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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    Mechanistic evidence for PI3K/Akt-driven reactivation of Nrf2/HO-1 by dapagliflozin in acute cisplatin hepatotoxicity
    (Oxford University Press, 2026-06-21) Doaa Abou El-ezz; Noha E Ibrahim; Marwan Khaled Fouad; Marwan A Abd El-Baset; Heba Shawky
    Background: While nephrotoxicity remains the most recognized adverse effect of cisplatin, hepatotoxicity is increasingly acknowledged as a significant clinical concern. Objective: This study evaluated the hepatoprotective effect of dapagliflozin (DAPA), a selective sodium–glucose cotransporter-2 inhibitor, focusing on its modulation of the PI3K/Akt–Nrf2/HO-1 signaling pathway. Methods: Male Wistar albino rats received oral dapagliflozin (5 or 10 mg/kg/day) for 14 days, with a single intraperitoneal injection of cisplatin (7.5 mg/kg) administered on Day 7. Biochemical, molecular, and histopathological assessments were conducted. Results: Cisplatin induced marked hepatic injury, evidenced by body weight loss, hepatomegaly, hyperglycemia, impaired liver function, oxidative stress, inflammation, and apoptosis dysregulation. Dapagliflozin pretreatment significantly and dose-dependently mitigated these effects. It reduced lipid peroxidation and nitric oxide levels while enhancing antioxidant defenses, including Nrf2, heme oxygenase-1, and superoxide dismutase. Additionally, dapagliflozin restored PI3K/Akt signaling, suppressed NF-κB-mediated inflammatory responses, and normalized apoptotic balance. Histological findings corroborated biochemical results, showing preservation of hepatic architecture, particularly at the higher dose. Conclusions: Dapagliflozin exerts significant hepatoprotective effects against cisplatin-induced toxicity via antioxidant, anti-inflammatory, and cytoprotective mechanisms, supporting its potential as an adjunct to improve cisplatin safety.
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    Efficacy of High-Intensity Laser Therapy for Meralgia Paresthetica: A Randomized, Double-Blind, Sham-Controlled Trial
    (Lippincott Williams and Wilkins Ltd., 2026-06-04) Mogahed, Hussein G.; ElMeligie, Mohamed M.; Radwan, Rafik E.; Elmahdy, Menan A.; Abdel-Aal, Nabil M.; Mohamed, Mahmoud H.
    Objective: To evaluate High-Intensity Laser Therapy (HILT) versus sham for pain, function, and nerve conduction in Meralgia Paresthetica (MP). Design: Randomized, double-blind, sham-controlled trial. Methods: Patients with MP (n=62 randomized, n=54 analyzed) received 12 sessions of HILT (1064 nm, 12 W, 600 J/cm²) or identical sham over 4 weeks. Primary outcome: Numeric Pain Rating Scale (NPRS). Secondary outcomes: Lower Extremity Functional Scale (LEFS), lateral femoral cutaneous nerve sensory conduction velocity (SNCV), and SF-36, assessed at baseline, weeks 4, 8, and 12. Results: At week 12, HILT demonstrated significantly greater improvements versus sham in pain (NPRS, P=0.006), function (LEFS, P=0.043), and SNCV (P=0.027). SNCV showed small but significant between-group differences favoring HILT, though values remained within normal limits. Mild, transient adverse events occurred more frequently with HILT (16.1% vs. 0%, P=0.0525). Conclusion: HILT significantly improved pain, function, and nerve conduction velocity compared to sham in MP patients over 12 weeks. These findings support HILT as a non-invasive treatment option; neurophysiological changes were small and within normative limits, warranting cautious interpretation.
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    Biowaste-derived magnetite biochar for adsorption of norfloxacin from water samples
    (Springer Science and Business Media B.V., 2026-06-18) Lamis M. Fahmy; Dalia Mohamed; Marianne Nebsen; Ahmed H. Nadim
    Pharmaceutical residues in water resources pose serious risks to human health and aquatic ecosystems. Herein, an environmentally friendly magnetite-loaded biochar was synthesized from K2CO3 activated tea waste and evaluated for the adsorptive removal of norfloxacin, a widely used fluoroquinolone antibiotic, from water samples. This study combines novel K2CO3 activated tea waste with the facile separation of magnetite adsorbent. The synthesized nanoparticles were characterized using transmission electron microscopy, Fourier transform infrared spectroscopy, X-ray diffraction, Brunauer-Emmett-Teller and dynamic light scattering. A validated spectrofluorimetric method has been developed for monitoring norfloxacin concentration throughout the treatment protocol. The effects of solution pH, adsorbent dosage, initial norfloxacin concentration, and contact time on adsorption efficiency were systematically investigated using a 24 full factorial experimental design. Initial drug concentration was identified as the most significant factor, followed by contact time. Under optimized conditions, a removal efficiency of 92 ± 0.41% was achieved for 25 µg mL− 1 norfloxacin within 2 h at pH 5. Adsorption kinetics and isotherm models were subsequently evaluated to elucidate the adsorption behavior. The adsorbent exhibited a maximum adsorption capacity of 136.99 mg g− 1. The reusability of these nanoparticles has been investigated for six treatment cycles, demonstrating the efficacy of the adsorbent after several uses. Furthermore, the applicability of the developed method was validated by screening and analyzing real water samples, including Nile River and tap water. The greenness and whiteness levels of the proposed method were assessed using Complex GAPI, AGREE, BAGI, and WAC tools. These findings demonstrate the potential of converting agricultural waste into a reusable adsorbent for facile and cost-effective treatment of antibiotic-contaminated water.
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    MTA-NPs induce preferential cytotoxicity, oxidative DNA damage, and mitochondrial apoptosis in human Hep-G2 hepatocellular carcinoma cells
    (Springer Science and Business Media Deutschland GmbH, 2026-06-22) Hanan R H Mohamed; Sara A Diab; Jana W Mofadal; Yasmine W Hamdy; Bassema E Elnewihy; Bassant Haitham; Basma M I El-Sherif; Ayman Diab; Gehan Safwat
    Hepatocellular carcinoma is one of the most aggressive and fatal malignancies worldwide, and the limited efficacy and severe toxic side effects of conventional chemotherapy emphasize the urgent need for safer and more effective therapeutic strategies. Nanotherapies have recently gained considerable attention due to their enhanced cellular uptake, improved bioavailability, and selective targeting of malignant cells. Although mineral trioxide aggregate nanoparticles (MTA-NPs) possess unique physicochemical and biological properties, their anticancer potential against hepatocellular carcinoma has not been fully explored. Accordingly, this study evaluated the cytotoxic activity and underlying molecular mechanisms of MTA-NPs in human hepatocellular carcinoma Hep-G2 cells, while simultaneously assessing their safety profile in normal human HFB4 melanocytes. The MTT assay results demonstrated that MTA-NPs exerted potent and selective cytotoxicity against Hep-G2 hepatocellular carcinoma cells, as demonstrated by a significant concentration-dependent decline in cancer cell viability and a markedly low IC50 value of 52.53 μg/ml. Conversely, exposure of normal HFB4 melanocytes to the same MTA-NPs concentrations resulted in only slight reductions in cell viability, primarily at the highest tested concentrations, with a substantially higher IC50 value of 239.30 μg/ml. These findings indicate the preferential anticancer activity of MTA-NPs toward Hep-G2 cells. Moreover, the calculated selectivity index of 4.55 further confirmed the selective cytotoxic potential of MTA-NPs against hepatocellular carcinoma Hep-G2 cells. Furthermore, exposure of Hep-G2 cancer cells to the IC50 concentration of MTA-NPs resulted in marked intracellular ROS overproduction, profound mitochondrial membrane depolarization, and severe genomic DNA damage, which collectively culminated in apoptotic cell death. qRT-PCR analysis further demonstrated significant downregulation of both the apoptotic p53 and mitochondrial ND3 gene expression levels, together with pronounced upregulation of the anti-apoptotic Bcl-2 gene. Collectively, these molecular alterations indicate the activation of a p53-independent mitochondria-mediated apoptotic pathway. In conclusion, MTA-NPs demonstrate potent and preferential anticancer activity against human hepatocellular carcinoma Hep-G2 cells by inducing ROS-mediated oxidative stress, genomic DNA instability, mitochondrial dysfunction, and p53-independent mitochondrial apoptosis. These findings highlight the promising therapeutic potential of MTA-NPs as a novel nanotherapeutic approach for hepatocellular carcinoma treatment. Nevertheless, additional in vitro and in vivo studies and comprehensive biosafety evaluations are still necessary prior to clinical application.
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    An innovative approach for predicting default risk in peer-to-peer lending using stacking ensemble models with explainable machine learning
    (Springer London, 2026-06-16) Markus Atef; Menna Ibrahim Gabr; Wafaa Seoud; Shimaa Ouf
    Peer-to-peer (P2P) lending has increased significantly during the past few years on a global scale. However, there are several challenges associated with P2P lending’s rapid rise. The major challenges are imbalanced datasets, which make machine learning difficult, an excessive number of features, and low-performing classification algorithms. Furthermore, machine learning models face another complex challenge referred to as the black-box problem. To address these challenges, an innovative approach was developed by first applying Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance in the Bondora dataset, followed by the implementation of multiple feature selection techniques: Chi-Square (filter), Sequential Backward Selection (SBS) (wrapper), and embedded methods such as Random Forest (RF), Gradient Boosting Machine (GBM), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost). A range of classifiers, linear (Logistic Regression (LR)), non-linear (Support Vector Machine (SVM), Naive Bayes (NB), and tree-based models (Decision Tree (DT), RF, Adaptive Boosting (AdaBoost), CatBoost), were then used to predict loan defaults. The top-performing models were integrated into various stacking ensembles using GBM, Extreme Gradient Boosting (XGBoost), and LightGBM as meta-learners to enhance predictive accuracy. The results declared that LightGBM exhibited an outstanding performance with accuracy, F-score, and Area Under the Curve (AUC) values of 0.981, 0.980, and 0.994, respectively, showing better performance than that reported in the literature. Explainable models were employed to interpret predictions and enhance user trust. Specifically, the LightGBM stacking model was combined with the Local Interpretable Model-agnostic Explanations (LIME) framework to provide interpretable insights into its prediction results.