A highly significant statistical difference was observed between the study groups regarding the PLI ,GI ,the percentage of bleeding on probing sites and the intensity of inflammation .TGF-?1 expression profile statistical analysis showed a high statistical significant difference among the study groups , A highly significant statistical difference was found between the PPD Scores while a significant statistical difference was revealed among the CAL Scores when the expression profile of TGF-?1 was compared.TGF-?1 was positively correlated with the clinical periodontal parameters (PLI, GI, and BOP) as well as with the intensity of inflammation in the three study groups. In chronic periodontitis group a highly significant positive linear correlation between the PPD and CAL with the TGF-?1 expression profile. Conclusions: TGF-?1 expression profile showed variations as the destructive character of the periodontal disease changed. Therefore, it could be proposed that TGF-?1 might contribute both to inflammatory regulation and remodeling events during periodontal disease.
(23)
(15)
(19)
(16)
Abstract
Multivariate GARCH Models take several forms , the most important DCC dynamic conditional correlation, and CCC constant conditional correlation , The Purpose of this research is the Comparison for both Models.Using three financial time series which is a series of daily Iraqi dinar exchange rate indollar, Global daily Oil price in dollar and Global daily gold price in dollarfor the period from 01/01/2014 till 01/01/2016, Where it has been transferred to the three time series returns to get the Stationarity, some tests were conducted including Ljung-Box , JarqueBera , Multivariate ARCH to Returns Series and Residuals Series for both models In Comparison
... Show More
(1)
(11)
(11)
The Co (II), Ni (II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II) complexes of mixed of amino acid (L-Alanine ) and Trimethoprim antibiotic were synthesized. The complexes were characterized using melting point, conductivity measurement and determination the percentage of the metal in the complexes by flame (AAS). Magnetic susceptibility, Spectroscopic Method [FTIR and UV-Vis]. The general formula have been given for the prepared mixed ligand complexes [M(Ala)2(TMP)(H2O)] where L- alanine (abbreviated as (Ala ) = (C5H9NO2) deprotonated primary ligand, L- Alanine ion .= (C5H8NO2 -) Trimethoprim (abbreviated as (TMP ) = C10H11N3O3S M(II) = Co (II),Ni(II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II). The results showed that the deprotonated L- Alanine by KOH (Ala
... Show More
(9)
(9)
(8)
(18)
Green biosynthesized selenium nanoparticles from
(126)
(117)
Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm
... Show More
(8)
(2)