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IL-25 and innate lymphoid cells induce pulmonary fibrosis (P4357)

2013· article· en· W72407319 on OpenAlexaff
Emily Hams, Michelle E. Armstrong, Jillian Barlow, Małgorzata Kubica, Sean P. Saunders, Gordon Cooke, Thomas B. Crotty, Nik Hirani, Robin J. Flynn, Seamas C. Donnelly, Andrew N. J. McKenzie, Padraic Fallon

Bibliographic record

VenueThe Journal of Immunology · 2013
Typearticle
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsTrinity College
Fundersnot available
KeywordsInnate lymphoid cellPulmonary fibrosisIdiopathic pulmonary fibrosisImmunologyFibrosisMedicineImmune systemLungCytokineInnate immune systemPathologyInternal medicine

Abstract

fetched live from OpenAlex

Abstract Disease conditions associated with pulmonary fibrosis are progressive and have a poor long-term prognosis with irreversible changes in airway architecture leading to marked morbidity and mortalities. Currently there are limited effective therapeutics for pulmonary fibrosis due to an inadequate understanding of the pathogenic process and underlying mechanisms. We now show that in human idiopathic pulmonary fibrosis (IPF) the cytokine interleukin (IL)-25 positively correlates with periostin a marker human pulmonary fibrosis, and the presence of IL-13-producing type 2 innate lymphoid cells (ILC2) in the lung. Using murine models of pulmonary fibrosis we demonstrate an essential role for IL-25-elicited ILC2 in the generation of pulmonary collagen deposition, independent of an adaptive T cell response. Furthermore, we define a mechanism whereby IL-25 evokes ILC2 to induce pulmonary fibrosis via the alternative activation of macrophages in the lung. Collectively, we present a new innate mechanism for the generation of pulmonary fibrosis, via IL-25 and ILC2 that occurs independently of T cell-mediated antigen-specific immune responses. These results indicate that IL-25 and ILC2 are potential therapeutic targets for the treatment of human fibrotic diseases where antigen-independent damage responses may magnify the disease.

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)0.001
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 score0.206
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.009
GPT teacher head0.196
Teacher spread0.187 · 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

Citations0
Published2013
Admission routes1
Has abstractyes

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