Glutathione S-transferases (GSTs) are enzymes that included, in a more range of detoxifying reactions by conjugation of glutathione, to electrophilic material. Polymorphisms n the genes that responsible of GSTs affect, the function of the GSTs. GSTs play an active role in protection of cell against oxidative stress mechanism. Polymorphisms of GSTP1 at codon 105 amino acids forms GSTP1 important site for bind of hydrophobic electrophiles and the substitution of Ile/Val affect substrate specially catalytic activity of the enzyme and may correlate with reach to different diseases in human like diabetes mellitus type2 disease. Correlation between these polymorphisms and changes in the parameters file of diabetic patients has also bee

Gestational diabetes mellitus is glucose intolerance of varying degree with onset or first detection duringpregnancy,it can causelong and short term morbidities in both the mother and the child, such as shoulder dystocia,preeclampsia, and high blood pressure. The most powerful endogenous vasoconstrictor peptide, urotensin II, andits receptor are involved in the etiology of gestational diabetes mellitus.Aim of the study: The study’s goal was to see if there is a link between Urotensin II levels and insulin resistancein pregnant women with gestational diabetes.Patients and method: A case-control study that was conducted in obstetrics and gynecology department atBaghdad Teaching hospital from the first of January 2019 to the end of D

During the period 1970-2006 the Marshes-land region was exposed to several change into many sides of vanishing steeling and growth as follow :
1- Drying this region after 1991,and re-flooded again during 2003. Many other large Marsh-land, like al-Hawaisa was dried by cutting off inlet-water fed from Iran sources .As asqunance there are transferred to different kinds of swamps ,followed by major change in the structure of the region as the rural settlement concerned. Rural settlement in this area starts new push of migration. The research did not take that in consideration in this thesis because some others took it in details in some thesis and researches. The situation of Marsh-land is getting anew face after those major changes which

The diabetic foot is considered one of the long term diabetes complications caused by a defect in blood vessel and nerve system. This requires dealing with diabetic foot with professional medical care, so as to prevent its development in advanced stages which could end to gangrene and amputation of the foot. This study has been initiated through follow-up of twelve patients with diabetes and the presence various occlusions in lower limb artery. One patient from them was chosen for investigation, this patient has stenosis in popliteal artery and presence multiple stenosis in superficial femoral artery. This study based on analysis present case of patient and prediction for progress stenosis in superficial femoral artery till arrive semi t

This study aimed to investigate the effect of oral administration of pomegranate seed oil on diabetic in male rabbits. A total of 32 adult male rabbits.6 months old weighting 1-2kg were divided in to four equal groups. G- Control (negative) Rabbits were received olive oil, G2- (control positive) Rabbits were received (30 mg/kg B.W/daily of the Pomegranate seed oil orally and daily for 45 day. G3-Rabbits were received (150mg/kg of Alloxan injected Intraperitonealy, G4-Rabbits were received the same dose orally of the Pomegranate seed oil four 45 days. There is significant increase (Insulin, Insulin resistance) and decreased glucose in group received Pomegranate seed oil (G4) as compared with G3 (diabetic group). On conclusion, the administra

The process of accurate localization of the basic components of human faces (i.e., eyebrows, eyes, nose, mouth, etc.) from images is an important step in face processing techniques like face tracking, facial expression recognition or face recognition. However, it is a challenging task due to the variations in scale, orientation, pose, facial expressions, partial occlusions and lighting conditions. In the current paper, a scheme includes the method of three-hierarchal stages for facial components extraction is presented; it works regardless of illumination variance. Adaptive linear contrast enhancement methods like gamma correction and contrast stretching are used to simulate the variance in light condition among images. As testing material

The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm

Recent years have seen an explosion in graph data from a variety of scientific, social and technological fields. From these fields, emotion recognition is an interesting research area because it finds many applications in real life such as in effective social robotics to increase the interactivity of the robot with human, driver safety during driving, pain monitoring during surgery etc. A novel facial emotion recognition based on graph mining has been proposed in this paper to make a paradigm shift in the way of representing the face region, where the face region is represented as a graph of nodes and edges and the gSpan frequent sub-graphs mining algorithm is used to find the frequent sub-structures in the graph database of each emotion. T

Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.