Machine Learning-Assisted Optimization of Drug Combinations in Zeolite-Based Delivery Systems for Melanoma Therapy.

Two independent artificial neural network (ANN) models were used to determine the optimal drug combination of zeolite-based delivery systems (ZDS) for cancer therapy. The systems were based on the NaY zeolite using silver (Ag+) and 5-fluorouracil (5-FU) as antimicrobial and antineoplastic agents. Different ZDS samples were prepared, and their characterization indicates the successful incorporation of both pharmacologically active species without any relevant changes to the zeolite structure. Silver acts as a counterion of the negative framework, and 5-FU retains its molecular integrity. The data from the A375 cell viability assays, involving ZDS samples (solid phase), 5-FU, and Ag+ aqueous solutions (liquid phase), were used to train two independent machine learning (ML) models. Both models exhibited a high level of accuracy in predicting the experimental cell viability results, allowing the development of a novel protocol for virtual cell viability assays. The findings suggest that the incorporation of both Ag and 5-FU into the zeolite structure significantly potentiates their anticancer activity when compared to that of the liquid phase. Additionally, two optimal AgY/5-FU@Y ratios were proposed to achieve the best cell viability outcomes. The ZDS also exhibited significant efficacy against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus); the predicted combination ratio is also effective against S. aureus, underscoring the potential of this approach as a therapeutic option for cancer-associated bacterial infections.

Doxorubicin delivery performance of superparamagnetic carbon multi-core shell nanoparticles: pH dependence, stability and kinetic insight.

In the past decade, magnetic nanoparticles (MNPs) have been among the most attractive nanomaterials used in different fields, such as environmental and biomedical applications. The possibility of designing nanoparticles with different functionalities allows for advancing the biomedical applications of these materials. Additionally, the magnetic characteristics of the nanoparticles enable the use of magnetic fields to drive the nanoparticles to the desired sites of delivery. In this context, the development of new MNPs in new approaches for drug delivery systems (DDSs) for cancer treatment has increased. However, the synthesis of nanoparticles with high colloidal stability triggered drug delivery, and good biocompatibility remains a challenge. Herein, multi-core shell MNPs functionalized with Pluronic ® F-127 were prepared and thoroughly characterized as drug carriers for doxorubicin delivery. The functionalized nanoparticles have an average size of 17.71 ± 4.2 nm, high water colloidal stability, and superparamagnetic behavior. In addition, the nanoparticles were able to load 936 µg of DOX per mg of functionalized nanomaterial. Drug release studies at different pH values evidenced a pH-triggered DOX release effect. An increase of 62% in cumulative drug release was observed at pH simulating tumor endosome/lysosome microenvironments (pH 4.5) compared to physiological conditions (pH 7.4). In addition, an innovative dynamic drug delivery study was performed as a function of pH. The results from this test confirmed the pH-induced doxorubicin release capability of carbon multi-core shell MNPs. The validity of traditional kinetic models to fit dynamic pH-dependent drug release was also studied for predictive purposes.

Surface functionalization of zeolite-based drug delivery systems enhances their antitumoral activity in vivo.

Zeolites have attractive features making them suitable carriers for drug delivery systems (DDS). As such, we loaded the anticancer drug 5-fluorouracil (5-FU), into two different zeolite structures, faujasite (NaY) and Linde Type L (LTL), to obtain different DDS. The prepared DDS were tested in vitro using breast cancer, colorectal carcinoma, and melanoma cell lines and in vivo using the chick embryo chorioallantoic membrane model (CAM). Both assays showed the best results for the Hs578T breast cancer cells, with a higher potentiation for 5-FU encapsulated in the zeolite LTL. To unveil the endocytic mechanisms involved in the internalization of the zeolite nanoparticles, endocytosis was inhibited pharmacologically in breast cancer and epithelial mammary human cells. The results suggest that a caveolin-mediated process was responsible for the internalized zeolite nanoparticles. Aiming to boost the DDS efficacy, the disc-shaped zeolite LTL outer surface was functionalized using amino (NH2) or carboxylic acid (COOH) groups and coated with poly-l-lysine (PLL). Positively functionalized surface LTL nanoparticles revealed to be non-toxic to human cells and, importantly, their internalization was faster and led to a higher tumor reduction in vivo. Overall, our results provide further insights into the mechanisms of interaction between zeolite-based DDS and cancer cells, and pave the way for future studies aiming to improve DDS anticancer activity.

Stability of colorimetric results in the detection of urine biomarkers using a paper-based analytical device.

Urinalysis allows obtaining information about many of the body's functions. Normally, urine is a very easily collected specimen, but in some cases, it can be an uncomfortable process. Moreover, standard methods such as microscopic examination or urine culturing represent time-consuming procedures. In this regard, this work explores the design of a device that combines disposable diapers, as a platform for sample collection, with part of the dipsticks method. Even though this is a desirable combination for a faster and comfortable approach, it is also convenient to extend the prescribed time, provided by the dipstick manufacturer, to read the results. This allows the stability and validity of the results for longer, preferably until the moment of the diaper changing, and it was also considered in the design. The desired conditions were reproduced for the reagent pads of glucose and nitrite. The results show that the RGB profile, obtained in glucose detection, varied after approximately 60 min. However, when the developed colors are visually compared with the reference colors, the results suggest that there were not significant variations. In the nitrite assay, by analyzing the RGB profile or by visual comparison with the reference colors, the color does not appear to change over time, but the results were not the expected. It seems that the proposed design is promising regarding results stability, but more experiments need to be done to check if the variations are constant for more biomarkers in the conditions provided by the device.