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Record W2149075421 · doi:10.1172/jci19711

Antigen-specific CD4+ T cells drive airway smooth muscle remodeling in experimental asthma

2005· article· en· W2149075421 on OpenAlexafffund
David Ramos‐Barbón, John F. Presley, Qutayba Hamid, Elizabeth D. Fixman, James G. Martin

Bibliographic record

VenueJournal of Clinical Investigation · 2005
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcGill UniversityChristie (Canada)
FundersCanadian Institutes of Health ResearchEuropean Respiratory SocietyMcGill UniversityGlaxoSmithKlineLady Davis Institute for Medical ResearchCanadian Lung AssociationAstraZeneca
KeywordsAsthmaAntigenImmunologyAirwayMedicineAnesthesia

Abstract

fetched live from OpenAlex

Airway smooth muscle (ASM) growth contributes to the mechanism of airway hyperresponsiveness in asthma. Here we demonstrate that CD4+ T cells, central to chronic airway inflammation, drive ASM remodeling in experimental asthma. Adoptive transfer of CD4+ T cells from sensitized rats induced an increase in proliferation and inhibition of apoptosis of airway myocytes in naive recipients upon repeated antigen challenge, which resulted in an increase in ASM mass. Genetically modified CD4+ T cells expressing enhanced GFP (EGFP) were localized by confocal microscopy in juxtaposition to ASM cells, which suggests that CD4+ T cells may modulate ASM cell function through direct cell-cell interaction in vivo. Coculture of antigen-stimulated CD4+ T cells with cell cycle-arrested ASM cells induced myocyte proliferation, dependent on T cell activation and direct T cell-myocyte contact. Reciprocally, direct cell contact prevented postactivation T cell apoptosis, which suggests receptor-mediated T cell-myocyte crosstalk. Overall, our data demonstrate that activated CD4+ T cells drive ASM remodeling in experimental asthma and suggest that a direct cell-cell interaction participates in CD4+ T cell regulation of myocyte turnover and induction of remodeling.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.464
Threshold uncertainty score0.445

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 integrity0.0000.001
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 head0.067
GPT teacher head0.367
Teacher spread0.301 · 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 designObservational
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

Citations125
Published2005
Admission routes2
Has abstractyes

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