Concepts in Magnetic Resonance Part A最新文献

The growth of NMR foodomics is described in the context of a study of beef storage. Thirty samples of three meat cuts (chuck, sirloin, and tenderloin) were analyzed using ¹H NMR spectroscopy to determine the influence of storage period and temperature. ¹H showed signals belonging to metabolites namely: acetate, adenosine, adenine, ADP, alanine, betaine, creatine, creatinine, carnosine, fumarate, glycerol, glycine, glutamine, isoleucine, lactate, leucine, methionine, and valine. The score plots (PCA) separated the samples of different storage time, reflecting possible meat degradation. Samples of no storage time (time zero) were grouped in the PC1 and PC2 negatives axis. The score plots suggest that the temperature has a huge influence on the degradation extent and possible influences the growth of the microbial populations.

S-parameter-based circuit simulators are well suited to obtaining accurate solutions of even the most complex rf probe circuits. The basic theory necessary for determining the relative S/N of the probe circuit, based on B₁/P^0.5, from the voltage, current, impedance, and S-parameter data that come from circuit simulators, is presented. Examples of simulator applications to circuits of increasing complexity are presented. A key requirement for effective utilization of circuit simulators in probe circuit optimizations is constructing an approximate analytical solution of the circuit, or an inverse simulation program, to accompany the direct circuit simulation, that calculates all the needed circuit component values based on minimal input data, such as B₀, desired nuclides, sample coil description, and hardware options and details such as characteristics of various leads. A method of developing the needed inverse simulation program is presented for a simplified single-coil HXY probe circuit. The inverse program is validated by the direct simulation itself. The methods are then applied to a detailed circuit that includes all significant leads, stray capacitances, couplings, and losses for a NB 28.2-T 1-mm HXYZ MAS probe. Similar HXY circuit models were validated by NMR experiments with rotor sizes from 0.75 mm to 3.2 mm at fields from 11.7 T to 21 T. Detailed HXYZ circuit model results at 11.7 T, including pulse widths, component values, voltages, and port isolations, agreed with experimental results within a few per cent. The 1200-MHz HXYZ simulation predicted a ¹H π/2 pulse of 1.3 μs at 25 W.

In Nuclear Magnetic Resonance (NMR) education, the introduction of the relaxation phenomenon and the relaxation times (T₁ and T₂) is an important and compulsory step, as is the description of the Carr-Purcell-Meiboom-Gill (CPMG) and inversion-recovery (IR) measurement sequences. Indeed those sequences are still used nowadays for, respectively, the measurement of T₂ and T₁ but also in Magnetic Resonance Imaging (MRI) and NMR spectroscopy. Practical works with the students, performed for example with water, allow to illustrate this part of the teaching. In this work we propose an alternative and funny way to introduce these important topics. With a few microliters of a concentrated Gd³⁺ solution, a few milliliters of an alcoholic beverage and a low resolution and low field NMR device, it is possible, thanks to the relaxation phenomenon and using CPMG and IR sequences, to measure the alcohol content of the beverage provided that the alcohol proton exchange with water protons is taken into account. First the method is validated with synthetic water-ethanol mixtures, then it is used to study nine different alcoholic beverages. The correlation of the ethanol volume fractions determined by NMR with the actual ethanol content of the beverages is rather good, especially for the method based on T₂ relaxation, with a correlation coefficient r² = 0.994. However, it seems that the method developed in this work always underestimates the ethanol volume fraction at high ethanol content for a reason which remains to be found.

Protein nuclear magnetic resonance (NMR) assignment can be a tedious and error-prone process, and it is often a limiting factor in biomolecular NMR studies. Challenges are exacerbated in larger proteins, disordered proteins, and often alpha-helical proteins, owing to an increase in spectral complexity and frequency degeneracies. Here, several multidimensional spectra must be inspected and compared in an iterative manner before resonances can be assigned with confidence. Over the last 2 decades, covariance NMR has evolved to become applicable to protein multidimensional spectra. The method, previously used to generate new correlations from spectra of small organic molecules, can now be used to recast assignment procedures as mathematical operations on NMR spectra. These operations result in multidimensional correlation maps combining all information from input spectra and providing direct correlations between moieties that would otherwise be compared indirectly through reporter nuclei. Thus, resonances of sequential residues can be identified and side-chain signals can be assigned by visual inspection of 4D arrays. This review highlights advances in covariance NMR that permitted to generate reliable 4D arrays and describes how these arrays can be obtained from conventional NMR spectra.

Nuclear magnetic resonance (NMR) spectroscopy is widely used across the physical, chemical, and biological sciences. A core component of NMR studies is multidimensional experiments, which enable correlation of properties from one or more NMR-active nuclei. In high-resolution biomolecular NMR, common nuclei are ¹H, ¹⁵N, and ¹³C, and triple resonance experiments using these three nuclei form the backbone of NMR structural studies. In other fields, a range of other nuclei may be used. Multidimensional NMR experiments provide unparalleled information content, but this comes at the price of long experiment times required to achieve the necessary resolution and sensitivity. Non-uniform sampling (NUS) techniques to reduce the required data sampling have existed for many decades. Recently, such techniques have received heightened interest due to the development of compressed sensing (CS) methods for reconstructing spectra from such NUS datasets. When applied jointly, these methods provide a powerful approach to dramatically improve the resolution of spectra per time unit and under suitable conditions can also lead to signal-to-noise ratio improvements. In this review, we explore the basis of NUS approaches, the fundamental features of NUS reconstruction using CS and applications based on CS approaches including the benefits of expanding the repertoire of biomolecular NMR experiments into higher dimensions. We discuss some of the recent algorithms and software packages and provide practical tips for recording and processing NUS data by CS.

NMR measurements are often performed in a serial manner, that is, the acquisition of an FID signal is repeated under various conditions, either controlled (as temperature or pH changes) or uncontrolled (as reaction progress). The traditional approach to process “serial” data is to perform the Fourier transform of each FID in a series. However, it suffers from several problems, in particular, from the need to sample full Nyquist grid and reach a sufficient signal-to-noise ratio in each separate spectrum. The problems become particularly cumbersome in the case of multidimensional signals, where sampling is costly and sensitivity is an issue. Over the years, several methods of alternative, “joint” processing of FID series have been proposed. In this paper, we discuss the principles of some of them: Accordion Spectroscopy, Multidimensional Decomposition, Radon transform, a combination of Compressed Sensing and the Laplace transform. According to our knowledge, this is the first review on serial NMR data processing approaches. The reader is provided with MATLAB scripts allowing to perform simulations and processing using these algorithms.