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201 results on '"Alharbi, Njud S."'

39. Silver Nanoparticles Biosynthesized Using Azadirachta indica Fruit and Leaf Extracts: Optimization, Characterization, and Anticancer Activity.

Author

Alharbi, Njud S. and Alsubhi, Nehad S.

Subjects
*FRUIT extracts, *SILVER nanoparticles, *NEEM, *ANTINEOPLASTIC agents, *PLANT extracts, *REDUCING agents
Abstract

Silver nanoparticles (AgNPs) are becoming increasingly important for various crucial applications, including antimicrobial, anticancer, catalytic, and anti-inflammatory. AgNPs biosynthesized from plant extracts have attracted considerable attention because of their eco-friendliness, simplicity, cost-effectiveness, and stability. This study investigated the potential of using fruit and leaf extracts of the medicinal plant Azadirachta indica as a capping and reducing agent for the biosynthesis of AgNPs. The size, shape, and optical properties of AgNPs significantly affect their chemical, physical, and biological activity. Therefore, this study optimized the biosynthesis conditions as a first attempt for A. indica fruit extracts to produce AgNPs with precise morphology. Subsequently, the biologically manufactured AgNPs were characterized using suitable techniques. Their potential anticancer activities were examined against in vitro human lung and breast cancer (H1975 and MCF-7) cell lines. The AgNPs were stable, with a high yield and a spherical shape, ranging in size from 14 to 19 nm and exhibiting an absorption band between 420 and 440 nm. The AgNPs biosynthesized using A. indica fruit and leaf extracts were shown to be highly toxic against in vitro H1975, with IC50 of 62.2 and 91 µg/mL, respectively. The IC50 values were 67.5 and 68.7 µg/mL when testing against the MCF-7 cells. These findings suggest that plant-derived nanoparticles have enormous potential for future biomedical applications, which warrants further investigation. [ABSTRACT FROM AUTHOR]

Published
2023
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40. Enhanced Classification of Heartbeat Electrocardiogram Signals Using a Long Short-Term Memory–Convolutional Neural Network Ensemble: Paving the Way for Preventive Healthcare.

Author

Alharbi, Njud S., Jahanshahi, Hadi, Yao, Qijia, Bekiros, Stelios, and Moroz, Irene

Subjects
*CONVOLUTIONAL neural networks, *CARDIOVASCULAR disease diagnosis, *PATTERN recognition systems, *INTEROCEPTION, *DEEP learning, *SEQUENTIAL learning
Abstract

In the rapidly evolving field of medical diagnosis, the accurate and prompt interpretation of heartbeat electrocardiogram (ECG) signals have become increasingly crucial. Despite the presence of recent advances, there is an exigent need to enhance the accuracy of existing methodologies, especially given the profound implications such interpretations can have on patient prognosis. To this end, we introduce a novel ensemble comprising Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN) models to enable the enhanced classification of heartbeat ECG signals. Our approach capitalizes on LSTM's exceptional sequential data learning capability and CNN's intricate pattern recognition strength. Advanced signal processing methods are integrated to enhance the quality of raw ECG signals before feeding them into the deep learning model. Experimental evaluations on benchmark ECG datasets demonstrate that our proposed ensemble model surpasses other state-of-the-art deep learning models. It achieves a sensitivity of 94.52%, a specificity of 96.42%, and an accuracy of 95.45%, highlighting its superior performance metrics. This study introduces a promising tool for bolstering cardiovascular disease diagnosis, showcasing the potential of such techniques to advance preventive healthcare. [ABSTRACT FROM AUTHOR]

Published
2023
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45. Co-circulation of three camel coronavirus species and recombination of MERS-CoVs in Saudi Arabia

Author

Sabir, Jamal S. M., Lam, Tommy T.-Y., Ahmed, Mohamed M. M., Li, Lifeng, Shen, Yongyi, Abo-Aba, Salah E. M., Qureshi, Muhammad I., Abu-Zeid, Mohamed, Zhang, Yu, Khiyami, Mohammad A., Alharbi, Njud S., Hajrah, Nahid H., Sabir, Meshaal J., Mutwakil, Mohammed H. Z., Kabli, Saleh A., Alsulaimany, Faten A. S., Obaid, Abdullah Y., Zhou, Boping, Smith, David K., Holmes, Edward C., Zhu, Huachen, and Guan, Yi

Published
2016

48. VIROLOGY: Co-circulation of three camel coronavirus species and recombination of MERS-CoVs in Saudi Arabia

Author

Sabir, Jamal S. M., Lam, Tommy T.-Y., Ahmed, Mohamed M. M., Li, Lifeng, Shen, Yongyi, Abo-Aba, Salah E. M., Qureshi, Muhammad I., Abu-Zeid, Mohamed, Zhang, Yu, Khiyami, Mohammad A., Alharbi, Njud S., Hajrah, Nahid H., Sabir, Meshaal J., Mutwakil, Mohammed H. Z., Kabli, Saleh A., Alsulaimany, Faten A. S., Obaid, Abdullah Y., Zhou, Boping, Smith, David K., Holmes, Edward C., Zhu, Huachen, and Guan, Yi

Published
2016
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49. Optimization, Characterization, and Anticancer Potential of Silver Nanoparticles Biosynthesized Using Olea europaea.

Author

Felimban, Afnan I., Alharbi, Njud S., and Alsubhi, Nehad S.

Subjects
*OLIVE, *SILVER nanoparticles, *ANTINEOPLASTIC agents, *CANCER treatment, *CANCER cells
Abstract

Green synthesis has attracted significant attention as an eco-friendly, low-cost, energy-efficient, and non-toxic method for preparing silver nanoparticles (AgNPs) for cancer therapy. This study optimized the green synthesis of AgNPs using Olea europaea extracts and evaluated their anticancer potential. The biosynthesized AgNPs were characterized using various methods, showing stable AgNPs with a desirable morphology and high yield, improving the properties of AgNPs for various medicinal applications. The biosynthesized AgNPs were predominantly spherical, with small sizes ranging from 13 to 21 nm and highly stable at −23 and −24 mV. The findings of this study suggest that green-synthesized AgNPs using Olea europaea and sunlight possess significant anticancer activity against cancer cells in vitro. Further investigation of green synthesis would help to form high-quality AgNPs that have promising potential in treating disease and fighting undesirable pathogens. [ABSTRACT FROM AUTHOR]

Published
2022
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