Objective. Infection with Coxsackie virus. This virus that damages pancreatic cells, has long been linked to the onset of insulin-dependent diabetic mellitus (IDDM). Pro-inflammatory cytokines can be produced as a result of this illness. Tumor necrosis factor-a is one of these pro-inflammatory cytokines. Materials and Methods. Blood sample were collected from 180 Iraqi participants. Ninety of them is type 1 diabetic patients and other 90 is healthy control .both groups were tested for the incidence of Coxsackie virus B IgG. So the patients groups is divided to two groups according to sero positivity of CVB-IgG .all 180 patients tested to measure of level of TNF-α. Results. The Results showed increasing in levels of TNF-α in CBV positive Type 1 Diabetes mellitus was (34.85 ± 11.00 pg/ml). The level of this interleukin in Type 1 Diabetes mellitus negative to that virus was (26.16 ± 7.79 pg/ml). While the results of this interleukin in control group was (13.82 ± 3.93 pg/ml) with p-value 0. Conclusion. The concentration of TNF-α, according to results, has been shown to be associated with type 1 diabetes mellitus patients infected with CVB-IgG and diabetic patients without CVB.
This study was conducted to know the effect of some phenotype characteristics of corn plant on infection by (CSB), using 13 genotypes of corn plant, planting during autumn season 1997 and 1998. The result revealed that the mean of plant height (with male flowering) was (183-219) cm, the mean of leaf No./ plant in all genotypes was (16-18) leaf but the leaf area of plant was (4350-6249) cm2, there were significant differences of phenotype characteristics between genotypes ,the percentage of infection by (CSB) was (5.9-35.9),% the result showed that the phenotype characteristics had non effect on the infection percentage by (CSB) and the correlation coefficient was not significant.
In recent decades, the identification of faces with and without masks from visual data, such as video and still images, has become a captivating research subject. This is primarily due to the global spread of the Corona pandemic, which has altered the appearance of the world and necessitated the use of masks as a vital measure for epidemic prevention. Intellectual development based on artificial intelligence and computers plays a decisive role in the issue of epidemic safety, as the topic of facial recognition and identifying individuals who wear masks or not was most prominent in the introduction and in-depth education. This research proposes the creation of an advanced system capable of accurately identifying faces, both with and
... Show MoreCommunity detection is useful for better understanding the structure of complex networks. It aids in the extraction of the required information from such networks and has a vital role in different fields that range from healthcare to regional geography, economics, human interactions, and mobility. The method for detecting the structure of communities involves the partitioning of complex networks into groups of nodes, with extensive connections within community and sparse connections with other communities. In the literature, two main measures, namely the Modularity (Q) and Normalized Mutual Information (NMI) have been used for evaluating the validation and quality of the detected community structures. Although many optimization algo
... Show MoreObjectives: to evaluate patient knowledge with hemodialysis and to determine the effectiveness of Self-regulation Fluid Program on Patients with hemodialysis self-efficacy for fluid adherence in Al-Diwaniyah Teaching Hospital.
Methodology: A quasi-experimental design (two group design: pre-test and post-test) was used. This study was conducted in Al-Diwaniya Teaching Hospital for the period from (15th of October 2018 to 20th of May 2019) on a non-probability (purposive) sample consisting of (60 patients) treatment in hemodialysis units. A questionnaire was built as a data collection tool and consisted of four parts:
First part: Demographic characteristics of the pati
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