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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
Tue Jun 30 2009
Journal Name
Al-kindy College Medical Journal
Serum Zinc in Iraqi Acute Leukemic Patients
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Background: Leukemia is a group of malignant disorders
associated with increased numbers of blood white blood
cells. Acute leukemia occurs at all ages. Because zinc
influences many body systems and functions, zinc is an
essential nutrient for tissue growth, cellular division,
protein synthesis DNA and RNA replication it also ought to
play a critical role in the growth of tumor. In this study,
serum zinc was estimated in leukemic patients and
compared with healthy subjects.
Methods: The subjects in the present study were; fourtyfour depressed patients aged (14-48 year), thirty-one
apparently healthy subjects were selected as control group.
Their sex and age were comparable to that of patients.
Determin

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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Physics: Conference Series
Autoantibody Profile in Systemic Lupus Erythematosus Patients
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Abstract<p>Systemic lupus erythematosus (SLE) is an autoimmune disease, in which the etiology is not well-understood; however, interactions between environmental and genetic factors in predisposed individuals have been recognized. As a consequence, immunological alternations occur and immune cells are involved, especially T and B lymphocytes that are activated to produce different immune components. Among these components are autoantibodies that react with self-antigens aside from non-self-antigens due to the proposed theory of molecular mimicry. Accordingly, the current study was designed to examine the profile of different autoantibodies in SLE patients by using the indirect membrane based enzyme immunoassay </p> ... Show More
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Practical Study for the Properties of Hueckel Edge Detection Operator
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Publication Date
Wed Apr 02 2014
Journal Name
Journal Of Theoretical And Applied Information Technology
TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Engineering
Detection and Diagnosis of Induction Motor Faults by Intelligent Techniques
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This paper presents a complete design and implementation of a monitoring system for the operation of the three-phase induction motors. This system is built using a personal computer and  two types of sensors (current, vibration) to detect some of the mechanical faults that may occur in the motor. The study and examination of several types of faults including (ball bearing and shaft misalignment faults) have been done through the extraction of fault data by using fast Fourier transform (FFT) technique. Results showed that the motor current signature analysis (MCSA) technique, and measurement of vibration technique have high possibility in the detection and diagnosis of most mechanical faults with high accuracy. Subsequently, diagnosi

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Publication Date
Sat Aug 01 2015
Journal Name
2015 37th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Tsallis entropy as a biomarker for detection of Alzheimer's disease
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Publication Date
Mon May 01 2017
Journal Name
Journal Of Stored Products Research
Detection and prediction of Sitophilus oryzae infestations in triticale via visible and near-infrared spectral signatures
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Triticale is a hybrid of wheat and rye grown for use as animal feed. In Florida, due to its soft coat, triticale is highly vulnerable to Sitophilus oryzae L. (rice weevil) and there is interest in development of methods to detect early-instar larvae so that infestations can be targeted before they become economically damaging. The objective of this study was to develop prediction models of the infestation degree for triticale seed infested with rice weevils of different growth stages. Spectral signatures were tested as a method to detect rice weevils in triticale seed. Groups of seeds at 11 different levels (degrees) of infestation, 0–62%, were obtained by combining different ratios of infested and uninfested seeds. A spectrophotometer wa

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Publication Date
Tue Mar 15 2022
Journal Name
Malaysian Journal Of Medicine And Health Sciences
Detection of Extended Spectrum β-lactamases and Metallo β-lactamases in Pseudomonas Aeruginosa isolated from Burns
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P. aeruginosa is one of the complex targets for antimicrobial chemotherapy. Also, it is intrinsically resistant to several antibiotics. It produces β-lactamases enzymes that are responsible for the widespread β-lactam antimicrobial resistance. There are three major groups of β-lactamase enzymes, MBLs and ESBLs forming Pseudomonas is a major issue for the treatment of burns victims. Methods: A total of 28 clinical isolates related to P. aeruginosa have been obtained from the burns specimens from patients attending to AL-Imam hospital/Baghdad-Iraq, through the period from October 2015 to March 2016. Also, all isolates have been recognized as P. aeruginosa via utilizing bacteriological assay and confirmed by Vitek 2. In addition, the suscep

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Publication Date
Sun Jan 01 2023
Journal Name
Bionatura
Detection of lukf-pv gene in Staphylococcus aureus isolated from pregnant women with Urinary tract infection
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Publication Date
Mon Sep 30 2024
Journal Name
Iraqi Journal Of Science
Overlapping Structure Detection in Protein-Protein Interaction Networks Using a Modified Version of Particle Swarm Optimization
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In today's world, the science of bioinformatics is developing rapidly, especially with regard to the analysis and study of biological networks. Scientists have used various nature-inspired algorithms to find protein complexes in protein-protein interaction (PPI) networks. These networks help scientists guess the molecular function of unknown proteins and show how cells work regularly. It is very common in PPI networks for a protein to participate in multiple functions and belong to many complexes, and as a result, complexes may overlap in the PPI networks. However, developing an efficient and reliable method to address the problem of detecting overlapping protein complexes remains a challenge since it is considered a complex and har

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