Decreased expression of the NF-κB family member RelB in lung fibroblasts from Smokers with and without COPD potentiates cigarette smoke-induced COX-2 expression
Bibliographic record
Abstract
BACKGROUND: Heightened inflammation, including expression of COX-2, is associated with COPD pathogenesis. RelB is an NF-κB family member that attenuates COX-2 in response to cigarette smoke by a mechanism that may involve the miRNA miR-146a. There is no information on the expression of RelB in COPD or if RelB prevents COX-2 expression through miR-146a. METHODS: RelB, Cox-2 and miR-146a levels were evaluated in lung fibroblasts and blood samples derived from non-smokers (Normal) and smokers (At Risk) with and without COPD by qRT-PCR. RelB and COX-2 protein levels were evaluated by western blot. Human lung fibroblasts from Normal subjects and smokers with and without COPD, along with RelB knock-down (siRNA) in Normal cells, were exposed to cigarette smoke extract (CSE) in vitro and COX-2 mRNA/protein and miR-146a levels assessed. RESULTS: Basal expression of RelB mRNA and protein were significantly lower in lung cells derived from smokers with and without COPD, the latter of which expressed more Cox-2 mRNA and protein in response to CSE. Knock-down of RelB in Normal fibroblasts increased Cox-2 mRNA and protein induction by CSE. Basal miR-146a levels were not different between the three groups, and only Normal fibroblasts increased miR-146a expression in response to smoke. There was a positive correlation between systemic RelB and Cox-2 mRNA levels and circulating miR-146a levels were higher only in GOLD stage I subjects. CONCLUSIONS: Our data indicate that RelB attenuates COX-2 expression in lung structural cells, such that loss of pulmonary RelB may be an important determinant in the aberrant, heightened inflammation associated with COPD pathogenesis.
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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) | 0.003 | 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".