Evidence map›Paper›PMID 37905230›Full record

ArticleMagnetic resonance (Gottingen, Germany)2021

Virtual decoupling to break the simplification versus resolution trade-off in nuclear magnetic resonance of complex metabolic mixtures.

Cyril Charlier, Neil Cox, Sophie Martine Prud'homme, Alain Geffard, Jean-Marc Nuzillard, Burkhard Luy, Guy Lippens

Abstract read
In one paragraph

Article in Magnetic resonance (Gottingen, Germany), 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. Introduction to "Geoffrey Bodenhausen Festschrift".Magnetic resonance (Gottingen, Germany) · 2023
    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

7 authors.

Cyril CharlierToulouse Biotechnology Institute (TBI), Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France.
Neil CoxToulouse Biotechnology Institute (TBI), Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France.
Sophie Martine Prud'hommeUniversité de Reims Champagne-Ardenne (URCA), UMR-I 02 SEBIO (Stress Environnementaux et Biosurveillance des milieux aquatiques), Moulin de la Housse, Reims, France.
Alain GeffardUniversité de Reims Champagne-Ardenne (URCA), UMR-I 02 SEBIO (Stress Environnementaux et Biosurveillance des milieux aquatiques), Moulin de la Housse, Reims, France.
Jean-Marc NuzillardUniversité de Reims Champagne Ardenne, CNRS, ICMR UMR 7312, 51097 Reims, France.
Burkhard LuyInstitute for Biological Interfaces 4 - Magnetic Resonance, Karlsruhe Institute of Technology (KIT), Herrmann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen, Germany.
Guy LippensToulouse Biotechnology Institute (TBI), Université de Toulouse, CNRS, INRAE, INSA, Toulouse, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The heteronuclear single quantum correlation (HSQC) experiment developed by Bodenhausen and Ruben (1980) in the early days of modern nuclear magnetic resonance (NMR) is without a doubt one of the most widely used experiments, with applications in almost every aspect of NMR including metabolomics. Acquiring this experiment, however, always implies a trade-off: simplification versus resolution. Here, we present a method that artificially lifts this barrier and demonstrate its application towards metabolite identification in a complex mixture. Based on the measurement of clean in-phase and clean anti-phase (CLIP/CLAP) HSQC spectra (Enthart et al., 2008), we construct a virtually decoupled HSQC (vd-HSQC) spectrum that maintains the highest possible resolution in the proton dimension. Combining this vd-HSQC spectrum with a

Identifiers

PMID37905230
PMCPMC10539796

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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.