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Record W2078201105 · doi:10.1073/pnas.100118997

IL-10 is necessary for the expression of airway hyperresponsiveness but not pulmonary inflammation after allergic sensitization

2000· article· en· W2078201105 on OpenAlexaff
Mika J. Mäkelä, Arihiko Kanehiro, Larry Borish, Azzeddine Dakhama, J Loader, Anthony Joetham, Manel Jordana, Gary L. Larsen, Erwin W. Gelfand

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2000
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcMaster University
FundersNational Institutes of HealthNational Heart, Lung, and Blood InstituteAcademy of Finland
KeywordsSensitizationAirway hyperresponsivenessImmunologyMedicineInflammationCytokineAirwayIn vivoAsthmaLungBiologyInternal medicine

Abstract

fetched live from OpenAlex

Cytokines play an important role in modulating inflammatory responses and, as a result, airway tone. IL-10 is a regulatory cytokine that has been suggested for treatment of asthma because of its immunosuppressive and anti-inflammatory properties. In contrast to these suggestions, we demonstrate in a model of allergic sensitization that mice deficient in IL-10 (IL-10-/-) develop a pulmonary inflammatory response but fail to exhibit airway hyperresponsiveness in both in vitro and in vivo assessments of lung function. Reconstitution of these deficient mice with the IL-10 gene fully restores development of airway hyperresponsiveness comparable to control mice. These results identify an important role of IL-10, downstream of the inflammatory cascade, in regulating the tone of the airways after allergic sensitization and challenge.

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)0.001
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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.024
GPT teacher head0.288
Teacher spread0.265 · 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

Citations200
Published2000
Admission routes1
Has abstractyes

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