Evidence map›Paper›PMID 33961178›Full record

ArticleJournal of biomolecular NMR2021

A simple approach for reconstruction of non-uniformly sampled pseudo-3D NMR data for accurate measurement of spin relaxation parameters.

Kyle W East, Frank Delaglio, George P Lisi

Abstract read
In one paragraph

Article in Journal of biomolecular NMR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

3 authors.

Kyle W EastDepartment of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI, 02903, USA.
Frank DelaglioInstitute of Bioscience and Biotechnology Research, National Institute of Standards and Technology, The University of Maryland, 9600 Gudelsky Dr. Rockville, College Park, MD, 20850, USA.
George P LisiDepartment of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI, 02903, USA. george_lisi@brown.edu.ORCID http://orcid.org/0000-0001-8878-5655

Funding

The role of Sirtuins in neurodegenerative diseaseP20GM109035 · NIGMS · BROWN UNIVERSITY · PI WONG, IAN Y · 2016 to 2025
$22.6M
Studies of Allostery between Multi-domain Proteins and Nucleic Acid ComplexesR01GM136815 · NIGMS · YALE UNIVERSITY · PI BATISTA, VICTOR S · 2021 to 2024
$1.4M
NIGMS NIH HHS P20 GM109035NIGMS NIH HHS R01 GM136815
6 · The paper itself

Abstract

We explain how to conduct a pseudo-3D relaxation series NUS measurement so that it can be reconstructed by existing 3D NUS reconstruction methods to give accurate relaxation values. We demonstrate using reconstruction algorithms IST and SMILE that this 3D approach allows lower sampling densities than for independent 2D reconstructions. This is in keeping with the common finding that higher dimensionality increases signal sparsity, enabling lower sampling density. The approach treats the relaxation series as ordinary 3D time-domain data whose imaginary part in the pseudo-dimension is zero, and applies any suitably linear 3D NUS reconstruction method accordingly. Best results on measured and simulated data were achieved using acquisitions with 9 to 12 planes and exponential spacing in the pseudo-dimension out to ~ 2 times the inverse decay time. Given these criteria, in typical cases where 2D reconstructions require 50% sampling, the new 3D approach generates spectra reliably at sampling densities of 25%.

Indexed as

AlgorithmsModels, ChemicalNuclear Magnetic Resonance, BiomolecularNon-uniform samplingSpectral reconstructionSpin relaxation

Identifiers

PMID33961178
PMCPMC8686007

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.