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Molecular detection of fimH& mrkDgenes of strong biofilm producers & MDR Klebsiella pneumoniae
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Klebsiella pneumoniae is an adaptable pathogen that forms biofilms on a variety of surfaces. This study's objective was to identify the presence of fimbrial genes (types 1 and 3) in K. pneumoniae strains isolated from various clinical sources based on their antibiotic resistance and ability to form biofilms. According to identification utilizing the vitek 2 technology and confirmation by molecular identification targeting the 16S rRNA gene with a particular primer, forty isolates were identified from clinical specimens. The vitek 2 compact system was utilized to evaluate the antibiotic susceptibility of all the isolates. The findings revealed a range of resistance percentages, including 52.5% for Penicillin, 40.5% for Trimethoprim/Sulfamethoxazole, 34.5% for Cephalosporins, 6.25 % for Fluoroquinolones, and 2.5% for each of Carbapenem, Aminoglycoside, Tetracycline, and Nitrofurantoin. The 96-well microtiter plate technique was utilized to generate biofilms. The results demonstrated that all 40 Klebsiella pneumoniae isolates (100%) produced potent biofilms. In order to identify the genes involved in biofilm formation (fimh & mrkd) and the genes responsible for adhesin in type 1& type 3 fimbriae using traditional PCR method, eleven isolates were chosen for molecular analysis that are powerful biofilm makers and MDR. 

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Wed Dec 30 2020
Journal Name
Al-kindy College Medical Journal
The Value of Diffusion Weighted MRI in the Detection and Localization of Prostate Cancer among a Sample of Iraqi Patients
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Background: Prostatic adenocarcinoma is the most widely recognized malignancy in men and the second cause of cancer-related mortality encountered in male patients after lung cancer.

Aim of the study:  To assess the diagnostic value of diffusion weighted imaging (DWI) and its quantitative measurement, apparent diffusion coefficient (ADC), in the identification and localization of prostatic cancer compared with T2 weighted image sequence (T2WI).

Type of the study: a prospective analytic study

Patients and methods: forty-one male patients with suspected prostatic cancer were examined by pelvic MRI at the MRI department of the Oncology Teaching Hospital/Medical City in Baghdad

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Publication Date
Wed Dec 30 2015
Journal Name
Al-kindy College Medical Journal
Microbiological and Molecular study On Candida species Isolated From Catheterized ur ine specimen In Ramadi general Teaching Hospital
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Background: A Catheter-associated with candidiasis infection is the most common nosocomial infection and the objective of this work is to isolate and identify Candida species from catheterized patients by ordinary culture and PCR.Objective:To study the isolation and identification of Candida species from catheterized patients by culture media and polymerase chain reaction(PCR).Methods: One hundred and thirty five Candida species isolates were obtained from urine culture of catheterized specimens from male and female patients , During the period between October 2011 to April 2012 , attending AL-Ramadi general teaching Hospital. A quantitative urine culture for isolation and identification of Candida species was. The isolation of Candida s

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Electrical Engineering
A Study of the Influence of Steel Brushes in Rail Surface Magnetic Flux Leakage Detection Using Finite Elements Simulation
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Publication Date
Sun Feb 12 2017
Journal Name
World J Exp Biosc
Detection and sequencing of blaVEB-1 gene in clinical isolates of Proteus mirabilis Isolates from Baghdad City`s hospitals
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In Present study, 25 clinical isolates of Proteus spp. of clinical samples, urine, wounds and burns collected from different hospitals in Baghdad city, all isolates were identified as Proteus mirabilis using different bacteriological media, biochemical assays and Vitek-2 system. It was found that 15 (60%) isolates were identifying as P. mirabilis. The susceptibility of P. mirabilis isolates to cefotaxime was 66.6 %, while to ceftazidime was 20%. Extended spectrum β-lactamses producing Proteus was 30.7 %. DNA of 5 isolates of P. mirabilis was extracted and detection for blaVEB-1 gene by using multiplex polymerase chain reaction (PCR). Results showed that the presence of this gene in all tested isolates, as an important indicator for increas

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Publication Date
Sat Dec 03 2022
Journal Name
Iraqi Journal Of Science
Detection of Spectral Reflective Changes for Temporal Resolution of Land Cover (LC) for Two Different Seasons in central Iraq
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The purpose of the study is the city of Baghdad, the capital of Iraq, was chosen to study the spectral reflection of the land cover and to determine the changes taking place in the areas of the main features of the city using the temporal resolution of multispectral bands of the satellite Landsat 5 and 8 for MSS and OLI sensors respectively belonging to NASA and for the period 1999-2021, and calculating the increase and decrease in the basic features of Baghdad. The main conclusions of the study were, This study from 1999 to 2021 and in two different seasons: the Spring of the growing season and Summer the dry season. When using the supervised classification method to determine the differences, the results showed remarkable changes. Where h

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Detection of RAF fusion transcripts in FFPE samples of Medullablastoma and Ependymom in Iraqi children with RT-RQPCR assays
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Medulloblastomas and ependymomas are the most common malignant brain tumors in children. However genetic abnormalities associated with their development and prognosis remain unclear. Recently two gene fusions, KIAA1549–BRAF and SRGAP3–RAF1 have been detected in a number of brain tumours. We report here our development and validation of RT-RQPCR assays to detect various isoforms of these two fusion genes in formalin fixed paraffin embedded (FFPE) tissues of medulloblastoma and ependymoma. We examined these fusion genes in 44 paediatric brain tumours, 33 medulloblastomas and 11 ependymomas. We detected both fusion transcripts in 8/33, 5/33 SRGAP3 ex10/RAF1 ex10, and 3/33 KIAA1549 ex16/BRAF ex9, meduloblastomas but none in the 11 ep

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Thu Jul 23 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Early detection of periodontitis among young adult cigarette smokers and non-smokers using cone beam computed tomography
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Background: Periodontitis is an inflammatory disease that affects the supporting tissues of the teeth; Smoking is an important risk factor for periodontitis induces alveolar bone loss and cause an imbalance between bone resorption and bone deposition. The purpose of this study is to detect and compare the presence of incipient periodontitis among young smokers and non-smokers by measuring the distance between cement-enamel junction and alveolar crest (CEJ-Ac) using Cone Beam Computed Tomography (CBCT). Material and methods: The total sample composed of fifty two participants, thirty one smokers and twenty one non-smokers (age range 14-22 years). Periodontal parameters: plaque index (PLI), gingival index (GI) were recorded for all teeth exc

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Publication Date
Fri Jan 01 2021
Journal Name
Analytical And Bioanalytical Chemistry Research
Mutual Derivatization in the Determination of Dapsone and Thymol Using Cloud Point Extraction Followed by Spectrophotometric Detection
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A procedure for the mutual derivatization and determination of thymol and Dapsone was developed and validated in this study. Dapsone was used as the derivatizing agent for the determination of thymol, and thymol was used as the derivatizing agent for the determination of Dapsone. An optimization study was performed for the derivatization reaction; i.e., the diazonium coupling reaction. Linear regression calibration plots for thymol and Dapsone in the direct reaction were constructed at 460 nm, within the concentration range of 0.3-7 μg ml-1 for thymol and 0.3-4 μg ml-1 for Dapsone, with limits of detection 0.086 and 0.053 μg ml-1, respectively. Corresponding plots for the cloud point extraction of thymol and Dapsone were constructed

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