Evidence map›Paper›PMID 35563838›Full record

ReviewCells2022

Applying a Fast-Scan Cyclic Voltammetry to Explore Dopamine Dynamics in Animal Models of Neuropsychiatric Disorders.

Vladimir P Grinevich, Amir N Zakirov, Uliana V Berseneva, Elena V Gerasimova, Raul R Gainetdinov, Evgeny A Budygin

Abstract readReview
In one paragraph

Review in Cells, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Synaptic effects of interleukin-6 on human iPSC-derived dopaminergic neurons.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026
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  4. 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

6 authors.

Vladimir P GrinevichDepartment of Neurobiology, Sirius University, 1 Olympic Ave., Sirius, Sochi 353340, Russia.
Amir N ZakirovDepartment of Neurobiology, Sirius University, 1 Olympic Ave., Sirius, Sochi 353340, Russia.ORCID 0000-0001-9627-0272
Uliana V BersenevaDepartment of Neurobiology, Sirius University, 1 Olympic Ave., Sirius, Sochi 353340, Russia.
Elena V GerasimovaDepartment of Neurobiology, Sirius University, 1 Olympic Ave., Sirius, Sochi 353340, Russia.ORCID 0000-0002-0623-8496
Raul R GainetdinovDepartment of Neurobiology, Sirius University, 1 Olympic Ave., Sirius, Sochi 353340, Russia.
Evgeny A BudyginDepartment of Neurobiology, Sirius University, 1 Olympic Ave., Sirius, Sochi 353340, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Progress in the development of technologies for the real-time monitoring of neurotransmitter dynamics has provided researchers with effective tools for the exploration of etiology and molecular mechanisms of neuropsychiatric disorders. One of these powerful tools is fast-scan cyclic voltammetry (FSCV), a technique which has progressively been used in animal models of diverse pathological conditions associated with alterations in dopamine transmission. Indeed, for several decades FSCV studies have provided substantial insights into our understanding of the role of abnormal dopaminergic transmission in pathogenetic mechanisms of drug and alcohol addiction, Parkinson's disease, schizophrenia, etc. Here we review the applications of FSCV to research neuropsychiatric disorders with particular attention to recent technological advances.

Indexed as

DopamineParkinson DiseaseAnimalsModels, AnimalNeurotransmitter AgentsDopamineNeurotransmitter Agentsaddictiondopaminefast-scan cyclic voltammetryneurotransmitter releaseParkinson’s diseaseschizophrenia

Identifiers

PMID35563838
PMCPMC9100021

What OpenQuestion holds

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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.