Evidence map›Paper›PMID 37067036›Full record

ArticleJournal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc2023

Simple and fast quantification of cannabinoids in animal feeds by liquid chromatography-tandem mass spectrometry.

Xin Xu, Lisa A Murphy

Abstract read
In one paragraph

Article in Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc, 2023. 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. Severe Cannabinoid Intoxication in a Ferret (Mustela putorius furo) Treated With Intravenous Lipid Emulsion.Journal of veterinary emergency and critical care (San Antonio, Tex. : 2001)
    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

2 authors.

Xin XuPennsylvania Animal Diagnostic Laboratory System Toxicology Laboratory, New Bolton Center, University of Pennsylvania, School of Veterinary Medicine, Kennett Square, PA, USA.ORCID 0000-0002-9240-9764
Lisa A MurphyPennsylvania Animal Diagnostic Laboratory System Toxicology Laboratory, New Bolton Center, University of Pennsylvania, School of Veterinary Medicine, Kennett Square, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is growing interest in using hemp materials as animal feed ingredients, which may raise safety concerns because of the potential transfer of active cannabinoids to the resultant products of animal origin. Hence, the detection and identification of cannabinoids in feeds would be useful. We developed a simple, fast, and sensitive method for simultaneous quantification of 4 major cannabinoids in animal feeds by liquid chromatography-tandem mass spectrometry (LC-MS/MS). We used a simple solvent extraction and dilution approach to extract cannabinoids from the feed matrix. We validated the method in 2 types of cattle feeds with acceptable intra-day and inter-day accuracy (87.5-116%) and precision (< 15%). The limit of detection was 0.05 µg/g, and the limit of quantification was 0.1 µg/g. Furthermore, the method was able to identify and quantify cannabinoids in cattle feeds mixed with hempseed cake as well as in several different hempseed materials, demonstrating its potential in veterinary laboratory applications.

Indexed as

CannabinoidsCannabisAnimal FeedAnimalsCattleChromatography, LiquidTandem Mass SpectrometryCannabinoidscannabinoidfeedhemphempseed cakeliquid chromatography–tandem mass spectrometry

Identifiers

PMID37067036
PMCPMC10331377

What OpenQuestion holds

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LicenceCC BY-NC
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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.