Scientia Pharmaceutica

Docetaxel (DTX)-loaded polymeric nanoparticles composed of Eudragit RL and RS 100 were developed by solvent evaporation using D-α-tocopheryl polyethene glycol 1000 succinate as an emulsifier and optimised by Central Composite Design. The effects of homogenisation and sonication times on entrapment efficiency (%EE) and drug release (%DR) were statistically analysed across nine batches. Particle size (PS) ranged from 302 ± 1.0 to 502 ± 2.0 nm, and zeta potential (ZP) from 25.8 ± 2.5 to 42.9 ± 1.7 mV. %EE and %DR (pH 1.2 for 2 h, then pH 7.4 for 22 h, 40 mL medium at 37 ± 0.5 °C) ranged from 69.32 ± 3.77 to 92.71 ± 0.16% and 19.24 ± 3.03 to 49.17 ± 1.98%, respectively. Optimised DTX nanoparticles (DNPs) showed EE of 78.18 ± 0.56%, DR of 46.21 ± 1.41% at 24 h, PS of 357.9 ± 2.4 nm, and ZP of 42.9 ± 3.7 mV. Scanning electron microscopy revealed ~300 nm cuboidal particles with smooth surfaces. X-Ray Diffraction and Differential Scanning Colorimetry confirmed reduced drug crystallinity in DNPs. In vitro haemolysis assays showed ~11.5-fold lower haemolytic potential (p < 0.0001) versus DTX, confirming improved safety. Fluorescence microscopy indicated enhanced cellular uptake of DNPs in MDA-MB-231 cells, while cytotoxicity assays of DNPs showed a lower IC₅₀ (39.52 µM) compared to DTX (60.81 µM), demonstrating superior anticancer efficacy. Overall, DNPs represent a promising oral chemotherapy platform for breast cancer management.

Bioactive ingredients are compounds, typically derived from natural sources, that provide specific health benefits or perform certain beneficial functions. Although they can play a role in maintaining good health, their effects can vary widely based on a person’s specific genotype and phenotype, leading to situations where certain ingredients induce beneficial responses for some individuals but not others. Herein, we report a method for the rapid discovery of relationships between genes, bioactive ingredients, and physiological effects. First, RNA-Seq was performed after applying 6 plant-derived ingredients to a three-dimensional skin model. After determining expression changes for each ingredient, these changes were ranked and visualized using score-based prediction models. Based on our analysis, we were able to quickly determine and visualize the effect (or lack thereof) of the ingredients on gene expression. Our findings demonstrate the utility of combining RNA-Seq with score-based models and visualizations for screening bioactive ingredients by gene expression, visualizing their impact based on ingredient or physiological effect, and the applicability of this method to any bioactive ingredient for rapid determination of potential ingredients relevant to maintaining health and wellness.

Diabetes mellitus (DM) is a disease that affects over 537 million people worldwide and results in 6.7 million deaths annually. Conventional treatment of this disease focuses on lifestyle changes and drug administration. However, very few people can adhere to a healthier lifestyle, and drugs are difficult to access, especially in low- and middle-income countries. An alternative as an adjuvant to the treatment of DM is the phenolic compounds from plants with reported anti-diabetic effects. However, the bioavailability of these compounds is very low since they are affected by the gastrointestinal tract and xenobiotic metabolism. To improve the availability of these compounds, an emerging technology such as encapsulation is being used since it has been reported that the encapsulation of phenolic compounds improves both their bioaccessibility and bioavailability, as well as their bioactivity. In this review, we will focus on compiling the most up-to-date information on the different encapsulation processes of phenolic compounds and the antidiabetic effect of encapsulated phenolic compounds using the databases PubMed, Scopus, Web of Science, and Google Scholar. We will discuss the mechanisms, pathways, and receptors involved in the modulation of DM, especially those related to inflammation, oxidative stress, and insulin resistance.