MSA Repository "MSAR"
MSAR University's Digital Repository is a documentation and digitization of all university outcomes that are of effective value in the scientific and academic community and reflects the university's image, work, and effective contribution to society Through MSAR Digital Repository, the university managed to collect, store, archive and publish digital content - including documents, audio files, images and data sets - all in a safe place. MSAR is one of the strongest University Digital Repositories in Egypt and documented in the DSPACE community with its latest versions.
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Recent Submissions
Clinical uses of cannabis and Catha edulis products
(Elsevier, 2024-01-01) Shahira M. Ezzat; Passent M. Abdel Baki; Rana M. Ibrahim; Doaa Abu Elezz; Mahmoud Abdelaziz; Mohamed A. Salem
The medicinal use of cannabis (Cannabis sativa) and khat (Catha edulis) as well as their products has been increased in the last decade. Medical cannabis and khat have been legalized in several countries. Additionally, the major cannabinoids, particularly cannabidiol and tetrahydrocannabinol, have been utilized for the development of FDA-approved pharmaceuticals. The clinical applications of cannabis and C. edulis products are complicated by legislation and regulations that are varied among countries. In this chapter, the pharmacological and the side effect profiles for the clinical uses of cannabis and C. edulis products are highlighted. Although, the clinical data for their use are continuing to evolve, the legal status needs to be authorized to keep the balance between clinical applications and limitations.
Industrially important enzymes of endophytic fungi
(Elsevier, 2024-01-01) Amira M.G. Darwish; Bassem Balbool; Fatma A. Abo Nouh
Endophytic fungi are a promising group of microorganisms that produce plant-associated bioactive metabolites with diverse chemical entities and structural functions including enzymes. Endophytic fungal enzymes have been gradually used in industrial production, and the production of amylase, cellulase, laccase, lipase, protein, xylanase, pectinase, phytase, and phenoxidase has been matured and industrialized. Safety and feasibility are the main keys for selective criteria of these enzymes. The ability of these fungi to produce a wide variety of enzymes makes their possible use in the most diverse fields, such as food, cosmetic, cleaning agents, biofuels, and pharmacy. Enzyme metabolites isolated from endophytic fungi exhibited various pharmacological properties, such as antimicrobial, anticancer, antioxidant, anti-inflammatory, and antidiabetic activities. Besides mining the endophytic fungi for novel bioactive compounds and enzymes, new molecular studies that deal with the activation of putative pathways to produce new compounds or enzymes were carried out such as the activation of the silent biosynthetic cluster genes targeting some novel strains using the genetic engineering tools. Endophytic fungi have the ability to cause highly selective catalytic conversion of high-value compounds in an environmentally friendly manner (biotransformation), which can be important for the production of innovative bioactive molecules for food and nutrition, agriculture, and environment. The request for microbial sources is projected to witness significant growth in the near future due to their wide range of food and feed processing applications; consequently, unique endophytes with properties of biosynthesizing will represent future targets of scale-up and therapeutic studies.
Extraction and isolation of cannabinoids
(Elsevier, 2024-01-01) Mohamed A. Salem; Rana M. Ibrahim; Passent M. Abdel Baki; Sohila M. Osman; Shahira M. Ezzat
Cannabis sativa L. is one of the most important medicinal plants that belongs to the family Cannabaceae. C. sativa is a herbaceous flowering plant that is indigenous to eastern Asia, but it is now cultivated worldwide due to the importance of its active constituents known as cannabinoids. Due to the growing interest in these compounds, various methods for their extraction and isolation were proposed. In this chapter, we will have an overview about the conventional and nonconventional methods for extraction of cannabinoids both from plant material and from biological samples for forensic purposes. Also we will review the methods for isolation of such compounds from different types of extracts as well as the modern methods for metabolomics and chemometric tools for analysis of cannabinoids.
Effect of Access Design and Location on Stress Distribution Within Endodontically Treated Maxillary Incisors: A Three-Dimensional Finite Element Analysis
(University of Dicle, 2024-10-04) Manal M. Abdelhafeez
The optimal approach to access cavity preparation in anterior teeth requiring root canal treatment, especially those affected by traumatic injuries, remains contentious among endodontists. Minimally invasive techniques aim to preserve tooth structure while maintaining strength. The effect of different access cavity designs on stress concentration and distribution in necrotized anterior teeth needing root canal treatment is not well documented. This study aims to evaluate and compare the effect of various access cavity designs on stress distribution in anterior teeth using three-dimensional finite element analysis. Three-dimensional finite element models of maxillary central incisors were created. Three groups with different access cavity designs were analyzed: Group A (Cervical access), Group B (Middle access), and Group C (Incisal access). A load of 100 N was applied at a 45-degree angle to the tooth axis in each model, and stress distribution was analyzed. Maximum stress values (in MPa) were recorded for each design. Group A: Enamel (587.52), Dentin (163.97), Composite (65.11); Group B: Enamel (880.93), Dentin (132.32), Composite (81.27); Group C: Enamel (493.92), Dentin (126.99), Composite (42.39). The study found significant differences in stress distribution among different access cavity designs, with traditional middle access showing the highest stress concentration. These findings could inform clinical decisions to optimize outcomes in root canal treatments.
ENHANCING DIABETES CARE VIA ARTIFICIAL INTELLIGENCE
(Little Lion Scientific, 2024-09-30) Turja Bhattacharjee; Mohamed El-Dosuky; Sherif Kamel
Artificial intelligence (AI) has become a potent tool in healthcare with the potential to completely change the way diabetes is treated. This study investigates how AI affects patient outcomes and diabetes treatment. Healthcare providers can extract insightful information from patient data using machine learning, data analytics, and AI-driven wearable devices, resulting in individualized treatment programs and better glycemic control. AI chatbots and virtual assistants improve patient support and engagement, encouraging improved treatment adherence. Despite privacy and ethical issues, AI is effective at cutting healthcare expenses and improving the quality of life for patients is obvious. Healthcare providers can use AI to develop a patient-centered strategy and improve diabetes care by working with researchers and politicians. This paper proposes a smart chatbot for enhancing diabetes care through natural language interactions. The chatbot's architecture uses pattern matching and keyword identification techniques to follow a multi-level interaction procedure. The proposed chatbot system simplifies diabetes diagnosis by using natural language interactions, asking questions based on previous responses through a multi-level diagnostic flow. It employs AIML-based memory techniques and pattern matching to identify keywords at each level, ensuring relevance and coherence in conversation. The system follows a search engine-like flow, using methods like the Sequence Words Deleted (SWD) technique and Triangular Number equation to optimize keyword matching, with Vpath values guiding the diagnostic path. The chatbot enhances patient diagnosis by providing structured, personalized guidance through these techniques.