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 In rheumatoid arthritis, your immune system attacks the tissue lining the joints on both sides of your body. Other parts of the body may also be affected. Unsure of the exact cause. Two separate genes termed IL12A (p35) and IL12 encode the heterodimeric cytokine known as IL12 (p40). Several different hematopoietic cell types can have several different hematopoietic cell types that can generate antigen-presenting cells (APCs), including DCs and macrophages. Objectives This study aimed to investigate if the interleukin IL-12B gene's common polymorphisms in an Iraqi population were associated with RA. Material and methods Blood samples were taken from 70 Iraqi patients with RA illnesses and 30 Iraqi controls during the periods from

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p

Letrozole (LZL) is a non-steroidal competitive aromatase enzyme system inhibitor. The aim of this study is to improve the permeation of LZL through the skin by preparing as nanoemulsion using various numbers of oils, surfactants and co-surfactant with deionized water. Based on solubility studies, mixtures of oleic acid oil and tween 80/ transcutol p as surfactant/co-surfactant (Smix) in different percentages were used to prepare nanoemulsions (NS). Therefore, 9 formulae of (o/w) LZL NS were formulated, then pseudo-ternary phase diagram was used as a useful tool to evaluate the NS domain at Smix ratios: 1:1, 2:1 and 3:1.

This paper proposes a new method Object Detection in Skin Cancer Image, the minimum
spanning tree Detection descriptor (MST). This ObjectDetection descriptor builds on the
structure of the minimum spanning tree constructed on the targettraining set of Skin Cancer
Images only. The Skin Cancer Image Detection of test objects relies on their distances to the
closest edge of thattree. Our experimentsshow that the Minimum Spanning Tree (MST) performs
especially well in case of Fogginessimage problems and in highNoisespaces for Skin Cancer
Image.
The proposed method of Object Detection Skin Cancer Image wasimplemented and tested on
different Skin Cancer Images. We obtained very good results . The experiment showed that