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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
Wed Oct 01 2025
Journal Name
Assiut Veterinary Medical Journal
MOLECULAR INVESTIGATION AND COMPARATIVE STUDIES OF THE BACTERICIDAL ACTION BETWEEN SILICA AND ZINC OXIDE NANOPARTICLES AGAINST KLEBSIELLA PNEUMONIAE
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Publication Date
Sun Dec 25 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Synthesis, Molecular Docking Study and Cytotoxicity Evaluation of some Quinazolinone Derivatives as Nonclassical Antifolates and Potential Cytotoxic Agents
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Abstract

A series of new 4(3H)-quinazolinone derivatives (S1-S4) were synthesized and characterized   by FTIR,1HNMR and 13CNMR .Their cytotoxic activity against a set of human cancer cell lines MCF-7 (breast) and A549 (lung) was evaluated using MTT assay. To detect their selectivity toward cancer cells, the compounds were also tested against epithelial cells derived from normal human fibroblast (NHF). Methotrexate (MTX) was used as a reference for comparison . All the tested compounds exhibited toxicity against the normal cells lower than cancer cells. All the tested compounds displayed higher cytotoxicity against lung cancer cell line (A549) than MTX with the most

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Publication Date
Wed Nov 15 2023
Journal Name
Oncology And Radiotherapy
Synthesis, spectroscopic characterization, molecular docking, antioxidant and anticancer studies of some metal complexes from tetraazamacrocyclic Schiff base ligand
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Five novel nickel, iron, cobalt, copper, and mercury complexes were synthesized from tetraazamacrocyclic Schiff base ligand (L), which were derived from 3-(4-(dimethyl amino) benzylidene) pentane-2,4-dione and 1,2- diaminocyclohexane in a 2:2 molar ratio. Many physico-chemical and spectroscopic techniques, including melting point, 1HNMR, 13CNMR, elemental analysis, molar conductance, magnetic susceptibility, UV-Vis, FT-IR, and thermogravimetric analysis (TGA), were used to characterize the Schiff base ligand and all metal complexes. The octahedral geometry of all the complexes [MLCl2] is confirmed by spectroscopic analyses. All substances' biological properties, such as their in vitro antioxidant activity or level of free radical scavenging

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Publication Date
Tue May 20 2025
Journal Name
Journal Of Experimental Zoology India
Molecular docking and toxicity profiling of quercetin and silibinin: A computational approach against key hepatitis C virus proteins
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Publication Date
Sat Jan 01 2022
Journal Name
Pakistan Journal Of Medical & Health Sciences
Roles of Il-36 in the Pathogenesis of Inflammatory Bowel Disease in a Sample of Iraqi Patients
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Publication Date
Wed May 01 2024
Journal Name
Scientific Visualization
Shadow Detection and Elimination for Robot and Machine Vision Applications
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Shadow removal is crucial for robot and machine vision as the accuracy of object detection is greatly influenced by the uncertainty and ambiguity of the visual scene. In this paper, we introduce a new algorithm for shadow detection and removal based on different shapes, orientations, and spatial extents of Gaussian equations. Here, the contrast information of the visual scene is utilized for shadow detection and removal through five consecutive processing stages. In the first stage, contrast filtering is performed to obtain the contrast information of the image. The second stage involves a normalization process that suppresses noise and generates a balanced intensity at a specific position compared to the neighboring intensit

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Al-mansoor College
An Improvement to Face Detection Algorithm for Non-Frontal Faces
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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
: financial fraud ,Audit risks ,inherent risk ,Detection risk, Data Mining .
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Abstract

The study seeks to use one of the techniques (Data mining) a (Logic regression) on the inherited risk through the use of style financial ratios technical analysis and then apply for financial fraud indicators,Since higher scandals exposed companies and the failure of the audit process has shocked the community and affected the integrity of the auditor and the reason is financial fraud practiced by the companies and not to the discovery of the fraud by the auditor, and this fraud involves intentional act aimed to achieve personal and harm the interests of to others, and doing (administration, staff) we can say that all frauds carried out through the presence of the motives and factors that help th

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Publication Date
Fri Feb 08 2019
Journal Name
Journal Of The College Of Education For Women
Online Sumarians Cuneiform Detection Based on Symbol Structural Vector Algorithm
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The cuneiform images need many processes in order to know their contents
and by using image enhancement to clarify the objects (symbols) founded in the
image. The Vector used for classifying the symbol called symbol structural vector
(SSV) it which is build from the information wedges in the symbol.
The experimental tests show insome numbersand various relevancy including
various drawings in online method. The results are high accuracy in this research,
and methods and algorithms programmed using a visual basic 6.0. In this research
more than one method was applied to extract information from the digital images
of cuneiform tablets, in order to identify most of signs of Sumerian cuneiform.

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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