Neuron-derived neurotrophic factor [NENF], a human plasma neurotrophic factor, also increases neurotrophic activity in conjunction with Parkinson's disease-related proteins in Neudesin. Although Neudesin (neuron-derived neurotrophic secreted protein) is a member of the membrane-associated progesterone receptor (MAPR) protein subclass, it is not evolutionary related to the other members of the same family. The expression of Neudesin is found in both brain and spinal cord from embryonic stages to adulthood, as w Neudesin levels in Parkinson's patients with osteoporosis disease and Parkinson's patients without osteoporosis disease, as well as the relationship between Neudesin levels, Anthropometric and Clinical Features (Age, Gender, BMI) and

Background: Understanding the morphological characteristics between the floor of the maxillary sinus and the tips of the maxillary posterior roots is crucial in orthodontics involving diagnosis and treatment planning. The aim of this study was to evaluate the distances from the maxillary posterior root apices to the inferior wall of the maxillary sinus, thickness and density of maxillary sinus floor using cone-beam computed tomography images and the relationships between roots and maxillary sinus according to gonial angle and skeletal pattern. Materials and methods: Three-dimensional images of each root were checked, and the distances were measured along the true vertical axis from the apex of the root to the sinus floor, and the thickne

Background: First six to twelve months after initial urinary tract infection, most infections are caused by Escherichiacoli, although in the first year of life Klebsiella pneumoniae, Pseudomonas, Enterobacter spp andEnterococcus spp, are more frequent than later in life, and there is a higher risk of urosepsis compared with adulthood

Objectives: To determine the prevalence of bacterial isolates from Urinary Tract Infections of children at a children hospital in Baghdad and their antimicrobial susceptibility patterns.

Type of the study: Cross-sectional study.

Methods: During six months of study (1 June to 31 Dece

This study showed the spreading of head lice in pupils of primary schools of Al-Nassirya city. The results showed that the percentage of males infected with lice was (5.4 %) and (9 %) for females. Also was obtained difference at age groups which we found maximum percentage of infection at age between (8 – 11) year. The highest infection for the hair tall at medium tall for both sex which the ratio (35.2 %) while for both sex with ratio (25 %) for girls. While the highest percentage for straight hair was (14.8 %) for girls

Background: Economic Globalization affects work condition by increasing work stress. Chronic work stress ended with burnout syndrome.

Objectives: To estimate the prevalence of burnout syndrome and the association of job title, and violence with it among physicians in Baghdad, and to assess the burnout syndrome at patient and work levels by structured interviews.

Subjects and Methods: A cross section study was conducted on Physicians in Baghdad. Sampling was a multistage, stratified sampling to control the confounders in the design phase. A mixed qualitative and quantitative

Background: Economic Globalization affects work condition by increasing work stress. Chronic work stress ended with burnout syndrome. Objectives: To estimate the prevalence of burnout syndrome and the association of job title, and violence with it among physicians in Baghdad, and to assess the burnout syndrome at patient and work levels by structured interviews. Subjects and Methods: A cross section study was conducted on Physicians in Baghdad. Sampling was a multistage, stratified sampling to control the confounders in the design phase. A mixed qualitative and quantitative approach (triangulation) was used. Quantitative method used self-administered questionnaires of Maslach Burn out Inventory. Qualitative approach used an open-end

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att