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Molecular Detection of Porphyromonas gingivalis in COVID-19 Patients
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Background:SARS-CoV-2 infection has caused a global pandemic that continues to negatively impact human health. A large group of microbial domains including bacteria co-evolved and interacted in complex molecular pathogenesis along with SARS-CoV-2. Evidence suggests that periodontal disease bacteria are involved in COVID-19, and are associated with chronic inflammatory systemic diseases. This study was performed to investigate the association between bacterial loads of Porphyromonas gingivalis and pathogenesis of SARS-CoV-2 infection. Fifty patients with confirmed COVID-19 by reverse transcriptase-polymerase chain reaction, their age ranges between 20-76 years, and 35 healthy volunteers (matched accordingly with age and sex to the patients) participated in this case control study. Oral hygiene status was determined by the simplified oral hygiene index. Blood and saliva samples were obtained from patients and controls, Porphyromonas gingivalis quantification from extracted DNA of blood and saliva samples performed by means of real-time polymerase chain reaction. The present result revealed that the quantity of salivary Porphyromonas gingivalis was significantly higher (p=0.003) in the patients’ group than in the controls group, while there was no significant difference in the number of bacteria in the blood samples between the two groups. Moreover, the number of bacteria in severe cases was higher than that in moderate and mild with no significant differences, and there was a significant increase in the number of bacteria among patients with poor oral hygiene compared to patients with good oral hygiene. This study demonstrated that the high level of salivary Porphyromonas gingivalis in patients increases in number with disease severity, which may indicate that bacterial infections contribute to the spread of the disease.

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Publication Date
Sat Dec 02 2023
Journal Name
Bulletin Of The Iraq Natural History Museum
MORPHOLOGICAL AND MOLECULAR STUDIES OF KAIS KINGFISH CYPRINION KAIS HECKEL, 1843 (PISCIES, CYPRINIFORMES, CYPRINIDAE) FROM THE MIDDLE OF IRAQ
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Cyprinidae species are the most abundant and widely distributed fish species in the inland waters of Iraq. Cyprinids are complex species, and it is difficult to identify them on the basis of morphology. Thus, the morphological characteristics must be achieved and confirmed by molecular analysis. Twenty specimens of Cyprinion kais Heckel, 1843 (Piscies, Cypriniformes, Cyprinidae) were collected from two localities at Tigris River in the middle of Iraq: five specimens from Al-Tharthar Lake, Saladin Province, and 15 specimens from Al- Zubaydiyah sub-district, Wasit Province

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Publication Date
Mon Dec 20 2021
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MORPHOLOGY AND MOLECULAR IDENTIFICATION OF THE LARVAL STAGE OF TWO SPECIES FROM THE GENUS CHRYSOBOTHRIS ESCHSCHOLTZ, 1829 (COLEOPTERA, BUPRESTIDAE)
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The genus of Chrysobothris Eschscholtz, 1829 is one of the most diverse and widespread genera of the family Buprestidae of some 700 described species distributed throughout the world. In Iraq, particularly in the Kurdistan region, about 4 species had been recorded so far, many of these species are sympatric, share larval host plants, and are difficult to reliably separate morphologically. The current study investigates species limits and relationships among the recognized species occurring within the Erbil Province; mitochondrial cytochrome C oxidase (COX I) molecular analysis confirmed the monophyly of two Chrysobothris species, Ch. affinis (Fabricius, 1794) and Ch. chrysostigma (Linnaeus, 1758). Implications of the resultant larval mor

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Publication Date
Tue Dec 19 2023
Journal Name
Bulletin Of The Iraq Natural History Museum
MORPHOLOGICAL AND MOLECULAR STUDIES OF KAIS KINGFISH CYPRINION KAIS HECKEL, 1843 (PISCIES, CYPRINIFORMES, CYPRINIDAE) FROM THE MIDDLE OF IRAQ
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Cyprinidae species are the most abundant and widely distributed fish species in the inland waters of Iraq. Cyprinids are complex species, and it is difficult to identify them on the basis of morphology. Thus, the morphological characteristics must be achieved and confirmed by molecular analysis. Twenty specimens of Cyprinion kais Heckel, 1843 (Piscies, Cypriniformes, Cyprinidae) were collected from two localities at Tigris River in the middle of Iraq: five specimens from Al-Tharthar Lake, Saladin Province, and 15 specimens from Al- Zubaydiyah sub-district, Wasit Province. The DNA sequences of C. kais were done using the mitochondrial DNA cytochrome b (cytb) gene. After analysis, the sequences were compared with sequences of ot

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Publication Date
Fri Feb 21 2025
Journal Name
2025 First International Conference On Advances In Computer Science, Electrical, Electronics, And Communication Technologies (ce2ct)
Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems
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The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Partial Encryption for Colored Images Based on Face Detection
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Publication Date
Tue Apr 16 2019
Journal Name
Proceedings Of The 2019 5th International Conference On Computer And Technology Applications
Four Char DNA Encoding for Anomaly Intrusion Detection System
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Recent research has shown that a Deoxyribonucleic Acid (DNA) has ability to be used to discover diseases in human body as its function can be used for an intrusion-detection system (IDS) to detect attacks against computer system and networks traffics. Three main factor influenced the accuracy of IDS based on DNA sequence, which is DNA encoding method, STR keys and classification method to classify the correctness of proposed method. The pioneer idea on attempt a DNA sequence for intrusion detection system is using a normal signature sequence with alignment threshold value, later used DNA encoding based cryptography, however the detection rate result is very low. Since the network traffic consists of 41 attributes, therefore we proposed the

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Publication Date
Tue Apr 02 2024
Journal Name
Advances In Systems Science And Applications
A New Face Swap Detection Technique for Digital Images
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Publication Date
Wed Apr 28 2021
Journal Name
2021 1st Babylon International Conference On Information Technology And Science (bicits)
Enhanced Twitter Community Detection using Node Content and Attributes
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Publication Date
Sat Dec 01 2018
Journal Name
Digest Journal Of Nanomaterials And Biostructures
Nanostructured silicon trapping for single Escherichia coli bacteria detection
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The detection for Single Escherichia Coli Bacteria has attracted great interest and in biology and physics applications. A nanostructured porous silicon (PS) is designed for rapid capture and detection of Escherichia coli bacteria inside the micropore. PS has attracted more attention due to its unique properties. Several works are concerning the properties of nanostructured porous silicon. In this study PS is fabricated by an electrochemical anodization process. The surface morphology of PS films has been studied by scanning electron microscope (SEM) and atomic force microscope (AFM). The structure of porous silicon was studied by energy-dispersive X-ray spectroscopy (EDX). Details of experimental methods and results are given and discussed

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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials & Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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