Ultrafast 2D NMR: Methods and Applications

Gouilleux, Boris; Rouger, Laetitia; Giraudeau, Patrick

doi:10.1016/bs.arnmr.2017.08.003

Cited by 40 publications

(25 citation statements)

References 158 publications

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“…35 Note that the principles of UF 2D NMR -which relies on a spatial encoding of the sample thanks to the combination of chirp pulses with magnetic field gradients-will not be described here but have been extensively reviewed in recent literature. 35,36 It is also fair to mention that UF 2D NMR suffers from a well-known sensitivity penalty compared to conventional NMR, 36 which explains why UF 2D NMR is best suited to relatively concentrated metabolite samples such as extracts. COSY (30 min at 700 MHz) on pig lipid serum extracts efficiently separates samples from pigs treated with a growth promoter (ractopamine) versus control pigs.…”

Section: Heteronuclear 1d Nmr Spectroscopymentioning

confidence: 99%

NMR-based metabolomics and fluxomics: developments and future prospects

Giraudeau

2020

Analyst

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Section: Heteronuclear 1d Nmr Spectroscopymentioning

confidence: 99%

NMR-based metabolomics and fluxomics: developments and future prospects

Giraudeau

2020

Analyst

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“…Unfortunately, sensitivity is severely decreased requiring highly concentrated samples and, in addition, reasonable linewidths can be hard to achieve in the 1 H dimension. Recent advances in single‐scan J res pulse sequence design report the detection of millimolar concentrations, offering a more acceptable sensitivity . In addition, an ultrafast heteronuclear single‐scan J res experiment has also been developed, which can be of interest for measuring 13 C‐isotopic enrichments in metabolic samples …”

Section: Homonuclear J‐resolved Experimentsmentioning

confidence: 99%

Current developments in homonuclear and heteronuclear J‐resolved NMR experiments

Parella

2018

Magnetic Reson in Chemistry

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Two-dimensional J-resolved (Jres) NMR experiments offer a simple, user-friendly spectral representation where the information of coupling constants and chemical shifts are separated into two orthogonal frequency axis. Since its initial proposal 40 years ago, Jres has been the focus of considerable interest both in improving the basic pulse sequence and in its successful application to a wide range of studies. Here, the latest developments in the design of novel Jres pulse schemes are reviewed, mainly focusing on obtaining pure absorption lineshapes, minimizing strong coupling artifacts, and also optimizing sensitivity and experimental measurements. A discussion of several Jres versions for the accurate measurement of a different number of homonuclear (J ) and heteronuclear (J ) coupling constants is presented, accompanied by some illustrative examples.

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“…However, the spectra have remaining overlapping signals, or the overlapping peaks themselves contain part of the information of the sample. In this regard, overlapping signals can be separated by two-dimensional (2D)-NMR, in which multiple free induction decays (FIDs) are measured over a small change in evolution time, but this approach is time consuming [20].…”

Section: Introductionmentioning

confidence: 99%

Signal Deconvolution and Noise Factor Analysis Based on a Combination of Time–Frequency Analysis and Probabilistic Sparse Matrix Factorization

Yamada

Kurotani

Chikayama

et al. 2020

IJMS

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Nuclear magnetic resonance (NMR) spectroscopy is commonly used to characterize molecular complexity because it produces informative atomic-resolution data on the chemical structure and molecular mobility of samples non-invasively by means of various acquisition parameters and pulse programs. However, analyzing the accumulated NMR data of mixtures is challenging due to noise and signal overlap. Therefore, data-cleansing steps, such as quality checking, noise reduction, and signal deconvolution, are important processes before spectrum analysis. Here, we have developed an NMR measurement informatics tool for data cleansing that combines short-time Fourier transform (STFT; a time-frequency analytical method) and probabilistic sparse matrix factorization (PSMF) for signal deconvolution and noise factor analysis. Our tool can be applied to the original free induction decay (FID) signals of a one-dimensional NMR spectrum. We show that the signal deconvolution method reduces the noise of FID signals, increasing the signal-to-noise ratio (SNR) about tenfold, and its application to diffusion-edited spectra allows signals of macromolecules and unsuppressed small molecules to be separated by the length of the T 2 * relaxation time. Noise factor analysis of NMR datasets identified correlations between SNR and acquisition parameters, identifying major experimental factors that can lower SNR.

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Ultrafast 2D NMR: Methods and Applications

Cited by 40 publications

References 158 publications

NMR-based metabolomics and fluxomics: developments and future prospects

NMR-based metabolomics and fluxomics: developments and future prospects

Current developments in homonuclear and heteronuclear J‐resolved NMR experiments

Signal Deconvolution and Noise Factor Analysis Based on a Combination of Time–Frequency Analysis and Probabilistic Sparse Matrix Factorization

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