Background: Rheumatoid arthritis is a chronic inflammatory autoimmune disease characterized by joint inflammation, involvement of exocrine salivary and lacrimal glands may occur as extra-articular mani¬festations in this disease. This study aimed to provide evidence of altered in function and composition of salivary gland in patients with rheumatoid arthritis by determine salivary flow rate and some biochemical parameters(total protein, amylase, peroxidase) and to investigate the relationship between disease activity and changes in function and composition of salivary gland. Materials and Methods: Fifty five patients with RA (7 males and 48 females) were enrolled in this study with age range (20-69) years. The patients were separated into two groups in proportion to their salivation: normal salivation group (37) and hypo salivation group (18). Thirty five (9 male and 26 female) apparently healthy volunteers were also participated in the study. Three ml of unstimulated saliva was collected from all patients and control to determine salivary flow rate on one hand and salivary total protein, α-amylase and peroxidase by colorimetric method on other hand. Results:Resultsshowed that there is highly significant decrease (P< 0.01; p< 0.001) in the median salivary levels of (flow rate, total protein, α-amylase and peroxidase) among RA patients when compared to control. There was highly significant reduction (P< 0.01) in median salivary levels of flow rate, total protein, α-amylase and peroxidase in two study groups (normal salivation and hypo salivation) as compared to that in control group. Also the levels of all these parameters (sialometry and sialochemistry) were significantly decrease (P =0.00) in RA patients with hypo salivation as compared to that in patients with normal salivation. There was strong positive correlation between total protein and salivary flow rate (r= 0.651, P=0.000), in one hand, and on the other hand, there was strong positive correlation between α-amylase and both salivary flow rate (r=623, P= 0.000) and total protein r=658, P=0.000). Conclusion: These findings indicate that the changes in salivary composition may represent involvement of salivary glands in patients with rheumatoid arthritis.
Wireless Multimedia Sensor Networks (WMSNs) are networks of wirelessly interconnected sensor nodes equipped with multimedia devices, such as cameras and microphones. Thus a WMSN will have the capability to transmit multimedia data, such as video and audio streams, still images, and scalar data from the environment. Most applications of WMSNs require the delivery of multimedia information with a certain level of Quality of Service (QoS). This is a challenging task because multimedia applications typically produce huge volumes of data requiring high transmission rates and extensive processing; the high data transmission rate of WMSNs usually leads to congestion, which in turn reduces the Quality of Service (QoS) of multimedia applications. To
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This study is studied one method of estimation and testing parameters mediating variables in a structural equations model SEM is causal steps method, in order to identify and know the variables that have indirect effects by estimating and testing mediation variables parameters by the above way and then applied to Iraq Women Integrated Social and Health Survey (I-WISH) for year 2011 from the Ministry of planning - Central statistical organization to identify if the variables having the effect of mediation in the model by the step causal methods by using AMOS program V.23, it was the independent variable X represents a phenomenon studied (cultural case of the
Background: Joint hypermobility was first mentioned by Hippocrates as an isolated feature, when he described the Celts' Incapacity to Pull a Bowstring or Throw a Dart, Due to The Slackness of Their Limbs
Objective: to determine the prevalence of mitral valve prolapse(MVP)in patients with benign hypermobility syndrome (BJHS).
Type of the study: Cross –sectional study.
Methods: Ninety patients with BJHS were included in this study. Full cardiological assessment was done for all of them, which include clinical examination, electrocardiography and echocardiography. Cardiac assessment was done for another sixty age and sex matched (
... Show MoreThis article suggests and explores a three-species food chain model that includes fear effects, refuges depending on predators, and cannibalism at the second level. The Holling type II functional response determines food consumption between stages of the food chain. This study examined the long-term behavior and impacts of the suggested model's essential elements. The model's solution properties were studied. The existence and stability of every probable equilibrium point were examined. The persistence needs of the system have been determined. It was discovered what conditions could lead to local bifurcation at equilibrium points. Appropriate Lyapunov functions are utilized to investigate the overall dynamics of the system. To support the a
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Predicting peterophysical parameters and doing accurate geological modeling which are an active research area in petroleum industry cannot be done accurately unless the reservoir formations are classified into sub-groups. Also, getting core samples from all wells and characterize them by geologists are very expensive way; therefore, we used the Electro-Facies characterization which is a simple and cost-effective approach to classify one of Iraqi heterogeneous carbonate reservoirs using commonly available well logs.
The main goal of this work is to identify the optimum E-Facies units based on principal components analysis (PCA) and model based cluster analysis(MC
... Show MoreMachine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed
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