Evidence map›Paper›PMID 37237091›Full record

ArticleScientific reports2023

Variation in mouse chemical signals is genetically controlled and environmentally modulated.

Romana Stopková, Tereza Matějková, Alica Dodoková, Pavel Talacko, Petr Zacek, Radislav Sedlacek, Jaroslav Piálek, Pavel Stopka

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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

8 authors.

Romana StopkováDepartment of Zoology, Faculty of Science, BIOCEV, Charles University, Vestec, Prague, Czech Republic.
Tereza MatějkováDepartment of Zoology, Faculty of Science, BIOCEV, Charles University, Vestec, Prague, Czech Republic.
Alica DodokováDepartment of Zoology, Faculty of Science, BIOCEV, Charles University, Vestec, Prague, Czech Republic.
Pavel TalackoDepartment of Zoology, Faculty of Science, BIOCEV, Charles University, Vestec, Prague, Czech Republic.
Petr ZacekDepartment of Zoology, Faculty of Science, BIOCEV, Charles University, Vestec, Prague, Czech Republic.
Radislav SedlacekCzech Centre for Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic.
Jaroslav PiálekResearch Facility Studenec, Institute of Vertebrate Biology, Czech Academy of Sciences, Brno, Czech Republic.
Pavel StopkaDepartment of Zoology, Faculty of Science, BIOCEV, Charles University, Vestec, Prague, Czech Republic. pstopka@natur.cuni.cz.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In most mammals and particularly in mice, chemical communication relies on the detection of ethologically relevant fitness-related cues from other individuals. In mice, urine is the primary source of these signals, so we employed proteomics and metabolomics to identify key components of chemical signalling. We show that there is a correspondence between urinary volatiles and proteins in the representation of genetic background, sex and environment in two house mouse subspecies Mus musculus musculus and M. m. domesticus. We found that environment has a strong influence upon proteomic and metabolomic variation and that volatile mixtures better represent males while females have surprisingly more sex-biased proteins. Using machine learning and combined-omics techniques, we identified mixtures of metabolites and proteins that are associated with biological features.

Indexed as

ProteinsProteomicsAnimalsCuesFemaleGenetic VariationMaleMammalsMiceSignal TransductionProteins

Identifiers

PMID37237091
PMCPMC10219973

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.