Background: Chronic kidney disease is a worldwide health problem, with adverse outcomes of cardiovascular disease and premature death, can be divided into five stages, depending on how severe the damage is to the kidneys, or the level of decrease in kidney function, the final stage of chronic kidney disease is called end-stage renal disease, salivary immunoglobulin A is the main immunoglobulin found in mucous secretions, including tears, saliva, colostrum and secretions from the genitourinary tract gastrointestinal tract, prostate and respiratory epithelium . It is also found in small amounts in blood.This study aimedto measuresalivary flow rate and salivaryimmunoglobulin Alevels in chronic kidney disease patients on hemodialysis treatment in comparison with healthy control subjects. Materials and Methods: Ninety (90) subjects were participated in this study; 45 Patients undergoing hemodialysis with chronic kidney diseases; 45 health control subjects. Saliva collected was measured and levels of salivary immunoglobulin A were measured by Enzyme Link Immunosorbent Assay (Elisa). Results:The present studyrevealed that the mean value of salivary flow rate in chronic kidney disease patients was (0.34 ± 0.19) ml/min, while for healthy control subjects was (1.02 ± 0.39) ml/min, there wasstatisticallysignificantly decrease in salivary flow rate ofchronic kidney disease on hemodialysis patients as compared to control healthy subjects.The present study revealed that the (Mean±SD) of the immunoglobulin A in chronic kidney disease patients on hemodialysis (388.81±227.86) µg./ml, while in control group (273.98±155.89) µg./ml, the result revealed statistically significant increase in chronic kidney disease patients on hemodialysis as compared to control subjects. Conclusions: Salivary immunoglobulin (IgA) reflects the functional capacity of the glands. Increased concentration of this component is usually marker of a poor general condition.
An anatomical study was carried out at the College of Agricultural Engineering Sciences, University of Baghdad, in 2017, on lupine crop (Lupinus albus) as a comparison guide of three seed weights of three lupine cultivars viz. ‘Giza-1’, ‘Giza-2’ and ‘Hamburg’. The nested design was used with four replications. The results showed that cultivars had a significant effect on stem anatomical traits. ‘Hamburg’ cultivar recorded the highest stem diameter, cortex thickness and xylem vascular diameter, while cultivar ‘Giza-1’ recorded the lowest values for the same traits as well as the highest collenchyma layer thickness, vascular bundle thickness, and xylem thickness. Cultivar ‘Giza-2’ recorded the lowest vascular b
... Show MoreThree-dimensional cavity was investigated numerical in the current study filled with porous medium from a saturated fluid. The problem configuration consists of two insulated bottom and right wall and left vertical wall maintained at constant temperatures at variable locations, using two discretized heaters. The porous cavity fluid motion was represented by the momentum equation generalized model. The present investigation thermophysical parameters included the local thermal equilibrium condition. The isotherms and streamlines was used to examine energy transport and momentum. The meaning of changing parameters on the established average Nusselt number, temperature and velocity distribution are highlighted and discussed.
: zonal are included in phraseological units, form metaphorical names for a person, give him various emotional and evaluative characteristics. This article examines the topic of zoomorphic metaphors that characterize a person in the Russian and Arabic languages in the aspect of their comparative analysis, since the comparative analysis of the metaphorical meanings of animalisms is an important method for studying cultural linguistics, since zoomorphic metaphors are a reflection of culture in a language.
Epithelial‐mesenchymal transition (
Investigating the heavy metals in soil is important to the life of humans and living organisms. Diyala River Lower Reaches was chosen due to the changes in environmental characteristics that took place in recent years. Twelve sediment samples were collected from four different sites. The physical, and chemical properties and the concentrations of nine heavy metals were indicated. The results showed that the average concentrations of arsenic, copper, chromium, cobalt, iron, manganese, nickel, lead, and zinc are 8.5, 45.7, 538.5, 12.2, 5.07, 991.7, 183.5, 16.07, 136.5 ppm, respectively. They reflect contamination with arsenic, chromium, and nickel, while they are free of lead, and zinc contamination, according to the Environmental P
... Show MoreFree radicals are reactive compounds, their excessive production is considered to be an important cause of oxidative damage in biomolecules causing degenerative diseases. Polyphenols are one of the most important groups of secondary metabolites of plants, which have an antioxidant activity depending on their properties as hydrogen donors. Echinops polyceras Boiss. (Asteraceae) is one of Echinops genus species that spread in Syria, Lebanon, and Palestine. Phytochemicals found in this species leaves have been extracted with gradient polarity solvents, and primary screening of the secondary metabolites was established. The phenolic compounds and flavonoids contents were determined. The free radicals scavenging act
... Show MoreVarious theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp
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