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Record W2944253064 · doi:10.1016/j.celrep.2019.04.023

Comparison of Co-housing and Littermate Methods for Microbiota Standardization in Mouse Models

2019· article· en· W2944253064 on OpenAlexafffund
Susan J. Robertson, Paul Lemire, Heather Maughan, Ashleigh Goethel, Williams Turpin, Larbi Bedrani, David S. Guttman, Kenneth Croitoru, Stephen E. Girardin, Dana J. Philpott

Bibliographic record

VenueCell Reports · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchConnaught FundUniversity of Toronto
KeywordsBiologyGut floraFecesIleumPhenotypeTransmission (telecommunications)ConfoundingGeneticsImmunologyMicrobiologyInternal medicineMedicineEndocrinologyGeneComputer science

Abstract

fetched live from OpenAlex

The intestinal microbiota is a fundamental factor that broadly influences physiology. Thus, studies using transgenic animals should be designed to limit the confounding effects of microbiota variation between strains. Here, we report the impact on intestinal microbiota of co-housed versus F2-generation littermates, two commonly used techniques to standardize microbiota in animal models. Our results establish that while fecal microbiota is partially normalized by extended co-housing, mucosal communities associated with the proximal colon and terminal ileum remain stable and distinct. In contrast, strain inter-crossing to generate F2 littermates allows robust microbiota standardization in fecal, colon, and ileum sampling locations. Using reciprocal inter-crosses of P1 parents, we identify dissymmetry in F2 community structures caused by maternal transmission, in particular of the Verrucomicrobiaceae. Thus, F2 littermate animals from a unidirectional P1 cross should be used as a standard method to minimize the influence of the microbiota in genotype-phenotype studies.

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)0.007
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.002

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 head0.024
GPT teacher head0.375
Teacher spread0.351 · 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 designBench or experimental
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

Citations200
Published2019
Admission routes2
Has abstractyes

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