Evidence map›Paper›PMID 26083377›Full record

ArticlePloS one2015

Detection of Illicit Drugs by Trained Honeybees (Apis mellifera).

Matthias Schott, Birgit Klein, Andreas Vilcinskas

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. 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
1.3field-weighted citation impact, top 24% 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, 22 citations in OpenAlex.

  1. Review
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  8. Aversive Learning of Colored Lights in Walking Honeybees.Frontiers in behavioral neuroscience · 2017
    Article
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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

3 authors at 2 institutions in 1 country.

Matthias SchottInstitute of Phytopathology and Applied Zoology, Justus-Liebig-University of Giessen, Giessen, Germany; Department Bioresources, Fraunhofer Institute for Molecular Biology and Applied Ecology (IME), Giessen, Germany.
Birgit KleinForensic Institute - Section Narcotics/Chemistry, State Office of Criminal Investigation Hessen, Wiesbaden, Germany.
Andreas VilcinskasInstitute of Phytopathology and Applied Zoology, Justus-Liebig-University of Giessen, Giessen, Germany; Department Bioresources, Fraunhofer Institute for Molecular Biology and Applied Ecology (IME), Giessen, Germany.
University of Giessen · DEBundeskriminalamt · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Illegal drugs exacerbate global social challenges such as substance addiction, mental health issues and violent crime. Police and customs officials often rely on specially-trained sniffer dogs, which act as sensitive biological detectors to find concealed illegal drugs. However, the dog "alert" is no longer sufficient evidence to allow a search without a warrant or additional probable cause because cannabis has been legalized in two US states and is decriminalized in many others. Retraining dogs to recognize a narrower spectrum of drugs is difficult and training new dogs is time consuming, yet there are no analytical devices with the portability and sensitivity necessary to detect substance-specific chemical signatures. This means there is currently no substitute for sniffer dogs. Here we describe an insect screening procedure showing that the western honeybee (Apis mellifera) can sense volatiles associated with pure samples of heroin and cocaine. We developed a portable electroantennographic device for the on-site measurement of volatile perception by these insects, and found a positive correlation between honeybee antennal responses and the concentration of specific drugs in test samples. Furthermore, we tested the ability of honeybees to learn the scent of heroin and trained them to show a reliable behavioral response in the presence of a highly-diluted scent of pure heroin. Trained honeybees could therefore be used to complement or replace the role of sniffer dogs as part of an automated drug detection system. Insects are highly sensitive to volatile compounds and provide an untapped resource for the development of biosensors. Automated conditioning as presented in this study could be developed as a platform for the practical detection of illicit drugs using insect-based sensors.

Indexed as

AnimalsBeesBehavior, AnimalBiosensing TechniquesConditioning, ClassicalDogsIllicit DrugsLearningMaleOdorantsSmellVolatile Organic CompoundsIllicit DrugsVolatile Organic Compounds

Identifiers

PMID26083377
PMCPMC4471073
OpenAlexW1942209805

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.