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Record W4415886252 · doi:10.1080/01902148.2025.2582970

Extracellular matrix and immune dysfunction: An overlooked relationship in idiopathic pulmonary fibrosis

2025· article· en· W4415886252 on OpenAlexafffund
Upama Nyaupane, Kerri A. Johannson, Margaret M. Kelly, FuiBoon Kai

Bibliographic record

VenueExperimental Lung Research · 2025
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchLung Health Foundation
KeywordsIdiopathic pulmonary fibrosisImmune systemExtracellular matrixPathogenesisImmune dysregulationFibrosisInnate immune system

Abstract

fetched live from OpenAlex

Idiopathic pulmonary fibrosis (IPF) is a progressive fatal disease. Current clinically approved treatments slow disease progression but are not curative. Thus, there is a critical need to better define the pathogenic mechanisms of IPF and develop novel approaches to treat this devastating lung condition. Immune dysregulation of both the innate and adaptive immune systems, accompanied by fibrosis, constitutes a key hallmark of IPF. IPF is generally considered to be a fibroproliferative disorder rather than an immune condition because, historically, immunomodulatory therapies have failed to produce significant clinical effect. This lack of response is frustrating given that there is evidence of immune dysfunction in IPF and highlights the need to clarify the role of immune cells and inflammatory pathways in IPF. There is increasing evidence that the extracellular matrix (ECM) directs cell fate and function, and we propose that ECM remodeling and immune dysfunction in IPF generate a self-perpetuating fibrotic circuit that is refractory to classical anti-inflammatory agents. Understanding the relationship between ECM and immune dysfunction in IPF pathogenesis could help identify novel therapeutic approaches for this devastating disease.

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 score0.745
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.030
GPT teacher head0.378
Teacher spread0.348 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

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