Abstract Background:Breast cancer is the most common female cancer worldwide. Although mastectomy is considered the treatment of choice for the majority of cases of breast cancer; a noticeable percentage of breast cancer survivors claim they were never advised about reconstruction. It has been proven that breast reconstruction helps breast cancer survivors to overcome the trauma of their diagnosis and improve their psychological well-being.Objectives: To assess the level of awareness and expectations regarding breast reconstruction surgery among female with breast cancer survivors in Baghdad, and to find if there is association between sociodemographic data and expectations of breast reconstruction.Methodology: This is a cross sectional stu

The oncolytic viruses are promising form of cancer therapy which is based on the selectively killing of the cancer cells. This study was aimed to investigate the role of Newcastle disease virus (NDV) Iraqi strain AD2141 in apoptosis. Firstly, the virulence of AD2141 was detected in embryonated chicken eggs after 48hrs of infection. It was observed a hemorrhage in the skin of infected embryos that led to death. Then, the ability of this strain for regression cancer cell lines was examined. By using cytotoxicity test, it was found 128 HAU/ml of AD2141 had a potent inhibition against growth of RD and AMN3 after 72hrs of exposure time; the inhibition rate was 86.8% and 86.98% respectively. Moreover, the apoptotic activity of AD2141 was exami

Background: The early detection of oral cancers gives the greatest chance of curing and the delay in presentation has a significant impact on the associated morbidity and mortality. The lack of general dental practitioners (GDP) knowledge in early cancer detection has been shown to contribute to delays in referral and treatment. The aim of this study was to investigate the oral cancer awareness among a group of GDP by assessing their knowledge of detection and prevention of oral cancer. Materials and methods: A questionnaire based study was designed. The questionnaire was delivered to 200 GDP assessing oral examination method, knowledge of oral cancer risk factors, clinical appearance and the most common site, point of referral and requests

Human Cytomegalovirus (HCMV) is an enveloped ubiquitous ds-DNA virus that has been implicated in several types of malignancies. The current work was conducted in the period extending from (November 2018 to the end of October 2019) and aimed to assess the frequency of glycoprotein N (gN) genotypes of HCMV. A total number of 91serum and plasma specimens were collected to fulfill this purpose from females (71 breast cancer patients, and a control group of 20 females) attending Al-Amal hospital for cancer management and Baghdad teaching hospital. The molecular part of this data was achieved through both PCR and Multiplex PCR for detection of HCMV gN (UL73) entire gene as well as for genotyping. gN was detected in 36/71 (50.7%) of breast cancer

Study of Direct Marketing techniques and determining the scope of the suitability of each of them in the application in the Iraqi market - An analytical and explorative study for sample of views for wholesaler in Baghdad. The essential idea of the research is to go into the most important concepts which have been mentioned in the direct marketing and determining its current and most important techniques and knowing the scope of applying these techniques in Baghdad main markets (Karrada, Jamilah, shorja, Baya area, zeyouna and new Baghdad) and which of those techniques most applicable in these markets. The research took a sample of (100) wholesalers who practice the activities of selling nutritional items, auto and outs spare part

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an