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Antimicrobial Efficacy of Pelargonium Graveolens Gold Nanoparticles: A Novel Mouthwash for Children
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ABSTRACT<sec> <title>Background

Nowadays, there is a trend to promote the use of natural materials in dentistry. One of these compounds that has lately grown significantly in relevance in clinical research is Pelargonium Graveolens .

Objectives

This study was conducted to evaluate the antimicrobial efficacy of gold nanoparticles (AuNPs) of Pelargonium Graveolens leaves extract for children in comparison with the commonly used chlorhexidine. There are no previously available studies concerning the anti‐microbial activity of Pelargonium Graveolens leaves.

Materials and Method

Sixty participants with mild to moderate gingivitis were randomly allocated in a ratio of 1:1 to receive twice‐daily mouthwash for 3 weeks (30 with a novel herbal mouthwash containing Pelargonium Graveolens AuNPs as a study group and 30 children with chlorhexidine as a control group). Clinical parameters (plaque index and gingival index) were assessed at the baseline (before the use of mouthwash), and then they were assessed 3 times at one‐week intervals after the first assessment through the period of the study. On the other hand, microbiological examination was done using supragingival plaque sampling with a curette for those participants at the baseline and three weeks after the use of the mouthwash.

Results

After completing the intervention, although the study group had lower plaque scores compared to the control group, the difference was statistically significant. On the other hand, the study group had a significant reduction in the gingival index scores compared to the control group ( p  = 0.000). The microbiological analysis revealed that the treatment mouthwash significantly depleted the count of S. mutans in the last visit.

Conclusion

The novel Pelargonium Graveolens AuNPs mouthwash was effective in improving (PI) and (GI), which mean improve oral health status. Rinsing with Pelargonium Graveolens AuNPs mouthwash reduced the count of oral Streptococcus mutans significantly in children. Clinical trial registration Number: ClinicalTrials.gov on April 15, 2023, with ClinicalTrials.gov ID: NCT05816512.

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Publication Date
Tue Jan 21 2025
Journal Name
Applied Biochemistry And Biotechnology
Synthesis and characterization of new (Au, Ru, and Rh) ion complexes and evaluating their activity as anticancer and antioxidants
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Publication Date
Mon Aug 01 2022
Journal Name
Journal Of Engineering
Production of Load Bearing Concrete Masonry Units (blocks) From Green Concrete Containing Plastic Waste and Nano Silica Sand Powder
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Industrial development has recently increased, including that of plastic industries. Since plastic has a very long analytical life, it will cause environmental pollution, so studies have resorted to reusing recycled waste plastic (sustainable plastic) to produce environmentally friendly concrete (green concrete). In this research, producing environmentally friendly load-bearing concrete masonry units (blocks) was considered where five concrete mixtures were compressed at the blocks producing machine. The cement content reduced from 400 kg/m3 (B-400) to 300 kg/m3 (B-300) then to 200 kg/m3 (B-200). While (B-380) was produced using 380 kg/m3 cement and 20 kg/m3 nano-sil

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Thermophysical properties of [EMIM][BF<sub>4</sub>] and [HMIM][PF<sub>6</sub>] imidazolium ionic liquids with MWCNTs
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Abstract<p>In this study, several ionanofluids (INFs) were prepared in order to study their efficiency as a cooling medium at 25 °C. The two-step technique is used to prepare ionanofluid (INF) by dispersing multi-walled carbon nanotubes (MWCNTs) in two concentrations 0.5 and 1 wt% in ionic liquid (IL). Two types of ionic liquids (ILs) were used: hydrophilic represented by 1-ethyl-3-methylimidazolium tetrafluoroborate [EMIM][BF<sub>4</sub>] and hydrophobic represented by 1-hexyl-3-methylimidazolium hexafluorophosphate [HMIM][PF<sub>6</sub>]. The thermophysical properties of the prepared INFs including thermal conductivity (TC), density and viscosity were measured experimental</p> ... Show More
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Publication Date
Sat May 01 2021
Journal Name
Pharmacological Research
Resveratrol-mediated attenuation of superantigen-driven acute respiratory distress syndrome is mediated by microbiota in the lungs and gut
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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Energy Storage
Intensifying the thermal response of PCM via fin-assisted foam strips in the shell-and-tube heat storage system
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Publication Date
Sun Mar 24 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Correlation between Therapeutic Drug Monitoring of Infliximab Serum Trough Levels and other Biomarkers in Iraqi Patients with Crohn's Disease
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Background: Inflammatory bowel disease (IBD) is a collection of chronic, recurrent inflammatory illnesses of the gastrointestinal system, including Crohn's disease (CD). Infliximab is one of the biological medications used to treat CD. Therapeutic drug monitoring has evolved as a treatment in IBD, aiming to optimize benefit while meeting more demanding, objective end criteria. Objective: To determine the achievement of target trough level (TL), develop anti-drug antibodies (ADAs) to infliximab, assess response to therapy, and study TL relations with different variables. Methods: The present study was cross-sectional and conducted from May 2022 to November 2022. It included 40 CD patients allotted into 2 groups: group 1 patients ach

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Publication Date
Sat Jan 29 2022
Journal Name
Phytoparasitica
Effects of Volatile Organic Compounds (VOCs) emitted by citrus infested with Aonidiella aurantii on the predator Rhyzobius lophanthae attraction
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Publication Date
Fri May 07 2021
Journal Name
Journal Of Evaluation In Clinical Practice
Exploring the acceptance of <scp>COVID</scp>‐19 vaccine among healthcare workers and general population using health belief model
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Abstract<sec><title>Rationale, aims and objectives

Little is known about hesitancy to receive the COVID‐19 vaccines. The objectives of this study were (1) to assess the perceptions of healthcare workers (HCWs) and the general population regarding the COVID‐19 vaccines, (2) to evaluate factors influencing the acceptance of vaccination using the health belief model (HBM), and (3) to qualitatively explore the suggested intervention strategies to promote the vaccination.

Methods

This was a cross‐sectional study based on electronic survey data that was collected in Iraq during December first‐19th, 2020. The electronic surve

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Publication Date
Tue Jun 29 2021
Journal Name
Frontiers In Immunology
The Ability of AhR Ligands to Attenuate Delayed Type Hypersensitivity Reaction Is Associated With Alterations in the Gut Microbiota
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Aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that regulates T cell function. The aim of this study was to investigate the effects of AhR ligands, 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD), and 6-Formylindolo[3,2-b]carbazole (FICZ), on gut-associated microbiota and T cell responses during delayed-type hypersensitivity (DTH) reaction induced by methylated bovine serum albumin (mBSA) in a mouse model. Mice with DTH showed significant changes in gut microbiota including an increased abundance of Bacteroidetes and decreased Firmicutes at the phylum level. Also, there was a decrease in Clostridium cluster XIV and IV, which promo

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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