(1) Background: Plant flavonoids are efficient in preventing and treating various diseases. This study aimed to evaluate the ability of hesperidin, a flavonoid found in citrus fruits, in inhibiting lipopolysaccharide (LPS) induced inflammation, which induced lethal toxicity in vivo, and to evaluate its importance as an antitumor agent in breast cancer. The in vivo experiments revealed the protective effects of hesperidin against the negative LPS effects on the liver and spleen of male mice. (2) Methods: In the liver, the antioxidant activity was measured by estimating the concentration of glutathione (GSH) and catalase (CAT), whereas in spleen, the concentration of cytokines including IL-33 and TNF-α was measured. The in vitro experiments including MTT assay, clonogenity test, and sulforhodamine 101 stain with DAPI (4′, 6-diamidino-2-phenylindole) were used to assess the morphological apoptosis in breast cancer cells. (3) Results: The results of this study revealed a significant increase in the IL-33 and TNF-α cytokine levels in LPS challenged mice along with a considerable elevation in glutathione (GSH); moreover, the catalase (CAT) level was higher compared to that of the control group. Cytotoxicity of the MCF-7 cell line revealed significant differences among the groups treated with different concentrations when compared to the control groups, in a concentration-dependent manner. Hesperidin significantly inhibited the colony formation of MCF7 cells when compared to that of control. Clear changes were observed in the cell shape, including cell shrinkage and chromatin condensation, which were associated with a later apoptotic stage. (4) Conclusion: The results indicate that hesperidin might be a potential candidate in preventing diseases.
Most companies use social media data for business. Sentiment analysis automatically gathers analyses and summarizes this type of data. Managing unstructured social media data is difficult. Noisy data is a challenge to sentiment analysis. Since over 50% of the sentiment analysis process is data pre-processing, processing big social media data is challenging too. If pre-processing is carried out correctly, data accuracy may improve. Also, sentiment analysis workflow is highly dependent. Because no pre-processing technique works well in all situations or with all data sources, choosing the most important ones is crucial. Prioritization is an excellent technique for choosing the most important ones. As one of many Multi-Criteria Decision Mak
... Show MoreAbstract: Background: Staphylococcus aureus is Gram-positive bacteria that lives as a normal flora in living organisms but can be pathogenic to humans. Although a relatively unspectacular, nonmotile coccoid bacterium, S. aureus is a dangerous human pathogen in both community-acquired and nosocomial infections. Due to the increasing emergence of new strains of this antibiotic-resistant bacteria, it has become essential to approach different methods to control this pathogen. One of these methods is the antimicrobial photodynamic inactivation process using a low-level laser, in this paper, the Photodynamic effects of Rose Bengal and LLLL on the virulence factors of S.aureus were evaluated.
Greywater is a possible water source that can be improved for meeting the quality required for irrigation. Treatment of greywater can range from uncomplicated coarse filtration to advanced biological treatment. This article presents a simple design of a small scale greywater treatment plant, which is a series of physical and natural processes including screening, aeration, sedimentation, and filtration using granular activated carbon filter and differentiates its performance with sand filter. The performance of these units with the dual filter media of (activated carbon with sand) in treatment of greywater from Iraqi house in Baghdad city during 2019 and that collected from several points including washbasins, kitchen si
... Show MoreAssessing water quality provides a scientific foundation for the development and management of water resources. The objective of the research is to evaluate the impact treated effluent from North Rustumiyia wastewater treatment plant (WWTP) on the quality of Diyala river. The model of the artificial neural network (ANN) and factor analysis (FA) based on Nemerow pollution index (NPI). To define important water quality parameters for North Al-Rustumiyia for the line(F2), the Nemerow Pollution Index was introduced. The most important parameters of assessment of water variation quality of wastewater were the parameter used in the model: biochemical oxygen demand (BOD), chemical oxygen dem
This paper compare the accurecy of HF propagation prediction programs for HF circuits links between Iraq and different points world wide during August 2018 when solar cycle 24 (start 2009 end 2020) is at minimun activity and also find out the best communication mode used. The prediction programs like Voice of America Coverage Analysis Program (VOACAP) and ITU Recommendation RS 533 (REC533 ) had been used to generat HF circuit link parameters like Maximum Usable Frequency ( MUF) and Frequency of Transsmision (FOT) .Depending on the predicted parameters (data) , real radio contacts had been done using a radio transceiver from Icom model IC 7100 with 100W RF
... Show MoreThe effects of nutrients and physical conditions on phytase production were investigated with a recently isolated strain of Aspergillus tubingensis SKA under solid state fermentation on wheat bran. The nutrient factors investigated included carbon source, nitrogen source, phosphate source and concentration, metal ions (salts) and the physical parameters investigated included inoculum size, pH, temperature and fermentation duration. Our investigations revealed that optimal productivity of phytase was achieved using wheat bran supplemented with: 1.5% glucose. 0.5% (NH4)2SO4, 0.1% sodium phytate. Additionally, optimal physical conditions were 1 × 105 spore/g substrate, initial pH of 5.0, temperature of fermentation 30˚C and fermentation dura
... Show MoreThis research aims to solve the problem of selection using clustering algorithm, in this research optimal portfolio is formation using the single index model, and the real data are consisting from the stocks Iraqi Stock Exchange in the period 1/1/2007 to 31/12/2019. because the data series have missing values ,we used the two-stage missing value compensation method, the knowledge gap was inability the portfolio models to reduce The estimation error , inaccuracy of the cut-off rate and the Treynor ratio combine stocks into the portfolio that caused to decline in their performance, all these problems required employing clustering technic to data mining and regrouping it within clusters with similar characteristics to outperform the portfolio
... Show More