Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

Background: Breast cancer (BC) is the most widespread cancer among women worldwide. Its incidence and mortality rates have risen in the previous three decades as a result of changes in risk factor profiles, improved cancer registry, and cancer detection. Objective: The study's goals were to establish if Ki-67 could be used as a potential marker in serum of cancer disease patients as well as their interaction with vascular endothelial growth factor (VEGF) and ES in various stages of breast cancer to assess their function in the progression of BC. Materials and Methods: The levels of Ki-67, VEGF and endostatin (ES) in serum were assessed by commercial enzyme linked immunosorbent assay (ELISA) kits in 60 women diagnosed with breast cancer

Objective: We hypothesized that attacking cancer cells by combining various modes of action can hinder them from taking the chance to evolve resistance to treatment. Incorporation of photodynamic therapy (PDT) with oncolytic virotherapy might be a promising dual approach to cancer treatment. Methods: NDV AMHA1 strain as virotherapy in integration with aminolaevulinic acid (ALA) using low power He-Ne laser as PDT in the existing work was examined against breast cancer cells derived from Iraqi cancer patients named (AMJ13). This combination was evaluated using Chou–Talalay analysis. Results: The results showed an increased killing rate when using both 0.01 and 0.1 Multiplicity of infection (MOI) of the virus when combined with a dose of 617

في الدراسة الحالية، تم تصنيع جسيمات ZrO2 النانوية باستخدام مستخلص نباتي مشتق من نبات Vitex agnus castus، ووسط قلوي مثل هيدروكسيد الصوديوم. تم استخدام أسلوب التخليق الحيوي لتحضير جزيئات أوكسيد الزركونيوم النانوية لهذا المشروع البحثي. تتميز هذه الطريقة عن غيرها بسبب فعاليتها من حيث التكلفة وبساطتها وقلة المخاطر المحتملة. وتم تشخيص العينات المحضرة باستخدام المجهر الإلكتروني النافذ TEM، المجهر الإلكتروني الماسح SEM،

This study was carrid out to produce animal gelatin from chicken skin. Gelatin was prepared by the chemical method using HCl 2% and extraction at the temperature degree 70, 80, 90 c° and at the period of time 4, 6, 8 hours, calculated the yield, functional and sensory characteristics were measured at. The result also demonstrated that the produced gelatin have good functional properties in solubility, viscosity, gelling capacity, water absorpation, lipid binding, emulsification. viscosity was higher in gelatin prepared at 70 c° and period of extraction 8 hours and reached 1.0846 cp. Gelatin prepared were featured by highe gelling capacity at 1% for all extraction time periods. The produced gelatin was characterized by good sensory qual

Background: CYP1A1 gene polymorphisms and tobacco smoking are among several risk factors for various types of cancers, but their influence on breast cancer remains controversial. We analyzed the possible association of CYP1A1 gene polymorphisms and tobacco smoking-related breast cancer in women from Iraq. Materials and methods: In this case-control study, gene polymorphism of CYP1A1 gene (CYP1A1m1, T6235C and CYP1A1m2, A4889G) of 199 histologically verified breast cancer patients' and 160 cancer-free control women's specimens were performed by using PCR-based restriction fragment length polymorphism. Results: Three genotype frequencies (TT, TC, and CC) of CYP1A1m1T/C appeared in 16.1, 29.6, and 54.3% of women with breast cancer, respectiv