This study was aimed to one of the most prevalent causes for endodontic treatment failure is the presence of Enterococcus faecalis bacterium within teeth root canals. To achieve successful treatment, it is so important to study E. faecalis behavior. The aim of study was to investigate biofilm production and antibiotic sensitivity of E. faecalis isolated from root canals. Results showed isolation of E. feacalis (65%) of samples, identified by specific gene by PCR technique. Most isolates were sensitive to Imipenem and resistant to Erythromycin, Clindamycin, Tetracycline and Trimethoprim. Strong biofilm production was detected among 29.5% of highest antibiotic resistant isolates. The results may indicate that infected root canals with E. feacalis may lead to serious complication for patients.
Staphylococcus Sp.is the most common type of bacteria found in contamination place, we design this
study to compare the contamination accident between two hospitals in Baghdad.One of them isthe Burns
Specialist Hospital in the Medical CityinRusafa and another one is Al-Karama Hospital in Karkh. The
samples were collected fromOperativeWard No1 (OW1), Operative Ward No2 (OW2), Consulting Pharmacy
(CP), Emergency Room (ER), Reception Room (RR), Women's Ward (WW) and Men's Ward (MW).The
samples were taken from inside each clinical unit, surfaces, food, and air. The results showed that the
number of samples containing Staphylococcus sp. bacteria is 81, including 45 belonging to Al-Karama Burns
Ward Ho
Aim: To evaluate the effect of ultrasonic agitation for retrograde biodceramic root repair, MTA and biodentine filling materials on push-out bond strength to dentine walls. Materials and Methods: Ninety extracted human teeth with single straight roots were selected randomly. After disinfection and cleaning, the coronal portions were sectioned to standardize the root canal length at 15mm. following root canal shaping, obturation and apical roots resection, retrograde cavities were prepared. Teeth were categorized depending on the filling material used into three groups, 30 teeth each. Group A filled with bioceramic root repair material, B with MTA and C with Biodentine material. These groups were divided in to three subgroup (n= 10). Subgrou
... Show MoreCandida Berkh. (1923) occurs naturally in the body. But it becomes opportunistic fungi, meaning that it infects humans when there is any weakening of the immune system, such as exposure to chemotherapy, diabetes, or organ transplantation. Most species of Candida grow at a temperature between 20-40 °C and have a pH of 3-8. Human pathogens of Candida species include C. albicans, C. glabrata, C. lusitaniae, C. parapsilosis, C. tropicalis and C. utili. C. albicans has many virulence factors that facilitate injury process. Virulence factors are considered as a measure of pathogenicity, and it is in the form of fungal toxins, enzymes, or cell structures that facilitate infection, as well as pathogen resistance in different conditions. This study
... Show MoreAbstract. Hassan FM, Mahdi WM, Al-Haideri HH, Kamil DW. 2022. Identification of new species record of Cyanophyceae in Diyala River, Iraq based on 16S rRNA sequence data. Biodiversitas 23: 5239-5246. The biodiversity and water quality of the Diyala River require screening water in terms of biological contamination, because it is the only water source in Diyala City and is used for many purposes. This study aimed to identify a new species record of Cynaophyceae and emphasize the importance of using molecular methods beside classic morphological approaches, particularly in the water-shrinkage-aqua system. Five different sites along Diyala River were selected for Cyanophyceae identification. Morphological examination and 16S rRNA sequen
... Show MoreThe accurate identification of internal and external pressures in thick-walled hyperelastic vessels is a challenging inverse problem with significant implications for structural health monitoring, biomedical devices, and soft robotics. Conventional analytical and numerical approaches address the forward problem effectively but offer limited means for recovering unknown load conditions from observable deformations. In this study, we introduce a Graph-FEM/ML framework that couples high-fidelity finite element simulations with machine learning models to infer normalized internal and external pressures from measurable boundary deformations. A dataset of 1386 valid samples was generated through Latin Hypercube Sampling of geometric and l
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