The current work was designed to investigate serum angiopoietin like protein-8 and hyaluronic acid among Iraqi hemodialysis patients with and without type 2 diabetes mellitus, and to find relationship between them, as well as if these patients are at risk of kidney fibrosis. Subjects & Methods: in this study, serum samples were obtained from (60) Iraqis patients with end stage renal diseases (ESRD)on hemodialysis (HD) (30 patients with T2DM (G2) and 30 patients withoutT2DM (G3)) in addition to (30) healthy individuals as a control group (G1), their ages ranged from (35-65) years. The patients attended the Al-Yarmouk Teaching Hospital, Baghdad. Results: the results in this study showed a highly a significant elevation inserum angiopoietin li

KE Sharquie, AF Hameed, AA Noaimi, Indian Journal of Pathology and Microbiology, 2016 - Cited by 12

Background: The purposes of this study were to determine the photogrammetric soft tissue facial profile measurements for Iraqi adults sample with class I normal occlusion using Standardized photographic techniques and to verify the existence of possible gender differences. Materials and methods: Eighty Iraqi adult subjects (40 males and 40 females) with an age ranged between 18-25 years having class I normal occlusion were chosen for this study. Each individual was subjected to clinical examination and digital standardized right side photographic records were taken in the natural head position which is mirror position which the patient looking straight into his eyes into the mirror mounted on the stand. The photographs were analyzed using A

Background: Difficulties arise when attempting to imagine the interpupillary line and comparing it with the Fox plane guide and not more difficult than holding any instrument over the movable pupils just to demonstrate the interpupillary line. The aim of this study was to introduce ear lobes as alternative landmarks for the interpupillary line during orientation of the occlusal plane. Also, the other aim was to compare the ear lobes with the pupils of the eyes to verify that they were indifferent as anatomical landmarks. Materials & methods: The alternative landmarks, ear lobes, were presented and the method for orienting the occlusal plane with these landmarks was introduced. Digital pictures of 30 subjects, who participated in the study,

Facial emotion recognition finds many real applications in the daily life like human robot interaction, eLearning, healthcare, customer services etc. The task of facial emotion recognition is not easy due to the difficulty in determining the effective feature set that can recognize the emotion conveyed within the facial expression accurately. Graph mining techniques are exploited in this paper to solve facial emotion recognition problem. After determining positions of facial landmarks in face region, twelve different graphs are constructed using four facial components to serve as a source for sub-graphs mining stage using gSpan algorithm. In each group, the discriminative set of sub-graphs are selected and fed to Deep Belief Network (DBN) f

Background: Bell's palsy was defined as facial weakness of lower motor neuron type caused by idiopathic facial nerve involvement outside the central nervous system without evidence of aural or more widespread neurologic disease. The cause is unclear, but the disorder occurs more commonly in diabetics.Objectives: to differentiate cases of idiopathic Bell's palsy from diabetic mononeuropathy presented with Facial nerve palsy by assessing the taste, because they differ in etiology, management & prognosis.Patients &Methods: One hundred and fifteen consecutive patients were referred for the treatment of facial palsy, from May the 5th 2012 to April 12th 2013 in Al-Kindy Teaching Hospital and The Neurosciences Hospital, in Baghdad / Ira

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

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