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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 toα-amylase and α-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 (TNFα) 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.Communicated by Ramaswamy H. Sarma.