Magnetic Resonance Relaxometry Research Articles

Facile One-Pot Green Synthesis of Magneto-Luminescent Bimetallic Nanocomposites with Potential as Dual Imaging Agent

Nanocomposites serving as dual (bimodal) probes have great potential in the field of bio-imaging. Here, we developed a simple one-pot synthesis for the reproducible generation of new luminescent and magnetically active bimetallic nanocomposites. The developed one-pot synthesis was performed in a sequential manner and obeys the principles of green chemistry. Briefly, bovine serum albumin (BSA) was exploited to uptake Au (III) and Fe (II)/Fe (III) ions simultaneously. Then, Au (III) ions were transformed to luminescent Au nanoclusters embedded in BSA (AuNCs-BSA) and majority of Fe ions were bio-embedded into superparamagnetic iron oxide nanoparticles (SPIONs) by the alkalization of the reaction medium. The resulting nanocomposites, AuNCs-BSA-SPIONs, represent a bimodal nanoprobe. Scanning transmission electron microscopy (STEM) imaging visualized nanostructures with sizes in units of nanometres that were arranged into aggregates. Mössbauer spectroscopy gave direct evidence regarding SPION presence. The potential applicability of these bimodal nanoprobes was verified by the measurement of their luminescent features as well as magnetic resonance (MR) imaging and relaxometry. It appears that these magneto-luminescent nanocomposites were able to compete with commercial MRI contrast agents as MR displays the beneficial property of bright luminescence of around 656 nm (fluorescence quantum yield of 6.2 ± 0.2%). The biocompatibility of the AuNCs-BSA-SPIONs nanocomposite has been tested and its long-term stability validated.

Lower Myelin Content Is Associated With Lower Gait Speed in Cognitively Unimpaired Adults.

Mounting evidence indicates that abnormal gait speed predicts the progression of neurodegenerative diseases, including Alzheimer's disease. Understanding the relationship between white matter integrity, especially myelination, and motor function is crucial to the diagnosis and treatment of neurodegenerative diseases. We recruited 118 cognitively unimpaired adults across an extended age range of 22-94 years to examine associations between rapid or usual gait speeds and cerebral myelin content. Using our advanced multicomponent magnetic resonance relaxometry method, we measured myelin water fraction (MWF), a direct measure of myelin content, as well as longitudinal and transverse relaxation rates (R1 and R2), sensitive but nonspecific magnetic resonance imaging measures of myelin content. After adjusting for covariates and excluding 22 data sets due to cognitive impairments or artifacts, our results indicate that participants with higher rapid gait speed exhibited higher MWF, R1, and R2 values, that is, higher myelin content. These associations were statistically significant within several white matter brain regions, particularly the frontal and parietal lobes, splenium, anterior corona radiata, and superior fronto-occipital and longitudinal fasciculus. In contrast, we did not find any significant associations between usual gait speed and MWF, R1, or R2, which suggests that rapid gait speed may be a more sensitive marker of demyelination than usual gait speed. These findings advance our understanding on the implication of myelination in gait impairment among cognitively unimpaired adults, providing further evidence of the interconnection between white matter integrity and motor function.

Molecular Dynamics of Jelly Candies by Means of Nuclear Magnetic Resonance Relaxometry

1H spin-lattice Nuclear Magnetic Resonance relaxation studies have been performed for different kinds of Haribo jelly and Vidal jelly in a very broad frequency range from about 10 kHz to 10 MHz to obtain insight into the dynamic and structural properties of jelly candies on the molecular level. This extensive data set has been thoroughly analyzed revealing three dynamic processes, referred to as slow, intermediate and fast dynamics occurring on the timescale of 10-6 s, 10-7 s and 10-8 s, respectively. The parameters have been compared for different kinds of jelly for the purpose of revealing their characteristic dynamic and structural properties as well as to enquire into how increasing temperature affects these properties. It has been shown that dynamic processes in different kinds of Haribo jelly are similar (this can be treated as a sign of their quality and authenticity) and that the fraction of confined water molecules is reduced with increasing temperature. Two groups of Vidal jelly have been identified. For the first one, the parameters (dipolar relaxation constants and correlation times) match those for Haribo jelly. For the second group including cherry jelly, considerable differences in the parameters characterizing their dynamic properties have been revealed.

Water Dynamics in Highly Concentrated Protein Systems—Insight from Nuclear Magnetic Resonance Relaxometry

1H spin-lattice relaxation experiments have been performed for water-Bovine Serum Albumin (BSA) mixtures, including 20%wt and 40%wt of BSA. The experiments have been carried out in a frequency range encompassing three orders of magnitude, from 10 kHz to 10 MHz, versus temperature. The relaxation data have been thoroughly analyzed in terms of several relaxation models with the purpose of revealing the mechanisms of water motion. For this purpose, four relaxation models have been used: the data have been decomposed into relaxation contributions expressed in terms of Lorentzian spectral densities, then three-dimensional translation diffusion has been assumed, next two-dimensional surface diffusion has been considered, and eventually, a model of surface diffusion mediated by acts of adsorption to the surface has been employed. In this way, it has been demonstrated that the last concept is the most plausible. Parameters describing the dynamics in a quantitative manner have been determined and discussed.

Determination of soil pore size distribution and water retention curve by internal magnetic field modulation at low field 1H NMR

The determination of the soil pore size distribution, water retention curve, and derived parameters that control important processes in soils, such as water supply for plants; infiltration; water and solute movement in soils; erosion; plant nutrients and contaminants transport, etc, are challenging and the available methods are expensive, time-consuming and prone to bias and errors. The use of 1H Nuclear Magnetic Resonance (NMR) relaxometry to characterise the soil porosity and hydraulic properties through spin-lattice and spin-spin relaxometry results in an ill-posed problem with two correlated unknown quantities: the pore length scales, and surface relaxivity. To overcome this limitation of NMR relaxometry, we propose the use of a method that directly accesses the NMR diffusion modes governed only by the pore size, and therefore, independent of the unknown surface relaxivity. The manuscript describes an unprecedent application in Soil Science of the Decay due to Diffusion in Internal Field (DDIF) method to successfully determine the pore size distribution of undisturbed soil samples, as well as to estimate the water retention curves from the pore size distribution.

Unusual water molecules at surfactant, lipid, and protein interfaces.

The structure and dynamics of water has captivated the interest of researchers for decades, motivated in large measure by the importance of these properties in biological systems at interfaces. However, techniques that can routinely deal with delicate, dynamic, and heterogenous natural systems, such as proteins embedded near or in lipid membranes, remains an area of active development. Magnetic Resonance (MR) experiments rely on resonance frequencies many orders of magnitude slower than those of, e.g., ultrafast laser experiments that have shown earlier promise for interrogating interfacial systems. Nonetheless, MR relaxometry techniques can still probe fast molecular dynamics in the frequency domain through a set of techniques known as relaxometry.

Low-field NMR investigations on dynamics of crude oil confined into nanoporous silica rods and white powder.

In the present study, to mimic the natural confinement of crude oils, model experiments are conducted with crude oils having different physical properties and maltenes of parent crude oils without asphaltenes confined into engineered nanoporous silica rods with pore diameters of 2.5 and 10.0nm and white powdered nanoporous silica with pore diameters of 2.5 and 4.0nm. This will help with suggesting potential treatments for enhancing crude oil recovery. Low-field nuclear magnetic resonance (LF-NMR) relaxometry has been applied to achieve this goal. The nanoporous proxies resemble real-life nanoporous rocks of reservoirs. The dynamics of confined crude oils with different oAPI gravity deviate from bulk dynamics, and deviation changes depending on the oAPI gravity. This suggests that treatments must be decided appropriately before crude oil production. Similar treatments could be applied for light and medium-heavy crude oils. Mathematical analysis of NMR relaxation curves of confined crude oils with different fractions of SARA (saturates, aromatics, resins, asphaltenes) indicates that the conventional SARA approach needs a better definition for the confined state of matter. The NMR relaxation behavior of confined maltenes shows that resin molecules might act like saturates in natural confinement with various scale pores from nano to micro and even macro, or aromatics might show resin-like behaviors. Confinement of brine and a light crude oil into white powdered nanoporous silica proxies demonstrates that brine could be utilized along with some additives such as nanoparticles for oil recovery. Therefore, these issues must be evaluated in deciding the proper treatments for crude oil production.

Graphene quantum dots-based magnetic relaxation switch involving magnetic separation for enhanced performances of endoglin detection using ultra-low-field nuclear magnetic resonance relaxometry

Magnetic relaxation switches (MRS) based on target-induced state changes of magnetic nanoparticles are vital approaches for biomolecule detection in in vitro diagnosis. Recently, magnetic graphene quantum dots have been employed as magnetic probes instead of iron oxide nanoparticles and showed high sensitivity. Introducing magnetic separation into an MRS assay before the relaxometry measurements can enhance the sensitivity, elevate accuracy, and expand the linear region. In this work, magnetic separation-assisted MRS was developed to detect endoglin utilizing iron oxide as the magnetic carrier and magnetic graphene quantum dots as the magnetic probe. The assay possesses a broad linear region from 5 ng/mL to 50 μg/mL and a sensitive limit of detection of 1.3 ng/mL, which is two orders of magnitude lower than that of MRS without magnetic separation. The high accuracy and consistency have been proved for endoglin (CD105) detection in real samples. This graphene quantum dot-based MRS involving magnetic separation provides a new route for enhancing the sensitivity and accuracy of biomolecule detection.

Nuclear magnetic resonance relaxometry to monitor chromium (VI) reduction by hydrogen peroxide, ascorbic acid, and aluminum powder.

The reduction of K2 Cr2 O7 solutions by H2 O2 was studied by nuclear magnetic resonance (NMR) relaxometry and UV-vis spectroscopy in HCl/KCl buffer (pH 2), NaCl/glycine/HCl buffer (pH 3), and sodium acetate/acetic acid buffer (pH 4). Because of Cr(III) paramagnetism, 1/T1 and 1/T2 of the solutions increase during the reduction of diamagnetic Cr(VI). This increase is proportional to the produced Cr(III) concentration. Using different initial H2 O2 concentrations, partially reduced Cr(VI) samples were prepared and studied by T1 and T2 relaxometry and by UV-vis spectroscopy. The correlation between the relaxation rates and the concentration of Cr(VI) remaining in the sample, measured by spectroscopy, was excellent. It was possible, thanks to the measurement of T2 , to study the kinetics of the reduction of K2 Cr2 O7 by H2 O2 in the pH 3 and pH 4 buffers. The reduction of Cr(VI) by ascorbic acid was successfully monitored by NMR relaxometry in the pH 2 buffer. The presence of complexing molecules/ions was shown to drastically influence the nuclear magnetic relaxation dispersion profiles of reduced K2 Cr2 O7 solutions: Both relaxation rates are divided by ~5 when citrate or acetate ions are present and by ~3 in the presence of ascorbic acid. Therefore, the comparison of relaxation results obtained in different reaction mixtures must be done carefully. When all the solutions are set to pH 0, which prevents any complexation, the longitudinal and transverse relaxation rates of all samples become comparable. Finally, as a proof of concept for a turbid solution, the kinetics of the reduction of a K2 Cr2 O7 solution by aluminum powder in the pH 2 buffer was successfully monitored.

An automatic [formula omitted]-based regularization method for the analysis of FFC dispersion profiles with quadrupolar peaks

Fast Field-Cycling Nuclear Magnetic Resonance relaxometry is a non-destructive technique to investigate molecular dynamics and structure of systems having a wide range of applications such as environment, biology, and food. Besides a considerable amount of literature about modeling and application of such technique in specific areas, an algorithmic approach to the related parameter identification problem is still lacking. We believe that a robust algorithmic approach will allow a unified treatment of different samples in several application areas. In this paper, we model the parameters identification problem as a constrained L1-regularized non-linear least squares problem. Following the approach proposed in [Analytical Chemistry2021 93 (24)], the non-linear least squares term imposes data consistency by decomposing the acquired relaxation profiles into relaxation contributions associated with 1H−1H and 1H−14N dipole-dipole interactions. The data fitting and the L1-based regularization terms are balanced by the so-called regularization parameter. For the parameters identification, we propose an algorithm that computes, at each iteration, both the regularization parameter and the model parameters. In particular, the regularization parameter value is updated according to a Balancing Principle and the model parameters values are obtained by solving the corresponding L1-regularized non-linear least squares problem by means of the non-linear Gauss-Seidel method. We analyse the convergence properties of the proposed algorithm and run extensive testing on synthetic and real data. A Matlab software, implementing the presented algorithm, is available upon request to the authors.

Quadrupolar 23Na+ NMR relaxation as a probe of subpicosecond collective dynamics in aqueous electrolyte solutions

Nuclear magnetic resonance relaxometry represents a powerful tool for extracting dynamic information. Yet, obtaining links to molecular motion is challenging for many ions that relax through the quadrupolar mechanism, which is mediated by electric field gradient fluctuations and lacks a detailed microscopic description. For sodium ions in aqueous electrolytes, we combine ab initio calculations to account for electron cloud effects with classical molecular dynamics to sample long-time fluctuations, and obtain relaxation rates in good agreement with experiments over broad concentration and temperature ranges. We demonstrate that quadrupolar nuclear relaxation is sensitive to subpicosecond dynamics not captured by previous models based on water reorientation or cluster rotation. While ions affect the overall water retardation, experimental trends are mainly explained by dynamics in the first two solvation shells of sodium, which contain mostly water. This work thus paves the way to the quantitative understanding of quadrupolar relaxation in electrolyte and bioelectrolyte systems.

Monitoring the Effect of Calcium Nitrate on the Induction Period of Cement Hydration via Low-Field NMR Relaxometry.

The hydration process of Portland cement is still not completely understood. For instance, it is not clear what produces the induction period, which follows the initial period of fast reaction, and is characterized by a reduced reactivity. To contribute to such understanding, we compare here the hydration process of two cement samples, the simple cement paste and the cement paste containing calcium nitrate as an accelerator. The hydration of these samples is monitored during the induction period using two different low-field nuclear magnetic resonance (NMR) relaxometry techniques. The transverse relaxation measurements of the 1H nuclei at 20 MHz resonance frequency show that the capillary pore water is not consumed during the induction period and that this stage is shortened in the presence of calcium nitrate. The longitudinal relaxation measurements, performed at variable Larmor frequency of the 1H nuclei, reveal a continuous increase in the surface-to-volume ratio of the capillary pores, even during the induction period, and this increase is faster in the presence of calcium nitrate. The desorption time of water molecules from the surface was also evaluated, and it increases in the presence of calcium nitrate.

Modification of the SDR equation for permeability prediction

We evaluate the potential of permeability prediction of the original and modified versions of the Schlumberger-Doll Research (SDR) equation that is applied to data of nuclear magnetic resonance (NMR) relaxometry. Different definitions of characteristic relaxation time are considered. In a further modification, pore radius replaces the characteristic relaxation time in the original SDR equation. Only a good estimate of the surface relaxivity enables a reliable transformation from the relaxation time distribution (RTD) into the pore radius distribution (PRD). A recently published approach considers the specific surface area per unit pore volume (Spor) and the weighted harmonic mean (T2hm) of the RTD for the determination of an individual value of surface relaxivity for each sample. The evaluation is performed for three sample sets originating from different sandstone formations. The good predictive quality of the original SDR equation is confirmed. However, the prefactors have to be adjusted by calibrating with core data. We demonstrate that the use of average pore radii instead of average relaxation times enables a better permeability prediction. The weighted harmonic mean of the PRD, which proves to be a reliable proxy for the effective hydraulic radius, provides a high quality permeability prediction.

Numerical study of NMR relaxation responses in synthetic clayey sandstone by dual-scale modeling

Nuclear Magnetic Resonance (NMR) relaxometry is a common technique for petrophysical characterization of sedimentary rocks. The standard interpretation of NMR relaxation response assumes that the fast diffusion limit is valid for the whole pore space, allowing to translate transverse relaxation components into pore apertures. However, porous media naturally exhibit multiple length scales. The diffusion between different sized pores may modify the transverse relaxation rate, weakening the relationship with corresponding pore size populations. Focusing on sandstones, we investigate the impact of diffusion coupling on transverse relaxation depending on kaolinite amount, spatial distribution and temperature. A series of synthetic clayey sandstone models with different clay amounts and morphological distributions (pore-lining, pore-filling and laminated) are generated based on a micro-CT image of an actual Bentheimer sandstone. A dual-scale random walk NMR relaxation simulation with resolved multi-porosity kaolinite models is utilized to avoid problems in near to interface exchange regions typical for effective medium representations. Simulations provide spatially resolved dynamics of magnetization exchange between different porosity populations. The results indicate that increased temperature and kaolinite clay amount with lower micro-porosity allows higher magnetization exchange between micro- and macro- porous regions. Pore-lining clay demonstrates stronger diffusional coupling effects, leading to an overestimation of micro-porosity. We further discuss the impact of diffusion coupling on NMR-estimated permeability via SDR and Coates models.

Variational Mode Decomposition for NMR Echo Data Denoising

Nuclear magnetic resonance (NMR) relaxometry, a noninvasive and nondestructive method, is a key technique for unconventional reservoir evaluation. Echo data detected from NMR instrument, a kind of weak signal, however, is characterized by a low signal-to-noise ratio (SNR). The achievement of NMR relaxation spectra inversion of a high precision, for echo data with a low SNR, is a challenge, which will also affect the unconventional reservoir evaluation of NMR logging. In this article, a variational mode decomposition (VMD) method was proposed for NMR echo data denoising. NMR echo data were decomposed into an ensemble of intrinsic mode functions (IMFs) by the VMD method. The IMF number is an important parameter for VMD, and VMD results are different with various IMF numbers. An optimal selection method for the IMF number was proposed. The decomposed IMFs compose of signals with different frequencies. Noise is from high-frequency signal, but valuable data are from low-frequency signal. The effective IMFs in VMD were selected and summed as the denoised echo data. Numerical simulations and field NMR logging data processing were undertaken to evaluate the NMR echo data denoising effectiveness and practicality of the proposed VMD-based method. The results showed that the inverted NMR spectra exhibit a higher quality after the VMD-based denoise, compared with those for raw echo data and after the empirical mode decomposition (EMD) denoise. This indicates that a higher denoising quality is achieved by the VMD-based method than by the EMD-based method for NMR echo data.

Multiparametric measuring flow complex for express control of oil quality by the method of proton magnetic resonance relaxometry

Multiparametric measuring flow complex for express control of oil quality by the method of proton magnetic resonance relaxometry

Investigation of the effects of high hydrostatic pressure on the functional properties of pea protein isolate

AbstractThis study investigates the effects of high hydrostatic pressure (HHP) on some functional properties of pea protein isolate (PPI). HHP was combined with various temperature and pH conditions to investigate the combined effects of HHP‐based food processing conditions on the functional properties of PPI. Herein, PPI solutions prepared at different pH conditions (3.0, 5.0, and 7.0) were subjected to 300, 400, and 500 MPa HHP treatment at 25 and 50°C for 5 min. Water‐holding capacity (WHC), solubility, and emulsification activity of PPI samples were determined. Additionally, nuclear magnetic resonance (NMR) relaxometry and Fourier transform infrared spectroscopy experiments were performed for further analysis. Maximum WHC (p < 0.05) was observed for the samples treated at 500 MPa‐pH 5.0‐50°C whereas maximum solubility (p < 0.05) belonged to the samples subjected to 300 MPa‐pH 7.0‐50°C treatment conditions. Better emulsification activity was achieved at pH 3.0 regardless of the pressure level applied. The novelty of this study is that NMR relaxometry was introduced as a fast/nondestructive technique to investigate the changes in the functional properties of PPI samples and one of the functional parameters was correlated with NMR relaxation data. Herewith, the longest transverse relaxation time (T2) (p < 0.05) belonged to the samples with maximum WHC. The results showed that HHP is able to modify the functional properties of PPI at specific temperature‐pH combinations, and NMR relaxometry technique has a high potential for such studies.Practical ApplicationsHigh hydrostatic pressure (HHP) is an emerging technology which is used for its diverse range of applications in food science and technology. Modification of physicochemical and functional properties of food ingredients is one of the latest applications of HHP treatment. This study demonstrated that HHP treatment was able to modify some functional properties of pea protein isolate (PPI) samples such as water‐holding capacity (WHC), solubility, and emulsification activity. In addition to pressure level, pH and temperature were also effective on modifying the functional properties of PPI samples. For instance, a high pressure (500 MPa) was required to improve WHC whereas lower pressures (300 MPa) improved the solubility of the samples at high pH and temperature. The results of this study could be used in model HHP studies to improve some functional properties of PPI for different purposes.

Deformation mechanisms of cement paste with ultra-low water-to-cement ratios under different curing conditions at early ages

Cement-based materials with ultra-low water-to-cement ratios (w/c) swell with external water supply, which may cause cracking and strength reduction. Studies on the volumetric stability of cement-based materials ignore the possible expansion occurring in the material before the starting point, standard curing (20 ± 2 ℃ and relative humidity (RH) > 95 %) for 28 d. Thereby, the deformation and mechanical properties of cement paste cured under standard and sealed conditions at early ages were compared. Deformation mechanisms were investigated by thermogravimetric analysis, 1H nuclear magnetic resonance relaxometry, and pore structure measurement. The saturation degree and hydration degree were both estimated. The results show that swelling occurs in cement-based materials with ultra-low w/c under standard curing, with increasing flexural and compressive strength. Gel water and capillary water contribute to large proportions of the total absorbed water. Cement paste with low w/c produces higher swelling when absorbs the same amount of water. Deformation mechanisms are attributed to the mitigation of self-desiccation shrinkage, calcium-silicate-hydrate gel swelling due to water absorbed, and solid volume increase of solids after hydration.

Span of regularization for solution of inverse problems with application to magnetic resonance relaxometry of the brain

We present a new regularization method for the solution of the Fredholm integral equation (FIE) of the first kind, in which we incorporate solutions corresponding to a range of Tikhonov regularizers into the end result. This method identifies solutions within a much larger function space, spanned by this set of regularized solutions, than is available to conventional regularization methods. An additional key development is the use of dictionary functions derived from noise-corrupted inversion of the discretized FIE. In effect, we combine the stability of solutions with greater degrees of regularization with the resolution of those that are less regularized. The span of regularizations (SpanReg) method may be widely applicable throughout the field of inverse problems.

The Endometriotic Neoplasm Algorithm for Risk Assessment (e-NARA) Index Sheds Light on the Discrimination of Endometriosis-Associated Ovarian Cancer from Ovarian Endometrioma.

Magnetic resonance (MR) relaxometry provides a noninvasive tool to discriminate endometriosis-associated ovarian cancer (EAOC) from ovarian endometrioma (OE) with high accuracy. However, this method has a limitation in discriminating malignancy in clinical use because the R2 value depends on the device manufacturer and repeated imaging is unrealistic. The current study aimed to reassess the diagnostic accuracy of MR relaxometry and investigate a more powerful tool to distinguish EAOC from OE. This retrospective study was conducted at our institution from December, 2012, to May, 2022. A total of 150 patients were included in this study. Patients with benign ovarian tumors (n = 108) mainly received laparoscopic surgery, and cases with suspected malignancy (n = 42) underwent laparotomy. Information from a chart review of the patients' medical records was collected. A multiple regression analysis revealed that the age, the tumor diameter, and the R2 value were independent malignant predicting factors. The endometriotic neoplasm algorithm for risk assessment (e-NARA) index provided high accuracy (sensitivity, 85.7%; specificity, 87.0%) to discriminate EAOC from OE. The e-NARA index is a reliable tool to assess the probability of malignant transformation of endometrioma.