Background: Breast cancer is the most common
malignancy affecting females worldwide. The association
of Epstein-Barr virus (EBV) with this cancer is a longstanding
interest to this field.
Aim: to investigate the presence of EBV in breast tumor
tissue in relation to age.
Patients and Methods: Paraffin-embedded tissue blocks
from 45 female patients with breast tumors (ranged in age
from 28 to 85 years) were retrieved. The cases were
grouped into two categories: group (A): included 30 cases
with breast carcinoma and group (B): included 15 cases
with benign breast diseases as a control group .The
expression of EBV protein was examined
immunohistochemically.
Results: Twelve (40%) of the 30 breast canc

This study aimed to evaluate serum levels of steroid hormones and human chorionic gonadotropin (hCG) hormone in preeclamptic Iraqi pregnancies compared to those of healthy pregnancies.This study enrolled 120 pregnant women, divided into four groups:1. 30 healthy pregnant women.2. 37 pregnant women with mild preeclampsia3. 53 pregnant women with severe preeclampsia4. 90 pregnant women with preeclampsia Preeclamptic women and their severe cases but not mild cases had significantly (P<0.01) increased levels of serum hCG as compared with healthy pregnancies. By contrast, sera levels of estradiol were significantly (P<0.01) decreased in total preeclamptic groups and their severe cases but not in mild group as compared to healthy pregnant wome

This study is designed to detect the level of cytokine IFN-γ concentration, and some antioxidants, including super oxide dismutase (SOD) and Vitamin C, and to estimate the level of sex hormones (FSH and LH), and to determine auto-antibodies (antiphospholipid antibodies (APA) IgG\IgM, and anticardiolipin antibodies (ACA) IgG\IgM) and to estimate the blood parameters in 51 miscarriage women infected with T.gondii distributed depending on the type of antibodies. Additionally, 39 volunteers non-infected with T.gondii included (19 miscarriage women, 10 pregnant women and 10 non-pregnant women). ELISA and spectrophotometer method were used in this study. The results of IFN-γ showed a significant increase)p<0.05) in the l

This  study  was undertaken  to shed light on the changes  of levels of CP

activity, Cu and  Fe in sera of .(53) normaJ non-smoker pregnant's  without complication, during  three1rimestcrs of pregnancy.

G1  inc.l_ude  (I 8) pre nants in  the 1' 1 tri nester, G2 19)  pret:,rp:all.ts  _wear

taken     m the  2"    tnmester  and  G3  (16) pregnants  m the  3rd  trunester.

/\nothe.r ('18) ·serum samples were taken from liealthy non-pregnant wqmen

age matched as control·group G4.

Results bowed a significant steady  elevation in CP .p:ctivity and &n

The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

Objective: Zerumbone (ZER) is a well-known natural compound that has been reported to have anti-cancer effect. Thus, this study investigated the ZER potential to inhibit Thymidine Phosphorylase (TP) and the ability to trigger Reactive oxygen species (ROS)-mediated cytotoxicity in non-small cell lung cancer, NCI-H460, cell line. Material and Method: The antiangiogenic activity for ZER was evaluated by using the thymidine phosphorylase inhibitory test. Reactive oxygen species (ROS) production was determined via DCFDA dye by using flow cytometry. Result and Discussion: ZER was found to be potent TP inhibitory with the IC50 value of 50.3± 0.31 μg/ml or 230±1.42 µM. NCI-H460 cells upon treatment with ZER produced sign

Objective: Zerumbone (ZER) is a well-known natural compound that has been reported to have anti-cancer effect. Thus, this study investigated the ZER potential to inhibit Thymidine Phosphorylase (TP) and the ability to trigger Reactive oxygen species (ROS)-mediated cytotoxicity in non-small cell lung cancer, NCI-H460, cell line. Material and Method: The antiangiogenic activity for ZER was evaluated by using the thymidine phosphorylase inhibitory test. Reactive oxygen species (ROS) production was determined via DCFDA dye by using flow cytometry. Result and Discussion: ZER was found to be potent TP inhibitory with the IC50 value of 50.3± 0.31 μg/ml or 230±1.42 µM. NCI-H460 cells upon treatment with ZER produced sign

Health literacy is an important method used by the authorities to strengthen the health system. The aim of this study is to assess the knowledge of some basic health principles among women of different educational states. This is a crosssectional study, performed from December 2014 until January 2016, Baghdad. All candidates were: females &gt; 18 years, neither medical staff nor students. They were divided into two groups: educated and uneducated. The sample included 213 women, there were 112 educated and 101 uneducated women. Regarding educated group, accurate answers regarding route of transmission of typhoid fever was 73.2% in educated subjects vs. 49.5% in uneducated subjects. Main source of information for both groups was p

Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are