Hesperidin (Hes) protects different organs from damage by acting as a potent antioxidant and anti-inflammatory. This study aims to evaluate the gastroprotective effects of free hesperidin and its chitosan nanoparticles (HNPs) against ethanol-induced gastric ulcers in rats, hypothesizing that HNPs will enhance bioavailability and therapeutic efficacy due to improved solubility and targeted delivery. HNPs were synthesized via ion gelation and characterized using TEM, SEM, and zeta potential analyses. Key assessments included gastric acidity, histological analysis, and markers of inflammation, oxidative stress, and apoptosis. HNPs significantly decreased gastric acidity, reduced inflammatory and apoptotic markers, and enhanced antioxidant enzyme activities compared to free hesperidin and esomeprazole. Furthermore, Sirt-1, PGC-1α, HO-1, and FOXO1 gene expression were also evaluated. HNPs raised Sirt-1, PGC-1α, HO-1, and downregulated FOXO1, and they suppressed the activities of NF-κB p65, COX-2, IL-1β, CD86, FOXO1 P53, and caspase-3 and increased Sirt-1 activity. HNPs treatment notably restored antioxidant enzyme activity, reduced oxidative stress and inflammatory markers, and improved histological outcomes more effectively than free hesperidin and esomeprazole. These results indicate that chitosan nanoparticles significantly enhance the gastroprotective effects of hesperidin against ethanol-induced gastric ulcers, potentially offering a more effective therapeutic strategy. Further research should explore the clinical applications of HNPs in human subjects.

Over the last years, extensive motivation has emerged towards the application of supercritical carbon dioxide (SCCO₂) for particle engineering. SCCO₂ has great potential for application as a green and eco-friendly technique to reach small crystalline particles with narrow particle size distribution. In this paper, an artificial intelligence (AI) method has been used as an efficient and versatile tool to predict and consequently optimize the solubility of oxaprozin in SCCO₂ systems. Three learning methods, including multi-layer perceptron (MLP), Kriging or Gaussian process regression (GPR), and k-nearest neighbors (KNN) are selected to make models on the tiny dataset. The dataset includes 32 data points with two input parameters (temperature and pressure) and one output (solubility). The optimized models were tested with standard metrics. MLP, GPR, and KNN have error rates of 2.079 × 10⁻⁸, 2.173 × 10⁻⁹, and 1.372 × 10⁻⁸, respectively, using MSE metrics. Additionally, in terms of R-squared, they have scores of 0.868, 0.997, and 0.999, respectively. The optimal inputs are the same as the maximum possible values and are paired with a solubility of 1.26 × 10⁻³ as an output.

Background: Orlistat (ORL) is an effective irreversible inhibitor of the lipase enzyme, and it possesses anticancer effects and limited aqueous solubility. This study was designed to improve the aqueous solubility, oral absorption, and tissue distribution of ORL via the formulation of nanocrystals (NCs). Methods: ORL-NC was prepared using the liquid antisolvent precipitation method (bottom-up technology), and it demonstrated significantly improved solubility compared with that of the blank crystals (ORL-BCs) and untreated ORL powder. The biodistribution and relative bioavailability of ORL-NC were investigated via the radiolabeling technique using Technetium-99m (^99mTc). Female Swiss albino mice were used to examine the antitumor activity of ORL-NC against solid Ehrlich carcinoma (SEC)-induced hepatic damage in mice. Results: The prepared NCs improved ORL’s solubility, bioavailability, and tissue distribution, with evidence of 258.70% relative bioavailability. In the in vivo study, the ORL-NC treatment caused a reduction in all tested liver functions (total and direct bilirubin, AST, ALT, and ALP) and improved modifications in liver sections that were marked using hematoxylin and eosin staining (H&E) and immunohistochemical staining (Ki-67 and ER-α) compared with untreated SEC mice. Conclusions: The developed ORL-NC could be considered a promising formulation approach to enhance the oral absorption tissue distribution of ORL and suppress the liver damage caused by SEC.

Background/Objectives: Methicillin-resistant Staphylococcus aureus (MRSA) presents a serious hurdle in combating antibiotic-resistant skin infections. This study aimed to repurpose losartan potassium (LOS) through its incorporation into cerosomal nanocarriers (CERs) and further functionalization with carbon dots (CDs) to enhance antibacterial efficacy. Methods: LOS-CERs were fabricated by the thin-film hydration method and further optimized using a D-optimal mixture design. Results: The optimized CERs, composed of phytantriol (20 mg), ceramide (30 mg), and CTAB (20 mg), exhibited high entrapment efficiency (97.07 ± 0.07%), a nanoscale particle size (372.50 ± 0.50 nm), and a positive zeta potential (+33.24 ± 0.04 mV). FT-IR analysis confirmed successful conjugation of CDs to CERs through surface functional interactions. Ex vivo permeation and confocal microscopy studies demonstrated that the CD-CER formulation sustained LOS release and enhanced its deposition within skin layers compared with the LOS solution. Using a murine model of MRSA USA300-induced skin infection, the CD-CER formulation achieved superior antibacterial efficacy, reducing the bacterial load by 3.85 log₁₀ CFU relative to the untreated control, compared with a 3.04 log₁₀ CFU reduction for the LOS solution. Histological evaluation supported improved healing in CD-CER-treated groups. Conclusions: Overall, CD-functionalized CERs offer a promising multifunctional nanoplatform for repurposing LOS as a topical therapeutic against MRSA-associated skin infections.

Inadequate bioavailability of therapeutic drugs, which is often the consequence of their unacceptable solubility and dissolution rates, is an indisputable operational challenge of pharmaceutical companies due to its detrimental effect on the therapeutic efficacy. Over the recent decades, application of supercritical fluids (SCFs) (mainly SCCO₂) has attracted the attentions of many scientists as promising alternative of toxic and environmentally-hazardous organic solvents due to possessing positive advantages like low flammability, availability, high performance, eco-friendliness and safety/simplicity of operation. Nowadays, application of different machine learning (ML) as a versatile, robust and accurate approach for the prediction of different momentous parameters like solubility and bioavailability has been of great attentions due to the non-affordability and time-wasting nature of experimental investigations. The prominent goal of this article is to review the role of different ML-based tools for the prediction of solubility/bioavailability of drugs using SCCO₂. Moreover, the importance of solubility factor in the pharmaceutical industry and different possible techniques for increasing the amount of this parameter in poorly-soluble drugs are comprehensively discussed. At the end, the efficiency of SCCO₂ for improving the manufacturing process of drug nanocrystals is aimed to be discussed.

Background/Objectives: PEGylated zein nanoparticles (PZNs) loaded with losartan potassium (LOS) were developed as a repurposed treatment for vaginal methicillin-resistant Staphylococcus aureus (MRSA) infection. PZNs were prepared using the ethanol injection method with different types and amounts of Brij^® surfactant. Methods: The prepared formulations were optimized using a D-optimal mixture design via Design-Expert^® software version 13. The assessed responses included entrapment efficiency (EE%), particle size (PS), and zeta potential (ZP). Results: The optimized PZNs, composed of 30 mg Brij^® O20 and 10 mg zein, exhibited spherical particles with an EE% of 90.58 ± 1.20%, PS of 200.81 ± 1.39 nm, PDI of 0.395 ± 0.01, and ZP of −36.59 ± 0.05 mV. Confocal laser scanning microscopy confirmed complete deposition of fluorescein-labeled PZNs within vaginal tissues. Ex vivo studies showed that PZNs resulted in prolonged permeation of LOS compared to the LOS solution. In a murine model of MRSA infection, the optimized PZNs demonstrated superior therapeutic efficacy over the LOS solution. Histopathological examinations confirmed the safety of the tested formulations. Conclusions: In conclusion, the optimized PZNs present a promising approach for the treatment of MRSA-related vaginal infections.