Identification of extracellular nanoparticle subsets by nuclear magnetic resonance

Exosomes are a subset of secreted lipid envelope-encapsulated extracellular vesicles (EVs) of 50–150 nm diameter that can transfer cargo from donor to acceptor cells. In the current purification protocols of exosomes, many smaller and larger nanoparticles such as lipoproteins, exomers and microvesicles are typically co-isolated as well. Particle size distribution is one important characteristics of EV samples, as it reflects the cellular origin of EVs and the purity of the isolation. However, most of the physicochemical analytical methods today cannot illustrate the smallest exosomes and other small particles like the exomers. Here, we demonstrate that diffusion ordered spectroscopy (DOSY) nuclear magnetic resonance (NMR) method enables the determination of a very broad distribution of extracellular nanoparticles, ranging from 1 to 500 nm. The range covers sizes of all particles included in EV samples after isolation. The method is non-invasive, as it does not require any labelling or other chemical modification. We investigated EVs secreted from milk as well as embryonic kidney and renal carcinoma cells. Western blot analysis and immuno-electron microscopy confirmed expression of exosomal markers such as ALIX, TSG101, CD81, CD9, and CD63 in the EV samples. In addition to the larger particles observed by nanoparticle tracking analysis (NTA) in the range of 70–500 nm, the DOSY distributions include a significant number of smaller particles in the range of 10–70 nm, which are visible also in transmission electron microscopy images but invisible in NTA. Furthermore, we demonstrate that hyperpolarized chemical exchange saturation transfer (Hyper-CEST) with ¹²⁹Xe NMR indicates also the existence of smaller and larger nanoparticles in the EV samples, providing also additional support for DOSY results. The method implies also that the Xe exchange is significantly faster in the EV pool than in the lipoprotein/exomer pool.

Diffusion and xenon NMR based methods to determine a very broad range of sizes and sub-sets of extracellular vesicles.     

Time-of-flight remote detection MRI of thermally modified wood

We demonstrate that time-of-flight (TOF) remote detection (RD) magnetic resonance imaging (MRI) provides detailed information about physical changes in wood due to thermal modification that is not available with conventional nuclear magnetic resonance (NMR) based techniques. In the experiments, xenon gas was forced to flow through Pinus sylvestris pine wood samples, and the flow paths and dispersion of gas atoms were observed by measuring ¹²⁹Xe TOF RD MRI images from the samples. MRI sensitivity of xenon was boosted by the spin exchange optical pumping (SEOP) method. Two different samples were studied: a reference sample, dried at low temperature, and a modified sample, which was thermally modified at 240 °C after the drying. The samples were taken next to each other from the same wood plank in order to ensure the comparability of the results. The most important conclusion is that both the smaller dispersion observed in all the TOF RD experiments independent of each other and the decreased amount of flow paths shown by the time projection of z-encoded TOF RD MRI experiment imply that a large amount of pits connecting tracheid cells are closed in thermal modification. Closed pits may be one reason for reduced moisture content and improved dimensional stability of wood achieved in thermal modification. This is the first time biological samples have been investigated by TOF RD MRI.     

Quantifying the diffusion of a fluid through membranes by double phase encoded remote detection magnetic resonance imaging

We demonstrate that a position correlation magnetic resonance imaging (MRI) experiment based on two phase encoding steps separated by a delay can be used for quantifying diffusion across a membrane. This method is noninvasive, and no tracer substance or concentration gradient across the membrane is required. Because, in typical membranes, the T1 relaxation time of the fluid spins is usually much longer than the T2 time, we developed and implemented a new position correlation experiment based on a stimulated spin-echo, in which the relaxation attenuation of the signal is dominated by T1 instead of T2. This enables using relatively long delays needed in the diffusion measurements. The sensitivity of the double encoded experiment detected in a conventional way is still low because of the low filling factor of the fluid inside the NMR coil around the sample. We circumvent this problem by using the remote detection technique, which significantly increases the sensitivity, making it possible to do the measurements with gaseous fluids that have a low spin-density compared to liquids. We derive a model that enables us to extract a diffusion constant characterizing the diffusion rate through the membrane from the obtained correlation images. The double phase encoded MRI method is advantageous in any kind of diffusion studies, because the propagator of fluid molecules can directly be seen from the correlation image.     

Characterization of microfluidic gas reactors using remote-detection MRI and parahydrogen-induced polarization

A substantial boost in sensitivity (almost 10(5) -fold) achieved by combining remote-detection MRI and parahydrogen-induced polarization enabled microfluidic reactor imaging. Quantitative estimates of nuclear spin hyperpolarization, reaction product distribution, mass transport, and adsorption in the microfluidic reactors could thus be determined in?situ. The reactors also serve as microfluidic nuclear spin polarizers.     

Xenon porometry at room temperature

Xenon porometry is a method in which porous material is immersed in a medium and the properties of the material are studied by means of 129Xe nuclear magnetic resonance (NMR) of xenon gas dissolved in the medium. For instance, the chemical shift of a particular signal (referred to as signal D) arising from xenon inside small pockets formed in the pores during the freezing of the confined medium is highly sensitive to the pore size. In the present study, we show that when naphthalene is used as the medium the pore size distribution of the material can be determined by measuring a single one-dimensional spectrum near room temperature and converting the chemical shift scale of signal D to the pore radius scale by using an experimentally determined correlation. A model has been developed that explains the curious behavior of the chemical shift of signal D as a function of pore radius. The other signals of the spectra measured at different temperatures have also been identified, and the influence of xenon pressure on the spectra has been studied. For comparison, 129Xe NMR spectra of pure xenon gas adsorbed to porous materials have been measured and analyzed.     

Lab‐on‐a‐Chip Reactor Imaging with Unprecedented Chemical Resolution by Hadamard‐Encoded Remote Detection NMR

The development of microfluidic processes requires information‐rich detection methods. Here we introduce the concept of remote detection exchange NMR spectroscopy (RD‐EXSY), and show that, along with indirect spatial information extracted from time‐of‐flight data, it provides unique information about the active regions, reaction pathways, and intermediate products in a lab‐on‐a‐chip reactor. Furthermore, we demonstrate that direct spatial resolution can be added to RD‐EXSY efficiently by applying the principles of Hadamard spectroscopy.     

Behavior of acetonitrile confined to mesoporous silica gels as studied by 129Xe NMR: a novel method for determining the pore sizes

129Xe NMR spectra of xenon dissolved in acetonitrile confined into three mesoporous silica gels with nominal pore diameters of 40, 60, and 100 A have been measured over the temperature range 170-245 K. The spectra consist of a number of lines, which contain detailed information on the system. The most interesting result is that the chemical shift of a particular signal observed below the melting point of confined acetonitrile is highly sensitive to the pore size, and hence its shape is sensitive to the pore size distribution function. This signal originates from the xenon atoms sited in very small cavities built up inside the pores during the freezing transition. It can be used to determine the size or even the size distribution function of the pores. In addition, the emergence of this signal reveals the phase transition temperature of acetonitrile inside the pores, which can also be used to determine the size of the pores. The difference in the chemical shifts of two other signals, which arise from xenon dissolved in bulk and confined acetonitrile, provides still another novel method for determining the size of the pores.     

Relativistic spin-orbit coupling effects on secondary isotope shifts of (13)C nuclear shielding in CX(2) (X = O, S, Se, Te)

Rovibrational corrections, temperature dependence, and secondary isotope shifts of the (13)C nuclear shielding in CX(2) (X = O, S, Se, Te) are calculated taking into account the relativistic spin-orbit (SO) interaction. The SO effect is considered for the first time for the secondary isotope shifts. The nuclear shielding hypersurface in terms of nuclear displacements is calculated by using a density-functional theory method. Ab initio multiconfiguration self-consistent field calculations are done at the equilibrium geometry for comparison. (13)C NMR measurements are carried out for CS(2). The calculated results are compared with both present and earlier experimental data on CO(2), CS(2), and CSe(2). The heavy-atom SO effects on the rovibrational corrections of (13)C shielding are shown to be significant. For CSe(2) and CTe(2), reliable prediction of secondary isotope effects and their temperature dependence requires the inclusion of the SO corrections. In particular, earlier discrepancies of theory and experiment for CSe(2) are fully resolved by taking the SO interactions into account.     

A Bayesian molecular interaction library

We describe a library of molecular fragments designed to model and predict non-bonded interactions between atoms. We apply the Bayesian approach, whereby prior knowledge and uncertainty of the mathematical model are incorporated into the estimated model and its parameters. The molecular interaction data are strengthened by narrowing the atom classification to 14 atom types, focusing on independent molecular contacts that lie within a short cutoff distance, and symmetrizing the interaction data for the molecular fragments. Furthermore, the location of atoms in contact with a molecular fragment are modeled by Gaussian mixture densities whose maximum a posteriori estimates are obtained by applying a version of the expectation-maximization algorithm that incorporates hyperparameters for the components of the Gaussian mixtures. A routine is introduced providing the hyperparameters and the initial values of the parameters of the Gaussian mixture densities. A model selection criterion, based on the concept of a `minimum message length' is used to automatically select the optimal complexity of a mixture model and the most suitable orientation of a reference frame for a fragment in a coordinate system. The type of atom interacting with a molecular fragment is predicted by values of the posterior probability function and the accuracy of these predictions is evaluated by comparing the predicted atom type with the actual atom type seen in crystal structures. The fact that an atom will simultaneously interact with several molecular fragments forming a cohesive network of interactions is exploited by introducing two strategies that combine the predictions of atom types given by multiple fragments. The accuracy of these combined predictions is compared with those based on an individual fragment. Exhaustive validation analyses and qualitative examples (e.g., the ligand-binding domain of glutamate receptors) demonstrate that these improvements lead to effective modeling and prediction of molecular interactions.     

Ultrafast Multidimensional Laplace NMR Using a Single‐Sided Magnet

Laplace NMR (LNMR) consists of relaxation and diffusion measurements providing detailed information about molecular motion and interaction. Here we demonstrate that ultrafast single‐ and multidimensional LNMR experiments, based on spatial encoding, are viable with low‐field, single‐sided magnets with an inhomogeneous magnetic field. This approach shortens the experiment time by one to two orders of magnitude relative to traditional experiments, and increases the sensitivity per unit time by a factor of three. The reduction of time required to collect multidimensional data opens significant prospects for mobile chemical analysis using NMR. Particularly tantalizing is future use of hyperpolarization to increase sensitivity by orders of magnitude, allowed by single‐scan approach.