Background: disturbed physiological rhythm of blood pressure in preeclampsia is a common finding. The role of oxidative stress in pathogenesis of preeclampsia is well accepted. Melatonin is a powerful free radical scavenger so it's rapidly consumed by enhanced reactive oxygen species in preeclampsia causing non-dipping in blood pressure.Objective: To evaluate the change in plasma melatonin levels in patients with preeclampsia and its relationship with blood pressure.Patients and methods: In this prospective case control study a total of 40 primigravidae pregnant women were recruited during the period of 11 months between August 2015 and August 2016 in Baghdad teaching hospital, medical city, Iraq, divided into two groups:First groups: (cases group) were 20 primigravidae pregnant women with PE.Second group: (control group) were 20 normal healthy primigravidae.Blood Pressure measurement, melatonin blood samples were taken, plasma melatonin levels measurement was done by ELISA immunoassay. Urine was collected over 24 hours for protein in urine measurement.Results : Plasma Melatonin level in control , day and night was (22.72 ± 2.6 pg/mL ) , (75.26 ± 2.99 pg/mL ) compared to Plasma Melatonin level in dipper PE day and night (20.5±2.4 pg/mL ) , (75.26 ± 1.8 pg/mL) which was statistically not significant( P value 0.055 ) , (P value 1.0) respectively .Plasma Melatonin level for non-dipper ( 22.45 ± 2.48 pg/mL) were similar to dipper (20.5±2.4 pg/mL) which is not significant (P value 0.1) , while Night time Plasma Melatonin of non-dipper (36.76 ± 1.27 ) were reduced when compared to control (75.26 ± 2.99 pg/mL) and to dipper group (75.26 ± 1.8 pg/mL ) which was highly significant (p <0.0001 , p <0.0001) respectively .Conclusion: Night time Plasma Melatonin level reduced in Primigravid Women with preeclampsia that did not show nocturnal dipping in blood pressure.
The study evaluates the incidence of inferior alveolar nerve injuries in mandibular fractures, the duration of their recovery, and the factors associated with them. Fifty-two patients with mandibular fractures involving the ramus, angle, and body regions were included in this study; the inferior alveolar nerve was examined for neurological deficit posttraumatically using sharp/blunt differentiation method, and during the follow-up period the progression of neural recovery was assessed. The incidence of neural injury of the inferior alveolar nerve was 42.3%, comminuted and displaced linear fractures were associated with higher incidence of inferior alveolar nerve injury and prolonged recovery time, and recovery of inferior alveolar nerve fun
... Show MoreIn this paper, simulation studies and applications of the New Weibull-Inverse Lomax (NWIL) distribution were presented. In the simulation studies, different sample sizes ranging from 30, 50, 100, 200, 300, to 500 were considered. Also, 1,000 replications were considered for the experiment. NWIL is a fat tail distribution. Higher moments are not easily derived except with some approximations. However, the estimates have higher precisions with low variances. Finally, the usefulness of the NWIL distribution was illustrated by fitting two data sets
This paper deals with constructing a model of fuzzy linear programming with application on fuels product of Dura- refinery , which consist of seven products that have direct effect ondaily consumption . After Building the model which consist of objective function represents the selling prices ofthe products and fuzzy productions constraints and fuzzy demand constraints addition to production requirements constraints , we used program of ( WIN QSB ) to find the optimal solution
The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue
... Show MoreIn this research a new system identification algorithm is presented for obtaining an optimal set of mathematical models for system with perturbed coefficients, then this algorithm is applied practically by an “On Line System Identification Circuit”, based on real time speed response data of a permanent magnet DC motor. Such set of mathematical models represents the physical plant against all variation which may exist in its parameters, and forms a strong mathematical foundation for stability and performance analysis in control theory problems.