Background: Salivary tumors are uncommon, being of low incidence worldwide. This study aimed to assess cases collected in this series of salivary gland tumors in regard to histopathological typing, in relation to age, site and gender. Materials and methods: This is a retrospective study; cases were collected from public and private laboratories. A total number of 171 cases were collected. The slides were reviewed and reclassified for histopathological typing according to WHO classification 2005. Results: Benign tumors were more common than malignant tumors. The most common histological type was benign mixed tumor, followed by Warthin’s tumor. The most common malignant tumor was adenoid cystic carcinoma. One hundred twenty three cases ou

Background: Rheumatoid arthritis is a chronic destructive inflammatory disease associated with destruction of joint connective tissues and bones, affecting 0.5%–1% of the population worldwide reporting higher prevalence of periodontitis among rheumatoid arthritis patients. The purpose of this study is to estimate level of salivary C-reactive protein in relation to the occurrence and severity of the periodontal disease and other oral parameters among group of patients with rheumatoid arthritis Material and methods: Fifty women patients with rheumatoid arthritis; twenty five on Methotrexate treatment and twenty five on combination treatment of Methotrexate and Etanercept selected as study groups with an age range (30-40) years old and

SKF Dr. Abbas S. Alwan, Dhurgham I. Khudher, INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY, 2015

The current study aimed to ascertain the levels of matrix metalloproteinase-12 (MMP-12) and Lysyl oxidase (LOX) in osteoporosis patients and their correlation with alkaline phosphatase (ALP), magnesium (Mg), vitamin D (Vit D), calcium (Ca), phosphorus (P), and T-score %. 110 participants recruited from Baghdad Teaching Hospital, Iraq, were enrolled in this study from November 2019 to March 2020). The participants were divided into two groups: Group 1 comprised 60 osteoporotic women and group 2 consisted of 50 healthy women. (MMP and LOX) were estimated using a quantitative enzyme-linked immunosorbent assay (ELISA. The results showed significant differences in serum LOX, age, ALP, Mg, and T-score %, while no significant differences i

This research aims to examine the role of global green finance as a critical driver of both economic and environmental sustainability within small and medium-sized agricultural enterprises (SMEs) in Iraq. Utilizing a convergent mixed-methods framework, the study integrates qualitative interviews with key stakeholders and a quantitative survey of 300 agricultural SMEs to assess the barriers, enablers, and institutional conditions influencing the adoption of green finance. The findings indicate that, despite growing awareness and substantial latent demand for sustainability-linked investments, adoption is significantly constrained by institutional fragmentation, regulatory ambiguity, and resource limitations at the firm level. Grounded in Ins

Background: Trastuzumab is a blockbuster monoclonal antibody that has revolutionized the treatment of HER2-positive breast and gastric cancers. With the increasing availability of biosimilar monoclonal antibodies in clinical practice, independent verification of biosimilarity using products sampled from a real-world supply chain is important to assure clinicians and the patients to use these products confidently. Objective: The aim of this study is to assess the biosimilarity of AryoTrust, a trastuzumab biosimilar, in comparison with the reference product Herceptin. AryoTrust and Herceptin products were randomly withdrawn from Iraqi hospitals to reflect medicines administered in real clinical settings. Methods: AryoTrust and Hercept

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