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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
Sun Dec 30 2012
Journal Name
Al-kindy College Medical Journal
Swine Flu 2009, Morbidity and Mortality in a Sample of patients Admitted in Al-kindy Teaching Hospital
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Objective; swine flu is known to be caused by influenza A subtypes H1N1,H1N2, H2N3, H3N1, and H3N2, was first proposed to be a disease related to human flu during the 1918 flu pandemic, Iraq face the epidemic of 2009, many patients admitted to the medical word of alkindy teaching hospital, the clinical features were observed and managed according to WHO protocols.
The aim of the study; is to asses some features of morbidity and mortality of swine flu epidemic admitted patients in 2009 in alkindy teaching hospital.
Methods; A total 131 patients with suspected influenza
admitted to Alkindy Teaching Hospital all complain of
fever more than 38c, sore throat with or without cough.
The admitted patients are of two main
groups

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Publication Date
Wed Apr 01 2020
Journal Name
Translational Andrology And Urology
Robotic-assisted magnetic resonance imaging ultrasound fusion results in higher significant cancer detection compared to cognitive prostate targeting in biopsy naive men
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Publication Date
Fri Jun 20 2025
Journal Name
Bulletin Of The Iraq Natural History Museum
A NEW RECORD OF TWO NEMATODES, MESORHABDITISFRANSENI FUCHS, 1933 (MESORHABDITIDAE) AND PRATYLENCHUSGOODEYI SHER AND ALLEN, 1953 (PRATYLENCHIDAE) WITH MOLECULAR DESCRIPTION FROM IRAQ
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rhabditid Mesorhabditis franseni Fuchs, 1933 (Family, Mesorhabditidae) and pratylenchid nematode Pratylenchus goodeyi Sher and Allen, 1953 (Family, Pratylenchidae). They were illustrated by molecular aspects. All specimens of both genera were cultured and reproduced for DNA extraction. M. franseni (IRQ.ZAh2 PP528819.1 isolate) was characterized. P. goodeyi (IRQ.ZAh5 PP535537 isolate) was also characterized. Selected specimens of these two species were molecularly characterized using the partial ITS-rRNA gene sequences. The ITS-rRNA sequence of IRQ.ZAh2 PP528819.1 isolate had a range of (98.62%-100%) sequence homology with ITS-rRNA sequence of M. franseni available in NCBI database. While, the ITS-rRNA sequence of IRQ.ZAh5 PP535537 isolate h

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Publication Date
Thu Oct 15 2020
Journal Name
International Journal Of Energy Research
Mixed-ligand complexes of ampicillin derived Schiffbase ligand and Nicotinamide: Synthesis, physico-chemical studies, DFT calculation, antibacterial study and molecular docking analysis
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A novel series of mixed-ligand complexes of the type, [ML 1 (L 2 ) 3 ]Cl x [M = Cr(III), Fe(III), Co(II),Ni(II), Cu(II), Cd(II) and Hg(II), n = 2, 3], was synthesized using Schiffbase (HL 1 ) as main ligand, nicotinamide (L 2 ) as secondary ligand, and the corresponding metal ions in 1:3:1 molar ratio. The main ligand, HL 1 was prepared by the interaction of ampicillin drug and 4-chlorobenzophenone. The synthesized mixed ligand complexes were characterized by elemental analysis, UV-Vis, FT-IR, 1 H-NMR, 13 C-NMR and TG/DTG studies. In the mixed-ligand complexes, the Schiffbase ligand, HL 1 showed coordination to the central metal ion in tridentate manner via azomethine nitrogen, β-lactam ring oxygen and deprotonated carboxylic oxy- gen atom

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Different garlic forms: (lobster, mashed, crushed) and their effect on quality qualities And the molecular life of the fermented cucumber and flavor
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This study aimed to isolate and identifye the growth of microorganisms and
their effect on pickled cucumber and cabbage, the study also investigated the effect of
garlic (in the form of segments, chopped or crushed) on the mentioned pickled –food
features . Furthermore, a sense based comparison is made between vinegar-preserved
samples and vinegar-garlic preserved ones.
The following results have been obtained:
1- The isolation of staph. aureus alone from the samples and the study of its physical
and biochemical features.
2- The fresh garlic (segments, chopped and crushed) with concentration of 5%, 7.5%,
and 10% showed a damaging percentage of 100% to bacterial growth of staph. Aureus
after 24 hours of inc

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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)
MOLECULAR CHARACTERIZATION OF ANISAKID NEMATODES HYSTEROTHYLACIUM SPECIES FROM JAPANESE THREADFIN BREAM NEMIPTERUS JAPONICUS (BLOCH, 1791) (PERCIFORMES, NEMIPERIDAE) FROM IRAQI MARINE WATER FISH
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The present study provides a new insight into valuable information on the diverse structure of the Anisakid population and discusses the limited species richness in the Nemipterus japonicus (Bloch,1791) (Perciformes, Nemiperidae). The fishing area consists of various locations in the Arabian Gulf (29°58 0 33 00 N48°28 0 20 E). A total of 315 marine fish were examined, (n=287) were infected. Larval stages (n= 763) encysted within the mesenteries peritoneum and viscera of fish organs were isolated, with a prevalence of 91.11% of infection and, the intensity was 2.65. Molecular analysis was carried out on thirty individuals who have examined the morphology and showed some appearance differences, by amplifying internal transcribed spacers

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Synthesis, characterization, molecular docking, ADMET prediction, and anti-inflammatory activity of some Schiff bases derived from salicylaldehyde as a potential cyclooxygenase inhibitor
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A series of Schiff base-bearing salicylaldehyde moiety compounds (1-4) had been designed, synthesized, subjected to insilico ADMET prediction, molecular docking, characterization by FT-IR, and CHNS analysis techniques, and finally to their Anti-inflammatory profile using cyclooxygenase fluorescence inhibitor screening assay methods along with standard drugs, celecoxib, and diclofenac. The ADMET studies were used to predict which compounds would be suitable for oral administration, as well as absorption sites, bioavailability, TPSA, and drug likeness. According to the results of ADME data, all of the produced chemicals can be absorbed through the GIT and have passed Lipinski’s rule of five. Through molecular docking with PyRx 0.8, these

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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Engineering
Practical comparation of the accuracy and speed of YOLO, SSD and Faster RCNN for drone detection
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Convolutional Neural Networks (CNN) have high performance in the fields of object recognition and classification. The strength of CNNs comes from the fact that they are able to extract information from raw-pixel content and learn features automatically. Feature extraction and classification algorithms can be either hand-crafted or Deep Learning (DL) based. DL detection approaches can be either two stages (region proposal approaches) detector or a single stage (non-region proposal approach) detector. Region proposal-based techniques include R-CNN, Fast RCNN, and Faster RCNN. Non-region proposal-based techniques include Single Shot Detector (SSD) and You Only Look Once (YOLO). We are going to compare the speed and accuracy of Faster RCNN,

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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