Altered Metabolism in Idiopathic Pulmonary Fibrosis
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".