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Record W4393384885 · doi:10.1038/s41467-024-45616-1

Dysregulation of Wnt/β-catenin signaling contributes to intestinal inflammation through regulation of group 3 innate lymphoid cells

2024· article· en· W4393384885 on OpenAlexfundno aff
Jiacheng Hao, Chang Liu, Zhijie Gu, Xuanming Yang, Xun Lan, Xiaohuan Guo

Bibliographic record

VenueNature Communications · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsnot available
FundersTsinghua UniversityNational Natural Science Foundation of ChinaYork University
KeywordsInnate lymphoid cellWnt signaling pathwayRAR-related orphan receptor gammaJUNBInflammationBiologyInflammatory bowel diseaseCell biologyImmunologyTranscription factorCancer researchSignal transductionInnate immune systemInternal medicineMedicineDiseaseImmune systemBiochemistry

Abstract

fetched live from OpenAlex

group 3 innate lymphoid cells (ILC3s) are essential for intestinal homeostasis. Dysregulation of ILC3s has been found in the gut of patients with inflammatory bowel disease and colorectal cancer, yet the specific mechanisms still require more investigation. Here we observe increased β-catenin in intestinal ILC3s from inflammatory bowel disease and colon cancer patients compared with healthy donors. In contrast to promoting RORγt expression in T cells, activation of Wnt/β-catenin signaling in ILC3s suppresses RORγt expression, inhibits its proliferation and function, and leads to a deficiency of ILC3s and subsequent intestinal inflammation in mice. Activated β-catenin and its interacting transcription factor, TCF-1, cannot directly suppress RORγt expression, but rather alters global chromatin accessibility and inhibits JunB expression, which is essential for RORγt expression in ILC3s. Together, our findings suggest that dysregulated Wnt/β-catenin signaling impairs intestinal ILC3s through TCF-1/JunB/RORγt regulation, further disrupting intestinal homeostasis, and promoting inflammation and cancer.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.017
GPT teacher head0.269
Teacher spread0.252 · 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 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

Citations31
Published2024
Admission routes1
Has abstractyes

Explore more

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