BACKGROUND: Carcinoma of urinary bladder is one of the most common malignancies worldwide and constitutes a major health problem. Multiple risk factors are associated with this tumor and its prognosis will depend on different clinicopathological parameters. Over expression of P53 protein and mutant Rb gene is associated with more aggressive clinical and histopathological features of the tumor such as advanced stage and higher grade. AIM: The immunohistochemical expression of Rb gene and P53 gene will be assessed through their protein products in transitional cell carcinoma (TCC) of the urinary bladder and then will be correlated with other well-known risk factors and prognostic parameters of bladder TCC, such as grading, tumor size, smoking

The present study aimed to identify the exact location and its relation to cognitive
method (risk_caution) to university students. The sample consisted of (300) students who
were chosen randomly and equally. The study results indicated that students possess an
internal exact location and they also use risk cognitive method. The study also indicated that
there is a prophesies which is an exact location for others to reach to caution cognitive
method. Depending on these results, the study recommended to benefit from the results of the
study variables and from the measurement of the exact location and method of cognitive
(risk_caution) to identify male and female students and especially by consulting units at
college

This study aimed to determine the effect of varicocelectomy on sperm parameters, oxidant- antioxidant status and chromatin maturity percent. The current study has been conducted on 154 infertile patients complaining from varicocele and varicocelomized men in addition to 25 fertile men as control. The results revealed significant decrease (P<0.05) in sperm concentration, progressive motile sperm percent, normal sperm morphology percent, GSH, SOD1, CAT levels and chromatin maturity percent and significant increase (P<0.05) in MDA and ROS concentrations in infertile patients with varicocele when compared to fertile men. The results revealed improvement (P<0.05) of sperm parameters quality, GSH, SOD1, CAT, MDA, ROS concentration and chromatin m

The purpose of this paper is to identifying the relationship between the moral climate and the decision-making of boxing referees from the standpoint of the coaches, and the research problem lies through the work of the researchers in training and managing the teams. It was noted that the role of the referees is one of the most important roles played by the workers to achieve the objectives of the federation, and that the moral climate that prevails among the administrative body the union and the referees on the one hand and between the referees and coaches on the other hand are among the factors of the success of everyone’s work and the survival and strengthening of confidence in their work and thus the continuity of success and

forty-six patients with asthma were tested for the scrum levels of total sialic and diffrental the results reveled a significant increased in the scra of asthmatic patients

BACKGROUND: Diabetes Mellitus is a complex chronic illness that has increased significantly around the world and is expected to affect 628 million in 2045. Undiagnosed type 2 diabetes may affect 24% - 62% of the people with diabetes; while the prevalence of prediabetes is estimated to be 470 million cases by 2030. AIM OF STUDY: To find the percentage of undiagnosed diabetes and prediabetes in a slice of people aged ≥ 45years, and relate it with age, gender, central obesity, hypertension, and family history of diabetes. METHODS: A cross sectional study that included 712 healthy individuals living in Baghdad who accepted to take part in this study and fulfilling the inclusion and exclusion criteria.

Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D