Background: Diabetic patients have been reported to be more susceptible to gingivitis and periodontitis than healthy subjects. Many intracellular enzymes like (alkaline phosphatase- (ALP), aspartate aminotransferase- (AST) and alanine aminotransferase- (ALT) that are released outside cells into the gingival crevicular fluid (GCF) and saliva after destruction of periodontal tissue during periodontitis. This study was conducted to determine the periodontal health status and the levels of salivary enzymes (ALP, AST and ALT) of the study and control groups and to correlate the levels of these enzymes with clinical periodontal parameters in each study group. Subjects, Materials and Methods: One hundred subjects were enrolled in the study, with an age range of (35-50) years, only males were included. The subjects were divided intostudy groups (group-I consists of 30 patients with controlled type 2 diabetes mellitus(T2DM), group-II consists of 30 patients with uncontrolled T2DM, group-III consists of 25 patients non-diabetics, all of them have chronic periodontitis(CP) and group-IV consists of 15 apparently- systemically healthy subjects and have healthy periodontium, as control group. Unstimulated saliva samples were collected for biochemical analysis of salivary enzymes (ALP, AST and ALT).The clinical periodontal parameters including: plaque index (PLI), gingival index (GI), bleeding on probing (BOP), probing pocket depth (PPD) and clinical attachment level (CAL) were recorded for all subjects at four sites per tooth except third molars. Results: All clinical periodontal and biochemical parameters were highest in uncontrolled T2DM with CP patients and all enzymes levels revealed highly significant differencesbetween all pairs of the study and control groups except AST enzyme level which demonstrated a non-significant difference between controlled T2 diabetics with CP and non-diabetics with CP. There were weak correlations between all clinical periodontal parameters and biochemical parameters except between PPDand ALT enzyme in non-diabetics with CP group and between CAL and AST enzyme in uncontrolled T2 diabetics with CP which demonstrated highly significant strong positive correlations. Conclusion: It was concluded that T2DM and poor glycemic control have negative impact on periodontal health status. Salivary enzymes were considered as good biochemical markers of periodontal tissue destruction and useful in diagnosis, monitoring and efficient management of periodontal diseases and T2DM. Key words: Enzymes, saliva, type 2 diabetes mellitus, periodontal diseases.
(3)
(1)
This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators
(2)
Facing industrial companies many pressures and challenges due to rapid changes in the business environment of contemporary, which requires them to do their performance look more inclusive rather than limiting performance evaluation on the financial perspective in spite of its importance, prompting companies to rethink their reality competitive through the adoption of methodologies and new philosophies to manage competitiveness of total quality management, and re-engineering of production processes, and knowledge management,... etc., as This study framework cognitive and practical "to evaluate the performance of a company Diyala General Electric Industries and how to rehabilitate
(1)
Background: Anaemia is a major public health concern and is one of the most prevalent health issue in women within reproductive age group.
Objective: to assess maternal knowledge related to anaemia during pregnancy.
Type of the study: A cross –sectional study.
Method: The study including 200 mothers who attended selected primary health care centres, Baghdad during November and December 2015, they completed a previously prepared questionnaire coveringsocio-demographic characteristics and knowledge regarding anaemia in 4 main domains. The responses were analysed by using frequency, percentage and percent score for each statement a
... Show More
(2)
Albizia lebbeck biomass was used as an adsorbent material in the present study to remove methyl red dye from an aqueous solution. A central composite rotatable design model was used to predict the dye removal efficiency. The optimization was accomplished under a temperature and mixing control system (37?C) with different particle size of 300 and 600 ?m. Highest adsorption efficiencies were obtained at lower dye concentrations and lower weight of adsorbent. The adsorption time, more than 48 h, was found to have a negative effect on the removal efficiency due to secondary metabolites compounds. However, the adsorption time was found to have a positive effect at high dye concentrations and high adsorbent weight. The colour removal effi
... Show More
(13)
(11)
The aim of this study was to know ( the impact of education differentiated strategy to modify the alternative developments of geographical concepts when students first grade average) .
To achieve the goal of this study , researcher relied on the experimental design of a partial set , the design is ( the experimental group with a control group of post-test ).
&nbs
... Show MoreExtracorporeal Shock Wave Lithotripsy (ESWL) is the most commonplace remedy for kidney stone. Shock waves from outside the body frame are centered at a kidney stone inflicting the stone to fragment. The success of the (ESWL) treatment is based on some variables such as age, sex, stone quantity stone period and so on. Thus, the prediction the success of remedy by this method is so important for professionals to make a decision to continue using (ESWL) or tousing another remedy technique. In this study, a prediction system for (ESWL) treatment by used three techniques of mixing classifiers, which is Product Rule (PR), Neural Network (NN) and the proposed classifier called Nested Combined Classi
... Show More
Research on the automated extraction of essential data from an electrocardiography (ECG) recording has been a significant topic for a long time. The main focus of digital processing processes is to measure fiducial points that determine the beginning and end of the P, QRS, and T waves based on their waveform properties. The presence of unavoidable noise during ECG data collection and inherent physiological differences among individuals make it challenging to accurately identify these reference points, resulting in suboptimal performance. This is done through several primary stages that rely on the idea of preliminary processing of the ECG electrical signal through a set of steps (preparing raw data and converting them into files tha
... Show More