Background: Hepatocellular carcinoma (HCC) is a prevalent and lethal form of liver cancer with limited treatment options. Silymarin, a flavonoid complex derived from milk thistle, has shown promise in liver disease treatment due to its antioxidant, anti-inflammatory, and anticancer properties. This study aims to explore the therapeutic potential of silymarin in HCC through a comprehensive in silico approach. Methods: This study employed a network pharmacology approach to identify key molecular targets of silymarin in HCC. The Genecards and Metascape databases were used for target identification and functional annotation. Molecular docking analysis was conducted on the primary silymarin components against VEGFA and SRC proteins, which are critical in HCC progression. MD simulations followed to assess the stability and interactions of the docked complexes. Results: Network pharmacology analysis identified several key molecular targets and pathways implicated in HCC. The molecular docking results revealed strong binding affinities of silymarin components to VEGFA and SRC, with Silybin A and Isosilybin B showing the highest affinities. MD simulations confirmed the stability of these interactions, indicating potential inhibitory effects on HCC progression. Conclusions: This study provides a comprehensive in silico evaluation of silymarin’s therapeutic potential in HCC. The findings suggest that silymarin, particularly its components Silybin A and Isosilybin B, may effectively target VEGFA and SRC proteins, offering a promising avenue for HCC treatment. Further experimental validation is warranted to confirm these findings and facilitate the development of silymarin-based therapeutics for HCC.

Background/Objectives: Silybum marianum extract, obtained via microwave-enhanced extraction, was evaluated for its antioxidant, antidiabetic, and antimicrobial activities to explore its therapeutic potential. Methods: The extraction was performed using microwave-enhanced techniques, and LC-MS/MS was employed to profile the metabolites in the extract. Total phenolic and flavonoid contents were quantified using spectrophotometric methods. Antioxidant activity was assessed using DPPH, ABTS, CUPRAC, Phenanthroline, and FRAP assays. Enzyme inhibition assays were conducted to evaluate antidiabetic activity against α-glucosidase and α-amylase. Antimicrobial activity was determined using the disc diffusion method, and in silico ADMET and drug-likeness analyses were performed for key metabolites. Results: The extract contained 251.2 ± 1.2 mg GAE/g of total phenolics and 125.1 ± 1.6 mg QE/g of total flavonoids, with 33 metabolites identified, including phenolic acids, tannins, flavonoids, and flavolignans. Strong antioxidant activity was observed, with IC50 values of 19.2 ± 2.3 μg/mL (DPPH), 7.2 ± 1.7 μg/mL (ABTS), 22.2 ± 1.2 μg/mL (CUPRAC), 35.2 ± 1.8 μg/mL (Phenanthroline), and 24.1 ± 1.2 μg/mL (FRAP). Antidiabetic effects were significant, with IC50 values of 18.1 ± 1.7 μg/mL (α-glucosidase) and 26.5 ± 1.3 μg/mL (α-amylase). Antimicrobial activity demonstrated inhibition zones of 8.9 ± 1.1 mm (Bacillus subtilis), 12.6 ± 1.6 mm (Escherichia coli), 8.2 ± 1.2 mm (Fusarium oxysporum), and 9.2 ± 1.1 mm (Aspergillus niger). In silico analyses showed high absorption, favorable metabolism and excretion, and minimal toxicity, with no hERG channel inhibition or hepatotoxicity. Conclusions: The comprehensive results highlight the significant antioxidant, antidiabetic, and antimicrobial activities of S. marianum extract, suggesting its potential for therapeutic and preventive applications.

This study examines the chemical composition, antioxidant properties, and urease inhibitory effects of Hyoscyamus muticus L. subsp. falezlez (Coss.) Maire. Using LC-ESI-MS/MS, 19 distinct phenolic compounds were identified, with chlorogenic acid being the most abundant. The ethanol extract demonstrated notable antioxidant activity, highlighting its potential for therapeutic use. Urease inhibition assays revealed a remarkable 91.35% inhibition by the H. muticus extract, with an IC50 value of 5.6 ± 1.20 μg/mL, indicating its promising role in addressing conditions linked to urease activity. Molecular docking studies further investigated the interaction between H. muticus phenolic compounds and urease, identifying hyperoside as a leading candidate, with a binding energy of −7.9 kcal/mol. Other compounds, such as rutin, luteolin, apigenin, kaempferol, hesperetin, chlorogenic acid, and rosmarinic acid, also demonstrated significant binding affinities, suggesting their potential to disrupt urease function. These findings highlight the therapeutic potential of H. muticus as a source of natural bioactive compounds, offering promising avenues for the development of novel treatments for urease-related disorders and oxidative stress.

In this study, we thoroughly investigated the stability of haloperidol using a comprehensive set of chromatographic and thermal analyses. Various stress conditions were examined, including exposure to oxidizing agents (such as hydrogen peroxide), dry heat, photolytic conditions, and acid and alkaline hydrolysis. Significant degradation was observed in acidic and alkaline environments, leading to the formation of degradation by-products, specifically DPA, DPB, DPC, and DPD for acidic and basic conditions. In contrast, haloperidol demonstrated robust stability under photolytic, oxidative, and dry-heat conditions. For the analysis of the drug and its degradation products, a C-18 column was employed, coupled with a mobile phase consisting of methanol and a phosphate buffer (pH = 9.8) in a 90:10 (v/v) ratio. The analytical method was rigorously validated according to ICH Q2 (R1) guidelines, ensuring its accuracy and reliability. This method exhibited excellent linearity within a concentration range of 1 to 50 µg/mL, with an R2 of 0.999. Additionally, this method is applicable to commercial formulations, without the need for prior extraction. LC-MS/MS analysis revealed distinct m/z values and fragmentation spectra corresponding to the degradation products, including an impurity not documented in the European Pharmacopoeia monograph for the drug. Three additional degradation products were identified based on m/z values and base fragments. Thermal analyses, including thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), and differential thermal analysis (DTA), provided further evidence of the active ingredient’s thermal stability, with a melting temperature of approximately 150 °C. These results collectively offer valuable insights into the degradation behavior of haloperidol, providing critical implications for its pharmaceutical quality and integrity under various environmental conditions.

The target molecule of this study is haloperidol, a neuroleptic from the butyrophenone family. It is one of the most widely used psychotropic drugs globally and is considered as effective as other low-potency psychotropic medications. The RP-HPLC method employed in this study utilizes a novel mobile phase composed of a 90:10 mixture of methanol and phosphate buffer (pH = 9.8) for isocratic elution. This method has been validated with a correlation coefficient (R) of 0.999 across a concentration range of 2.5 to 50 µg/mL. It exhibits excellent sensitivity, with a relative standard deviation (RSD) of less than 2% for both precision and accuracy. The method is highly effective for the analysis of haloperidol in oral commercial formulations. The mobile phase is cost-efficient, environmentally friendly, and simple to use, making it suitable for analyzing haloperidol in both liquid and powder forms. Additionally, the method is applied to monitor haloperidol degradation under various stress conditions. For powder samples, the maximum degradation observed was 6.20% after 48 h of sunlight exposure. For liquid haloperidol samples, stability was retained only under oxidative stress conditions, with the highest degradation (57.36%) occurring after 48 h of sunlight exposure and the lowest degradation (10.03%) observed under thermal stress at 60 °C over seven days.

Olive mill wastewater (OMW) is a significant environmental pollutant due to its high organic load and toxicity, necessitating effective treatment methods. This study evaluates the impact of treating OMW through infiltration-percolation on the germination of cereal seeds, specifically durum wheat (Triticum durum Desf.) and barley (Hordeum vulgare L.). The treatment involved using sand filters combined with lime and eucalyptus sawdust. Key physicochemical parameters, including pH, electrical conductivity (EC), biological oxygen demand (BOD₅), mineral matter (MM), organic matter (OM), and total organic carbon (TOC), were analyzed for both untreated OMW and the filtrates produced by the treatment. The results showed that the use of lime, alone or with eucalyptus sawdust, in the filtration process significantly increased the pH and EC, while leading to a highly significant reduction in BOD5, MM, OM, and TOC. Germination tests indicated that the highest germination rates, 80

This study investigates the degradation kinetics of polycyclic aromatic hydrocarbons (PAHs) in contaminated soil using hydrogen peroxide (H2O2) and the Fenton process (H2O2/Fe2+). The effect of oxidant concentration and the Fenton molar ratio on PAH decomposition efficiency is examined. Results reveal that increasing H2O2 concentration above 25 mmol/samples leads to a slight increase in the rate constants for both first- and second-order reactions. The Fenton process demonstrates higher efficiency in PAH degradation compared to H2O2 alone, achieving decomposition yields ranging from 84.7% to 99.9%. pH evolution during the oxidation process influences PAH degradation, with alkaline conditions favoring lower elimination rates. Fourier-transform infrared (FTIR) spectroscopy analysis indicates significant elimination of PAHs after treatment, with both oxidants showing comparable efficacy in complete hydrocarbon degradation. The mechanisms of PAH degradation by H2O2 and the Fenton process involve hydroxyl radical formation, with the latter exhibiting greater efficiency due to Fe2+ catalysis. Gaussian process regression (GPR) modeling accurately predicts reduced concentration, with optimized ARD-Exponential kernel function demonstrating superior performance. The Improved Grey Wolf Optimizer algorithm facilitates optimization of reaction conditions, yielding a high degree of agreement between experimental and predicted values. A MATLAB 2022b interface is developed for efficient optimization and prediction of C/C0, a critical parameter in PAH degradation studies. This integrated approach offers insights into optimizing the efficiency of oxidant-based PAH remediation techniques, with potential applications in contaminated soil remediation.

The search results offer comprehensive insights into the phenolic compounds, antioxidant, anti-inflammatory, cytotoxic effects, LC-MS/MS analysis, molecular docking, and MD simulation of the identified phenolic compounds in the Astragalus arpilobus subsp. hauarensis extract (AAH). The analysis revealed substantial levels of total phenolic content (TPC), with a measured value of 191 ± 0.03 mg GAE/g DM. This high TPC was primarily attributed to two key phenolic compounds: total flavonoid content (TFC) and total tannin content (TTC), quantified at 80.82 ± 0.02 mg QE/g DM and 51.91 ± 0.01 mg CE/g DM, respectively. LC-MS/MS analysis identified 28 phenolic compounds, with gallic acid, protocatechuic acid, catechin, and others. In the DPPH scavenging assay, the IC50 value for the extract was determined to be 19.44 ± 0.04 μg/mL, comparable to standard antioxidants like BHA, BHT, ascorbic acid, and α-tocopherol. Regarding anti-inflammatory activity, the extract demonstrated a notably lower IC50 value compared to both diclofenac and ketoprofen, with values of 35.73 µg/mL, 63.78 µg/mL, and 164.79 µg/mL, respectively. Cytotoxicity analysis revealed significant cytotoxicity of the A. arpilobus extract, with an LC50 value of 28.84 µg/mL, which exceeded that of potassium dichromate (15.73 µg/mL), indicating its potential as a safer alternative for various applications. Molecular docking studies have highlighted chrysin as a promising COX-2 inhibitor, with favorable binding energies and interactions. Molecular dynamic simulations further support chrysin’s potential, showing stable interactions with COX-2, comparable to the reference ligand S58. Overall, the study underscores the pharmacological potential of A. arpilobus extract, particularly chrysin, as a source of bioactive compounds with antioxidant and anti-inflammatory properties. Further research is warranted to elucidate the therapeutic mechanisms and clinical implications of these natural compounds.

Phytolacca americana L. is of great interest as a traditional additive in various folk remedies in several countries, including Turkey. We aimed to determine the chemical profile (assisted by high-Performance liquid chromatography-electrospray ionization-tandem mass apectrometry (HPLC-ESI-MS/MS) experiments of three extracts obtained by different polarity solvents viz. ethyl acetate (to extract semipolar compounds), methanol and water (to extract highly polar metabolites) from P. americana leaves. Their anti-diabetic effects were investigated in vitro by assessing their inhibition to alpha-amylase and alpha-glucosidase. Assessment of the neuroprotective potential of the three extracts was carried out against acetyl-(AChE) and butyryl-(BChE) cholinesterase enzymes. HPLC-ESI-MS/MS experiments showed a total of 17 chromatographic peaks primarily classified to six flavonoids, two saponins, and six fatty acids. Antioxidant assays revealed remarkable activity for the ethyl acetate and methanol extracts. The BChE inhibition was considerably more significant (4.08 mg galantamine equivalent (GALAE)/g) for the ethyl acetate extract, whereas the methanol extract had good inhibitory efficacy for AChE (2.05 mg GALAE/g). Through network pharmacology, the compounds' mechanism of action of targeted key gene in their associated diseases were identified. The hubb gene signal transducer and activator of transcription 3 (STAT3) and tumour necrosis factor (TNF alpha) where the P. americana compound's site of action in inflammation bowel disease. The results offer possibilities for the prospective application of P. americana in metabolic regulation, blood glucose control, and as a source of bioactive compounds with cholinesterase enzyme inhibitory characteristics which could be of relevance in the cosmetic or pharmaceutical industry for combating melanogenesis.

The prediction of ultrasound-assisted extraction (UAE) for total phenolic content (TPC) and total flavonoid content (TFC) from Carthamus caeruleus L. rhizomes was conducted using a Gaussian process regression model (GPR) with a multi-objective Grey Wolf optimization approach (MOGWO). A central composite design (CCD) was employed first, examining ethanol concentration, temperature, time, and solvent-to-solid ratio as independent variables. TPC and TFC responses were analyzed under various conditions, revealing significant quadratic and interaction effects (p < 0.05). The GPR was then utilized to predict TPC and TFC, showing high accuracy with correlation coefficients near 1 and minimal root mean square error (RMSE) values. To simultaneously maximize TPC and TFC, the MOGWO was used in a multi-objective framework. Validation through CCD and GPR highlighted GPR's superior predictive accuracy. Optimal conditions (10 % ethanol, 40 degrees C, 20 minutes sonication, and 50 mL g(-1) solvent to solid ratio) showed significant discrepancies in CCD predictions but high accuracy in GPR predictions. An interactive tool predicts TPC and TFC using CCD and GPR models. Users input extraction parameters and receive predictions, with a GWO-based optimization module for optimal conditions. The interface enables model comparison, improves process understanding, and optimizes bioactive compound extraction.

This study presents an innovative approach utilizing artificial intelligence (AI) for the prediction and classification of water quality parameters based on physico-chemical measurements. The primary objective was to enhance the accuracy, speed, and accessibility of water quality monitoring. Data collected from various water samples in Algeria were analyzed to determine key parameters such as conductivity, turbidity, pH, and total dissolved solids (TDS). These measurements were integrated into deep neural networks (DNNs) to predict indices such as the sodium adsorption ratio (SAR), magnesium hazard (MH), sodium percentage (SP), Kelley’s ratio (KR), potential salinity (PS), exchangeable sodium percentage (ESP), as well as Water Quality Index (WQI) and Irrigation Water Quality Index (IWQI). The DNNs model, optimized through the selection of various activation functions and hidden layers, demonstrated high precision, with a correlation coefficient (R) of 0.9994 and a low root mean square error (RMSE) of 0.0020. This AI-driven methodology significantly reduces the reliance on traditional laboratory analyses, offering real-time water quality assessments that are adaptable to local conditions and environmentally sustainable. This approach provides a practical solution for water resource managers, particularly in resource-limited regions, to efficiently monitor water quality and make informed decisions for public health and agricultural applications.

This study investigated the effects of genetic diversity in the allergenicity of peanut and assessed the allergenic capacity of six Arachis hypogaea accessions using a Balb/c mouse model. It also explored potential cross-reactivities between Ara h 3 (peanut allergen) and Gly m (soybean allergen) using computational tools. Female Balb/c mice were injected with peanut protein extracts and alum. Serum-specific antibodies (IgE, IgGt, IgG1, IgG2a) were measured using ELISA, and allergic protein profiles were examined via western blot. Structural homology, B cell epitopes, and molecular interactions between Ara h 3 and Gly m with human IgE were also investigated. The mice developed high sIgE and sIgG1 responses, with antibodies recognizing 19 bands on western blot. Notably, Saharan accessions showed unique features such as no bands on western blot profiles, reduced anaphylactic symptoms, lower IgE titers, and less intestinal tissue damage. Molecular docking results suggest significant cross-allergenicity, supported by allergenicity predictions and structural homology analysis. This comprehensive analysis provides insights into shared epitopes, potential competition for binding sites, and molecular dynamics of cross-reactive responses, enhancing understanding of food allergen interactions. The study recommends using Algerian Sahara peanut accessions in breeding, genomics studies, and industry for safer peanut options for individuals with allergies. Significance The significance of this study lies in its contribution to addressing a major public health issue: peanut allergy, which represents a significant cause of anaphylaxis affecting numerous individuals and families worldwide. By exploring the genetic diversity of peanut proteins and identifying hypoallergenic accessions through experimental and computational approaches, this research offers valuable insights for mitigating allergic reactions. The findings highlight that certain accessions from the Saharan region exhibit reduced allergenicity, resulting in attenuated anaphylactic symptoms, lower IgE levels, and reduced intestinal damage in murine models. Furthermore, the study's in silico analysis sheds light on the issue of cross-reactivity between peanut and soybean allergens, providing crucial information for understanding allergen interactions at the molecular level. Overall, this research contributes to advancing knowledge in the field of food allergen research and has practical implications for improving the quality of life for individuals allergic to peanuts, particularly through the selection of safer peanut varieties and their cultivation.

Ovarian cancer poses a significant challenge to women's health, necessitating innovative therapeutic approaches. This study investigates the therapeutic potential of compounds derived from Hyoscyamus niger, a medicinal plant with a history of traditional use, focusing on their antioxidant properties and their ability to inhibit epidermal growth factor-receptor (EGFR) tyrosine kinase a promising target in cancer therapy. LC-ESI-MS/MS analysis of H. niger extract revealed the presence of 21 phenolic compounds, with luteolin and p-coumaric acid notably exhibiting the highest concentrations. The extract displayed robust antioxidant activity across multiple assays, and its performance in the Reducing Power assay highlights its potential in reducing oxidative stress. Molecular docking results indicate that several phenolic compounds may serve as EGFR inhibitors, offering promising avenues for further investigation in cancer therapy. Notably, hyperoside emerged as a strong candidate due to its favorable binding energy and interactions within the EGFR active site. This study demonstrates the therapeutic promise of H. niger-derived compounds in targeting ovarian cancer through antioxidant activity and EGFR inhibition. Further research is warranted to validate their efficacy and safety, potentially opening up new avenues for ovarian cancer treatment.

Background: Optimal glycemic control is crucial in type 2 diabetes treatment, with αglucosidase inhibitors emerging as promising candidates. Avenanthramides, compounds found in oats, exhibit therapeutic potential, but their efficacy as α-glucosidase inhibitors requires thorough evaluation. Objective: This study investigates the potential of avenanthramides and their derivatives as inhibitors of α-glucosidase for the treatment of type 2 diabetes through comprehensive computational analysis. Methods: Structure-Based Virtual Screening of 3543 avenanthramides and their analog compounds was conducted using FlexX. The top 30 ranked compounds were subjected to visual inspection of their binding mode within the α-glucosidase binding site to eliminate false positives. The top-ranked molecule was subjected to dynamic simulation and ADMET prediction. Results: The results revealed that 1634 compounds were found to exhibit a greater α-glucosidase inhibitory potency than miglitol, the reference molecule. Compound S1 exhibited superior αglucosidase inhibitory potency with a binding energy of -45.7786 kJ/mol compared to miglitol, which had a binding energy of -26.5186 kJ/mol. S1 was predicted to occupy the entire binding site with an optimized number of hydrogen bonds and hydrophobic interactions. Molecular dynamics simulations demonstrated that S1 had a lower average RMSD (0.15 ± 0.01 nm) compared to miglitol (0.16 ± 0.01 nm), indicating superior stability within the α-glucosidase binding site. S1 exhibited favorable drug-like properties, suggesting its potential as a lead compound for further development in type 2 diabetes treatment. Conclusion: These findings highlight S1's potential for diabetes treatment and pave the way for future experimental investigations. The computational approach utilized offers valuable insights into the inhibitory potential of avenanthramides, providing a foundation for further drug development for type 2 diabetes.

The green synthesis of silver nanoparticles (AgNPs) using plant extracts is an eco-friendly method with potential for biomedical and environmental applications. This study aims to synthesize silver nanoparticles (SO-AgNPs) using Salvia officinalis L. extract and evaluate their antioxidant and antibacterial properties, positioning them as candidates for applications in sustainable biomedicine and wastewater treatment. S. officinalis L. extract was used to synthesize AgNPs under optimized conditions, with a 10% extract/AgNO₃ ratio and a reaction time of 180 min. The SO-AgNPs were characterized using ATR-FTIR, XRD, SEM, DLS, and Zeta potential analysis. The antioxidant activity of the extract and SO-AgNPs was evaluated using ABTS+• and DPPH• radical scavenging assays. Antibacterial activity was tested against 11 bacterial strains and bacteria isolated from industrial effluent, with minimal inhibitory concentrations (MIC) determined for both the extract and SO-AgNPs. The SO-AgNPs demonstrated potent antioxidant activity, with IC₅₀ values of 0.233 mg/mL and 0.305 mg/mL in the ABTS+• assay, and 0.173 mg/mL and 0.185 mg/mL in the DPPH• assay for the extract and SO-AgNPs, respectively. Antibacterial testing showed MIC values of 0.25 mg/mL for SO-AgNPs and between 3.12 and 6.25 mg/mL for S. officinalis L. extract against E. coli, P. aeruginosa, A. baumannii, MRSA, B. cereus, and S. epidermidis. For bacteria isolated from industrial effluent, the MIC values were 0.125 mg/mL for SO-AgNPs and 0.5 mg/mL for the extract. This study highlights the dual antioxidant and antibacterial capabilities of S. officinalis L. extract and SO-AgNPs, demonstrating their potential for use in both biomedical and environmental applications, including wastewater treatment.

Investigations into cholinesterase inhibition have received attention from researchers in recent years for the treatment of Alzheimer’s disease. Cholinesterase enzymes, namely, acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), hold pivotal significance in Alzheimer’s disease (AD) treatment. In this study, we utilized the ethanolic extract of Astragalus crenatus followed by liquid chromatography–electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) to separate and identify at least 21 compounds in the extract. Rosmarinic acid exhibited the highest concentration (96.675 ± 1.3 mg/g extract), succeeded by hesperidin (79.613 ± 1.2 mg/g extract), hesperetin (75.102 ± 1.4 mg/g extract), rutin (68.156 ± 1.6 mg/g extract), chlorogenic acid (67.645 ± 1.5 mg/g extract), fisetin (66.647 ± 2.3 mg/g extract), and hyperoside (63.173 ± 1.5 mg/g extract). A. crenatus extract efficiently inhibited both AChE and BChE activities in a dosage-dependent manner. Molecular docking was employed to scrutinize the anticholinesterase mechanisms of the identified phytocompounds. Notably, a network pharmacology analysis was executed for the most efficacious compound. Based on binding energies, hesperidin emerged as the most potent inhibitor against both AChE and BChE, exhibiting scores of −10.5 Kcal/mol and −9.8 Kcal/mol, respectively. Due to its dual inhibition of AChE and BChE activities, hesperidin from Astragalus crenatus holds promise for the development of novel therapeutics aimed at neurological disorders, particularly AD.

An asymmetric synthesis is a favorable approach for obtaining enantiomerically pure substances, but racemic resolution remains an efficient strategy. This study aims to elucidate the chiral resolution of aromatic amino acids and their elution order using glycopeptides as chiral selectors through molecular docking analysis. Chiral separation experiments were conducted using Vancomycin as a chiral additive in the mobile phase (CMPA) at various concentrations, coupled with an achiral amino column as the stationary phase. The Autodock Vina 1.1.2 software was employed to perform molecular docking simulations between each enantiomer (ligand) and Vancomycin (receptor) to evaluate binding affinities, demonstrate enantiomeric resolution feasibility, and elucidate chiral recognition mechanisms. Utilizing Vancomycin as CMPA at a concentration of 1.5 mM enabled the separation of tryptophan enantiomers with a resolution of 3.98 and tyrosine enantiomers with a resolution of 2.97. However, a poor chiral resolution was observed for phenylalanine and phenylglycine. Molecular docking analysis was employed to elucidate the lack of separation and elution order for tryptophan and tyrosine enantiomers. By calculating the binding energy, docking results were found to be in good agreement with experimental findings, providing insights into the underlying mechanisms governing chiral recognition in this system and the interaction sites. This comprehensive approach clarifies the complex relationship between chiral discrimination and molecular architecture, offering valuable information for creating and improving chiral separation protocols.

Vacuum membrane distillation (VMD) is a compelling technique for desalinating water because it exhibits superior pure water permeability at lower operating temperatures compared to other membrane distillation technologies. This leads to reduced energy consumption, lower heat loss via conduction across the membrane surface, and minimal heat transfer through conduction due to the low pressure on the permeate side. Detailed modelling of heat and mass transfer in VMD is essential for optimizing the process as it provides valuable insights that contribute to the advancement and successful implementation of seawater desalination using VMD technology. The aim of this study is to establish a comprehensive numerical model that describes the water vapor transfer across a hydrophobic micro-porous membrane in single-stage and multi-stage VMD processes for seawater desalination. The numerical predictions were compared to experimental data in addition to numerical computations based on an existing literature database, and good agreement has been found. The investigation also conducted a sensitivity analysis of process variables and membrane specifications on the VMD performance, as well as an assessment of the impact of temperature and concentration polarization. The obtained results showed that the permeation flux reached 18.42 kg/m2·h at 35 g/L feed concentration, 65 °C feed temperature, 50 L/h feed flow rate, and 3 kPa vacuum pressure. Moreover, the findings revealed that the feed temperature was the most significant factor, while the feed flow rate was the least important in determining the permeation flux. Additionally, the findings suggested that the effectiveness of the VMD process heavily relies on the composition and permeability of the support materials. Finally, the results confirmed that temperature polarization had a more significant effect on the reduction of the permeate flux than the concentration polarization.

This study aimed to investigate the chemical composition and antidiabetic properties of cultivated Hyoscyamus albus L. The ethanol extract was analyzed using LC-MS/MS, and 18 distinct phenolic compounds were identified. Among these, p-coumaric acid (6656.8 ± 3.4 µg/g), gallic acid (6516 ± 1.7 µg/g), luteolin (6251.9 ± 1.3 µg/g), apigenin (6209.9 ± 1.1 µg/g), and rutin (5213.9 ± 1.3 µg/g) were identified as the most abundant polyphenolic molecules. In the in vitro antidiabetic experiment, the ability of the plant extract to inhibit α-glucosidase and α-amylase activities was examined. The results indicated that the extract from H. albus L. exhibited a higher inhibitory effect on α-amylase compared to α-glucosidase, with an IC50 of 146.63 ± 1.1 µg/mL and 270.43 ± 1.1 µg/mL, respectively. Docking simulations revealed that luteolin, fisetin, and rutin exhibited the most promising inhibitory activity against both enzymes, as indicated by their high contrasting inhibition scores. To further investigate the in vivo antidiabetic effects of H. albus L., an experiment was conducted using STZ-induced diabetic mice. The results demonstrated that the plant extract effectively reduced the levels of cholesterol and triglycerides. These findings suggest that H. albus L. may have therapeutic potential for managing hyperlipidemia, a common complication associated with diabetes. This highlights its potential as a natural remedy for diabetes and related conditions.