Evidence map›Paper›PMID 36615506›Full record

ReviewMolecules (Basel, Switzerland)2022

Towards Non-Targeted Screening of Lipid Biomarkers for Improved Equine Anti-Doping.

Kathy Tou, Adam Cawley, Christopher Bowen, David P Bishop, Shanlin Fu

Abstract readReview
In one paragraph

Review in Molecules (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Kathy TouCentre for Forensic Science, University of Technology Sydney, Sydney, NSW 2007, Australia.ORCID 0000-0002-4937-3292
Adam CawleyAustralian Racing Forensic Laboratory, Racing NSW, Sydney, NSW 2000, Australia.
Christopher BowenMass Spectrometry Business Unit, Shimadzu Scientific Instruments (Australasia), Sydney, NSW 2116, Australia.
David P BishopHyphenated Mass Spectrometry Laboratory (HyMAS), University of Technology, Sydney, NSW 2007, Australia.
Shanlin FuCentre for Forensic Science, University of Technology Sydney, Sydney, NSW 2007, Australia.ORCID 0000-0002-6238-3612

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current approach to equine anti-doping is focused on the targeted detection of prohibited substances. However, as new substances are rapidly being developed, the need for complimentary methods for monitoring is crucial to ensure the integrity of the racing industry is upheld. Lipidomics is a growing field involved in the characterisation of lipids, their function and metabolism in a biological system. Different lipids have various biological effects throughout the equine system including platelet aggregation and inflammation. A certain class of lipids that are being reviewed are the eicosanoids (inflammatory markers). The use of eicosanoids as a complementary method for monitoring has become increasingly popular with various studies completed to highlight their potential. Studies including various corticosteroids, non-steroidal anti-inflammatories and cannabidiol have been reviewed to highlight the progress lipidomics has had in contributing to the equine anti-doping industry. This review has explored the techniques used to prepare and analyse samples for lipidomic investigations in addition to the statistical analysis and potential for lipidomics to be used for a longitudinal assessment in the equine anti-doping industry.

Indexed as

InflammationLipidomicsAnimalsBiomarkersEicosanoidsHorsesLipid MetabolismLipidsBiomarkersEicosanoidsLipidsanalyticalcorticosteroidslipidomicsNSAIDsreview

Identifiers

PMID36615506
PMCPMC9822433

What OpenQuestion holds

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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.