Quercetin, one of the flavonoids family member, can be found in many vegetables, fruits, and beverages with a noticeable nutritional pharmacological properties. This study was aimed to evaluate the ability of quercetin to inhibit lipopolysaccharide (LPS) that induced lethal toxicity in vivo, and to elucidate the importance of the quercetin as an antitumor agent in breast cancer cell line MCF-7.In vivo experiments included the effect of hesperidin and LPS on the liver and spleen of male mice. In the liver, the antioxidant activity was measured by estimating the concentration of glutathione (GSH), and catalase (CAT), while in the spleen, the concentration of cytokines was measured including IL-33 and TNF-α. In vitro experiments included MTT assay, colonogenicity test and Sulforhadamine 101 to assess breast cancer cells morphological apoptosis. The studies revealed the following results: highly significant increase in IL-33 and TNF-αcytokine levels in LPS challenge mice along with significant glutathione (GSH), and catalase (CAT) level increased compared to control group. The cytotoxicity on MCF-7 cell line showed significant differences between groups treated with different concentrations in comparison with control groups in a concentration-dependent manner. The colony measurement test showed that quercetin significantly inhibited colony formation of MCF7 cells compared to control. Apoptotic morphological results showed clear changes in the shape associated with a later stage of apoptosis, including cell shrinking and chromatin condensation. The obtained results indicate that hesperidin might be a potential beneficial compound as a preventive agent
Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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Melanoides tuberculata (O. F. Müller, 1774), a freshwater snail native to eastern Mediterranean, eastern Africa, southeast Asia, southern Asia, India, and Malaysia, it is an effective invader and is now nearly globally distributed. This snail has been studied with interest because of its rapidly distributed, and because of being can serve as compatible intermediate host for many of trematodes in the world. We have summarized information from many articles in order to highlight the most important aspects of this invader snail life.
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The pure ZnS and ZnS-Gr nanocomposite have been prepared
successfully by a novel method using chemical co-precipitation. Also
conductive polymer PPy nanotubes and ZnS-PPy nanocomposite
have been synthesized successfully by chemical route. The effect of
graphene on the characterization of ZnS has been investigated. X-ray
diffraction (XRD) study confirmed the formation of cubic and
hexagonal structure of ZnS-Gr. Dc-conductivity proves that ZnS and
ZnS-Gr have semiconductor behavior. The SEM proved that
formation of PPy nanotubes and the Gr nanosheet. The sensing
properties of ZnS-PPy/ZnS-Gr for NO2 gas was investigated as a
function of operating temperature and time under optimal condition.
The sensitivity,
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Rheumatoid arthritis is a chronic, progressive, inflammatory autoimmune disease of unidentified etiology, associated with articular, extra-articular and systemic manifestation that require long-standing treatment. Taking patient’s beliefs about the prescribed medication in consideration had been shown to be an essential factor that affects adherence of the patient in whom having positive beliefs is an essential for better adherence. The purpose of the current study was to measure beliefs about medicines among a sample of Iraqi patients with Rheumatoid arthritis and to determine possible association between this belief and some patient-certain factors. This study is a cross-sectional study carried out on 250 already diagnosed rheumatoid
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This paper describes the problem of online autonomous mobile robot path planning, which is consisted of finding optimal paths or trajectories for an autonomous mobile robot from a starting point to a destination across a flat map of a terrain, represented by a 2-D workspace. An enhanced algorithm for solving the problem of path planning using Bacterial Foraging Optimization algorithm is presented. This nature-inspired metaheuristic algorithm, which imitates the foraging behavior of E-coli bacteria, was used to find the optimal path from a starting point to a target point. The proposed algorithm was demonstrated by simulations in both static and dynamic different environments. A comparative study was evaluated between the developed algori
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