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Record W2781320385 · doi:10.1016/j.celrep.2017.12.026

The NLR Protein NLRP6 Does Not Impact Gut Microbiota Composition

2017· article· en· W2781320385 on OpenAlexafffund
Paul Lemire, Susan J. Robertson, Heather Maughan, Ivan Tattoli, Catherine Streutker, Jaye M. Platnich, Daniel A. Muruve, Dana J. Philpott, Stephen E. Girardin

Bibliographic record

VenueCell Reports · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGut microbiota and health
Canadian institutionsUniversity of CalgarySt. Michael's HospitalUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsColitisWeaningGut floraBiologyIntestinal epitheliumChemistryInternal medicineImmunologyEndocrinologyEpitheliumMedicineGenetics

Abstract

fetched live from OpenAlex

NLRP6 is a Nod-like receptor expressed in the intestinal epithelium. Previous studies reported a protective role for NLRP6 against intestinal injury and colitis-associated carcinogenesis via the regulation and establishment of a healthy microbiota. However, these results were not obtained using littermate animals, leaving the possibility that the pro-colitogenic microbiota phenotype associated with knockout (KO) mice was stochastically acquired and genotype independent. Here, we analyzed the microbiota at three intestinal locations from Nlrp6 −/− and wild-type (WT) littermates, either co-caged or individually caged after weaning. Our results demonstrate that NLRP6 does not significantly influence the intestinal microbiota at homeostasis, and they support a previously reported sex-biased microbial community structure. Moreover, WT and Nlrp6 −/− littermate mice displayed comparable sensitivity to dextran sulfate sodium (DSS)-induced colitis, although increased sensitivity was noted in KO females. Our results clarify the role of NLRP6 in microbiota and colitis control, and they highlight the importance of analyzing littermate animals in such 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.008
GPT teacher head0.273
Teacher spread0.265 · 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

Citations98
Published2017
Admission routes2
Has abstractyes

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