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Record W2140634473 · doi:10.1126/scitranslmed.3000284

Identification of an Autoantigen Demonstrates a Link Between Interstitial Lung Disease and a Defect in Central Tolerance

2009· article· en· W2140634473 on OpenAlexafffund
Anthony K. Shum, Jason DeVoss, Catherine L. Tan, Yafei Hou, Kellsey Johannes, Clodagh O’Gorman, Kirk D. Jones, Etienne Sochett, Lawrence Fong, Mark S. Anderson

Bibliographic record

VenueScience Translational Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsHospital for Sick Children
FundersNational Eye InstituteNational Cancer InstituteNational Institute of Diabetes and Digestive and Kidney DiseasesNational Heart, Lung, and Blood InstituteNational Institute of Allergy and Infectious DiseasesCanadian Institutes of Health Research
KeywordsInterstitial lung diseaseImmunologyDiseaseLungIdentification (biology)MedicineImmune systemImmune toleranceAutoimmunityAntigenBiologyPathologyInternal medicine

Abstract

fetched live from OpenAlex

Interstitial lung disease (ILD) is a common manifestation of systemic autoimmunity characterized by progressive inflammation or scarring of the lungs. Patients who develop these complications can exhibit significantly impaired gas exchange that may result in hypoxemia, pulmonary hypertension, and even death. Unfortunately, little is understood about how these diseases arise, including the role of specific defects in immune tolerance. Another key question is whether autoimmune responses targeting the lung parenchyma are critical to ILD pathogenesis, including that of isolated idiopathic forms. We show that a specific defect in central tolerance brought about by mutations in the autoimmune regulator gene (Aire) leads to an autoreactive T cell response to a lung antigen named vomeromodulin and the development of ILD. We found that a human patient and mice with defects in Aire develop similar lung pathology, demonstrating that the AIRE-deficient model of autoimmunity is a suitable translational system in which to unravel fundamental mechanisms of ILD pathogenesis.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.298

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.015
GPT teacher head0.316
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

Citations68
Published2009
Admission routes2
Has abstractyes

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