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Record W4409510873 · doi:10.1111/imr.70018

Pathobiology and Regulation of Eosinophils, Mast Cells, and Basophils in Allergic Asthma

2025· review· en· W4409510873 on OpenAlexaff
Christiane E. Whetstone, Tooba Javed, Gail M. Gauvreau

Bibliographic record

VenueImmunological Reviews · 2025
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcMaster University
Fundersnot available
KeywordsImmunologyEosinophiliaAllergic inflammationEosinophilAsthmaMedicineInflammationAllergenAllergyPulmonary EosinophiliaInterleukin 5InterleukinCytokine

Abstract

fetched live from OpenAlex

Eosinophilia is a hallmark of allergic disorders, including asthma, allergic rhinitis, and atopic dermatitis. The onset and maintenance of allergic inflammation in atopic adults involves the activation of selective hemopoietic processes and the migration of mature and immature eosinophils to allergic tissue, where these cells release mediators of inflammation that participate in the regulation of inflammation. Eosinophils function in close cooperation with basophils and mast cells in allergic tissue, where crosstalk between these central effector cells regulates the inflammatory process. This chapter will review the cellular events leading to the accumulation of eosinophils and their progenitors in the airways in allergic asthma, with a particular focus on models of allergen-induced allergic inflammation. Inhaled allergen challenges in allergic asthmatics have advanced understanding of the pathogenesis of allergen exposure leading to early and late asthmatic responses and the associated airway hyperresponsiveness and type 2 airway inflammation. This chapter will also discuss the mechanisms of commonly used asthma therapies on allergen-induced eosinophilia and compare the effects of novel therapies targeting specific immune pathways for a better understanding of how to regulate airway eosinophil levels in patients with asthma.

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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.976
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.043
GPT teacher head0.332
Teacher spread0.289 · 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 designOther design
Domainnot available
GenreReview

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

Citations21
Published2025
Admission routes1
Has abstractyes

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