Evidence map›Paper›PMID 26870348›Full record

ArticleBiomedical reports2016

Mass spectrometric signatures of the blood plasma metabolome for disease diagnostics.

Petr G Lokhov, Elena E Balashova, Anna A Voskresenskaya, Oxana P Trifonova, Dmitry L Maslov, Alexander I Archakov

Abstract read
In one paragraph

Article in Biomedical reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

  1. Article
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  10. Review
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  12. Article
  13. A Metabolomics Approach to Pharmacotherapy Personalization.Journal of personalized medicine · 2018
    Review
  14. Review
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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

6 authors.

Petr G LokhovInstitute of Biomedical Chemistry, Moscow 119121, Russia.
Elena E BalashovaInstitute of Biomedical Chemistry, Moscow 119121, Russia.
Anna A VoskresenskayaInstitute of Biomedical Chemistry, Moscow 119121, Russia.
Oxana P TrifonovaInstitute of Biomedical Chemistry, Moscow 119121, Russia.
Dmitry L MaslovInstitute of Biomedical Chemistry, Moscow 119121, Russia.
Alexander I ArchakovInstitute of Biomedical Chemistry, Moscow 119121, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In metabolomics, a large number of small molecules can be detected in a single run. However, metabolomic data do not include the absolute concentrations of each metabolite. Generally, mass spectrometry analyses provide metabolite concentrations that are derived from mass peak intensities, and the peak intensities are strictly dependent on the type of mass spectrometer used, as well as the technical characteristics, options and protocols applied. To convert mass peak intensities to actual concentrations, calibration curves have to be generated for each metabolite, and this represents a significant challenge depending on the number of metabolites that are detected and involved in metabolome-based diagnostics. To overcome this limitation, and to facilitate the development of diagnostic tests based on metabolomics, mass peak intensities may be expressed in quintiles. The present study demonstrates the advantage of this approach. The examples of diagnostic signatures, which were designed in accordance to this approach, are provided for lung and prostate cancer (leading causes of mortality due to cancer in developed countries) and impaired glucose tolerance (which precedes type 2 diabetes, the most common endocrinology disease worldwide).

Indexed as

blood plasmadiagnosticsdirect infusionmass spectrometrymetabolic signaturemetabolomequintile

Identifiers

PMID26870348
PMCPMC4726863

What OpenQuestion holds

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Registered trials

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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.