Low levels of the AhR in chronic obstructive pulmonary disease (COPD)-derived lung cells increases COX-2 protein by altering mRNA stability
Bibliographic record
Abstract
Heightened inflammation, including expression of COX-2, is associated with chronic obstructive pulmonary disease (COPD) pathogenesis. The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that is reduced in COPD-derived lung fibroblasts. The AhR also suppresses COX-2 in response to cigarette smoke, the main risk factor for COPD, by destabilizing the Cox-2 transcript by mechanisms that may involve the regulation of microRNA (miRNA). Whether reduced AhR expression is responsible for heightened COX-2 in COPD is not known. Here, we investigated the expression of COX-2 as well as the expression of miR-146a, a miRNA known to regulate COX-2 levels, in primary lung fibroblasts derived from non-smokers (Normal) and smokers (At Risk) with and without COPD. To confirm the involvement of the AhR, AhR knock-down via siRNA in Normal lung fibroblasts and MLE-12 cells was employed as were A549-AhRko cells. Basal expression of COX-2 protein was higher in COPD lung fibroblasts compared to Normal or Smoker fibroblasts but there was no difference in Cox-2 mRNA. Knockdown of AhR in lung structural cells increased COX-2 protein by stabilizing the Cox-2 transcript. There was less induction of miR-146a in COPD-derived lung fibroblasts but this was not due to the AhR. Instead, we found that RelB, an NF-κB protein, was required for transcriptional induction of both Cox-2 and miR-146a. Therefore, we conclude that the AhR controls COX-2 protein via mRNA stability by a mechanism independent of miR-146a. Low levels of the AhR may therefore contribute to the heightened inflammation common in COPD patients.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".