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Record W7116745361 · doi:10.1002/jcp.70112

Altered Metabolism in Idiopathic Pulmonary Fibrosis

2025· article· en· W7116745361 on OpenAlexafffund
Neal I. Callaghan, Locke Davenport Huyer

Bibliographic record

VenueJournal of Cellular Physiology · 2025
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsNova Scotia Health AuthorityDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIdiopathic pulmonary fibrosisDiseaseLungPulmonary fibrosisInterstitial lung diseaseFibrosisMetabolomicsExtracellular matrixCellular respiration

Abstract

fetched live from OpenAlex

Idiopathic pulmonary fibrosis (IPF) is an incurable lung disease that ultimately terminates in death or lung transplantation. It is characterized by a restrictive pattern with impaired diffusion capacity, and typically presents with repeated acute exacerbations that result in permanent and progressive loss of respiratory function. IPF bears complicated and likely multifactorial etiology manifesting in the dysfunction of multiple cell types, a 2-year mortality over 40%, and available treatments can only slow disease progression. Distinct metabolic disturbances in IPF underscore the mechanisms of deranged cell function, including regional oxidative stress, fibrotic extracellular matrix production, and epithelial dysfunction including impaired pulmonary surfactant production. Although the precise profile of metabolic derangements in IPF remain contentious across multiple studies and models of disease, metabolism represents a critically untapped pathway for therapeutic intervention. In this review, the mechanisms underlying IPF development and progression are isolated and linked to cell-specific alterations in metabolic function. We furthermore compare various in vivo and in vitro models of IPF with focus on metabolic analyses, and critically compare them to patient-derived data. Finally, new metabolically-associated biomarkers of IPF progression are discussed, and recommendations for further IPF modeling and metabolic targeting of IPF-related processes are provided. This review serves to provide a consensus survey of the current metabolomic IPF landscape, as well as a critical discussion of next steps for in vitro modeling to develop disease-modifying therapeutics targeting dysregulated metabolism in IPF.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score0.563

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.007
GPT teacher head0.251
Teacher spread0.244 · 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 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

Citations3
Published2025
Admission routes2
Has abstractyes

Explore more

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