Introduction: Breast cancer is the most common cancer and the major cause of cancer related deaths among Iraqi women. Due to the relatively late detection of breast cancer, the majority of the patients are still treated by modified radicle mastectomy. Aim: To assess the time lag between diagnosis of breast cancer and mastectomy among Iraqi patients; correlating the findings with other clinicopathological characteristics of the disease. Patients and methods: This retrospective study enrolled 226 Iraqi female patients who were diagnosed with breast cancer. Data were registered on the exact time period between signing the histopathological report and the surgical treatment. Other recorded variables included the age of the patients, their level

The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

Over the last 40 years, rate of cesarean delivery has risen from less than10% to over 30% around the world, and almost simultaneously a 10-foldraise in the incidence of placenta accrete spectrum. Fine coordinationamong vascular endothelial growth factor, soluble fms-like tyrosine kinase1 and placental growth factor is important for normal placentaldevelopment and trophoblast invasion. To measure and compare the levelsof circulating vascular endothelial growth factor, placental growth factorand soluble fms-like tyrosine kinase 1 in pregnant women with placentaaccreta to a control group. A case control study which involved one hundredpregnant females were recruited from the Obstetric ward in BaghdadTeaching Hospital who were pregnant with 28

     Systemic Lupus Erythematosus (SLE) is a multifactorial chronic systemic autoimmune disease. It is characterized by a lack of immune tolerance to autoantigens such as nuclear antigens. The aim of the study is to assess the interferon-alpha (IFN-α) serum level in Iraqi patients with SLE and determine its potential relation to different clinical and laboratory parameters and disease activity. 100 SLE patients were all females and with a mean of age 31.3 ± 10 years (16-63years) and disease duration of 5.8 ± 3.7years (1 month to 15 years). The average of SLEDAI score ranged from 2 to 22 with a mean of (8.53 ±3.42). Proteinuria, ESR, creatinine and AST were significantly higher (65% vs. 10% and 0.62±0.11 vs. 0.70±0.14 mg/dl resp

Background: Polycystic ovary syndrome (PCOS) is the most common endocrine abnormality in women, there is an increasing evidence for an oxidative stress in PCOS that induce genomic and mitochondrial deoxyribonucleic acid damage that leads directly to reduced fertility. The objectives of this study are to assess and compare the periodontal health status by measuring clinical periodontal parameters (PLI, GI and BOP)as well as serum levels of superoxide dismutase at gingivitis ,gingivitis with PCOS and healthy periodontium groups, then correlate between clinical and biochemical parameters. Materials and Methods: 60 females with an age range between (25-40) years old had been tested and divided into3 groups ,the control group consists of (20) f

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

In this work, Kinetic Phosphorescence Analyzer (KPA) has been used to measure the concentrations of uranium (UC) and Amorphous crystals (AMO) in urine samples of breast cancer patients in Baghdad. Additionally, a relation between UC and AMO with respect to patient's age has been deduced and studied.
Forty one urine samples of patients and five for healthy were taken from females lived in different residential area of Baghdad. The measured maximum UC value for urine samples of patients was 2.35 ± 0.053, the minimum value was 0.86 ± 0.034 μg/L, and an overall average was 1.6 ± 0.027 μg/L while the average UC for healthy females was 1.03 ± 0.020 μg/L.
From these results, AMO concentrations were found for all breast cancer patie

         The emergence of staphylococci, either coagulase negative (CNS) or coagulase positive (CPS), as important human pathogens has implied that reliable methods for their identification are of large significance in understanding the diseases caused by them. The identification and characterization of staphylococci from biopsies taken from human breast tumors is reported here. Out of 32 tissue biopsies, a total of 12 suspected staphylococci grew on mannitol salt agar (MSA) medium, including 7 fermenters and 5 non-fermenter staphylococci based on traditional laboratory methods. Polymerase chain reaction (PCR) successfully identified seven isolates at the genus level as methicillin resistant St

Breast cancer has got much attention in the recent years as it is a one of the complex diseases that can threaten people lives. It can be determined from the levels of secreted proteins in the blood. In this project, we developed a method of finding a threshold to classify the probability of being affected by it in a population based on the levels of the related proteins in relatively small case-control samples. We applied our method to simulated and real data. The results showed that the method we used was accurate in estimating the probability of being diseased in both simulation and real data. Moreover, we were able to calculate the sensitivity and specificity under the null hypothesis of our research question of being diseased o

Breast cancer is the commonest cancer and the leading cause of malignancies-related mortality in women worldwide. Understanding the underlying biology of the disease could improve patients’ stratification and may offer novel therapeutic targets and strategies. This study was set to investigate the association between BRCA1 gene expression and some of the clinical features of breast cancer patients in Baghdad-Iraq. Eighty peripheral blood samples were collected from sixty patients diagnosed with breast cancer and twenty healthy age-matched controls for BRCA1 qPCR gene expression analysis.

     The results showed a significant reduction in BRCA1 gene expression in all of the bre