Background: Patients requiring renal biopsies have various glomerular diseases according to their demographic characteristics.
Objective: To study types of glomerular disease among adult Iraqi patients in a single center in Baghdad/Iraq
Material and Methods: A total of 120 native kidney biopsies were studied. All biopsies were adequate and were processed for Light Microscopy.
The age range of the study patients was 17-67 years, with a mean of 38.5 years. The mean follow up period was 28 weeks (4-52 weeks)
Indication for biopsy included: Nephrotic syndrome (N=72; 60%), Asymptomatic proteinuria (N=21; 17.5%), acute nephritic presentation (N=17; 14.16%), asymptomatic haematuria (N=10; 8.33%).
Results: Primary glomerulonephrit

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

Adenosine deaminase (ADA; Ec: 3.5.4.4), 5´- Nucleotidase (5´– NT; Ec: 3.1.3.5), and AMP – amino hydrolase (AMP – deaminase AMPDA; Ec: 3.5.4.6) activities were measured in sera of ovarian cancer patients before surgery, and after chemotherapy. The results indicated that ADA specific activity increased significantly (P<0.05), while 5´-NT and AMPDA specific activity decreased significantly (P<0.05) in ovarian cancer patients before surgery in comparison with those of their corresponding control women and benign tumors groups. When the activities of these enzymes were measured after chemotherapy, a significant decrease (P<0.05) in ADA activity, and a significant increase (P<0.05) in 5´- NT and AMPDA activities w

         This study investigated the effect of using brainstorming as a teaching technique on the students’ performance in writing different kinds of essays and self regulation among the secondary students. The total population of this study, consisted of (51) female students of the 5^th Secondary grade in Al –kawarzmi School in Erbil during the academic year 2015-2016. The chosen sample consisted of 40 female students, has been divided into two groups. Each one consists of (20) students to represent the experimental group and the control one. Brainstorming technique is used to teach the experimental group, and the conventional method is used to teach the control group. The study inst

Background: Obesity is an evolving major health problem in both developed and developing countries. Traditional obesity indices as body mass index, waist circumference, waist-hip-ratio are well known measures to identify obese subjects, however, neck circumference as an index of upper-body obesity was found to be a simple and time-saving screening measure that can be used to identify obesity and the likelihood of developing metabolic syndrome in type 2 diabetic patients.
Aim: to investigate the relationship of neck circumference (NC) to obesity and metabolic syndrome in Iraqi subjects with type 2 diabetes.
Methods: The study group included 90 type 2 diabetic subjects (48 men and 42 women) aged 30-68 years. The subjects were those w

In this study, the Halder-Wagner method was used for an analysisX-ray lines of Tio2 nanoparticles. Where the software was used to calculate the FWHM and integral breath (β) to calculate the area under the curve for each of the lines of diffraction. After that, the general equation of the halder- Wagner method is applied to calculate the volume (D), strain (ε), stress (σ), and energy per unit(u). Volume (β). Where the value of the crystal volume was equal to (0.16149870 nm) and the strain was equal to (1.044126), stress (181.678 N / m2), and energy per unit volume (94.8474 J m-3).The results obtained from these methods were then compared with those obtained from each of the new paradigm of the HalderWagner method, the Shearer developm

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c