Evidence map›Paper›PMID 25729356›Full record

ArticleFrontiers in behavioral neuroscience2015

Developing highER-throughput zebrafish screens for in-vivo CNS drug discovery.

Adam Michael Stewart, Robert Gerlai, Allan V Kalueff

Open access · goldAbstract read
In one paragraph

Article in Frontiers in behavioral neuroscience, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
4.2field-weighted citation impact, top 5% 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

25 citing papers in PubMed, 80 citations in OpenAlex.

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  8. Towards Zebrafish Models of CNS Channelopathies.International journal of molecular sciences · 2022
    Review
  9. Towards Modeling Anhedonia and Its Treatment in Zebrafish.The international journal of neuropsychopharmacology · 2022
    Article
  10. Article
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  14. Structural Analysis and Spatiotemporal Expression ofInternational journal of molecular sciences · 2021
    Article
  15. A New Zebrafish Model for Pseudoxanthoma Elasticum.Frontiers in cell and developmental biology · 2021
    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 2 countries.

Adam Michael StewartZENEREI Institute and The International Zebrafish Neuroscience Research Consortium Slidell, LA, USA.
Robert GerlaiDepartment of Psychology, University of Toronto Mississauga ON, Canada.
Allan V KalueffZENEREI Institute and The International Zebrafish Neuroscience Research Consortium Slidell, LA, USA ; Research Institute for Marine Drugs and Nutrients, College of Food Science and Technology, Guangdong Ocean University Zhanjiang, Guangdong, China.
Guangdong Ocean University · CNUniversity of Toronto · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high prevalence of brain disorders and the lack of their efficient treatments necessitate improved in-vivo pre-clinical models and tests. The zebrafish (Danio rerio), a vertebrate species with high genetic and physiological homology to humans, is an excellent organism for innovative central nervous system (CNS) drug discovery and small molecule screening. Here, we outline new strategies for developing higher-throughput zebrafish screens to test neuroactive drugs and predict their pharmacological mechanisms. With the growing application of automated 3D phenotyping, machine learning algorithms, movement pattern- and behavior recognition, and multi-animal video-tracking, zebrafish screens are expected to markedly improve CNS drug discovery.

Indexed as

big dataCNS drug discoveryhigh-throughput screensphenomicszebrafish models

Identifiers

PMID25729356
PMCPMC4325915
OpenAlexW2085357826

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.