Background: The beneficial gut bacterium E. coli can cause blood poisoning, diarrhoea, and other gastrointestinal and systemic disorders. Objective: This study amid to examines the antibiofilm activity of Laurus nobilis leaves extract on E. coli isolates and compares pre- and post-treatment gene expression of fimA and papC genes. Subjects and Methods: Ten isolates of E. coli were obtained from the Genetic Engineering and Biotechnology Institute, University of Baghdad, which was previously collected from Baghdad city hospitals and diagnosed by chemical tests, the diagnosis was confirmed using VITEK-2 System. The preparation of the aqueous and methanolic Laurus nobilis leaves extracts was done by using the maceration method and Soxhlet apparatus respectively. HPLC were conducted to determine the active compounds in the extracts. Moreover, molecular detection of fimA and papC genes and analysis of the gene expression by comparing the isolates treated with sub MIC of methanolic L. nobilis leaves extract with the untreated isolates. Results: Methanolic and aqueous extracts contained alkaloids, tannins, phenols, saponins, flavonoids, and glycosides. Seven polyphenolic compounds, four flavonoids derivatives (Apigenin, Luteolin, Rutin, and kaempferol) and three phenolic acids (Caffeic acid, Gallic acid, and Syringic acid), were identified by matching retention time with the standards. Laurus nobilis methanolic leaf extract inhibited 90% and 100% of E. coli biofilm development at 32 and 64 mg/ml. Conclusion: The result of the gene expression revealed that there is a decrease in the expression of the fimA and papC genes. The present study concluded that the Laurus nobilis leaves extract have rich phytochemical contents, so the methanolic extract had an excellent reduction effect on biofilm formation and showed remarkable down-regulation on the papC and fimA genes, which are responsible for the biofilm formation in E. coli.
AW Ali T, Journal of the Faculty of Medicine, 2015 - Cited by 3
Objective: Pregnancy-induced hypertension (PIH) is a major pregnancy complication that leads to maternal mortality. Here, we have scrutinized the correlation between serum levels of hydrogen peroxide (H2O2) and superoxide dismutase (SOD) in PIH.Methods: Serum samples were collected from 80 Iraqi women (40 women with PIH as patients group, 20 normotensive pregnant women as a positive control, and 20 normotensive non-pregnant women as a negative control) all groups were diagnosed clinically.Results: Serum of H2O2 and SOD levels was measured for all studied groups. Results showed that there were no significant variances in age and gestational age distribution between all studied groups. Furthermore, result showed that the serum level o
... Show More
Type 1 diabetes (T1D) is an autoimmune disease with chronic nature resulting from a combination of both factors genetic and environmental. The genetic contributors of T1D among Iraqis are unexplored enough. The study aimed to shed a light on the contribution between genetic variation of interleukin2 (IL2) gene to T1D as a risk influencer in a sample of Iraqi patients. The association between IL2−330 polymorphism (rs2069762) was investigated in 322 Iraqis (78 T1D patients and 244 volunteers as controls). Genotyping for the haplotypes using polymerase chain reaction test – specific sequence primer (PCR-SSP) for (GG, GT, and TT) genotypes corresponding to (G and T) alleles were performed. A significant association revealed a decreased freq
... Show More
(1)
(1)
(3)
(3)
In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
... Show More
(2)
(3)
This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
(5)
(3)
(3)
(40)
(44)