Biomedical
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Item Machine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials(Scientific Reports, 2025-01) Nazari, Simin; Abdelrasoul, AmiraMembrane incompatibility poses significant health risks, including severe complications and potential fatality. Surface modification of membranes has emerged as a pivotal technology in the membrane industry, aiming to improve the hemocompatibility and performance of dialysis membranes by mitigating undesired membrane-protein interactions, which can lead to fouling and subsequent protein adsorption. Affinity energy, defined as the strength of interaction between membranes and human serum proteins, plays a crucial role in assessing membrane-protein interactions. These interactions may trigger adverse reactions, potentially harmful to patients. Researchers often rely on trial-and-error approaches to enhance membrane hemocompatibility by reducing these interactions. This study focuses on developing machine learning algorithms that accurately and rapidly predict affinity energy between novel chemical structures of membrane materials and human serum proteins, based on a molecular docking dataset. Various membrane materials with distinct characteristics, chemistry, and orientation are considered in conjunction with different proteins. A comparative analysis of linear regression, K-nearest neighbors regression, decision tree regression, random forest regression, XGBoost regression, lasso regression, and support vector regression is conducted to predict affinity energy. The dataset, comprising 916 records for both training and test segments, incorporates 12 parameters extracted from data points and involves six different proteins. Results indicate that random forest (R² = 0.8987, MSE = 0.36, MAE = 0.45) and XGBoost (R² = 0.83, MSE = 0.49, MAE = 0.49) exhibit comparable predictive performance on the training dataset. However, random forest outperforms XGBoost on the testing dataset. Seven machine learning algorithms for predicting affinity energy are analyzed and compared, with random forest demonstrating superior predictive accuracy. The application of machine learning in predicting affinity energy holds significant promise for researchers and professionals in hemodialysis. These models, by enabling early interventions in hemodialysis membranes, could enhance patient safety and optimize the care of hemodialysis patients.Item Ethnobotanical survey of medicinal plants used in north-central Morocco as natural analgesic and anti-inflammatory agents(Elsevier, 2024-06-05) LEFRIOUI, Youssra; CHEBAIBI, Mohamed; djiddi bichara, mehdi; MSSILLOU, Ibrahim; BEKKARI, hicham; Giesy, John; BOUSTA, dalilaFor centuries, the Moroccan population has relied on herbs as medicine to treat a variety of diseases, especially inflammation and pain-related ones. To the best of our knowledge, no survey had ever been conducted to address this subject in the Fez-Meknes region of Morocco. Thus, a survey was conducted of 544 interviewees, using a semi-structured ethnopharmacological survey designed with “Why-How” questions about plants used, their vernacular names, parts used, mode of preparation, and mode of administration. Fidelity level (FL), relative frequency of citation (RFC), frequency of citation (FC), informant consensus factor (ICF), and family importance value (FIV) were calculated. A total of 104 plant species belonging to 49 families used for inflammatory and pain treatment were documented. Lamiaceae (16 species) was the most used family and Curcuma longa L. (RFC=0.069) was the most frequently prescribed by local traditional healers and herbalists. Leaves were the most used part for herbal remedies, appearing in 30.8 % of preparations. Decoctions and infusions were the most popular preparation methods with percentages of 38.3 % and 19.2 %, respectively. Inflammations and pain in the digestive system had the largest widespread affections (IFC= 0.729) in the Fez-Meknes region. The findings of this study uncovered a reliable and original source of ethnomedicinal data pertaining to plants used to treat inflammation and inflammatory pain in the Fez-Meknes region, which could serve as a credible source of knowledge to determine new-based phytomedicines.Item In vivo and in silico studies of the effects of oil extracted from Cannabis sativa L. seeds on healing of burned skin wounds in rats(Frontiers, 2024-06-11) Saoudi, Mouna; CHEBAIBI, Mohamed; AMRATI, fatima ez-zahra; Souirti, Zouhayr; SAGHROUCHNI, Hamza; EL ATKI, Yassine; Bekkouche, khalid; Mourabiti, hajar; Amina, BARI; Giesy, John; Mohany, Mohamed; AL-REJAIE, SALIM; Aboul-Soud, Mourad; BOUSTA, dalilaIntroduction: This study investigates the potential effects of cannabis seed oil (CSO) on the wound healing process. The aim was to assess the efficacy of CSO in treating skin wounds using an animal model and to explore its anti-inflammatory properties through in silico analysis. Methods: Eighteen male albino Wistar rats, weighing between 200 and 250 g, were divided into three groups: an untreated negative control group, a group treated with the reference drug silver sulfadiazine (SSD) (0.01 g/mL), and a group treated topically with CSO (0.962 g/mL). The initial wound diameter for all groups was 1 cm. In silico studies were conducted using Maestro 11.5 to evaluate the anti-inflammatory effects of phytoconstituents against cyclooxygenase-1 (COX-1) and cyclooxygenase-2 (COX-2). Results: CSO and SSD treatments led to a significant reduction (p <0.05) in the size of burned skin wounds by day 5, with contraction rates of 53.95% and 45.94%, respectively, compared to the untreated negative control group. By day 15, wounds treated with CSO and SSD had nearly healed, showing contraction rates of 98.8% and 98.15%, respectively. By day 20, the wounds treated with CSO had fully healed (100%), while those treated with SSD had almost completely healed, with a contraction rate of 98.97%. Histological examination revealed granulated tissue, neo-blood vessels, fibroblasts, and collagen fibers in wounds treated with CSO. In silico studies identified arachidic acid, γ-linolenic acid, and linolenic acid as potent inhibitors of COX-1 and COX-2. Serum biochemical parameters indicated no significant changes (p > 0.05) in liver and kidney function in rats treated with CSO, whereas a significant increase (p < 0.01) in ALAT level was observed in rats treated with SSD. Discussion: The findings demonstrate that CSO has a promising effect on wound healing. The CSO treatment resulted in significant wound contraction and histological improvements, with no adverse effects on liver and kidney function.However, the study's limitations, including the small sample size and the need for detailed elucidation of CSO's mechanism of action, suggest that further research is necessary. Future studies should focus on exploring the molecular pathways and signaling processes involved in CSO’s pharmacological effects.Item Unveiling the Antianemic Activity, Physicochemical Aspects, Antioxidant Properties, and Mineral Profile of Petroselinum crispum L(ACS Publications, 2024-06-17) NOUIOURA , Ghizlane ; Fatima zahra , LAFDIL; Kandsi, Fahd; Mohammad Salamatullah, Ahmad; TIJI, Salima; SOULO, Najoua; Giesy, John; Aboul-Soud, Mourad; Lyoussi, Badiaa; derwich, elhoussineAnemia is a widespread global health concern necessitating effective, accessible, and natural interventions. The potential of medicinal plants to address anemia has garnered significant interest. Among these plants, parsley (Petroselinum crispum (Petroselinum crispum) L.) stands out as an edible and herbal-based option for combating anemia. Aim of the study: This study investigated the potential of P. crispum (PC-Ext) as an emerging antianemic product, focusing on its physicochemical attributes, antioxidant properties, and mineral profile. Both qualitative and quantitative analyses of the phenolic compounds in P. crispum were conducted by using high-performance liquid chromatography with a diode array detector (HPLC-DAD). Anemia was induced in rats by intravenous injections of phenylhydrazine, administered at a dose of 40 mg/kg for two consecutive days. The antianemic activity of PC-Ext was assessed at a dose of 500 mg/kg twice daily for 5 weeks by estimating blood parameters, such as serum iron and ferritin. Additionally, the osmotic fragility test measured the capacity of red blood cells to withstand osmotic shock of various concentrations of saline. Aqueous extract of P. crispum was rich in phytochemical compounds, including syringic acid, quercetin, catechin, gallic acid, and luteolin. The findings demonstrate the effectiveness of P. crispum in ameliorating phenylhydrazine-induced reductions in red blood cell count (RBCs), hemoglobin (Hb), and hematocrit (HCT) levels. Consequently, PC-Ext exhibits significant activity against phenylhydrazine-induced anemia in rats, as demonstrated by its ability to prevent hemolysis. Iron estimation within PC-Ext further confirms its utility in addressing both iron deficiency and ferritin-deficiency anemia. Therefore, PC exhibits a favorable effect against both types of anemia, iron deficiency, and hemolysis. The results of this study provide robust scientific validation for ethnomedicinal use and the potential utility of P. crispum, positioning it as a promising source for future pharmaceutical development.Item Antiviral Activities of Compounds Derived from Medicinal Plants against SARS-CoV-2 Based on Molecular Docking of Proteases(Fez Multidisciplinary, 2024-07-30) CHEBAIBI, Mohamed; MSSILLOU, Ibrahim; Aimad, Allali; bourhia, mohammed; Bousta, Dalila; Gonçalves, Rene; Hoummani, Hasnae; Aboul-Soud, Mourad; Augustyniak, Maria; Giesy, John; Achour, SanaeThis work aimed to evaluate the inhibitory effect of the main polyphenols and flavonoids of Syzygium aromaticum and Citrus limon as well as the main organosulfur compounds of Allium sativum against SARS-CoV-2 6LU7 and 6Y2E proteases using in silico molecular docking analysis. Structures of 34 natural products found in three medicinal plants were docked to these two critical proteins. For 6LU7 protease, 24 compounds exhibited binding affinities greater than or equal to -6 Kcal/mol. While, for 6Y2E protease, 6 compounds exhibited binding affinities greater than or equal to -6 Kcal/mol. Molecules with a maximum binding affinity equal to -8.4 kcal/mol show good hydrogen bonds with the two proteases under investigation, 6LU7 and 6Y2E. Diosmin, ellagic acid, narirutin, neoeriocitrin, and neohesperidin were suggested as inhibitors of SARS-COV-2. These compounds might be used therapeutically as complementary medicines and/or to conceptualize new drugs against COVID-19.Item Extrusion bioprinting from a fluid mechanics perspective(ACCSCIENCE, 2024-08-30) Gharraei, Reza; Bergstrom, Donald; Chen, Xiongbiao (Daniel)Bioprinting is an emerging technology for fabricating intricate and diverse structures that closely mimic natural tissues and organs for such applications as tissue engineering, drug delivery, and cancer research as well. Among the various bioprinting techniques, extrusion-based bioprinting stands out due to its capability to apply a wide range of biomaterials and living cells and its controllability over printed structures. In bioprinting, the bioink stored in a syringe is forced to flow through the nozzle connected to the syringe, and then to exit and deposit onto the printing stage to form three-dimensional (3D) structures. The bioprinting process involves the flow of bioink in both syringe and nozzle and then its flow or spreading on a printing stage. As a result, fluid mechanics plays a crucial role in extrusion bioprinting. Notably, the biomaterials used in bioprinting are typically non-Newtonian fluids, which have complex viscoelastic and thixotropic behaviors; and the influence of these behaviors on the bioprinting process has been drawn considerable attention by employing various methods, including the numerical simulations via computational fluid dynamics (CFD). This paper reviews the latest development in the fluid mechanics aspects of extrusion-based bioprinting to shed light on the challenges and key considerations involved. It covers the topics of extrusion bioprinting (including driving mechanisms, printability, cell viability), biomaterial rheology and its effect on bioprinting, multi-material bioprinting and numerical simulation of bioprinting. Key issues and challenges are also discussed along with the recommendations for future research.Item Printability of Alginate-Chitosan Biomaterials for Tissue Scaffolds(2024) Tabil, Xavier L.; Chen, Daniel X.; Cao, Tate N.