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Effect of Hydroxychloroquine Drugs on Amino Acids in the Kidneys of White Mice (Mus musculas)
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Hydroxychloroquine (HQC) and chloroquine drugs belong to a class of drugs known as 4-aminoquinoline, its structure weak bases due to the presence of the essential side chain, and this chain contributes to the accumulation of drugs in the intracellular parts. A 21 mice were taken and divided into three groups, the first group (A) was the control group that administered oral distilled water for 30 days, and the second group (B) treated group that was dose with 15 mg/kg/day of drug for 30 days, and the third group (C) was the treated group by injected drug with a concentration of 30 mg/kg/day for 30 days also. The result of amino acids studied in the kidney of adult white mice (Mus musculus) showed the presence of (18) amino acid represented: asparagine (Asn), alanine (Ala), arginine (Arg), citrulline (Cit), glutamine (Glu), glycine (Gly), histidine (His), isoleucine (Ile), leucine (Leu), lysine (Iys), methionine (Met), proline (Pro), phenylalanine (Phe), serine (Ser), threonine (Thr), taurine (Tau), tyrosine (Tyr) and valine (Val). Statistical analysis showed high significant differences in the concentration of amino acids between the two groups of experiments treated with the drug (HQC) with a concentration (15 and 30) mg/kg/day and control group, as well as significant differences between the three groups.

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Publication Date
Thu Jan 01 2026
Journal Name
Journal Of The Iranian Chemical Society
Synthesis, characterization and evaluating their activity as antioxidants and anticancer of new metal ion complexes with new Azo dye
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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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Publication Date
Wed Dec 13 2023
Journal Name
Drug And Chemical Toxicology
Single and repeat-dose toxicity and local tolerance assessment of newly developed oil emulsion adjuvant formulations for veterinary purposes
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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
Sat Jul 01 2023
Journal Name
Journal Of Water Process Engineering
Removal kinetics of organic carbon from palm oil mill effluent by native duckweeds and its potential as a biofertilizer
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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 Jan 23 2014
Journal Name
مجلة إبن الھيثم للعلوم الصرفة و التطبيقية
Synthesis of Tetra Dentate N2O2 and their Complexes With Cu[II), Zn[II), Cd[II) and Hg[II) Ions
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Publication Date
Sat Jun 01 2024
Journal Name
Results In Engineering
Thermodynamic modeling and performance analysis of photovoltaic-thermal collectors integrated with phase change materials: Comprehensive energy and exergy analysis
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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
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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