Visceral leishmaniasis is a neglected tropical disease on the rise in different regions of Iraq, especially in areas with poor hygiene and among refugee populations. The effectiveness of existing chemotherapy for leishmaniasis is constrained by its high toxicity, cost, and the development of drug resistance. The current research examined various concentrations (ranging from 125 to 1000 μM) of lupeol to evaluate its ability to boost the generation of nitric oxide, which has anti-leishmanial properties, in an ex-vivo macrophage model. Griess assay was used to detect the nitric oxide (NO) production in Leishmania donovani infected U937 cell-line macrophages along 24 and 48 hours post treated. The nitric oxide concentration was significantly increased (P≤0.05) in the treated infected-macrophages after 24 and 48 hours post treated. Furthermore, the infectivity index was calculated for ex vivo amastigote-macrophage infection and the results showed a significant decrease in the percentage of invasion at higher concentrations of Lupeol at all periods of incubation (P≤0.05); whereas, the average of amastigotes per cell in lupeol-treated macrophages increased significantly (P≤0.05) only after 48hours of incubation. The results indicate that lupeol has the potential to enhance anti-leishmanial nitric oxide production by macrophages, enabling them to eliminate intracellular amastigote forms of the parasite. Further details on effect of Lupeol can be studied as a promising anti-leishmanial compound.
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
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
... Show MoreRelease of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are
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