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bsj-4514
Detection of Leishmania tropica Using Nested-PCR and Some of Their Virulence Factors in Thi-Qar Province, Iraq
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Cutaneous leishmaniasis is one of endemic diseases in Iraq. It is considered as widely health problem and is an uncontrolled disease. The aim of the study is to identify of Leishmania species that cause skin lesions among patients in Thi-Qar Province, South of Iraq, also to detect some virulence factors of L. tropica. This study includes three local locations, Al-Hussein Teaching, Suq Al-Shyokh General and Al-Shatrah General Hospitals in Province for the period from the beginning of December 2018 to the end of September 2019. The samples were collected from 80 patients suffering from cutaneous leishmaniasis, both genders, different ages, various residence places and single and multiple lesions. Nested-PCR technique was used to amplify kinetoplast minicircle fragments DNA (kDNA). Conventional-PCR was performed for determination of some virulence factors (LPG1, GP63, CPA and PPG1 genes). The electrophoresis findings of kDNA gene showed two species of the parasite found in the study area, 65 samples were positive for cutaneous leishmaniasis, L. tropica at 750bp and L. major at 560bp. Generally, L. tropica (57.5%) was the most common specie and L. major (23.75%) appeared in a low level. There are no significant differences between the infections of males and females, while there are significant differences at the comparison between age groups. All virulence genes (LPG1, GP63, CPA and PPG1) appeared in all L. tropica isolates with high percentage (100%). L. tropica is the major specie which that caused CL in Thi-Qar province, while L. major appeared in low incidence. The virulence genes, which were reviewed, are necessary and important in pathogenesis of L. tropica.

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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Accumulation, Bioavailability, and Health Risk of Heavy Metals in Some Plants Obtained from Abu-Ghraib Land, Baghdad, Iraq
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The study of the distribution of major oxides and heavy metals in some plants collecting and analyzing eighteen plant samples of vegetables including carrot, onion, eggplant, cucumber, and okra obtained from Abu Ghraib land located about 20 km west of Baghdad, Iraq. Eighteen plant samples of vegetables,.Heavy metals can have a severe impact if released into the environment, even in trace quantities. These can enter the food chain from aquatic and agricultural ecosystems and indirectly threaten human health.. Trace elements and oxides of As, Cd, Co, Cr, Cu, Mn, Mo, Ni, Pb, Se, Th, U, V, and Zn were measured in plant samples using an X-Ray Fluorescence Instrument (XRF). TEs analyses of vegetables were performed in the Iraqi German Lab

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model
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The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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Publication Date
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
Simulation Study of Mass Transfer Coefficient in Slurry Bubble Column Reactor Using Neural Network
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The objective of this study was to develop neural network algorithm, (Multilayer Perceptron), based correlations for the prediction overall volumetric mass-transfer coefficient (kLa), in slurry bubble column for gas-liquid-solid systems. The Multilayer Perceptron is a novel technique based on the feature generation approach using back propagation neural network. Measurements of overall volumetric mass transfer coefficient were made with the air - Water, air - Glycerin and air - Alcohol systems as the liquid phase in bubble column of 0.15 m diameter. For operation with gas velocity in the range 0-20 cm/sec, the overall volumetric mass transfer coefficient was found to decrease w

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Publication Date
Sat Jul 25 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
Wed Feb 15 2023
Journal Name
Full Text Book Of Minar Congress 7
EVALUATING THE CHANGE DETECTION OF(NDVI) FOR BABYLON CITY USING REMOTE SENSING AND GIS TECHNIQUES (2015-2020)
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The normalized difference vegetation index (NDVI) is an effective graphical indicator that can be used to analyze remote sensing measurements using a space platform, in order to investigate the trend of the live green vegetation in the observed target. In this research, the change detection of vegetation in Babylon city was done by tracing the NDVI factor for temporal Landsat satellite images. These images were used and utilized in two different terms: in March 19th in 2015 and March 5th in 2020. The Arc-GIS program ver. 10.7 was adopted to analyze the collected data. The final results indicate a spatial variation in the (NDVI), where it increases from (1666.91 𝑘𝑚2) in 2015 to (1697.01 𝑘𝑚2)) in 2020 between the t

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Publication Date
Wed Jan 01 2020
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees20
Change detection of the land cover for three decades using remote sensing data and geographic information system
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Publication Date
Wed Dec 30 2020
Journal Name
Biodiversitas Journal Of Biological Diversity
Assessment of some heavy metals in various aquatic plants of Al-Hawizeh Marsh, southern of Iraq
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Abstract. Al-Abbawy DAH, Al-Thahaibawi BMH, Al-Mayaly IKA, Younis KH. 2021. Assessment of some heavy metals in various aquatic plants of Al-Hawizeh Marsh, southern of Iraq. Biodiversitas 22: 338-345. In order to describe the degree of contamination of aquatic environments in Iraq, heavy metals analysis (Fe, Ni, Cr, Cd, Pb, and Zn) was conducted for six aquatic macrophytes from different locations of Al-Hawizeh Marsh in southern Iraq. The six species were Azolla filiculoides (floating plant), Ceratophyllum demersum, Potamogeton pectinatus, Najas marina (submerged plants), Phragmites australis, and Typha domingensis (emergent plants). The results indicate that cadmium, chromium, and iron concentrations in aquatic plants were above the

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Publication Date
Wed Apr 01 2020
Journal Name
Indian Journal Of Forensic Medicine And Toxicology
Study the genotoxicity of aqueous and alcoholic extracts of adhatoda vasica on the roots of allium cepa L. By RAPD-PCR technique
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Publication Date
Tue Dec 08 2020
Journal Name
Acs Infectious Diseases
Antileishmanial Chemotherapy through Clemastine Fumarate Mediated Inhibition of the <i>Leishmania</i> Inositol Phosphorylceramide Synthase
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Publication Date
Thu Feb 07 2019
Journal Name
Journal Of The College Of Education For Women
SPEECH RECOGNITION OF ARABIC WORDS USING ARTIFICIAL NEURAL NETWORKS
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The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. T

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