The current study was conducted in the period extending from November 2018 to October 2019 and designed as a case-control study and aimed to assess the seroprevalence of HCMV. However, a total number of 91serum specimens were collected to fulfill this purpose from females (71 breast cancer patients, and control group of 20 females) attending Al-Amal hospital for cancer management and Baghdad teaching hospital and the practical part was performed in College of Science, University of Baghdad. The study protocol was approved by the Ethics Committee at the Department of Biology (Reference: BEC/0220/0011). The immunological part for evaluation of seroprevalence of HCMV was accomplished by ELISA technique which revealed that anti-HCMV IgG was scored positive in 67/71 (94.36%) and 19/20 (95%) of breast cancer patients and control group respectively, whereas anti-HCMV IgM was only detected in 6/71 (8.45%) of the patients of breast cancer. Moreover, levels of IgG were elevated in 81.69% of breast cancer patients compared to 40% only of control group.
Globally, breast cancer is the common malignancy affecting women and understanding its associated molecular events could help in disease prevention and management strategies. The present study was set to investigate an association between total antioxidant capacity (TAC) and endothelial nitric oxide synthase (eNOS) polymorphisms with breast cancer. For this purpose, 100 subjects were participated in this work, including 50 female patients diagnosed with breast cancer recruited from Oncology hospital, Baghdad - Iraq and 50 healthy women as a control group. The concentration of antioxidants was measured in the serums collected from blood samples of breast cancer patients and healthy controls. While eNOS SNPs (rs1799983, G894T and rs2070744, T
... Show MoreBackground: Urinary tract infections (UTIs) and their complications such as Bladder cancer (Bl. C.) are a health growing problem worldwide. Objective: To shed light on this subject, present study was done to investigate relationship between recurrent urinary tract infection (RUTI) due to Escherichia coli (E. coli) and Bl. C.Type of study: Cross-sectional study. Methods: This study included 130 patients with RUTI, 50 patients with Bl. C. and 50 control of both sexes (aged 7-85 years) attending Al-Zahra Teaching Hospital in Al-Kut/Wassit governorate and Al-Harery Teaching Hospital of specialized surgeries/Baghdad. The patients were divided into two groups: the first group (n=130) included those who were suffering from recurrent UTI without
... Show MoreCysteine-cysteine chemokine ligand 5 (CCL5) is known to play an important role with immunoregulatory and inflammatory activities in the formation of granuloma during infection with Mycobacterium tuberculosis. About 90 subjects, involving 50 patients with pulmonary TB and 40 apparently healthy individuals (as a control group) were collected from primary health care center\AL-Sadur city sector/ Baghdad City/ Iraq, and at specialized chest and respiratory diseases center in Wassit City /Iraq during the period from January 2019 to May 2019. The study was carried out to investigate serum level of CCL-5 of both patients and control by using enzyme linked immunosorbent assay (ELISA), and to determine the association between CCL5 genotypes with pul
... Show MoreBackground: Computerized tomography scan can show the detailed anatomy of the nose and paranasal sinuses. The sphenoid sinus is a very important corridor for the skull base because of its central position. This sinus has a great range of variation and can put structures around at risk during surgery. This study aims to examine the variation of the sphenoid sinus, and its relation to other structures around it, in this sample of Iraqi patients. Materials and Methods: CT scans of 122 patients, were obtained, and submitted for examination and measurements, during the period between September 2020 and September 2021. Observation of The sphenoid sinus pneumatization pattern, clival extension, Onodi cell, and lateral pneumatization of SS.
... Show MoreDiabetes mellitus, or simply diabetes, is a group of metabolic diseases in which a person has high blood sugar, either because the pancreas does not produce enough insulin, or because cells do not respond to the insulin that is produced. This high blood sugar produces the classical symptoms of polyuria (frequent urination), polydipsia (increased thirst), and polyphagia (increased hunger). The aim of the study is to measure several biochemical parameters in T2DM patients and the effect of these parameters in development the disease. Laboratory investigations including Ceruloplasmin , fasting blood glucose (FBG) , malondialdehyde (MDA), serum protein, uric acid, and protein electrophoresis have been measured in patients with type
... Show MoreBackground: Hyperthyroidism is a serious public concern, due the continuous increase in its prevalence and its impact on the mortality rates. Autoimmune hyperthyroidism is seen as a thyroid gland problem. Pro-inflammatory cytokines are crucial for the growth and development of hyperthyroidism, it was shown that the level of several pro-inflammatory cytokines were higher in the hyperthyroidism patients. Objective: This work was aimed to assessment the concentration of certain cytokine in hyperthyroid patients. Materials and Methods: Sixty hyperthyroidism patients and 30 healthy individuals with age range from (30-65) years old were enrolled in this study through their presence at the National Center for Diabetes Treatment and Research in Bag
... Show MoreProblem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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