Abstract: Recombinant Newcastle disease virus (rNDV) has shown an anticancer effect in preclinical studies, but has never been tested in a lung cancer models. In this study we explored the anticancer activity of genetically modified NDV expressing IL-2-P53 (rClone30–IL-2-P53) in lung cancer model. We have cloned IL-2 and P53 genes and inserted them in the viral genome of New Castle Disease Virus to create a genetically modified rNDV- IL-2-P53 virus and tested the anti-tumor activity of the new virus in vitro on different types of cancer cell lines by MTT assay. TheIL-2 and P53 gene were successfully cloned and inserted into the viral genome by using a Mlu I and Sfi I endonucleases, viral vector was constructed correctly and successfully; sequencing results also showed that the recombinant plasmid was successfully constructed resulting in the formation of rClone30 NDV expressing both IL2 and P53 gene. In this study, P53 and IL-2 gene were successfully constructed into the NDV genome, by the use of reverse genetics technology, then successfully rescue of all recombinant rNDVclone30s and got high titer recombinant viruses. Keywords: rNDV, IL-2, P53, lung cancer, MTT assay
Hepatitis B virus (HBV) infection is a significant global health problem. Populations of different ethnicities show great heterogeneity in HBV genotype frequency distributions. A cross-sectional study was conducted during June–October 2018 to determine frequency of HBV genotypes among chronic HBV patients from Baghdad, Iraq. The method of detection was nested polymerase chain reaction system. Further, the study assessed the impact of HBV genotypes on serum level of liver-function tests: total serum bilirubin, alkaline phosphatase, alanine aminotransferase and aspartate aminotransferase. Eighty chronic HBV patients were enrolled in the study. Six HBV genotypes were identified (A, B, C, D, E and F). The most frequently encountered genotypes
... Show MoreAlthough the number of stomach tumor patients reduced obviously during last decades in western countries, but this illness is still one of the main causes of death in developing countries. The aim of this research is to detect the area of a tumor in a stomach images based on fuzzy clustering. The proposed methodology consists of three stages. The stomach images are divided into four quarters and then features elicited from each quarter in the first stage by utilizing seven moments invariant. Fuzzy C-Mean clustering (FCM) was employed in the second stage for each quarter to collect the features of each quarter into clusters. Manhattan distance was calculated in the third stage among all clusters' centers in all quarters to disclosure of t
... Show MoreThe current research focuses on examining the isohyets in a set of (3) climatic maps of Iraq. Two of these maps were published in the Iraq Climate Atlas and the third one was published in an English source about the geography of Iraq. The first map represents the period from 1923-to-1944, the second is for the period from 1961-to-1990, whereas the third represents the period from 1971-to-2000. Comparing among these three maps, it has become clear that there are noticeable changes of rain in Iraq. In the first map, which represents the decade of the twenties, thirties and early forties, Iraq was located between two Isohyet lines (127 mm) in the far south and (1270 mm) in the far north. As for the second map, which represents the sixties,
... Show MoreKE Sharquie, AA Al-Nuaimy, FA Al-Shimary, Saudi medical journal, 2005 - Cited by 20
Toxoplasmosis is a parasitic infection that triggers immune cells to produce cytokines and inflammatory mediators that are responsible for abnormal or aborted immune responses. This study highlights the evaluation of the Dectin-1 receptor and cytokine IL-37 in the serum of 80 patients who had miscarried in the first trimester and were infected with toxoplasmosis, as well as 40 pregnant women in the first trimester who had a successful pregnancy (control groups). The serum was first screened for the T. gondii IgM and IgG antibodies by an enzyme-linked immunosorbent assay (ELISA) and then the serum levels of IL-37 and Dectin-1 were determined. The results showed that the serum level of Dectin-1 was significantly increased in anti-
... Show MoreThe mean age of AS patients was (35.0 ± 9.8) years.When the patients and control subjects were divided into different age groups (>40, 30-40, <30 years), the differences were not significantin terms of disease prevalence. The results also showed that the percentage of male patients is higher than that of females. There was no significant difference (P?0.05) between patients and controls in the distribution of males and females.Most of the patients had the disease for a period of 5 years or higher, with a disease severity of ? 2.1 and functional disability degree of I, II. The resultsshoweddifferent patterns of distribution for the three tested cytokines. A significant increase in the level of TNF-?, anon-significantincrease i
... Show MoreType 2 daibetes mellitus (T2DM) is a global concern boosted by both population growth and ageing, the majority of affected people are aged between (40- 59 year). The objective of this research was to estimate the impact of age and gender on glycaemic control parameters: Fasting blood glucose (FBC), glycated hemoglobin (HbA1C), insulin, insulin resistance (IR) and insulin sensitivity (IS), renal function parameters: urea, creatinine and oxidative stress parameters: total antioxidant capacity (TAC) and reactive oxygen species (ROS). Eighty-one random samples of T2DM patients (35 men and 46 women) were included in this study, their average age was 52.75±9.63 year. Current study found that FBG, HbA1C and IR were highly significant (P<0.01) inc
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a
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