Evidence map›Paper›PMID 35006075›Full record

ArticleeLife2022

Comparative transcriptomic analysis reveals translationally relevant processes in mouse models of malaria.

Athina Georgiadou, Claire Dunican, Pablo Soro-Barrio, Hyun Jae Lee, Myrsini Kaforou, Aubrey J Cunnington

Open access · goldAbstract readComparative Study
In one paragraph

Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

13 citing papers in PubMed, 22 citations in OpenAlex.

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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 at 2 institutions in 2 countries.

Athina Georgiadou *Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, United Kingdom.ORCID 0000-0002-0440-9335
Claire Dunican *Section of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, United Kingdom.
Pablo Soro-BarrioSection of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, United Kingdom.ORCID 0000-0003-4509-6109
Hyun Jae LeeInstitute for Molecular Bioscience, University of Queensland, Brisbane, Australia.
Myrsini KaforouSection of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, United Kingdom.ORCID 0000-0001-9878-4007
Aubrey J CunningtonSection of Paediatric Infectious Disease, Department of Infectious Disease, Imperial College London, London, United Kingdom.ORCID 0000-0002-1305-3529
Imperial College London · GBThe University of Queensland · AU

Funding

Biotechnology and Biological Sciences Research Council BB/K003240/1Department of HealthMedical Research Council MR/L006529/1Medical Research Council MR/M008924/1Wellcome Trust 206508/Z/17/ZWellcome Trust WT097835MFWellcome Trust WT101650MA
6 · The paper itself

Abstract

Recent initiatives to improve translation of findings from animal models to human disease have focussed on reproducibility but quantifying the relevance of animal models remains a challenge. Here, we use comparative transcriptomics of blood to evaluate the systemic host response and its concordance between humans with different clinical manifestations of malaria and five commonly used mouse models.

Indexed as

TranscriptomeAnemiaAnimalsDisease Models, AnimalFemaleGene Expression ProfilingHost-Parasite InteractionsHumansMalariaMalaria, FalciparumMiceMice, Inbred C57BLPlasmodiumReproducibility of Resultsgeneticsgenomicsmalariamousemouse modelstranscriptomics

Identifiers

PMID35006075
PMCPMC8747512
OpenAlexW4221130204

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.