Evidence map›Paper›PMID 34439683›Full record

ArticleBrain sciences2021

Chronic Fentanyl Self-Administration Generates a Shift toward Negative Affect in Rats during Drug Use.

Angela N Dao, Nicholas J Beacher, Vivian Mayr, Annalisa Montemarano, Sam Hammer, Mark O West

Abstract read
In one paragraph

Article in Brain sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
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  4. 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.

Angela N DaoDepartment of Psychology, Rutgers University, Piscataway, NJ 08854, USA.ORCID 0000-0002-2942-0020
Nicholas J BeacherDepartment of Psychology, Rutgers University, Piscataway, NJ 08854, USA.
Vivian MayrDepartment of Psychology, Rutgers University, Piscataway, NJ 08854, USA.
Annalisa MontemaranoDepartment of Psychology, Rutgers University, Piscataway, NJ 08854, USA.
Sam HammerDepartment of Psychology, Rutgers University, Piscataway, NJ 08854, USA.
Mark O WestDepartment of Psychology, Rutgers University, Piscataway, NJ 08854, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Drug addiction is thought to be driven by negative reinforcement, and it is thought that a shift from positive affect upon initial exposure to negative affect after chronic exposure to a drug is responsible for maintaining self-administration (SA) in addicted individuals. This can be modeled in rats by analyzing ultrasonic vocalizations (USVs), a type of intraspecies communication indicative of affective state based on the frequency of the emission: calls in the 22 kHz range indicate negative affect, whereas calls in the 50 kHz range indicate positive affect. We employed a voluntary chronic, long-access model of fentanyl SA to analyze affective changes in the response to chronic fentanyl exposure. Male Sprague-Dawley rats self-administered either fentanyl (N = 7) or saline (N = 6) for 30 consecutive days and USVs were recorded at four different time points: the day before the first SA session (PRE), the first day of SA (T01), the last day of SA (T30), and the first day of abstinence (ABS). At T01, the ratio of 50 to 22 kHz calls was similar between the fentanyl and saline groups, but at T30, the ratio differed between groups, with the fentanyl group showing significantly fewer 50 kHz calls and more 22 kHz calls relative to saline animals. These results indicate a shift toward a negative affect during drug use after chronic exposure to fentanyl and support negative reinforcement as a main driving factor of opioid addiction.

Indexed as

affectfentanylopioidsself-administrationultrasonic vocalizations

Identifiers

PMID34439683
PMCPMC8394963

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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.