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- ItemTargeted T1 Magnetic Resonance Imaging Contrast Enhancement with Extraordinarily Small CoFe2O4 Nanoparticles(Washington, DC : American Chemical Society, 2019) PichĂ©, Dominique; Tavernaro, Isabella; Fleddermann, Jana; Lozano, Juan G.; Varambhia, Aakash; Maguire, Mahon L.; Koch, Marcus; Ukai, Tomofumi; Hernández RodrĂguez, Armando J.; Jones, Lewys; Dillon, Frank; Reyes Molina, Israel; Mitzutani, Mai; González Dalmau, Evelio R.; Maekawa, Toru; Nellist, Peter D.; Kraegeloh, Annette; Grobert, NicoleExtraordinarily small (2.4 nm) cobalt ferrite nanoparticles (ESCIoNs) were synthesized by a one-pot thermal decomposition approach to study their potential as magnetic resonance imaging (MRI) contrast agents. Fine size control was achieved using oleylamine alone, and annular dark-field scanning transmission electron microscopy revealed highly crystalline cubic spinel particles with atomic resolution. Ligand exchange with dimercaptosuccinic acid rendered the particles stable in physiological conditions with a hydrodynamic diameter of 12 nm. The particles displayed superparamagnetic properties and a low r2/r1 ratio suitable for a T1 contrast agent. The particles were functionalized with bile acid, which improved biocompatibility by significant reduction of reactive oxygen species generation and is a first step toward liver-targeted T1 MRI. Our study demonstrates the potential of ESCIoNs as T1 MRI contrast agents.
- ItemA Review on Data Fusion of Multidimensional Medical and Biomedical Data(Basel : MDPI, 2022) Azam, Kazi Sultana Farhana; Ryabchykov, Oleg; Bocklitz, ThomasData fusion aims to provide a more accurate description of a sample than any one source of data alone. At the same time, data fusion minimizes the uncertainty of the results by combining data from multiple sources. Both aim to improve the characterization of samples and might improve clinical diagnosis and prognosis. In this paper, we present an overview of the advances achieved over the last decades in data fusion approaches in the context of the medical and biomedical fields. We collected approaches for interpreting multiple sources of data in different combinations: image to image, image to biomarker, spectra to image, spectra to spectra, spectra to biomarker, and others. We found that the most prevalent combination is the image-to-image fusion and that most data fusion approaches were applied together with deep learning or machine learning methods.
- ItemThe 2018 correlative microscopy techniques roadmap(Bristol : IOP Publishing, 2018) Ando, Toshio; Bhamidimarri, Satya Prathyusha; Brending, Niklas; Colin-York, H; Collinson, Lucy; De Jonge, Niels; de Pablo, P J; Debroye, Elke; Eggeling, Christian; Franck, Christian; Fritzsche, Marco; Gerritsen, Hans; Giepmans, Ben N G; Grunewald, Kay; Hofkens, Johan; Hoogenboom, Jacob P; Janssen, Kris P F; Kaufmann, Rainer; Klumpermann, Judith; Kurniawan, Nyoman; Kusch, Jana; Liv, Nalan; Parekh, Viha; Peckys, Diana B; Rehfeldt, Florian; Reutens, David C; Roeffaers, Maarten B J; Salditt, Tim; Schaap, Iwan A T; Schwarz, Ulrich S; Verkade, Paul; Vogel, Michael W; Wagner, Richard; Winterhalter, Mathias; Yuan, Haifeng; Zifarelli, GiovanniDevelopments in microscopy have been instrumental to progress in the life sciences, and many new techniques have been introduced and led to new discoveries throughout the last century. A wide and diverse range of methodologies is now available, including electron microscopy, atomic force microscopy, magnetic resonance imaging, small-angle x-ray scattering and multiple super-resolution fluorescence techniques, and each of these methods provides valuable read-outs to meet the demands set by the samples under study. Yet, the investigation of cell development requires a multi-parametric approach to address both the structure and spatio-temporal organization of organelles, and also the transduction of chemical signals and forces involved in cell–cell interactions. Although the microscopy technologies for observing each of these characteristics are well developed, none of them can offer read-out of all characteristics simultaneously, which limits the information content of a measurement. For example, while electron microscopy is able to disclose the structural layout of cells and the macromolecular arrangement of proteins, it cannot directly follow dynamics in living cells. The latter can be achieved with fluorescence microscopy which, however, requires labelling and lacks spatial resolution. A remedy is to combine and correlate different readouts from the same specimen, which opens new avenues to understand structure–function relations in biomedical research. At the same time, such correlative approaches pose new challenges concerning sample preparation, instrument stability, region of interest retrieval, and data analysis. Because the field of correlative microscopy is relatively young, the capabilities of the various approaches have yet to be fully explored, and uncertainties remain when considering the best choice of strategy and workflow for the correlative experiment. With this in mind, the Journal of Physics D: Applied Physics presents a special roadmap on the correlative microscopy techniques, giving a comprehensive overview from various leading scientists in this field, via a collection of multiple short viewpoints.
- ItemSpin-Dependent Phenomena in Semiconductor Micro-and Nanoparticles - From Fundamentals to Applications(Basel : MDPI, 2020) Fomin, Vladimir M.; Timoshenko, Victor Y.The present overview of spin-dependent phenomena in nonmagnetic semiconductor microparticles (MPs) and nanoparticles (NPs) with interacting nuclear and electron spins is aimed at covering a gap between the basic properties of spin behavior in solid-state systems and a tremendous growth of the experimental results on biomedical applications of those particles. The first part of the review represents modern achievements of spin-dependent phenomena in the bulk semiconductors from the theory of optical spin orientation under indirect optical injection of carriers and spins in the bulk crystalline silicon (c-Si)—via numerous insightful findings in the realm of characterization and control through the spin polarization—to the design and verification of nuclear spin hyperpolarization in semiconductor MPs and NPs for magnetic resonance imaging (MRI) diagnostics. The second part of the review is focused on the electron spin-dependent phenomena in Si-based nanostructures, including the photosensitized generation of singlet oxygen in porous Si and design of Si NPs with unpaired electron spins as prospective contrast agents in MRI. The experimental results are analyzed by considering both the quantum mechanical approach and several phenomenological models for the spin behavior in semiconductor/molecular systems. Advancements and perspectives of the biomedical applications of spin-dependent properties of Si NPs for diagnostics and therapy of cancer are discussed.