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Record W4386070214 · doi:10.1093/cei/uxad100

Female-specific enhancement of eosinophil recruitment and activation in a type 2 innate inflammation model in the lung

2023· article· en· W4386070214 on OpenAlexafffund
Rami Karkout, Véronique Gaudreault, Lydia Labrie, Haya Aldossary, Noelia Azalde Garcia, Jichuan Shan, Elizabeth D. Fixman

Bibliographic record

VenueClinical & Experimental Immunology · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicIL-33, ST2, and ILC Pathways
Canadian institutionsMcGill University Health Centre
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchMcGill University Health CentreMcGill University
KeywordsImmunologyInnate lymphoid cellEosinophilInnate immune systemChemokineAcquired immune systemInterleukin 5InflammationBiologyAsthmaCytokineImmune systemMedicineInterleukin

Abstract

fetched live from OpenAlex

A sex disparity in asthma prevalence and severity exists in humans. Multiple studies have highlighted the role of innate cells in shaping the adaptive immune system in chronic asthma. To explore the sex bias in the eosinophilic response, we delivered IL-33 to the lungs of mice and delineated the kinetics by which the inflammatory response was induced. Our data demonstrate that females recruited more eosinophils capable of responding to IL-33. Eosinophil activation occurred selectively in the lung tissue and was enhanced in females at all time points. This increase was associated with increased ex vivo type 2 cytokine and chemokine production and female-specific expansion of group 2 innate lymphoid cells lacking expression of the killer-cell lectin-like receptor G1. Our findings suggest that the enhanced eosinophilic response in females is due, firstly, to a greater proportion of eosinophils recruited to the lungs in females that can respond to IL-33; and secondly, to an enhanced production of type 2 cytokines in females. Our data provide insight into the mechanisms that guide the female-specific enhancement of eosinophil activation in the mouse and form the basis to characterize these responses in human asthmatics.

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 score0.062
Threshold uncertainty score0.532

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 studies0.0000.000
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 head0.151
GPT teacher head0.390
Teacher spread0.239 · 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

Citations9
Published2023
Admission routes2
Has abstractyes

Explore more

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