Abstract
Although the concepts of nonuniform sampling (NUS) and non-Fourier spectral reconstruction in multidimensional NMR began to emerge 4 decades ago , it is only relatively recently that NUS has become more commonplace. Advantages of NUS include the ability to tailor experiments to reduce data collection time and to improve spectral quality, whether through detection of closely spaced peaks (i.e., "resolution") or peaks of weak intensity (i.e., "sensitivity"). Wider adoption of these methods is the result of improvements in computational performance, a growing abundance and flexibility of software, support from NMR spectrometer vendors, and the increased data sampling demands imposed by higher magnetic fields. However, the identification of best practices still remains a significant and unmet challenge. Unlike the discrete Fourier transform, non-Fourier methods used to reconstruct spectra from NUS data are nonlinear, depend on the complexity and nature of the signals, and lack quantitative or formal theory describing their performance. Seemingly subtle algorithmic differences may lead to significant variabilities in spectral qualities and artifacts. A community-based critical assessment of NUS challenge problems has been initiated, called the "Nonuniform Sampling Contest" (NUScon), with the objective of determining best practices for processing and analyzing NUS experiments. We address this objective by constructing challenges from NMR experiments that we inject with synthetic signals, and we process these challenges using workflows submitted by the community. In the initial rounds of NUScon our aim is to establish objective criteria for evaluating the quality of spectral reconstructions. We present here a software package for performing the quantitative analyses, and we present the results from the first two rounds of NUScon. We discuss the challenges that remain and present a roadmap for continued community-driven development with the ultimate aim of providing best practices in this rapidly evolving field. The NUScon software package and all data from evaluating the challenge problems are hosted on the NMRbox platform.
Highlights
Jeener (1971) devised the conceptual basis for converting multiple-resonance NMR experiments into multidimensional experiments by parametric sampling of the free induction decays (FIDs) along “indirect time dimensions.” The subsequent application of the discrete Fourier transform (DFT) to the analysis of pulsed NMR experiments revolutionized NMR spectroscopy, opened the door to multidimensional experiments, and resulted in the 1991 Nobel Prize in Chemistry being awarded to Richard Ernst (Ernst, 1997)
The Nonuniform Sampling Contest” (NUScon) software, contest, and archive of spectral evaluation data provide a comprehensive platform for addressing the most challenging questions related to nonuniform sampling (NUS) experiments and even to broader topics in the quantitative analysis of NMR data
The NUScon workflow will expand in scope as new challenges are addressed, and the quantitative modules deployed in the workflow will be subjected to continuous refinement
Summary
Jeener (1971) devised the conceptual basis for converting multiple-resonance NMR experiments into multidimensional experiments by parametric sampling of the free induction decays (FIDs) along “indirect time dimensions.” The subsequent application of the discrete Fourier transform (DFT) to the analysis of pulsed NMR experiments revolutionized NMR spectroscopy, opened the door to multidimensional experiments, and resulted in the 1991 Nobel Prize in Chemistry being awarded to Richard Ernst (Ernst, 1997). The constraints of US are demonstrated by the following three observations: (1) sampling must be performed to an evolution time of π × T2 in order to resolve a pair of signals separated by one linewidth; (2) uniform data collection beyond 1.26×T2 reduces the signal-to-noise ratio (SNR) (Matson, 1977; Rovnyak, 2019), a proxy for sensitivity, with the majority of SNR obtained by ∼ 0.6 × T2; and (3) sampling must be performed rapidly to avoid signal aliasing described by the Nyquist sampling theorem (Nyquist, 1928), which means that attaining high resolution along any indirect dimension that is sampled parametrically will be costly in terms of the data acquisition time. Higher-dimensionality experiments help access the increased resolution afforded by high-field magnets by introducing separation of closely spaced peaks along perpendicular dimensions but at the cost of longer experiment times
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
