Evidence map›Paper›PMID 31592223›Full record

ArticleJournal of equine science2019

Identification of metabolomic changes in horse plasma after racing by liquid chromatography-high resolution mass spectrometry as a strategy for doping testing.

Toshiki Ueda, Teruaki Tozaki, Satoshi Nozawa, Kenji Kinoshita, Hitoshi Gawahara

Abstract read
In one paragraph

Article in Journal of equine science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. 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

5 authors.

Toshiki UedaDrug Analysis Department, Laboratory of Racing Chemistry, Tochigi 320-0851, Japan.
Teruaki TozakiGenetic Analysis Department, Laboratory of Racing Chemistry, Tochigi 320-0851, Japan.
Satoshi NozawaDrug Analysis Department, Laboratory of Racing Chemistry, Tochigi 320-0851, Japan.
Kenji KinoshitaDrug Analysis Department, Laboratory of Racing Chemistry, Tochigi 320-0851, Japan.
Hitoshi GawaharaDrug Analysis Department, Laboratory of Racing Chemistry, Tochigi 320-0851, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, the illegal use of novel technologies, such as gene and cell therapies, has become a great concern for the horseracing industry. As a potential way to control this, metabolomics approaches that comprehensively analyze metabolites in biological samples have been gaining attention. However, it may be difficult to identify metabolic biomarkers for doping because physiological conditions generally differ between resting and exercise states in horses. To understand the metabolic differences in horse plasma between the resting state at training centres and the sample collection stage after racing for doping test (SAD), we took plasma samples from these two stages (n=30 for each stage) and compared the metabolites present in these samples by liquid chromatography-high resolution mass spectrometry. This analysis identified 5,010 peaks, of which 1,256 peaks (approximately 25%) were annotated using KEGG analysis. Principal component analysis showed that the resting state and SAD groups had entirely different metabolite compositions. In particular, the levels of inosine, xanthosine, uric acid, and allantoin, which are induced by extensive exercise, were significantly increased in the SAD group. In addition, many metabolites not affected by extensive exercise were also identified. These results will contribute to the discovery of biomarkers for detecting doping substances that cannot be detected by conventional methods.

Indexed as

doping controlgene and cell dopinghorse racingliquid chromatography-high resolution mass spectrometrymetabolomics

Identifiers

PMID31592223
PMCPMC6773618

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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.