Molecular Mechanism of Ultrasound-Induced Structural Defects in Liposomes: A Nonequilibrium Molecular Dynamics Simulation Study

Ultrasonic Dispersion for Iron Recovery from Slime Tailings: Microprocesses Unveiled through Molecular Dynamics Simulations

Chemical dispersion has been commonly used to mitigate the negative effects of ultrafine particles in iron ore concentration processes. However, mechanical solutions such as ultrasound are proving to be more effective and without harmful side effects. This study compared the performance of different dispersants and ultrasound as pretreatments for reverse cationic flotation of goethite-rich slime tailings through sedimentation, dispersion, and flotation tests, along with particle size analysis. Additionally, large-scale molecular dynamics simulations were used for the first time to investigate the effects of ultrasonic shockwaves on mineral particle interactions. The results showed that ultrasonication is a superior pretreatment, enhancing particle dispersion and separation performance, cleaning mineral surfaces, and improving flotation results. Ultrasound achieved an increase in metallurgical recovery of around 9% while using only a dispersant reagent did not reach 5%. Simulations demonstrated the known effects of ultrasound, such as extreme temperature, bubble cavitation, and particle detachment, revealing the crucial microscopic mechanisms involved in particle separation by sonic waves. This study bridges experimental data with computational simulations, offering a comprehensive understanding of ultrasonication's effects on particle separation, paving the way for more efficient and sustainable processing technologies.

Computational Methods for Modeling Lipid-Mediated Active Pharmaceutical Ingredient Delivery

Lipid-mediated delivery of active pharmaceutical ingredients (API) opened new possibilities in advanced therapies. By encapsulating an API into a lipid nanocarrier (LNC), one can safely deliver APIs not soluble in water, those with otherwise strong adverse effects, or very fragile ones such as nucleic acids. However, for the rational design of LNCs, a detailed understanding of the composition-structure-function relationships is missing. This review presents currently available computational methods for LNC investigation, screening, and design. The state-of-the-art physics-based approaches are described, with the focus on molecular dynamics simulations in all-atom and coarse-grained resolution. Their strengths and weaknesses are discussed, highlighting the aspects necessary for obtaining reliable results in the simulations. Furthermore, a machine learning, i.e., data-based learning, approach to the design of lipid-mediated API delivery is introduced. The data produced by the experimental and theoretical approaches provide valuable insights. Processing these data can help optimize the design of LNCs for better performance. In the final section of this Review, state-of-the-art of computer simulations of LNCs are reviewed, specifically addressing the compatibility of experimental and computational insights.

Ultrasound enhanced diffusion in hydrogels: An experimental and non-equilibrium molecular dynamics study

Focused ultrasound has experimentally been found to enhance the diffusion of nanoparticles; our aim with this work is to study this effect closer using both experiments and non-equilibrium molecular dynamics. Measurements from single particle tracking of 40 nm polystyrene nanoparticles in an agarose hydrogel with and without focused ultrasound are presented and compared with a previous experimental study using 100 nm polystyrene nanoparticles. In both cases, we observed an increase in the mean square displacement during focused ultrasound treatment. We developed a coarse-grained non-equilibrium molecular dynamics model with an implicit solvent to investigate the increase in the mean square displacement and its frequency and amplitude dependencies. This model consists of polymer fibers and two sizes of nanoparticles, and the effect of the focused ultrasound was modeled as an external oscillating force field. A comparison between the simulation and experimental results shows similar mean square displacement trends, suggesting that the particle velocity is a significant contributor to the observed ultrasound-enhanced mean square displacement. The resulting diffusion coefficients from the model are compared to the diffusion equation for a two-time continuous time random walk. The model is found to have the same frequency dependency. At lower particle velocity amplitude values, the model has a quadratic relation with the particle velocity amplitude as described by the two-time continuous time random walk derived diffusion equation, but at higher amplitudes, the model deviates, and its diffusion coefficient reaches the non-hindered diffusion coefficient. This observation suggests that at higher ultrasound intensities in hydrogels, the non-hindered diffusion coefficient can be used.

Highly-Controlled Soft-Templating Synthesis of Hollow ZIF-8 Nanospheres for Selective CO2 Separation and Storage

Global warming is an ever-rising environmental concern, and carbon dioxide (CO2) is among its major causes. Different technologies, including adsorption, cryogenic separation, and sequestration, have been developed for CO2 separation and storage/utilization. Among these, carbon capture using nano-adsorbents has the advantages of excellent CO2 separation and storage performance as well as superior heat- and mass-transfer characteristics due to their large surface area and pore volume. In this work, an environmentally friendly, facile, bottom-up synthesis of ZIF-8 hollow nanospheres (with reduced chemical consumption) was developed for selective CO2 separation and storage. During this soft-templating synthesis, a combined effect of ultra-sonication and low-temperature hydrothermal synthesis showed better control over an oil-in-water microemulsion formation and the subsequent growth of large-surface-area hollow ZIF-8 nanospheres having excellent particle size distribution. Systematic studies on the synthesis parameters were also performed to achieve fine-tuning of the ZIF-8 crystallinity, hollow structures, and sphere size. The optimized hollow ZIF-8 nanosphere sample having uniform size distribution exhibited remarkable CO2 adsorption capability (∼2.24 mmol g-1 at 0 °C and 1.75 bar), a CO2/N2 separation selectivity of 12.15, a good CO2 storage capacity (1.5-1.75 wt %), and an excellent cyclic adsorption/desorption performance (up to four CO2 adsorption/desorption cycles) at 25 °C. In addition, the samples showed exceptional structural stability with only ∼15% of overall weight loss up to 600 °C under a nitrogen environment. Therefore, the hollow ZIF-8 nanospheres as well as their highly controlled soft-templating synthesis method reported in this work are useful in the course of the development of nanomaterials with optimized properties for future CO2 capture technologies.

Milk-Derived Exosomes as a Promising Vehicle for Oral Delivery of Hydrophilic Biomacromolecule Drugs

Exosomes, as promising vehicles, have been widely used in the research of oral drug delivery, but the generally low drug loading efficiency of exosomes seriously limits its application and transformation. In this study, we systematically investigated the effects of drug loading methods and physicochemical properties (lipophilicity and molecular weight) on drug loading efficiency of milk-derived exosomes to explore the most appropriate loading conditions. Our finding revealed that the drug loading efficiency of exosomes was closely related to the drug loading method, drug lipophilicity, drug molecular weight and exosome/drug proportions. Of note, we demonstrated the universality that hydrophilic biomacromolecule drugs were the most appropriate loading drugs for milk-derived exosomes, which was attributed to the efficient loading capacity and sustained release behavior. Furthermore, milk-derived exosomes could significantly improve the transepithelial transport and oral bioavailability of model hydrophilic biomacromolecule drugs (octreotide, exendin-4 and salmon calcitonin). Collectively, our results suggested that the encapsulation of hydrophilic biomacromolecule drugs might be the most promising direction for milk exosomes as oral drug delivery vehicles.

Ultrasound Triggering of Liposomal Nanodrugs for Cancer Therapy: A Review

Efficient conventional chemotherapy is limited by its nonspecific nature, which causes severe systemic toxicity that can lead to patient discomfort and low therapeutic efficacy. The emergence of smart drug delivery systems (SDDSs) utilizing nanoparticles as drug nanocarriers has shown great potential in enhancing the targetability of anticancer agents and limiting their side effects. Liposomes are among the most investigated nanoplatforms due to their promising capabilities of encapsulating hydrophilic, lipophilic, and amphiphilic drugs, biocompatibility, physicochemical and biophysical properties. Liposomal nanodrug systems have demonstrated the ability to alter drugs' biodistribution by sufficiently delivering the entrapped chemotherapeutics at the targeted diseased sites, sparing normal cells from undesired cytotoxic effects. Combining liposomal treatments with ultrasound, as an external drug release triggering modality, has been proven effective in spatially and temporally controlling and stimulating drug release. Therefore, this paper reviews recent literature pertaining to the therapeutic synergy of triggering nanodrugs from liposomes using ultrasound. It also highlights the effects of multiple physical and chemical factors on liposomes' sonosensetivity, several ultrasound-induced drug release mechanisms, and the efficacy of ultrasound-responsive liposomal systems in cancer therapy. Overall, liposomal nanodrug systems triggered by ultrasound are promising cancer therapy platforms that can potentially alleviate the detriments of conventional cancer treatments.

Modeling Polyzwitterion-Based Drug Delivery Platforms: A Perspective of the Current State-of-the-Art and Beyond

Drug delivery platforms are anticipated to have biocompatible and bioinert surfaces. PEGylation of drug carriers is the most approved method since it improves water solubility and colloid stability and decreases the drug vehicles' interactions with blood components. Although this approach extends their biocompatibility, biorecognition mechanisms prevent them from biodistribution and thus efficient drug transfer. Recent studies have shown (poly)zwitterions to be alternatives for PEG with superior biocompatibility. (Poly)zwitterions are super hydrophilic, mainly stimuli-responsive, easy to functionalize and they display an extremely low protein adsorption and long biodistribution time. These unique characteristics make them already promising candidates as drug delivery carriers. Furthermore, since they have highly dense charged groups with opposite signs, (poly)zwitterions are intensely hydrated under physiological conditions. This exceptional hydration potential makes them ideal for the design of therapeutic vehicles with antifouling capability, i.e., preventing undesired sorption of biologics from the human body in the drug delivery vehicle. Therefore, (poly)zwitterionic materials have been broadly applied in stimuli-responsive "intelligent" drug delivery systems as well as tumor-targeting carriers because of their excellent biocompatibility, low cytotoxicity, insignificant immunogenicity, high stability, and long circulation time. To tailor (poly)zwitterionic drug vehicles, an interpretation of the structural and stimuli-responsive behavior of this type of polymer is essential. To this end, a direct study of molecular-level interactions, orientations, configurations, and physicochemical properties of (poly)zwitterions is required, which can be achieved via molecular modeling, which has become an influential tool for discovering new materials and understanding diverse material phenomena. As the essential bridge between science and engineering, molecular simulations enable the fundamental understanding of the encapsulation and release behavior of intelligent drug-loaded (poly)zwitterion nanoparticles and can help us to systematically design their next generations. When combined with experiments, modeling can make quantitative predictions. This perspective article aims to illustrate key recent developments in (poly)zwitterion-based drug delivery systems. We summarize how to use predictive multiscale molecular modeling techniques to successfully boost the development of intelligent multifunctional (poly)zwitterions-based systems.