Low-cost standalone magnetic particle spectroscopy device for fast and sensitive immunoassays

The recent pandemic has shown how important reliable assays are for determining whether someone is infectious. One promising alternative to the established testing methods are immunoassays with magnetic nanoparticle (MNP) markers using magnetic particle spectroscopy (MPS). In this work we present the development of our “immunoMPS” which was especially built at low cost for immunoassays with infectious samples. It is a completely self-contained, mobile device with total costs of only 300€ that could be used in S2+ laboratories. The device delivers high performance on par or exceeding our lab equipment. Thus, we achieved a significantly lower limit of detection (LOD) of 4x10^8 viruses/mL of our magnetic immunoassays (MIAs) for the detection of mimic SARS-CoV-2 which is about one order of magnitude better than previous results in this research topic. In addition, it is possible to further improve the limit by optimizing the experimental setup and using DC fields

Improvements of magnetic nanoparticle assays for SARS-CoV-2 detection using a mimic virus approach

Immunoassays with magnetic nanoparticles (MNPs) as markers are a promising approach for the fast and sensitive virus detection. Upon binding of antibody-functionalized MNP on virus proteins, the hydrodynamic diameter increases and a change in the Brownian relaxation time can be measured. In this study, we detect the whole SARS-CoV-2 by mimicking it with streptavidin-coated polystyrene beads with biotinylated spike proteins. Changes of the MNP dynamics are measured by alternating current susceptometry and magnetic particle spectroscopy. Due to the multiple binding sites of MNP and virus, crosslinking enlarges the change of the hydrodynamic diameter. In order to improve the sensitivity and the limit of detection of the assay, the ratio of the virus to the MNP amount RMV/MNP is investigated in detail. High RMV/MNP ratios lead to a saturation of the MNPs with viruses, so that the cluster size and therefore the sensitivity decrease again. Additionally, it is found that the smallest virus concentrations can be detected for small MNP concentrations. It is also shown that the RMV/MNP range that can be used for an unambiguous detection of viruses depends on the virus/MNP concentration; it shifts with increasing MNP concentration to smaller RMV/MNP values. For very small virus concentrations, an increase of the Brownian relaxation time is detected implying a decrease of the hydrodynamic diameter. Furthermore, the optimal antibody concentration for MNP functionalization was determined. It is also found that a washing process with a centrifuge improves the sensitivity by reliably removing unbound antibodies and eliminating small MNPs with improper functionalization

Robust approaches for model‐free small‐angle scattering data analysis

The small‐angle neutron scattering data of nanostructured magnetic samples contain information regarding their chemical and magnetic properties. Often, the first step to access characteristic magnetic and structural length scales is a model‐free investigation. However, due to measurement uncertainties and a restricted q range, a direct Fourier transform usually fails and results in ambiguous distributions. To circumvent these problems, different methods have been introduced to derive regularized, more stable correlation functions, with the indirect Fourier transform being the most prominent approach. Here, the indirect Fourier transform is compared with the singular value decomposition and an iterative algorithm. These approaches are used to determine the correlation function from magnetic small‐angle neutron scattering data of a powder sample of iron oxide nanoparticles; it is shown that with all three methods, in principle, the same correlation function can be derived. Each method has certain advantages and disadvantages, and thus the recommendation is to combine these three approaches to obtain robust results.Three different approaches are compared for determination of the correlation function from the small‐angle neutron scattering data of a powder sample of iron oxide nanoparticles

Assessing excitation field frequency for various magnetic nanoparticles

Magnetic detection is presently used in a handheld probe to identify metastasis bearing lymph nodes (LNs) fora variety of oncology applications. This approach utilises the underlying assumption that injected magneticnanoparticles (MNPs) will migrate to LNs with the shortest path to a tumor and therefore will generate a localizedmagnetic signal. Nonlinear magnetic detection is specific for magnetic nanoparticles and negates the influenceof human tissue and surgical instruments. Our nonlinear DiffMag principle uses a combination of an AC and DCmagnetic field to activate MNPs and records the consequent magnetic signal. MNP detection can be optimised tomaximise detection parameters, such as iron sensitivity and detection depth. Tuning the excitation field frequencyto physical properties of MNPs (such as particle diameter) leads to improved detection.This study assesses the magnetic properties of various MNPs (SHP15, SHP20, SHP25, SHP30) and compare thefindings to clinically available MNP (Magtrace®). Magnetization response of these MNPs was acquired using theSuperParamagnetic Quantifier (SPaQ) at various AC field frequencies (1, 2.5, 5, 7.5, 10, 12.5 and 15 kHz). Two featurescapturing magnetization response (maximum signal difference and full width at half maximum) were extracted tocompare MNPs. Additional acquisition captured AC susceptibility (ACS) in the range 10Hz-1MHz.SPaQ results show an optimal excitation frequency between 5 and 12.5 kHz for the various types of MNPs. ACSresults show small particles (SHP15) are Néel dominated, large MNPs (SHP30) are Brownian dominated and thesizes in between show a combination of Néel and Brownian relaxation. The larger, Brownian dominated MNPsperform best in nonlinear magnetic detection

The Dissociation Rate of Acetylacetonate Ligands Governs the Size of Ferrimagnetic Zinc Ferrite Nanocubes

Magnetic nanoparticles are critical to a broad range of applications, from medical diagnostics and therapeutics to biotechnological processes and single molecule manipulation. To advance these applications, facile and robust routes to synthesize highly magnetic nanoparticles over a wide size range are needed. Here, we demonstrate that changing the degassing temperature of thermal decomposition of metal acetylacetonate precursors from 90 to 25°C tunes the size of ferrimagnetic ZnxFe3-xO4 nanocubes from 25 to 100 nm, respectively. We show that degassing at 90°C nearly entirely removes acetylacetone ligands from the reaction, which results in an early formation of monomers and a reaction-controlled growth following LaMer\u27s model towards small nanocubes. In contrast, degassing at 25°C only partially dissociates acetylacetone ligands from the metal center and triggers a delayed formation of monomers, which leads to intermediate assembled structures made of tiny irregular crystallites and an eventual formation of large nanocubes via a diffusion-controlled growth mechanism. Using complementary techniques, we determine the substitution fraction x of Zn2+ to be in the range of 0.35-0.37. Our method reduces the complexity of the thermal decomposition method by narrowing the synthesis parameter space to a single physical parameter and enables fabrication of highly magnetic and uniform zinc ferrite nanocubes over a broad size range. The resulting particles are promising for a range of applications, from magnetic fluid hyperthermia to actuation of macromolecules

Robust approaches for model-free small-angle scattering data analysis

The small-angle neutron scattering data of nanostructured magnetic samples contain information regarding their chemical and magnetic properties. Often, the first step to access characteristic magnetic and structural length scales is a model-free investigation. However, due to measurement uncertainties and a restricted q range, a direct Fourier transform usually fails and results in ambiguous distributions. To circumvent these problems, different methods have been introduced to derive regularized, more stable correlation functions, with the indirect Fourier transform being the most prominent approach. Here, the indirect Fourier transform is compared with the singular value decomposition and an iterative algorithm. These approaches are used to determine the correlation function from magnetic small-angle neutron scattering data of a powder sample of iron oxide nanoparticles; it is shown that with all three methods, in principle, the same correlation function can be derived. Each method has certain advantages and disadvantages, and thus the recommendation is to combine these three approaches to obtain robust results