MétaCan
Menu
Back to cohort
Record W4413443901 · doi:10.1038/s41467-026-73293-9

RANK-DEPENDENT CONTROL OF TUFT AND BEST4 CELL DEVELOPMENT IN THE INTESTINE

2025· article· en· W4413443901 on OpenAlexafffund
Reegan J. Willms, Tori McCabe, Lena O. Jones, Ruth Schade, Edan Foley

Bibliographic record

VenueNature Communications · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDigestive system and related health
Canadian institutionsMacEwan UniversityWomen and Children’s Health Research InstituteUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsTuftRank (graph theory)Control (management)Large intestineCryptMathematicsBiologyComputer scienceCombinatoricsPhysicsEndocrinologyArtificial intelligenceBiochemistryThermodynamics

Abstract

fetched live from OpenAlex

Specialist intestinal epithelial cells are critical for barrier integrity and immune responses at the mucosal boundary, yet the pathways that govern their development are incompletely defined. Here, we identify an essential role for TNFRSF11A/RANK in shaping intestinal epithelial specialization in zebrafish. Using lineage trajectory analysis, we identify two tuft cell subtypes, including a subtype enriched for expression of genes required to produce pro-inflammatory leukotrienes. We show that RANK deficiency reduces the abundance of immune-regulatory tuft and BEST4 cells, increases goblet cell frequency, and promotes the accumulation of pro-inflammatory leukocytes in the gut. Functionally, we demonstrate that the number of cells expressing the BEST4 cell marker cftr expand following infection with a pandemic strain of Vibrio cholerae, and we show that RANK deficiency enhances fish susceptibility to host colonization by Vibrio, implicating this lineage in host defenses against an enteric pathogen. Together, our findings implicate RANK signaling in intestinal epithelial diversification and immune regulation.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.492
Threshold uncertainty score0.158

Codex and Gemma teacher scores by category

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

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 head0.008
GPT teacher head0.287
Teacher spread0.279 · 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 teacher head, 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueNature CommunicationsSame topicDigestive system and related healthFrench-language works237,207