Synthesis of magnetic responsive poly(NIPAAm-co-VSA)/Fe3O4 IPN ferrogels and modeling their deswelling and heating behaviors under AMF by using artificial neural networks

Biomedical applications of stimuli-responsive "smart" interpenetrating polymer network hydrogels

In recent years, owing to the ongoing advancements in polymer materials, hydrogels have found increasing applications in the biomedical domain, notably in the realm of stimuli-responsive "smart" hydrogels. Nonetheless, conventional single-network stimuli-responsive "smart" hydrogels frequently exhibit deficiencies, including low mechanical strength, limited biocompatibility, and extended response times. In response, researchers have addressed these challenges by introducing a second network to create stimuli-responsive "smart" Interpenetrating Polymer Network (IPN) hydrogels. The mechanical strength of the material can be significantly improved due to the topological entanglement and physical interactions within the interpenetrating structure. Simultaneously, combining different network structures enhances the biocompatibility and stimulus responsiveness of the gel, endowing it with unique properties such as cell adhesion, conductivity, hemostasis/antioxidation, and color-changing capabilities. This article primarily aims to elucidate the stimulus-inducing factors in stimuli-responsive "smart" IPN hydrogels, the impact of the gels on cell behaviors and their biomedical application range. Additionally, we also offer an in-depth exposition of their categorization, mechanisms, performance characteristics, and related aspects. This review furnishes a comprehensive assessment and outlook for the advancement of stimuli-responsive "smart" IPN hydrogels within the biomedical arena. We believe that, as the biomedical field increasingly demands novel materials featuring improved mechanical properties, robust biocompatibility, and heightened stimulus responsiveness, stimuli-responsive "smart" IPN hydrogels will hold substantial promise for wide-ranging applications in this domain.

Removal of pharmaceuticals from aqueous medium by alginate/polypyrrole/ZnFe2O4 beads via magnetic field enhanced adsorption

The physicochemical and structural characteristics of the magnetic materials can be modulable due to exposition to a magnetic field, which allows, for example, to enhance its adsorption performance. In this sense, this study describes the preparation of magnetic beads of alginate/polypyrrole/ZnFe₂O₄ (Alg/PPy/ZnFe₂O₄) and investigates the effect of an external magnetic field (EMF) on their adsorption performance towards two overconsumed drugs, acetaminophen (ACT) and ibuprofen (IBU). Characterization analyses confirmed the composite formation and magnetic nature of Alg/PPy/ZnFe₂O₄. Conversely to the pristine beads (Alg/PPy), the presence of an EMF altered the swelling and pH_PZC behavior of the magnetic beads, indicating that these properties are affected by this external stimulus. Batch experiments revealed that the amount of ACT and IBU adsorbed by Alg/PPy/ZnFe₂O₄ in 60-70 min is appreciably high (106.7 ad 108.2 mg/g). The presence of an EMF modulated the structure of Alg/PPy/ZnFe₂O₄ beads enhancing their adsorption capacity towards ACT and IBU by 14% and 12% compared to Alg/PPy. Kinetic analysis revealed that the adsorption of both drugs on Alg/PPy/ZnFe2O4 followed a pseudo-second-order. Besides, the adsorption mechanism was fitted by the Freundlich isotherm. Reuse experiments showed that the magnetic beads keep a high adsorption capacity for both drugs even after ten consecutive reuse cycles. The results presented here suggest that magnetic-responsive materials like Alg/PPy/ZnFe₂O₄ are prominent and modulable tools for improving the treatment of water/wastewater containing this class of contaminants.

The Application of Artificial Intelligence in Magnetic Hyperthermia Based Research

The development of nanomedicine involves complex nanomaterial research involving magnetic nanomaterials and their use in magnetic hyperthermia. The selection of the optimal treatment strategies is time-consuming, expensive, unpredictable, and not consistently effective. Delivering personalized therapy that obtains maximal efficiency and minimal side effects is highly important. Thus, Artificial Intelligence (AI) based algorithms provide the opportunity to overcome these crucial issues. In this paper, we briefly overview the significance of the combination of AI-based methods, particularly the Machine Learning (ML) technique, with magnetic hyperthermia. We considered recent publications, reports, protocols, and review papers from Scopus and Web of Science Core Collection databases, considering the PRISMA-S review methodology on applying magnetic nanocarriers in magnetic hyperthermia. An algorithmic performance comparison in terms of their types and accuracy, data availability taking into account their amount, types, and quality was also carried out. Literature shows AI support of these studies from the physicochemical evaluation of nanocarriers, drug development and release, resistance prediction, dosing optimization, the combination of drug selection, pharmacokinetic profile characterization, and outcome prediction to the heat generation estimation. The papers reviewed here clearly illustrate that AI-based solutions can be considered as an effective supporting tool in drug delivery, including optimization and behavior of nanocarriers, both in vitro and in vivo, as well as the delivery process. Moreover, the direction of future research, including the prediction of optimal experiments and data curation initiatives has been indicated.