Evidence map›Paper›PMID 34299389›Full record

ArticleMolecules (Basel, Switzerland)2021

Optimization of Sample Preparation for Metabolomics Exploration of Urine, Feces, Blood and Saliva in Humans Using Combined NMR and UHPLC-HRMS Platforms.

Cécile Martias, Nadine Baroukh, Sylvie Mavel, Hélène Blasco, Antoine Lefèvre, Léa Roch, Frédéric Montigny, Julie Gatien, Laurent Schibler, Diane Dufour-Rainfray and 2 more

Open access · goldAbstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.9field-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

27 citing papers in PubMed, 63 citations in OpenAlex.

  1. Biomaterials for biomarker imaging and detection.Journal of advanced research · 2026
    Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. A Reproducibility Crisis for Clinical Metabolomics Studies.Trends in analytical chemistry : TRAC · 2024
    Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Article
  16. Review
  17. Review
  18. Antimicrobial Properties ofAntibiotics (Basel, Switzerland) · 2023
    Article
  19. 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 at 2 institutions in 1 country.

Cécile MartiasUMR 1253, iBrain, University of Tours, Inserm, 37044 Tours, France.ORCID 0000-0001-5035-0197
Nadine BaroukhUMR 1253, iBrain, University of Tours, Inserm, 37044 Tours, France.
Sylvie MavelUMR 1253, iBrain, University of Tours, Inserm, 37044 Tours, France.
Hélène BlascoUMR 1253, iBrain, University of Tours, Inserm, 37044 Tours, France.
Antoine LefèvreUMR 1253, iBrain, University of Tours, Inserm, 37044 Tours, France.
Léa RochALLICE, Phenotyping Station, 37380 Nouzilly, France.
Frédéric MontignyUMR 1253, iBrain, University of Tours, Inserm, 37044 Tours, France.
Julie GatienALLICE, Phenotyping Station, 37380 Nouzilly, France.
Laurent SchiblerALLICE, Phenotyping Station, 37380 Nouzilly, France.ORCID 0000-0003-3137-0859
Diane Dufour-RainfrayUMR 1253, iBrain, University of Tours, Inserm, 37044 Tours, France.
Lydie Nadal-DesbaratsUMR 1253, iBrain, University of Tours, Inserm, 37044 Tours, France.
Patrick EmondUMR 1253, iBrain, University of Tours, Inserm, 37044 Tours, France.
Université de Tours · FRBiologie des oiseaux et aviculture · FR

Funding

Conseil Régional du Centre-Val de Loire 201700117267
6 · The paper itself

Abstract

Currently, most clinical studies in metabolomics only consider a single type of sample such as urine, plasma, or feces and use a single analytical platform, either NMR or MS. Although some studies have already investigated metabolomics data from multiple fluids, the information is limited to a unique analytical platform. On the other hand, clinical studies investigating the human metabolome that combine multi-analytical platforms have focused on a single biofluid. Combining data from multiple sample types for one patient using a multimodal analytical approach (NMR and MS) should extend the metabolome coverage. Pre-analytical and analytical phases are time consuming. These steps need to be improved in order to move into clinical studies that deal with a large number of patient samples. Our study describes a standard operating procedure for biological specimens (urine, blood, saliva, and feces) using multiple platforms (

Indexed as

MetabolomeBloodChromatography, High Pressure LiquidFecesHumansMagnetic Resonance SpectroscopySalivaSpecimen HandlingUrine1H-NMRbiological fluidsextraction protocolmetabolomic cardUHPLC-HRMS

Identifiers

PMID34299389
PMCPMC8305469
OpenAlexW3180514920

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.