Abstract Background: The human epidermal growth factor receptor 2(HER2) proto-oncogene is overexpressed or amplified in approximately 15%-25% of invasive breast cancers. Approximately 35% of HER2-amplified breast cancers have coamplification of the topoisomerase II-alpha (TOP2A) gene encoding an enzyme that is a major target of anthracyclines. Hence, the determination of genetic alteration (amplification or deletion) of both genes is considered as an important predictive factor that determines the response of breast cancer patients to treatment. The aims of this study are to determinate TOP2A status gene amplification in a set of Iraqi patients with breast cancer that have had an equivocal (2+) and positive HER2/neu by immunohistochemistry

Background: The relation between insulin resistance ,leptin levels and other hormones in women with polycystic ovary syndrome(PCOS) is still controversial.Metformin therapy is proved effective in reducing insulin resistance and also in some studies it was seen to be effective in reducing leptin levels.
Al- Kindy Col Med J 2012 ; Vol .8 No. (2) p: 65
Objective: to study the effect of metformin on reducing leptin levels and enhancing ovulation in PCOS women.
Methods:metformin 500mg 3 times daily for 3 months was was given to 36 women
with proved PCOS, in addition to that, other parameters were included.
Results:28 women out of 36(77.78%) showed an evidence of ovulation ovulation after 3 months of metformin therapy(p<0.01)

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback

This paper presents the results of experimental investigation carried out on concrete model piles to study the behaviour of defective piles. This was achieved by employing non-destructive tests using ultrasonic waves. It was found that the reduction in pile stiffness factor is found to be about (26%) when the defect ratio increased from (5%) to (15%). The modulus of elasticity reduction factor as well as the dynamic modulus of elasticity reduction factor increase with the defect ratio

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel

Digital change detection is the process that helps in determining the changes associated with land use and land cover properties with reference to geo-registered multi temporal remote sensing data. In this research change detection techniques have been employed to detect the changes in marshes in south of Iraq for two period the first one from 1973 to 1984 and the other from 1973 to 2014 three satellite images had been captured by land sat in different period. Preprocessing such as geo-registered, rectification and mosaic process have been done to prepare the satellite images for monitoring process. supervised classification techniques such maximum likelihood classification has been used to classify the studied area, change detection aft

Aim This study is an overview of NPEV investigated during AFP surveillance programs for the period 2010–2017 in Iraq. Methods Stool samples from 4296 AFP cases and 2933 healthy contacts among children less than 15 years of age were processed for virus isolation as a part of AFP surveillance for the Global Polio Eradication Program in Iraq at National Polio Laboratory. NPEV detection was performed by virus isolation on cell culture according to WHO recommendations. Results The NPEV isolation rate was 14% of total AFP cases and 14.5% of healthy contacts. The infection rate was higher in males than females with a male/female ratio of 1.5: 1. The highest NPEV infection rate was observed among the children aged 1-2 years and decrease significa

In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne