Background: Nicotine is the foremost chemical constituent responsible for addiction in tobacco products, in the non-ionized condition can be easily absorbed via epithelial tissue of the lung, the mouth, the nose  and across the skin

Objective:The study examines the harmful effect of   the nicotine which is an important component of cigarette in vitro.

Type of the study: Cross-sectional study.

Methods: Examines the harmful effect of   the nicotine which is an important component of cigarette in vitro by using two types of lung cancer cell lines (H460 TP53+/+, H441 TP53-/-).

Background: While two-thirds of breast cancers express hormone receptors for either estrogen (ER) and/or progesterone (PR) , genetically altered PI3K pathway was found in more than 70% of ER-positive breast cancers.An aberrant activity of cyclin-dependent kinase 1 (CDK1) in a wide variety of human cancers has selectively constituted an attractive pharmacological targets in MYC-dependent human breast cancer cells.

Aim of the study:  Role of p110-beta as well as and CDK 1  in the pathogenesis of subset of breast cancers and contribution in their carcinogenesis.

Type of the study: is a retrospective study

Methods: This retr

This research aims to Measurement provide the service from Two perspectives The first perspective Service Provider (doctors) and the second recipient of the service (patients) in Numan General Hospital, and represented the research problem in perceptions of medical staff in the hospital assigned to them responsibility by providing superior services satisfy customers, and how they maintained ready to assist customers and provide services that exceed their perceptions of these services through the use of the developer scale by (Frimpong and Wilson, 2012), includes orientation to provide the service scale four dimensions (Internal cooperative behaviors, service Competence, Service Responsiveness and Enhanced service) and includes do

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

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

This study was performd on 50 urine specimens of patients with type 2 diabetes, in addition, 50 normal specimens were investigated as control group. The activity rate of maltase in patients (6.40±2.17) I.U/ml and activity rate of maltase in normal (0.44±0.20)I.U/ml. The results of the study reveal that maltase activity of type 2 diabetes patient's urine shows significant increase (P<0.01) compare to normal.

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

Fever is a common illness in the pediatric age group ,the causes could be viral ,bacterial and fungal , this study was focused on bacterial pathogens as gram positive like Staphylococci, coagulase positive or negative ,Streptococci and gram negative like E-coli , Klebsialla ,Proteus, Pseudomonas, Burkhoderia , Acinetobacter and others like Pusturella ,E-alkalescendiaper, Haemophillus influenza and yeast like candida . Four thousand and seventy eight blood samples (4078)were collected in a period between January 2011 and the end of May 2012 at the child welfare hospital ,all the samples were cultured on suitable culture media and then biochemical tests were done using API-E 20 and sugar fermentation tests ,sensitivity