Papers by Shaimaa Mohammed
Journal of Herbmed Pharmacology, 2021
Introduction: Non-communicable diseases are a cluster of metabolic diseases, which include type-2... more Introduction: Non-communicable diseases are a cluster of metabolic diseases, which include type-2 diabetes, cancer, and cardiovascular diseases (CVDs). The aim of the current research was to incorporate dietary fibers (mucilage) and phytosterol for enriching chia seeds oil for producing new dietary supplements for cardio-protection from oxidative stress, inflammation, and dyslipidemia. Methods: Fatty acids profile, phytosterols, and phenolic compounds content of the prepared dietary supplement were assessed. The cardioprotective potency of the dietary supplement was evaluated in rats fed on a high-fat diet for a month. Biochemical parameters related to inflammation, oxidative stress, lipid profile, cardiac enzymes, and kidney function were determined in all rats. Results: The results revealed that dietary supplement was rich in omega-3 fatty acids. Beta-sitosterol and campesterol were the major phytosterols in chia seeds oil dietary supplement. Phenolic compounds were present by 25....
Egyptian Journal of Chemistry, 2021
The present study aims to evaluate the antioxidant and anti-cancer activities of nutraceuticals p... more The present study aims to evaluate the antioxidant and anti-cancer activities of nutraceuticals prepared from apricot kernel and grape seeds extracts. Different bioactive compounds were determined in the prepared nutraceuticals (total phenolic compounds, flavonoids, β-carotene, phytosterols and fatty acids). Acute toxicity of these nutraceuticals was evaluated. Apricot kernel showed the highest content of protein and fat, while grape seeds were rich in carbohydrates. Apricot kernel nutraceutical (AKN) showed the highest content of hydrocarbons, while grape seeds nutraceutical (GSN) showed the highest phytosterol content. Stigmasterol was the major phytosterol present in both nutraceuticals. Oleic acid and linoleic acid were the major unsaturated fatty acids present in AKN and GSN, respectively. GSN showed the highest content of phenolic compounds and total flavonoids, while AKN showed the highest content of β-carotene (2.91mg/100g). GSN showed the highest antioxidant activity in all the studied methods (DPPH, reducing power and ferric thiocynate) compared with apricot kernel nutraceutical. Both nutraceuticals showed anti-cancer activity against liver carcinoma cells (HEPG2), breast cancer cells (MCF7) and lung cell cancer (H460). GSN was the most promising in all types of cancer cells. GSN showed complete safety, while AKN was completely safe up to 6 g/kg mice body weight.
Ameliorative Effect of Probiotic-Fermented Milk and Costus Extract in Alzheimer’s Disease Model Induced by D-Galactose and Aluminum Chloride
Egyptian Journal of Chemistry, 2021
IEEE Access, 2020
Breast cancer is one of the most common types of cancer and early detection can significantly dec... more Breast cancer is one of the most common types of cancer and early detection can significantly decrease the associated mortality rate. Different kinds of segmentation methods were applied to extract regions of interest from breast cancer images that are necessary to improve the classification. In this paper, a segmentation method for breast cancer from thermal images is introduced based on a proposed Chaotic Salp Swarm Algorithm (CSSA). Although the Salp Swarm Algorithm (SSA) shows superiority in single-objective optimization problems, it suffers from a low convergence rate and local optima stagnation. In the proposed method, a segmentation algorithm is formulated using the quick-shift method for superpixels extraction whose parameters are optimized by CSSA. The quick-shift method generates compact and nearly uniform superpixels by clustering the breast thermal image pixels. CSSA algorithm is developed based on ten chaotic maps to enhance the original SSA convergence rate while accuracy could be improved by controlling the balance between exploration and exploitation. The proposed algorithm is applied to realworld thermal images for the breast area. The results demonstrate that the proposed CSSA algorithm achieves fast convergence for the unimodal benchmark functions and outperforms the original SSA algorithm. Moreover, a dataset from Mastology Research with Infrared Image (DMR-IR) is used to test the performance of the proposed algorithm. In experiments, the proposed optimized segmentation algorithm extracts the breast area from the background accurately where the region of interest is focused on the breast area and removes the unwanted area such as underarms and stomach which intern can enhance the results of cancer detection. Furthermore, the proposed algorithms achieve robustness for the segmentation of different healthy and unhealthy cases images compared to the state-of-the-art methods.
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Papers by Shaimaa Mohammed