A videographic assessment of ferrofluid during magnetic drug targeting: An application of artificial intelligence in nanomedicine

Pair correlations of the easy magnetisation axes of superparamagnetic nanoparticles in a ferrofluid/ferrocomposite

The widespread use of magnetic nanoparticles in modern technologies and medical applications highlights the need for reliable theoretical models that can predict their physical properties. The pair correlation function of two randomly selected superparamagnetic nanoparticles in a ferrofluid/ferrocomposite is studied to depict the joint probability density of the easy magnetisation axes across the planes of parameters of major importance; these are the interaction of ferroparticles with an external magnetic field, the energy of magnetic anisotropy inside the superparamagnetic nanoparticle, and the interparticle magnetic dipole-dipole interaction. Assuming the rotational symmetry of the system, we come to the conclusion that the pair correlations of interest are dependent only on the polar angles, determining the inclinations of the ferroparticle easy axes from the direction of an external magnetic field. The dimer configuration, where two ferroparticles are in close contact along a magnetic field with their easy magnetisation axes aligned, is the most probable. This configuration becomes more pronounced with increasing anisotropy energy, dipolar coupling constant, and external magnetic field.

A Journey of Challenges and Victories: A Bibliometric Worldview of Nanomedicine since the 21st Century

Nanotechnology profoundly affects the advancement of medicine. Limitations in diagnosing and treating cancer and chronic diseases promote the growth of nanomedicine. However, there are very few analytical and descriptive studies regarding the trajectory of nanomedicine, key research powers, present research landscape, focal investigative points, and future outlooks. Herein, articles and reviews published in the Science Citation Index Expanded of Web of Science Core Collection from first January 2000 to 18th July 2023 are analyzed. Herein, a bibliometric visualization of publication trends, countries/regions, institutions, journals, research categories, themes, references, and keywords is produced and elaborated. Nanomedicine-related academic output is increasing since the COVID-19 pandemic, solidifying the uneven global distribution of research performance. While China leads in terms of publication quantity and has numerous highly productive institutions, the USA has advantages in academic impact, commercialization, and industrial value. Nanomedicine integrates with other disciplines, establishing interdisciplinary platforms, in which drug delivery and nanoparticles remain focal points. Current research focuses on integrating nanomedicine and cell ferroptosis induction in cancer immunotherapy. The keyword "burst testing" identifies promising research directions, including immunogenic cell death, chemodynamic therapy, tumor microenvironment, immunotherapy, and extracellular vesicles. The prospects, major challenges, and barriers to addressing these directions are discussed.

Influence of a bias dc field and an ac field amplitude on the dynamic susceptibility of a moderately concentrated ferrofluid

In this paper, we study the effect of a bias dc field on the dynamic response of a moderately concentrated ferrofluid to an ac magnetic field of arbitrary amplitude. The ferrofluid is modeled by an ensemble of interacting moving magnetic particles; the reaction of particle magnetic moments to ac and dc magnetic fields occurs according to the Brownian mechanism; and the ac and dc magnetic fields are parallel. Based on a numerical solution of the Fokker-Planck equation for the probability density of the orientation of the magnetic moment of a random magnetic particle, dynamic magnetization and susceptibility are determined and analyzed for various values of the ac field amplitude, the dc field strength, and the intensity of dipole-dipole interactions. It is shown that the system's magnetic response is formed under the influence of competing interactions, such as dipole-dipole, dipole-ac field, and dipole-dc field interactions. When the energies of these interactions are comparable, unexpected effects are observed: the system's susceptibility can either increase or decrease with increasing ac field amplitude. This behavior is associated with the formation of nose-to-tail dipolar structures under the action of the dc field, which can hinder or promote the system's dynamic response to the ac field. The obtained results provide a theoretical basis for predicting the dynamic properties of ferrofluids to improve their use in biomedical applications, such as, in magnetic induction hyperthermia.

A Review of Advanced Multifunctional Magnetic Nanostructures for Cancer Diagnosis and Therapy Integrated into an Artificial Intelligence Approach

The new era of nanomedicine offers significant opportunities for cancer diagnostics and treatment. Magnetic nanoplatforms could be highly effective tools for cancer diagnosis and treatment in the future. Due to their tunable morphologies and superior properties, multifunctional magnetic nanomaterials and their hybrid nanostructures can be designed as specific carriers of drugs, imaging agents, and magnetic theranostics. Multifunctional magnetic nanostructures are promising theranostic agents due to their ability to diagnose and combine therapies. This review provides a comprehensive overview of the development of advanced multifunctional magnetic nanostructures combining magnetic and optical properties, providing photoresponsive magnetic platforms for promising medical applications. Moreover, this review discusses various innovative developments using multifunctional magnetic nanostructures, including drug delivery, cancer treatment, tumor-specific ligands that deliver chemotherapeutics or hormonal agents, magnetic resonance imaging, and tissue engineering. Additionally, artificial intelligence (AI) can be used to optimize material properties in cancer diagnosis and treatment, based on predicted interactions with drugs, cell membranes, vasculature, biological fluid, and the immune system to enhance the effectiveness of therapeutic agents. Furthermore, this review provides an overview of AI approaches used to assess the practical utility of multifunctional magnetic nanostructures for cancer diagnosis and treatment. Finally, the review presents the current knowledge and perspectives on hybrid magnetic systems as cancer treatment tools with AI models.

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.

Advanced biomedical applications of iron oxide nanostructures based ferrofluids

Ferrofluids or magnetic nanofluids are highly stable colloidal suspensions of magnetic nanoparticles (NPs) dispersed into various base fluids. These stable ferrofluids possess high thermal conductivity, improved thermo-physical properties, higher colloidal stability, good magnetic properties, and biocompatibility, which are the primary driving forces behind their excellent performance, and thus enable them to be used for a wide range of practical applications. The most studied and advanced ferrofluids are based on iron oxide nanostructures especially NPs, because of their easy and large-scale synthesis at low costs. Although in the last decade, several review articles are available on ferrofluids but mainly focused on preparations, properties, and a specific application. Hence, a collective and comprehensive review article on the recent progress of iron oxide nanostructures based ferrofluids for advanced biomedical applications is undeniably required. In this review, the state of the art of biomedical applications is presented and critically analyzed with a special focus on hyperthermia, drug delivery/nanomedicine, magnetic resonance imaging, and magnetic separation of cells. This review article provides up-to-date information related to the technological advancements and emerging trends in iron oxide nanostructures based ferrofluids research focused on advanced biomedical applications. Finally, conclusions and outlook of iron oxide nanostructures based ferrofluids research for biomedical applications are presented.

Heat induction in two-dimensional graphene-Fe3O4 nanohybrids for magnetic hyperthermia applications with artificial neural network modeling

We report the synthesis and characterization of graphene functionalized with iron (Fe3+) oxide (G-Fe3O4) nanohybrids for radio-frequency magnetic hyperthermia application. We adopted the wet chemical procedure, using various contents of Fe3O4 (magnetite) from 0-100% for making two-dimensional graphene-Fe3O4 nanohybrids. The homogeneous dispersal of Fe3O4 nanoparticles decorated on the graphene surface combined with their biocompatibility and high thermal conductivity make them an excellent material for magnetic hyperthermia. The morphological and magnetic properties of the nanohybrids were studied using scanning electron microscopy (SEM) and a vibrating sample magnetometer (VSM), respectively. The smart magnetic platforms were exposed to an alternating current (AC) magnetic field of 633 kHz and of strength 9.1 mT for studying their hyperthermic performance. The localized antitumor effects were investigated with artificial neural network modeling. A neural net time-series model was developed for the assessment of the best nanohybrid composition to serve the purpose with an accuracy close to 100%. Six Nonlinear Autoregressive with External Input (NARX) models were obtained, one for each of the components. The assessment of the accuracy of the predicted results has been done on the basis of Mean Squared Error (MSE). The highest Mean Squared Error value was obtained for the nanohybrid containing 45% magnetite and 55% graphene (F45G55) in the training phase i.e., 0.44703, which is where the model achieved optimal results after 71 epochs. The F45G55 nanohybrid was found to be the best for hyperthermia applications in low dosage with the highest specific absorption rate (SAR) and mean squared error values.

Self-Assembled Hexagonal Superparamagnetic Cone Structures for Fabrication of Cell Cluster Arrays

In this study, we demonstrated that arrays of cell clusters can be fabricated by self-assembled hexagonal superparamagnetic cone structures. When a strong out-of-plane magnetic field was applied to the ferrofluid on a glass substrate, it will induce the magnetic poles on the upper/lower surfaces of the continuous ferrofluid to increase the magnetostatic energy. The ferrofluid will then experience hydrodynamic instability and be split into small droplets with cone structures because of the compromising surface tension energy and magnetostatic energy to minimize the system's total energy. Furthermore, the ferrofluid cones were orderly self-assembled into hexagonal arrays to reach the lowest energy state. After dehydration of these liquid cones to form solid cones, polydimethylsiloxane was cast to fix the arrangement of hexagonal superparamagnetic cone structures and prevent the leakage of magnetic nanoparticles. The U-343 human neuronal glioblastoma cells were labeled with magnetic nanoparticles through endocytosis in co-culture with a ferrofluid. The number of magnetic nanoparticles internalized was (4.2 ± 0.84) × 10⁶ per cell by the cell magnetophoresis analysis. These magnetically labeled cells were attracted and captured by hexagonal superparamagnetic cone structures to form cell cluster arrays. As a function of the solid cone size, the number of cells captured by each hexagonal superparamagnetic cone structure was increased from 48 to 126 under a 2000 G out-of-plane magnetic field. The local magnetic field gradient of the hexagonal superparamagnetic cone was 117.0-140.9 G/mm from the cell magnetophoresis. When an external magnetic field was applied, we observed that the number of protrusions of the cell edge decreased from the fluorescence images. It showed that the local magnetic field gradient caused by the hexagonal superparamagnetic cones restricted the cell growth and migration.

Chemically reactive MHD micropolar nanofluid flow with velocity slips and variable heat source/sink

The two-dimensional electrically conducting magnetohydrodynamic flow of micropolar nanofluid over an extending surface with chemical reaction and secondary slips conditions is deliberated in this article. The flow of nanofluid is treated with heat source/sink and nonlinear thermal radiation impacts. The system of equations is solved analytically and numerically. Both analytical and numerical approaches are compared with the help of figures and tables. In order to improve the validity of the solutions and the method convergence, a descriptive demonstration of residual errors for various factors is presented. Also the convergence of an analytical approach is shown. The impacts of relevance parameters on velocity, micro-rotation, thermal, and concentration fields for first- and second-order velocity slips are accessible through figures. The velocity field heightens with the rise in micropolar, micro-rotation, and primary order velocity parameters, while other parameters have reducing impact on the velocity field. The micro-rotation field reduces with micro-rotation, secondary order velocity slip, and micropolar parameters but escalates with the primary order velocity slip parameter. The thermal field heightens with escalating non-uniform heat sink/source, Biot number, temperature ratio factor, and thermal radiation factor. The concentration field escalates with the increasing Biot number, while reduces with heightening chemical reaction and Schmidt number. The assessment of skin factor, thermal transfer, and mass transfer are calculated through tables.

Numerical simulation of electroosmosis regulated peristaltic transport of Bingham nanofluid

The effects of slip condition and Joule heating on the peristaltic flow of Bingham nanofluid are investigated. The flow is taken in a porous channel with elastic walls. Mathematical formulation is presented under the assumption of long wavelength and small Reynolds number. The transformed equations for the flow are solved to seek values for the nanoparticles velocity, concentration and temperature along the channel length. Graphs are plotted to evaluate the behavior of various physical parameters on flow quantities in both slip and no-slip cases. The main features of the physical parameters are highlighted on the inclined non uniform channel. The results show an increment in velocity with rise in inclination and porosity while it reduces with magnetic field. Moreover, nanofluid favors the heat transfer and decline the concentration.

Darcy–Forchheimer Radiative Flow of Micropoler CNT Nanofluid in Rotating Frame with Convective Heat Generation/Consumption

Since 1991, from the beginning of the carbon nanotube era, this has been a focus point for investigation due to its synthetic and simple nature. Unique properties like good stiffness, high surface area, and resilience of carbon nanotubes (CNTs) have been investigated in many engineering applications such as hydrogen storage, composite material, energy storage, electrochemical super-capacitors, transistors, sensors, and field-emitting devices. Keeping in view these applications, we investigate single and multi-walled CNTs nanofluid flow having water as the base fluid between parallel and horizontal rotating plates with microstructure and inertial properties. The thermal radiation effect is considered for variable phenomenon of heat generation/consumption. The principal equations are first symmetrically transformed to a system of nonlinear coupled ordinary differential equations (ODEs), and then, Homotopy Analysis Technique (HAM) and numerical method are employed for solving these coupled equations. The obtained analytical and numerical results are explained graphically and through different tables. The HAM and numerical results show an excellent agreement. The Skin friction and the Nusselt number are numerically calculated and then analyzed with the already published results, and these results are found to be in agreement with one another. The impact of important parameters are shown graphically.

Numerical Simulation and Mathematical Modeling of Electro-Osmotic Couette–Poiseuille Flow of MHD Power-Law Nanofluid with Entropy Generation

The basic motivation of this investigation is to develop an innovative mathematical model for electro-osmotic flow of Couette–Poiseuille nanofluids. The power-law model is treated as the base fluid suspended with nano-sized particles of aluminum oxide (Al2O3). The uniform speed of the upper wall in the axial path generates flow, whereas the lower wall is kept fixed. An analytic solution for nonlinear flow dynamics is obtained. The ramifications of entropy generation, magnetic field, and a constant pressure gradient are appraised. Moreover, the physical features of most noteworthy substantial factors such as the electro-osmotic parameter, magnetic parameter, power law fluid parameter, skin friction, Nusselt number, Brinkman number, volume fraction, and concentration are adequately delineated through various graphs and tables. The convergence analysis of the obtained solutions has been discussed explicitly. Recurrence formulae in each case are also presented.

Energy Storage Analysis of UIO-66 and Water Mixed Nanofluids: An Experimental and Theoretical Study

The thermal energy storage properties of a working fluid can be modified by the exothermic and endothermic adsorption and desorption of fluid molecules in the micro/nanoporous materials. In this study, thermogravimetric (TG) analysis experiments and molecular simulations (molecular dynamics, MD, and grand canonical Monte Carlo, GCMC) were employed to examine the thermal energy storage properties of the UIO-66 metal organic framework material, UIO-66/H2O nanofluids and pure water. Our results showed that the molecular simulation calculations were, in principle, consistent with the obtained experimental data. The thermal energy storage performance of UIO-66/H2O nanofluids was enhanced with the increase in the UIO-66 mass fraction. In addition, the differences between the simulation calculations and experimental results could be mainly ascribed to the different structures of UIO-66 and the evaporation of fluid samples. Furthermore, this work indicated that molecular simulations contributed to developing novel working pairs of metal organic heat carriers (MOHCs).