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Record W2886616492 · doi:10.1186/s12931-018-0857-1

Comprehensive gene expression profiling identifies distinct and overlapping transcriptional profiles in non-specific interstitial pneumonia and idiopathic pulmonary fibrosis

2018· article· en· W2886616492 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRespiratory Research · 2018
Typearticle
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsVictoria HospitalUniversity of TorontoLondon Health Sciences CentreWestern University
FundersSchulich School of Medicine and DentistryCanadian Institutes of Health ResearchLawson Health Research InstituteF. Hoffmann-La Roche
KeywordsIdiopathic pulmonary fibrosisGene expression profilingBiologyPulmonary fibrosisGeneGene expressionUsual interstitial pneumoniaFibrosisPneumoniaGeneticsPathologyComputational biologyMedicineLungInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The clinical-radiographic distinction between idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP) is challenging. We sought to investigate the gene expression profiles of IPF and NSIP vs. normal controls. METHODS: Gene expression from explanted lungs of patients with IPF (n = 22), NSIP (n = 10) and from normal controls (n = 11) was assessed. Microarray analysis included Significance Analysis of Microarray (SAM), Ingenuity Pathway, Gene-Set Enrichment and unsupervised hierarchical clustering analyses. Immunohistochemistry and serology of proteins of interest were conducted. RESULTS: NSIP cases were significantly enriched for genes related to mechanisms of immune reaction, such as T-cell response and recruitment of leukocytes into the lung compartment. In IPF, in contrast, these involved senescence, epithelial-to-mesenchymal transition, myofibroblast differentiation and collagen deposition. Unlike the IPF group, NSIP cases exhibited a strikingly homogenous gene signature. Clustering analysis identified a subgroup of IPF patients with intermediate and ambiguous expression of SAM-selected genes, with the interesting upregulation of both NSIP-specific and senescence-related genes. Immunohistochemistry for p16, a senescence marker, on fibroblasts differentiated most IPF cases from NSIP. Serial serum levels of periostin, a senescence effector, predicted clinical progression in a cohort of patients with IPF. CONCLUSIONS: Comprehensive gene expression profiling in explanted lungs identifies distinct transcriptional profiles and differentially expressed genes in IPF and NSIP, supporting the notion of NSIP as a standalone condition. Potential gene and protein markers to discriminate IPF from NSIP were identified, with a prominent role of senescence in IPF. The finding of a subgroup of IPF patients with transcriptional features of both NSIP and senescence raises the hypothesis that "senescent" NSIP may represent a risk factor to develop superimposed 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.

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 categoriesMeta-epidemiology (narrow)
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 score0.800
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.063
GPT teacher head0.340
Teacher spread0.277 · 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