miR-146a-5p plays an essential role in the aberrant epithelial–fibroblast cross-talk in COPD
Bibliographic record
Abstract
We previously reported that epithelial-derived interleukin (IL)-1α drives fibroblast-derived inflammation in the lung epithelial–mesenchymal trophic unit. Since miR-146a-5p has been shown to negatively regulate IL-1 signalling, we investigated the role of miR-146a-5p in the regulation of IL-1α-driven inflammation in chronic obstructive pulmonary disease (COPD). Human bronchial epithelial (16HBE14o-) cells were co-cultured with control and COPD-derived primary human lung fibroblasts (PHLFs), and miR-146a-5p expression was assessed with and without IL-1α neutralising antibody. Genomic DNA was assessed for the presence of the single nucleotide polymorphism (SNP) rs2910164. miR-146a-5p mimics were used for overexpression studies to assess IL-1α-induced signalling and IL-8 production by PHLFs. Co-culture of PHLFs with airway epithelial cells significantly increased the expression of miR-146a-5p and this induction was dependent on epithelial-derived IL-1α. miR-146a-5p overexpression decreased IL-1α-induced IL-8 secretion in PHLFs via downregulation of IL-1 receptor-associated kinase-1. In COPD PHLFs, the induction of miR-146a-5p was significantly less compared with controls and was associated with the SNP rs2910164 (GG allele) in the miR-146a-5p gene. Our results suggest that induction of miR-146a-5p is involved in epithelial–fibroblast communication in the lungs and negatively regulates epithelial-derived IL-1α induction of IL-8 by fibroblasts. The decreased levels of miR-146a-5p in COPD fibroblasts may induce a more pro-inflammatory phenotype, contributing to chronic inflammation in COPD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".