Watermelon is known to be infested by multiple insect pests both simultaneously and in sequence. Interactions by pests have been shown to have positive or negative, additive or non additive, compensatory or over compensatory effects on yields. Hardly has this sort of relationship been defined for watermelon vis-à-vis insect herbivores. A 2-year, 2-season (4 trials) field experiments were laid in the Research Farm of Federal University Wukari, to investigate the interactive effects of key insect pests of watermelon on fruit yield of Watermelon in 2016 and 2017 using natural infestations. The relationship between the dominant insect pests and fruit yield were determined by correlation (r) and linear regression (simple and multiple) analys

Researchers have recently increased their focus on the link between autoimmune diseases and infections. Most of the recent research indicates that silent human cytomegalovirus (HCMV), may have diverse roles in the initiation, development, and exacerbation of autoimmune diseases, such as coeliac Disease (CD) and inflammatory bowel disease. The aim of this study is to evaluate the role of HCMV infection in Iraqi patients with CD. Serum samples were obtained from 60 patients with CD, and from 60 healthy subjects. Enzyme-linked immunosorbent assay was used to determine the Anti-Transglutaminase IgG/IgA, Anti-gliadin IgA/ IgG, as well as the HCMV IgM/ IgG levels in the serum samples. Significantly higher percentage of positivity for seru

Investment in Human is one of the best and most important investments as it is renewed and developed resource over time in comparison with depleted material resources. Human resources is considered the part of the population that could be employed economically to contribute in increasing production energies as it is the support pillar of the society and have great energies that construct the society and raise of nations as well as he is distinguished with characteristics of ambitions to freedom.

Iraq is one of the countries that has large number of population in age of work and production and reduce in age dependent classes (children and old people).This dynamic in population led to step

STAG3 is the meiotic component of cohesin and a member of the Cancer Testis Antigen (CTA) family. This gene has been found to be overexpressed in many types of cancer, and recently, its variants have been implicated in other disorders and many human diseases. Therefore, this study aimed to analyze the major variants of STAG3. Western blot (WB) and immunoprecipitation (IP) assays were performed using two different anti-STAG3 antibodies that targeted the relevant protein in MCF-7, T-47D, MDA-MB-468, and MDA-MB-231 breast cancer cells with Jurkat and MCF-10A cells as positive and negative controls, respectively. In silico analyses were searched to study the major isoforms. WB and IP assays revealed two abundant polypeptides < 191 kDa and

The human blood physiology is an active system that is closely connected with environmental and lifestyle changes, which affect such processes as erythropoiesis, coagulation, platelet activity, nitric oxide (NO) signaling system, and oxygen transport. It is a synthesis of evidence based on recent research (2020-2026) on four modulators that relate to each other physically: exercise, high-altitude hypoxia, climate change-induced high and low temperatures, and consumption of non-nutritive sugar substitutes such as erythritol. Adaptive changes that are generally observed in response to exercise and altitude are increased erythropoiesis and improved vascular functions, whereas maladaptive changes, including oxidative stress, inflammator

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature