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Record W4408938949 · doi:10.3389/falgy.2025.1530122

In vitro models to study viral-induced asthma exacerbation: a short review for a key issue

2025· review· en· W4408938949 on OpenAlexaff
Clément Droillard, Gilles Devouassoux, Manuel Rosa‐Calatrava

Bibliographic record

VenueFrontiers in Allergy · 2025
Typereview
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsAsthmaImmunologyExacerbationCrosstalkImmune systemInflammationPathophysiologyMedicineDiseaseEffectorBiologyPathology

Abstract

fetched live from OpenAlex

Asthma is a heterogenous inflammatory bronchial disease involving complex mechanisms, several inflammatory pathways, and multiples cell-type networks. Bronchial inflammation associated to asthma is consecutive to multiple aggressions on epithelium, such as microbiologic, pollutant, and antigenic agents, which are responsible for both T2 and non-T2 inflammatory responses and further airway remodeling. Because asthma physiopathology involves multiple crosstalk between several cell types from different origins (epithelial, mesenchymal, and immune cells) and numerous cellular effectors, no single and/or representative in vitro model is suitable to study the overall of this disease. In this short review, we present and discuss the advantages and limitations of different in vitro models to decipher different aspects of virus-related asthma physiopathology and exacerbation.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.873
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
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 head0.043
GPT teacher head0.351
Teacher spread0.309 · 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.

Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

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