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Record W2883316455 · doi:10.1084/jem.20172359

ICAM-1 controls development and function of ILC2

2018· article· en· W2883316455 on OpenAlexfundno aff
Aihua Lei, Qiang Xiao, Gao-Yu Liu, Kun Shi, Qiong Yang, Xing Li, Yufeng Liu, Haikun Wang, Weiping Cai, Yu-Juan Guan, Dmitry I. Gabrilovich, Jie Zhou

Bibliographic record

VenueThe Journal of Experimental Medicine · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsnot available
FundersHigher Education Discipline Innovation ProjectNatural Science Foundation of Guangdong ProvinceSun Yat-sen UniversityNational Natural Science Foundation of ChinaGuangzhou Science and Technology Program key projectsChina Postdoctoral Science FoundationNational Key Research and Development Program of ChinaSunnybrook Research Institute
KeywordsFunction (biology)BiologyCell biology

Abstract

fetched live from OpenAlex

Group 2 innate lymphoid cells (ILC2s) are emerging as key players in the pathogenesis of allergic airway inflammation. The mechanisms regulating ILC2, however, are not fully understood. Here, we found that ICAM-1 is required for the development and function of ILC2. ICAM-1–deficient (ICAM-1−/−) mice displayed significantly lower levels of ILC2s in the bone marrow and peripheral tissues than wild-type controls. CLP transfer and in vitro culture assays revealed that the regulation of ILC2 by ICAM-1 is cell intrinsic. Furthermore, ILC2s from ICAM-1−/− mice were functionally impaired, as indicated by the diminished production of type-2 cytokines in response to IL-33 challenge. The reduction in lung ILC2s caused a clear remission of airway inflammation in ICAM-1−/− mice after administration of papain or Alternaria alternata. We further demonstrate that ILC2 defects caused by ICAM-1 deficiency are due to ERK signaling-dependent down-regulation of GATA3 protein. Collectively, these observations identify ICAM-1 as a novel regulator of ILC2.

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 score0.001
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.020
GPT teacher head0.263
Teacher spread0.243 · 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

Citations71
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Experimental MedicineSame topicIL-33, ST2, and ILC PathwaysFrench-language works237,207