Evidence map›Paper›PMID 36250972›Full record

ArticleDisease models & mechanisms2022

Animals, quality and the pursuit of relevance.

Karen L Svenson, Stephen D Krasinski, Michael Ellis, Nadia Rosenthal, Edison T Liu, Kenneth H Fasman

Open access · goldAbstract read
In one paragraph

Article in Disease models & mechanisms, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 32% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Synergistic modelling of human disease.Disease models & mechanisms · 2024
    Article
  2. Impactful in disease research: a DMM year in review.Disease models & mechanisms · 2023
    Article
  3. Article
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 at 1 institution in 1 country.

Karen L SvensonThe Jackson Laboratory, Bar Harbor, ME 04609, USA.ORCID 0000-0002-7928-1911
Stephen D KrasinskiThe Jackson Laboratory, Bar Harbor, ME 04609, USA.
Michael EllisThe Jackson Laboratory, Bar Harbor, ME 04609, USA.
Nadia RosenthalThe Jackson Laboratory, Bar Harbor, ME 04609, USA.ORCID 0000-0002-7599-7365
Edison T LiuThe Jackson Laboratory, Bar Harbor, ME 04609, USA.ORCID 0000-0003-4293-4795
Kenneth H FasmanThe Jackson Laboratory, Bar Harbor, ME 04609, USA.
Jackson Laboratory · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In 2021, the National Institutes of Health Advisory Committee to the Director (ACD) announced recommendations to improve the reproducibility of biomedical research using animals. In response, The Jackson Laboratory faculty and institutional leaders identified key strategies to further address this important issue. Taking inspiration from the evolution of clinical trials over recent decades in response to similar challenges, we identified opportunities for improvement, including establishment of common standards, use of genetically diverse populations, requirement for robust study design with appropriate statistical methods, and improvement in public databases to facilitate meta-analyses. In this Perspective, we share our response to ACD recommendations, with a specific focus on mouse models, with the aim of promoting continued active dialogue among researchers, using any animal system, worldwide. Such discussion will help to inform the biomedical community about these recommendations and further support their much-needed implementation.

Indexed as

Biomedical ResearchAnimalsHumansLaboratoriesMiceReproducibility of ResultsResearch DesignResearch Personnel

Identifiers

PMID36250972
PMCPMC9612867
OpenAlexW4306408158

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.