Metabolic heterogeneity of idiopathic pulmonary fibrosis: a metabolomic study
Bibliographic record
Abstract
INTRODUCTION: Idiopathic pulmonary fibrosis (IPF) is a chronic and fatal disease of unknown cause characterised by progressive fibrotic formation in lung tissue. We hypothesise that disrupted metabolic pathways in IPF contribute to disease pathogenesis. METHODS: Metabolomics of human IPF was performed using mass spectroscopy (IPF lung=8; donor lung=8). Gene expression of key metabolic enzymes was measured using microarrays. Of the 108 metabolites whose levels were found altered, 48 were significantly increased, whereas 60 were significantly decreased in IPF samples compared with normal controls. RESULTS: Specific metabolic pathways mediating the IPF remodelling were found with a downregulated sphingolipid metabolic pathway but an upregulated arginine pathway in IPF. In addition, disrupted glycolysis, mitochondrial beta-oxidation and tricarboxylic acid cycle, altered bile acid, haem and glutamate/aspartate metabolism were found in IPF samples compared with control. CONCLUSIONS: Our results show alterations in metabolic pathways for energy consumption during lung structural remodelling, which may contribute to IPF pathogenesis. We believe that this is the first report of simultaneously and systemically measuring changes of metabolites involving nine metabolic pathways in human severe IPF lungs. The measurement of the metabolites may serve in the future diagnosis and prognosis of 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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".