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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RESEARCH & LANGUAGES CENTERS 18

Recent Submissions

Smart strategy for monitoring and removal of certain pharmaceuticals from wastewater with TLC, innovative implementation of ImageJ software: A view through greenness assessment
(Elsevier B.V., 2025-09-09) Heba T. Elbalkiny; Mona S. Elshahed; Dalia Mohamed; Azza A. Ashour; Rasha Th. El-Eryan
Pharmaceutical residuals in untreated hospital wastewater (HWW) can disrupt the delicate balance in the ecosystem. The monitoring and treatment of water sources from pharmaceuticals are of critical importance. In the present work, zeolite nanoparticles were used for the removal of azithromycin (AZI), barcitinib (BAR), and prednisolone acetate (PRD), which are frequently found pharmaceuticals in HWW. An I-Optimal design was used for the optimization of the adsorption conditions. For the monitoring of AZI, BAR, and PRD concentrations in synthetic HWW, a thin-layer chromatographic method was developed. The proposed method includes the novel use of ImageJ software for the simultaneous determination of fluorescent and non-fluorescent drugs on the same TLC plate. The developed mobile phase includes the use of n-hexane, diethylamine, ethanol, and ammonia in a ratio of 6:3:1:0.1 (v/v), respectively, on a silica gel aluminum plate with fluorescence detection (F254). The utilized conditions permitted the determination of AZI, BAR, and PRD in the linearity range of 0.60–5.0 µg/spot. This method is designed to be sustainable and environmentally friendly, minimizing the use of harmful solvents and reducing waste. The need, quality, and sustainability index (NQS index) was used to benchmark the environmental importance of the proposed method.
Liraglutide orchestrates ferroptosis defense against murine cisplatin acute kidney injury: NRF2 activation via both KEAP1-dependent and -independent mechanisms is essential for SLC7A11/GPX4 renoprotection
(Elsevier GmbH, 2025-09-16) Nermeen S. Abdel Razek; Noha N. Nassar; Rabab H. Sayed; Ayman E. El-Sahar; Dalaal M. Abdallah
Objective: Acute kidney injury (AKI) induced by oxidative stress, and recently associated with ferroptosis, represents a major complication of the chemotherapeutic cisplatin that often necessitates treatment cessation. The glucagon-like peptide 1 receptor (GLP1R) agonist liraglutide possesses reno-protective potential via its antioxidant character in different kidney injury settings while reducing iron overload in other models. Hence, we investigated the potential protective role of liraglutide in cisplatin-induced AKI targeting KEAP1-dependent and -independent ferroptosis pathways. Methods: Rats were assigned to one of four groups: vehicle control, liraglutide control, cisplatin-induced AKI, and liraglutide-pretreated AKI. Renal function markers and histopathological changes were assessed. SLC7A11, NRF2, and KEAP1-canonical and non-canonical hubs were analyzed to elucidate the drug's molecular mechanisms on ferroptosis. Results: Liraglutide significantly improved renal function, evidenced by the reduction of serum cystatin C, creatinine, and BUN, along with renal histological improvements. In the kidney, liraglutide activated/phosphorylated AKT, mTOR, and P62 to reduce KEAP1 and inactivated GSK3β to enhance NRF2-mediated GPX4 and SLC7A11 formation, thus inhibiting cisplatin-ferroptosis-triggered renal injury. Conclusion: Therefore, liraglutide is a promising treatment candidate for attenuating cisplatin-induced AKI by SLC7A11/GPX4 trajectory through upregulating the AKT/mTOR/P62/KEAP1/NRF2 and AKT/GSK3β/NRF2 signaling pathways to increase GPX4 alongside with SLC7A11. Indeed, the GLP1R-mediated AKT activation acts as a potential target for Liraglutide reno-protective actions; hence, the GLP1R can be considered a therapeutic entity in such a renal injurious paradigm.
Influence of Bioactive Desensitizers on Bonding of Self-adhesive Resin Cement: A SEM/EDX Microanalysis Study
(The Open Dentistry Journal, 2025-07-28) Alaa Turkistani; Rasha R. Basheer
Introduction: Bioactive desensitizing agents are increasingly used to alleviate dentin hypersensitivity; however, their impact on the bonding performance of self-adhesive resin cements remains unclear. This in vitro study evaluated the effect of bioactive desensitizers on the bond strength of a self-adhesive resin cement to dentin and examined elemental changes on the dentin surface using Energy-Dispersive X-ray (EDX) spectrometry. Methods: Dentin surfaces of extracted molars were exposed and treated with a glutaraldehyde-based desensitizer (Dentin Desensitizer; DD), a calcium phosphate-based desensitizer (Teethmate Desensitizer; TM), a hydroxyapatite-based desensitizer (Predicta Bioactive; PB), or fluoride gel (APF Fluoride Gel; FL). The control group received no treatment. Self-adhesive resin cement (Panavia SA Cement Universal) was applied in cylindrical molds. After thermocycling, microshear bond strength was measured, and failure modes were analyzed. Scanning Electron Microscopy (SEM) combined with EDX analysis was performed to assess changes in the dentin surface. Results: The DD group showed the highest bond strength (11.15 ± 1.32 MPa), followed by PB (5.98 ± 1.79 MPa), the control group (5.08 ± 1.17 MPa), and FL (4.78 ± 0.75 MPa). TM showed the lowest value (4.09 ± 0.52 MPa). ANOVA with post-hoc comparisons confirmed significant differences, with DD outperforming all other groups (p < 0.001). Adhesive failure was the most common, followed by mixed-type failures. EDX results indicated increased mineral and decreased carbon content across all treated groups, most notably in the PB group. Discussion: Although bioactive desensitizers altered dentin composition, their inconsistent effect on bond strength may be attributed to the distinct microstructural changes each induces. Conclusion: Clinicians must carefully consider the balance between enhancing patient comfort and preserving the long-term integrity of the restoration.
Gender Classification in Panoramic Dental X-Rays using few-shot learning and Ensemble models
(IEEE, 2025-08-15) Aly Essam; Mohaned Gamal; Ayman Atia
Integrating advanced technologies has revolutionized dental practice, transforming patient diagnosis and treatment. Radiographic examinations remain one of the most essential tools for identifying hidden dental conditions with precision. According to the American Dental Association (ADA), nearly 90% of dental procedures rely on radiographic analysis, which uncovers hidden issues in over 80% of cases. This study focuses on leveraging Machine learning methodology to improve the diagnostic process by enabling automated classification X-ray images with high accuracy, significantly reducing the time required for manual interpretation. Gender determination from panoramic X-rays plays a crucial role in forensic odontology and clinical diagnosis, as certain diseases are more prevalent in one gender than the other. Studies have shown that statistically significant gender differences exist in craniofacial parameters such as the gonial angle, ramus height, and bigonial width, with these parameters increasing with age. Moreover, this difference is particularly significant on the right side for gonial angle and ramus height [23]. Incorporating gender classification into automated diagnostic systems can further enhance the precision of dental assessments and support more personalized treatment strategies. Our approach integrates various advanced techniques and algorithms, including Few-Shot Learning, Ensemble Models, Convolutional Neural Networks (CNNs), and Transfer Learning models, to get the best model for this dataset. The proposed framework achieved a high accuracy of 96.9%, demonstrating its ability to improve diagnostic precision and efficiency in dental radiography.
Dynamic Location-Based Transaction Limits for Enhanced Fraud Prevention in Financial Services
(IEEE, 2025-08-19) Mahmoud Raafat Elrashidy; Hesham Mansour
This paper presents a novel, dynamic location-based transaction limit system designed to enhance financial fraud prevention by adapting security measures in real-time. Traditional static fraud prevention methods are increasingly ineffective in dynamic, high-risk environments, particularly against geolocation spoofing. Our proposed system addresses this by integrating multi-source geolocation verification, cryptographic checksums, and digital signatures to ensure location data integrity. Utilizing machine learning, the system dynamically classifies locations into risk zones (high, medium, low) and adjusts transaction limits accordingly. Performance evaluations demonstrate over 90% accuracy in risk assessment, a 30% reduction in fraud incidents compared to static methods, and an average response time of 300 milliseconds. Notably, the system reduces false-positive alerts by 25%, significantly improving user experience. This research contributes a scalable and adaptable solution for location-sensitive financial security, with future work focusing on advanced predictive analytics for risk zone refinement and personalized risk adjustments based on user behavior.