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Record W3208517554 · doi:10.1172/jci.insight.149699

IL-33 activates group 2 innate lymphoid cell expansion and modulates endometriosis

2021· article· en· W3208517554 on OpenAlexafffund
Jessica E. Miller, Harshavardhan Lingegowda, Lindsey K. Symons, Olga Bougie, Steven L. Young, Bruce A. Lessey, Madhuri Koti, Chandrakant Tayade

Bibliographic record

VenueJCI Insight · 2021
Typearticle
Languageen
FieldMedicine
TopicEndometriosis Research and Treatment
Canadian institutionsKingston General HospitalQueen's University
FundersQueen's UniversityCanadian Institutes of Health ResearchGreenville Health System
KeywordsEndometriosisInnate lymphoid cellInflammationMedicineFibrosisInterleukin 33PathophysiologyInnate immune systemImmune systemImmunologyLesionInterleukinPathologyCytokine

Abstract

fetched live from OpenAlex

Chronic inflammation and localized alterations in immune cell function are suspected to contribute to the progression of endometriosis and its associated symptoms. In particular, the alarmin IL-33 is elevated in the plasma, peritoneal fluid, and endometriotic lesions from patients with endometriosis; however, the exact role of IL-33 in the pathophysiology of endometriosis is not well understood. In this study, we demonstrate, in both humans and a murine model, that IL-33 contributes to the expansion of group 2 innate lymphoid cells (ILC2s), and this IL-33-induced ILC2 expansion modulates the endometriosis lesion microenvironment. Importantly, we show that IL-33 drives hallmarks of severe endometriosis, including elevated inflammation, lesion proliferation, and fibrosis, and that this IL-33-induced aggravation is mediated by ILC2s. Finally, we demonstrate the functionality of IL-33 neutralization as a promising and potentially novel therapeutic avenue for treating the debilitating symptoms of endometriosis.

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 score0.003

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 communication0.0000.000
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 head0.019
GPT teacher head0.270
Teacher spread0.251 · 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

Citations56
Published2021
Admission routes2
Has abstractyes

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