Background: Coenzyme Q10 (CoQ10) is widely recognized for its powerful antioxidant properties, sparking considerable interest in its application within skincare treatments. However, its inherently poor water solubility has posed a major challenge in formulating effective skincare products. Methods: This research aimed to develop and evaluate a water‐soluble CoQ10 serum by forming a complex with hydroxypropyl β‐cyclodextrin (HPβCD). The study focused on assessing its physicochemical properties, CoQ10 concentration, spread ability, viscosity, pH, physical stability, irritation potential, and diffusion performance. The complexation process was carried out using kneading and trituration techniques, with thorough characterization via validated analytical methods such as solubility tests, Fourier transform infrared spectroscopy (FTIR), and differential scanning calorimetry (DSC) analyses. Results: The CoQ10–HPβCD complex prepared using the trituration technique at a 2:1 ratio (CoQ10 to HPβCD) demonstrated superior water solubility, reaching 17.5 ± 1.8 mg mL ⁻¹ , the highest among the tested formulations. Moreover, this formulation achieved the greatest encapsulation efficiency, retaining 71% ± 3.8% of CoQ10. FTIR and DSC analyses confirmed the successful formation of the complex. The formulated serum exhibited shear‐thinning behavior, an optimal pH of 4.3 ± 0.2 closely aligning with the skin's natural acidity for enhanced compatibility—along with excellent spreadability and stability. Diffusion tests revealed a significant enhancement in solubility when CoQ10 was complexed, effectively overcoming its solubility barrier. Irritation tests validated the serum's safety for topical use. Conclusion: This study successfully developed a CoQ10 serum that overcame its solubility limitation, demonstrating favorable properties for skincare application. With its strong physicochemical characteristics and biocompatibility, this formulation shows significant promise for broader incorporation into skincare products.

Quorum sensing (QS) is a molecular communication mechanism among bacterial cells. It is critical in regulating virulence factors, motility, antibiotic resistance, and biofilm formation. Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen linked to healthcare-associated infections, food poisoning, and biofilm formation. Treating infections caused by pathogenic bacteria has become a challenge due to the development of multi-antibiotic resistance upon continuous exposure of bacteria to antibiotics. An alternative strategy to conventional antimicrobials to decrease the bacterial pathogenicity is QS inhibition, also known as quorum quenching. Using plant-derived compounds is an environmentally friendly strategy to block the bacterial QS and inhibit bacterial growth. Portulaca oleracea is a popular plant in different countries and is also used in traditional medicine. It is widely consumed raw in salads and as garnishes, though it can be cooked as a vegetarian dish. This study evaluates the antimicrobial activity of the methanolic extract of P. oleracea and its effectiveness in blocking or attenuating the QS of P. aeruginosa. The agar well diffusion method used for screening the antibacterial activity showed a significant growth inhibition of P. aeruginosa by the extract at 500 mg/mL with a minimum inhibitory concentration of 31.25 mg/mL. A bioindicator bacterium, Chromobacterium violaceum CV026, was used to determine the effect of the methanolic extract on the QS of P. aeruginosa. The results indicated a significant reduction in biofilm formation, pyocyanin production, and LasA staphylolytic activity. The phytochemical analysis by Gas Chromatography–Mass Spectrometry showed that the methanolic extract contained several phenols, alkaloids, esters, and other compounds previously reported to have antibacterial and antioxidant effects. These findings highlight the effectiveness of P. oleracea methanolic extract in attenuating the QS and virulence factors of P. aeruginosa. This study suggests that P. oleracea is an important source of natural antimicrobials and its use would be beneficial in food and pharmaceutical applications.

This study aimed to develop and verify a simple HPLC-based quantitative approach to simultaneously determine the phosphodiesterase-5 inhibitors (PDE5Is) sildenafil, vardenafil, udenafil, avanafil, and tadalafil in a tablet dosage form mixed with honey obtained form Jordanian market in rat plasma. PDE5Is block phosphodiesterase-5 (PDE-5). This blockage, in turn, triggers vasodilation by phosphorylating downstream effector molecules. Chromatographic separation was performed on a Hypersil^TM C₁₈ column (150 mm × 4.6 mm, 5 µm, Thermo Fisher Inc., Waltham, MA, USA). An acetonitrile:10% Triethylamine solution (57:43) at pH 5.5 (adjusted with orthophosphoric acid), 20 µL injection volume, 1 mL/min flow rate, 25 °C temperature, and eluent monitoring at 250 nm was used to execute the current approach. Linearity was observed in the 9.6–14.4 µg/mL concentration ranges for sildenafil, udenafil, avanafil, and tadalafil, and 2.4–3.6 µg/mL for vardenafil. Each dosage form was recovered within acceptable limits at three distinct concentrations, and the assay selectivity indicated no interference from the inactive substances in the formulation. Sildenafil, vardenafil, udenafil, avanafil, and tadalafil had retention times of 3.5, 4.3, 6.2, 9.7, and 12.8 min, respectively, and tadalafil was 12.8 min. The present analytical method is comprehensive and universal for measuring the five drugs. Such an analytical method can be routinely used to detect the combination of these drugs.

Objective: This study aimed to develop a PEGylated liposomal formulation combining Metformin (MET) and Phenyl Butyric Acid (PBA) for colorectal cancer treatment. Current colorectal cancer therapies face limitations such as poor drug solubility, rapid clearance, and systemic toxicity. Combining MET and PBA in liposomes could potentially overcome these limitations by enhancing drug stability, prolonging circulation time, and improving targeted delivery. Methods: A High-Performance Liquid Chromatography (HPLC) method was optimized and validated for the simultaneous quantification of MET and PBA, achieving calibration curve R² values above 0.99. Liposomal formulations were prepared, and encapsulation efficiencies were evaluated. Sustained drug release was studied over 72 h at 37 °C. Cytotoxicity assays were conducted using colorectal cancer cell lines HCT116 and HT29. Additionally, colony formation assays assessed the formulation's long-term effects on cell proliferation. Results: The liposomal formulation showed encapsulation efficiencies of 48% for Lip-MET and 56.8% and 83.9% for Lip-MET-PBA. Sustained release profiles were observed, with 60% of MET and 55% of PBA released over 72 h. Cytotoxicity assays revealed that Lip-MET-PBA significantly reduced cell viability in HCT116 and HT29 cell lines, with IC50 values of 0.65 mmol and 0.82 mmol, respectively, compared to MET alone (1.1 mmol and 1.3 mmol). Colony formation assays demonstrated a concentration-dependent reduction in colony numbers, highlighting the enhanced anticancer efficacy of the combination. Statistical analysis showed significant differences (p<0.05) in cell viability and colony formation between the liposomal formulation and the free drugs. Conclusion: This is the first PEGylated liposomal formulation combining MET and PBA, offering a promising strategy for colorectal cancer therapy. The formulation combines sustained release, improved cytotoxicity, and a significant impact on colony formation, warranting further in vivo investigations.

The integration of machine learning (ML) into nanoscience has transformed the fabrication and characterization of silver nanoparticles (AgNPs), enabling precise control over particle size, shape, and functionalization. This review highlights the application of supervised and unsupervised ML models, such as artificial neural networks (ANNs), support vector machines (SVMs), and decision trees, in optimizing AgNP synthesis parameters, including temperature, pH, and reducing agent concentration. Emphasis is placed on green synthesis methods using plant extracts, where ML predicts eco-friendly conditions with minimal experimental input. Characterization techniques benefit from ML-driven image and spectral data analysis, enhancing speed and accuracy. ML is also pivotal in predicting the toxicity and biocompatibility of AgNPs, reducing reliance on animal testing and enabling safer biomedical applications. ML reduced synthesis optimization time by 30%," and to specify the types of ML techniques applied, like neural networks or support vector machines (SVMs). Furthermore, ML enhances functionalization strategies for drug delivery, biosensing, and environmental remediation. By quantifying performance outcomes and improving reproducibility, ML supports the scalable and sustainable development of AgNPs. This review offers a detailed synthesis of current advances and identifies future opportunities for intelligent, data-driven nanomaterial design.

Nowadays, silver nanoparticles (AgNPs) have drawn significant interest due to their unique properties, making them advantageous in biomedical applications, sensors, antimicrobial agents, catalysts, and optical fibers. Green synthesis is the safest and easiest method for producing silver nanoparticles (AgNPs). This study aimed to investigate the antibacterial and cytotoxic activities of silver nanoparticles synthesized using aqueous extracts of Hedera helix (AHE) against S. aureus, P. aeruginosa, and A549 lung cancer cell lines. Silver nanoparticles (Hh-AgNPs) were synthesized using the aqueous extracts of Hedera helix (AHE) as a reducing agent and polyvinylpyrrolidone (PVP) as a stabilizer and characterized by UV-visible spectrophotometry and particle size analysis via dynamic light scattering (DLS). The silver nanoparticles (Hh-AgNPs) were successfully synthesized, showing maximum absorption at 448 nm, with enhanced cytotoxic activity against A549 lung cancer cell lines (IC₅₀ = 15.16 µg/ml) and antibacterial activity against S. aureus (MIC = 0.156 mg/ml) and P. aeruginosa (MIC = 0.3125 mg/ml), compared to AHE alone. Biological methods are cost-effective and eco-friendly and thus can serve as an economical and efficient alternative for the large-scale synthesis of silver nanoparticles.