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bijps-2494
Protective Effect of Cafestol on Doxorubicin-induced Genotoxicity in Rats
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Doxorubicin is an efficient antineoplastic agent that has a broad antitumour spectrum; however, its genotoxic adverse effects on normal cells can be produced through oxidative damage, and this limits its clinical application. Cafestol is a naturally-occurring diterpene in unfiltered coffee with noteworthy antioxidant, antimutagenic and anti-inflammatory activities.

The present study aimed to investigate the possible protective effect of cafestol against doxorubicin-induced chromosomal and DNA damage in rat bone marrow cells. Wistar

Albino rats of both sexes were administered cafestol (5mg/kg body weight once daily for 14 consecutive days) by oral gavage alone or with doxorubicin which was injected as a single dose (90 mg/kg intraperitoneally at day 14) to induce toxicity. The bone marrow was harvested 24 hours after doxorubicin’s injection in all groups for the assessment of structural chromosomal aberration, micronucleus, and comet assays. The result showed that rats in the doxorubicin-only group exhibited a significant decrease (P<0.05) in mitotic index with a significant elevation (P<0.05) in the % DNA in Tail, micronucleus appearance and total structural chromosomal aberrations compared to those of the negative control group; while oral administration of cafestol 14 days prior to doxorubicin, significantly-reduced the % DNA in Tail, micronucleus appearance, and the total number of chromosomal aberrations (P<0.05), and improved the mitotic index compared to rats intraperitoneally-injected with doxorubicin alone.

This study revealed that cafestol has protective effects against the genotoxicity induced by doxorubicin.

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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
Sun Jan 01 2023
Journal Name
Materials Today: Proceedings
Preparation, characterization and preliminary cytotoxic evaluation of 6-mercaptopurine-coated biotinylated carbon dots nanoparticles as a drug delivery system
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Publication Date
Fri Mar 10 2017
Journal Name
Superconductor Science And Technology
Conceptual designs of conduction cooled MgB<sub>2</sub> magnets for 1.5 and 3.0 T full body MRI systems
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Publication Date
Mon Feb 01 2021
Journal Name
Meta Gene
Association analysis of FTO gene polymorphisms rs9939609 and obesity risk among the adults: A systematic review and meta-analysis
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Publication Date
Sun Jan 01 2023
Journal Name
Materials Today: Proceedings
Preparation, characterization and preliminary cytotoxic evaluation of 6-mercaptopurine-coated biotinylated carbon dots nanoparticles as a drug delivery system
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Publication Date
Fri Jan 01 2021
Journal Name
Aip Conference Proceedings
Preparation and characterization of biomass-alumina composite as adsorbent for safranine-o dye from aqueous solution at different temperatures
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Publication Date
Thu Feb 06 2020
Journal Name
Scientific Reports
Waste foundry sand/MgFe-layered double hydroxides composite material for efficient removal of Congo red dye from aqueous solution
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Abstract<p>We aimed to obtain magnesium/iron (Mg/Fe)-layered double hydroxides (LDHs) nanoparticles-immobilized on waste foundry sand-a byproduct of the metal casting industry. XRD and FT-IR tests were applied to characterize the prepared sorbent. The results revealed that a new peak reflected LDHs nanoparticles. In addition, SEM-EDS mapping confirmed that the coating process was appropriate. Sorption tests for the interaction of this sorbent with an aqueous solution contaminated with Congo red dye revealed the efficacy of this material where the maximum adsorption capacity reached approximately 9127.08 mg/g. The pseudo-first-order and pseudo-second-order kinetic models helped to describe the sorption measure</p> ... Show More
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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
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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Publication Date
Sat Jun 01 2024
Journal Name
Case Studies In Chemical And Environmental Engineering
Optimization of photocatalytic process with SnO2 catalyst for COD reduction from petroleum refinery wastewater using a slurry bubble photoreactor
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