Evidence map›Paper›PMID 36530463›Full record

ArticleJournal of magnetic resonance open2022

A new limit for blood metabolite analysis using

G A Nagana Gowda, Vadim Pascua, Daniel Raftery

Open access · goldAbstract read
In one paragraph

Article in Journal of magnetic resonance open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

9 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. NMR-based metabolomics: Where are we now and where are we going?Progress in nuclear magnetic resonance spectroscopy
    Review
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 at 1 institution in 1 country.

G A Nagana GowdaNorthwest Metabolomics Research Center.
Vadim PascuaNorthwest Metabolomics Research Center.
Daniel RafteryNorthwest Metabolomics Research Center.
University of Washington · US

Funding

UW Center for Translational Muscle Research (Overall Application)P30AR074990 · NIAMS · UNIVERSITY OF WASHINGTON · PI Jennifer Michelle Davis, DANIEL RAFTERY · 2019 to 2026
$7.5M
Modeling Homeostasis of Human Blood MetabolitesR01GM131491 · NIGMS · UNIVERSITY OF WASHINGTON · PI RAFTERY, DANIEL, ZHANG, DABAO · 2020 to 2023
$2.2M
Quantitative Analysis of Labile Metabolites in Biological SamplesR01GM138465 · NIGMS · UNIVERSITY OF WASHINGTON · PI GOWDA, G. A. NAGANA, RAFTERY, DANIEL · 2021 to 2024
$1.5M
NIAMS NIH HHS P30 AR074990NIGMS NIH HHS R01 GM131491NIGMS NIH HHS R01 GM138465
6 · The paper itself

Abstract

Human blood is the most widely used biospecimen in the clinic and the metabolomics field. While both mass spectrometry and NMR spectroscopy are the two premier analytical platforms in the metabolomics field, NMR exhibits several unsurpassed characteristics for blood metabolite analysis, the most important of which are its ability to identify unknown metabolites and its quantitative nature. However, the relatively small number of metabolites accessible by NMR has restricted the scope of its applications. Enhancing the limit of identified metabolites in blood will therefore greatly impact NMR-based metabolomics. Continuing our efforts to address this major issue, our current study describes the identification of 12 metabolites, which expands the number of quantifiable blood metabolites by ~15%. These results, in combination with our earlier efforts, now provide access to nearly 90 metabolites, which is the highest to date for a simple 1D

Indexed as

1d nmr, 2d nmrBlood metabolomicsEnergy coenzymesLabile metabolitesRedox coenzymesUnknown metabolite identification

Identifiers

PMID36530463
PMCPMC9757760
OpenAlexW4308986530

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.