Evidence map›Paper›PMID 42100496›Full record

ArticleNeuroscience applied2026

Striking a balance: A proposed benefit assessment matrix for ethical animal research.

Anton Bespalov, Ulrich Dirnagl, Chantelle Ferland-Beckham, Javier Guillén, Kathy Laber, Patricia V Turner, Penny Reynolds

Abstract read
In one paragraph

Article in Neuroscience applied, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Anton BespalovPAASP, Heidelberg, Germany.
Ulrich DirnaglQUEST Center for Responsible Research, Berlin Institute of Health at Charité Universitätsmedizin Berlin, Germany.
Chantelle Ferland-BeckhamMindMeld Consulting, Greenville, SC, USA.
Javier GuillénAAALAC International, Pamplona, Spain.
Kathy LaberRetired National Institute of Environmental Health Sciences, Durham, NC, USA.
Patricia V TurnerDepartment of Pathobiology, University of Guelph, Guelph, Canada.
Penny ReynoldsDepartment of Anesthesiology, STatistics in Anesthesiology Research (STAR) Core, University of Florida College of Medicine, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The debate about the continued use of animals in research has intensified in recent years, with few signs that consensus can be achieved in the near future. Animal activist groups and their supporters call for an immediate halt to all animal research. The counterargument from research scientists and many others across various facets of society is that suitable alternatives have not been sufficiently established and validated to enable all animal research to cease without halting scientific progress. We suggest a compromise rooted in the existing regulations and based on the consensus that not all research efforts contribute enough benefit to ethically justify the use of animals in research. More specifically, we describe a Benefit Assessment Matrix that can provide a streamlined and practical guide for both scientists and Animal Ethics Committees or equivalent bodies such as Institutional Animal Care and Use Committees to assess the benefit of proposed research. The organizational premise is that rigorous high-quality research is more likely to produce tangible benefit than poor quality, low rigor research. Implementation of the Benefit Assessment Matrix will enable more rapid phasing out of poor-quality research and support the objective of promoting rigorous high-quality research, meeting expectations of both sides of the debate.

Identifiers

PMID42100496
PMCPMC13145364

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.