Evidence map›Paper›PMID 35550910›Full record

ArticleJournal of magnetic resonance (San Diego, Calif. : 1997)2022

High fidelity sampling schedules for NMR spectra of high dynamic range.

Sven G Hyberts, Gerhard Wagner

Open access · greenAbstract read
In one paragraph

Article in Journal of magnetic resonance (San Diego, Calif. : 1997), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.4field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Non-Uniform Sampling for Quantitative NOESY.Magnetic resonance in chemistry : MRC · 2025
    Article
  3. Evaluating metrics of spectral quality in nonuniform sampling.Journal of magnetic resonance open · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Sven G HybertsDepartment of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, United States. Electronic address: sven_hyberts@hms.harvard.edu.
Gerhard WagnerDepartment of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA 02115, United States.
Harvard University · US

Funding

TR&D 4 -- Advanced Magic Angle Spinning NMR methodsP41GM132079 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GRIFFIN, ROBERT GUY · 2019 to 2021
$3.6M
Next Generation Solution NMR Techniques for GPCR Structure, Dynamics and FunctionR01GM129026 · NIGMS · HARVARD MEDICAL SCHOOL · PI WAGNER, GERHARD · 2018 to 2021
$2.0M
NIGMS NIH HHS P41 GM132079NIGMS NIH HHS R01 GM129026
6 · The paper itself

Abstract

The ability to reconstruct non-uniformly sampled (NUS) NMR spectra has mostly been accepted. Still a concern is lingering regarding artifacts from sampling non-uniformly. As experienced, some sampling schedules yield better results than others. Finding a useful schedule is relatively trivial for a low dynamic range spectrum and a conservative sparsity, but not so when the dynamic range is large and/or when extreme sparsity is used. High dynamic range is typically found in NOESY and spectra of metabolites, where quantification of peak heights is desired at high fidelity. Extreme sparsity is desired when high throughput is a goal. In all cases, selecting a poor sampling schedule can create unnecessary artifacts. Effectively, it is important to select a sampling schedule that provides a signal-to-artifact apex ratio (SAAR) value in par or better than the signal-to-noise ratio (SNR) value. Notably, by signal-to-artifact apex ratio we consider reconstruction fidelity as the apex intensity likeness, i.e., as the true signal to the tallest artifact. We show that the quality of reconstruction depends on the particular sampling schedule. We evaluate the reconstruction quality in the frequency domain following a matched Lorentz-to-Gauss transform plus common apodization and Fourier Transform. As the Lorentz-to-Gauss transform improves resolution and reduces ridges we include this when defining the Signal-to-Artifact Apex Ratio (SAAR) metric. This metric measures the ratio of simulated reconstructed peak height to the tallest artifact of reconstruction in a spectrum without noise. Once a NUS schedule is found with an optimal SAAR it will be satisfactory for all spectra recorded with the same parameter set. Tables with good seed values are provided in the supplement.

Indexed as

AlgorithmsArtifactsFourier AnalysisMagnetic Resonance SpectroscopyNuclear Magnetic Resonance, BiomolecularSignal-To-Noise RatioHigh dynamic rangeIterative soft threshold reconstructionNon-uniform samplingOptimizing NUS fidelityReduced time multidimensional NMR spectroscopy

Identifiers

PMID35550910
PMCPMC10675079
OpenAlexW4224885288

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.