Evidence map›Paper›PMID 30830443›Full record

ReviewMetabolomics : Official journal of the Metabolomic Society2019

Optimizing 1D

Catherine Deborde, Jean-Xavier Fontaine, Daniel Jacob, Adolfo Botana, Valérie Nicaise, Florence Richard-Forget, Sylvain Lecomte, Cédric Decourtil, Kamar Hamade, François Mesnard and 2 more

Abstract readReview
In one paragraph

Review in Metabolomics : Official journal of the Metabolomic Society, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Application ofPlants (Basel, Switzerland) · 2026
    Article
  2. Molecules (Basel, Switzerland) · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Compound-Specific 1DACS omega · 2023
    Article
  8. Article
  9. Review
  10. NMR, LC-MS Characterization ofMolecules (Basel, Switzerland) · 2022
    Article
  11. Article
  12. Metabolite Fingerprinting UsingMolecules (Basel, Switzerland) · 2021
    Article
  13. Review
  14. Article
  15. Automatic 1DMetabolites · 2021
    Review
  16. Article
  17. Article
  18. Review
  19. The Zebra Mussel (Metabolites · 2020
    Article
  20. 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

12 authors.

Catherine DebordeUMR1332 Biologie du Fruit et Pathologie, Centre INRA de Nouvelle Aquitaine Bordeaux, INRA, Univ. Bordeaux, av Edouard Bourlaux, 33140, Villenave d'Ornon, France. catherine.deborde@inra.fr.ORCID 0000-0001-5687-9059
Jean-Xavier FontaineBIOPI - EA 3900, Univ. Picardie Jules Verne, 1, rue des Louvels, 80037, Amiens Cedex, France.ORCID 0000-0001-8189-9238
Daniel JacobUMR1332 Biologie du Fruit et Pathologie, Centre INRA de Nouvelle Aquitaine Bordeaux, INRA, Univ. Bordeaux, av Edouard Bourlaux, 33140, Villenave d'Ornon, France.ORCID 0000-0002-6687-7169
Adolfo BotanaJEOL UK, Silver Court, Watchmead Road, Welwyn Garden City, AL7 1LT, UK.
Valérie NicaiseUR1264 MycSA, INRA, Centre INRA de Nouvelle Aquitaine Bordeaux, av Edouard Bourlaux, 33140, Villenave d'Ornon, France.ORCID 0000-0002-5023-8725
Florence Richard-ForgetUR1264 MycSA, INRA, Centre INRA de Nouvelle Aquitaine Bordeaux, av Edouard Bourlaux, 33140, Villenave d'Ornon, France.
Sylvain LecomteBIOPI - EA 3900, Univ. Picardie Jules Verne, 1, rue des Louvels, 80037, Amiens Cedex, France.
Cédric DecourtilBIOPI - EA 3900, Univ. Picardie Jules Verne, 1, rue des Louvels, 80037, Amiens Cedex, France.
Kamar HamadeBIOPI - EA 3900, Univ. Picardie Jules Verne, 1, rue des Louvels, 80037, Amiens Cedex, France.
François MesnardBIOPI - EA 3900, Univ. Picardie Jules Verne, 1, rue des Louvels, 80037, Amiens Cedex, France.
Annick MoingUMR1332 Biologie du Fruit et Pathologie, Centre INRA de Nouvelle Aquitaine Bordeaux, INRA, Univ. Bordeaux, av Edouard Bourlaux, 33140, Villenave d'Ornon, France.ORCID 0000-0003-1144-3600
Roland MoliniéBIOPI - EA 3900, Univ. Picardie Jules Verne, 1, rue des Louvels, 80037, Amiens Cedex, France.ORCID 0000-0003-4399-8838

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionProton nuclear magnetic resonance spectroscopy (

objectivesThe aim of the present work is to provide advice for minimizing uncontrolled variability in plant sample preparation before and during NMR metabolomic profiling, taking into account sample composition, including its specificity in terms of pH and paramagnetic ion concentrations, and NMR spectrometer performances.

methodsAn automation of spectrometer preparation routine standardization before NMR acquisition campaign was implemented and tested on three plant sample sets (extracts of durum wheat spikelet, Arabidopsis leaf and root, and flax leaf, root and stem). We performed

resultsComparability of large- (Arabidopsis) and medium-size (flax) datasets measured at 600 MHz and from the wheat sample set recorded at the three sites (400, 500 and 600 MHz) was exceptionally good in terms of spectral quality. The coefficient of variation of the full width at half maximum (FWHM) and the signal-to-noise ratio (S/N) of two selected peaks was comprised between 5 and 10% depending on the size of sample set and the spectrometer field. EDTA addition improved citrate and malate resonance patterns for wheat sample sets. A collection of 22 samples of wheat spikelet extracts was used as a proof of concept and showed that the data collected at the three sites on instruments of different field strengths and manufacturers yielded the same discrimination pattern of the biological groups.

conclusionStandardization or automation of several steps from extract preparation to data reduction improves data quality for small to large collections of plant samples of different origins.

Indexed as

ArabidopsisAutomationFlaxHigh-Throughput Screening AssaysMagnetic Resonance ImagingMagnetic Resonance SpectroscopyMetabolomicsPlant ExtractsPlant LeavesProton Magnetic Resonance SpectroscopyReference StandardsSpecimen HandlingTriticumPlant ExtractsMetabolomicsNMR acquisitionNMR spectra processingSample preparation

Identifiers

PMID30830443
PMCPMC6394467

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.