Antibiotic resistance is the major growing threat facing the pharmacological treatment of bacterial infections. Therefore, bioprospecting the medicinal plants could provide potential sources for antimicrobial agents. Mimusops, the biggest and widely distributed plant genus of family Sapotaceae, is used in traditional medicines due to its promising pharmacological activities. This study was conducted to elucidate the antimicrobial effect of three unexplored Mimusops spp. (M. kummel, M. laurifolia and M. zeyheri). Furthermore, the mechanisms underlying such antibacterial activity were studied. The Mimusops leaf extracts revealed significant antibacterial activities against the five tested bacter

الخلفية: إن سمية الدواء والآثار الجانبية للعلاج الكيميائي تؤثر سلبا على مرضى سرطان الثدي. الأهداف: لتقييم فعالية التدخلات الصيدلانية في تحسين معرفة مرضى سرطان الثدي ومواقفهم وممارساتهم فيما يتعلق بالعلاج الكيميائي لسرطان الثدي.

Mammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti

Background: Pomegranate (punicagranatum L, Punicaceae), is an edible fruit consumed around the world. The edible part of pomegranate is rich in compounds that possess antioxidant and anti-inflammatory activities. The aim of this study is to investigate the antioxidant; anti-inflammatory and gingival wound healing effects of Punicagrantum L. seed extract oral supplementation in rabbit. Methods and Methods: Forty five male rabbits were divided into 3 groups, base line (5 rabbits) left without buccal gingival wound as( group 1),study group, 20 rabbits (group2) with buccal gingival wound treated with ethanolic extract of Punicagranatum L. seed extract and control, 20 rabbits (group 3) with buccal gingival wound only. Buccal gingival wounds w

Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimum err

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

BACKGROUND: Breast cancer remains the most common malignancy among the Iraqi population. Affected patients exhibit different clinical behaviours according to the molecular subtypes of the tumour. AIM: To identify the clinical and pathological presentations of the Iraqi breast cancer subtypes identified by Estrogen receptors (ER), Progesterone receptors (PR) and HER2 expressions. PATIENTS AND METHODS: The present study comprised 486 Iraqi female patients diagnosed with breast cancer. ER, PR and HER2 contents of the primary tumours were assessed through immunohistochemical staining; classifying the patients into five different groups: Triple Negative (ER/PR negative/HER2 negative), Triple Positive (ER/PR positive/HER2 positive), Luminal A (ER

Contracting cancer typically induces a state of terror among the individuals who are affected. Exploring how glucose excess, estrogen excess, and anxiety work together to affect the speed at which breast cancer cells multiply and the immune system’s response model is necessary to conceive of ways to stop the spread of cancer. This paper proposes a mathematical model to investigate the impact of psychological panic, glucose excess, and estrogen excess on the interaction of cancer and immunity. The proposed model is precisely described. The focus of the model’s dynamic analysis is to identify the potential equilibrium locations. According to the analysis, it is possible to establish four equilibrium positions. The stability analys