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Record W3005335304 · doi:10.1101/2020.02.09.940981

Gut microbiome modulates behaviour and life history in two wild rodents

2020· preprint· en· W3005335304 on OpenAlexafffund
Joël W. Jameson, Denis Réale, Steven W. Kembel

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2020
Typepreprint
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of CanadaUniversities Space Research AssociationAmerican Society of MammalogistsAnimal Behavior Society
KeywordsPeromyscusMicrobiomeBiologyAbundance (ecology)ZoologyLife history theoryEcologyHost (biology)Range (aeronautics)Life historyGenetics

Abstract

fetched live from OpenAlex

ABSTRACT Laboratory studies demonstrate that the gut microbiome can regulate host anxiety and exploratory behaviour. While this has implications for human health, it could have ecological and evolutionary implications for wild populations, a hitherto untested hypothesis. We tested whether the microbiome can directly modulate host behaviour and thereby affect life history in wild mice ( Peromyscus maniculatus ) and voles ( Myodes gapperi ). We compared the microbiome composition, exploration and anxiety behaviours, and home range of mice and voles before and after chronic antibiotic treatment and measured survival during treatment. Treated animals had lower diversity and relative abundance of most bacterial phyla save for Proteobacteria which increased in relative abundance. In mice, antibiotic treatment increased exploration and decreased home range without impacting survival. In voles, it lowered survival such that we could not test its effect on behaviour. Therefore, the microbiome can directly impact behaviour and host life history in the wild.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.032
GPT teacher head0.278
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2020
Admission routes2
Has abstractyes

Explore more

Same venuebioRxiv (Cold Spring Harbor Laboratory)Same topicNeuroendocrine regulation and behaviorFrench-language works237,207