Decline in NRF2‐Regulated Antioxidant Pathway in Advanced COPD Patient Lungs Due to DJ‐1 Deficit
Bibliographic record
Abstract
NRF2, a bZIP transcription factor regulates a battery of cytoprotective genes and protects mice from cigarette smoke‐induced emphysema by attenuating oxidative stress and inflammation. However, NRF2's role in human COPD is unknown. Here, we analyzed expression of NRF2 and its transcriptional targets in non‐emphysematous (NE) lungs, mild COPD lungs (GOLD 1‐2), and advanced COPD lungs (GOLD 3‐4). NRF2‐mediated transcriptional targets (NQO1, HO‐1 and GCLM) declined in advanced COPD, even though there was greater oxidative stress, as evident from increased lipid peroxidation and decreased GSH levels. NRF2 protein but not NRF2 mRNA was dramatically reduced in advanced COPD lungs. KEAP1 protein, the cytoplasmic inhibitor of NRF2, showed no significant difference between NE and COPD lungs. Conversely, DJ‐1, which stabilizes NRF2, showed a significant decrease in both mRNA and protein expression in advanced COPD lungs. Knockdown of DJ‐1 in human lung epithelial (Beas2B) cells and mouse lungs by siRNA significantly decreased Nrf2 protein expression and attenuated induction of antioxidants in response to cigarette smoke exposure. Taken together, in advanced COPD patient lungs, there is a significant decline in Nrf2 protein stability that results in decreased antioxidant protection and increased oxidative stress. Decline in the NRF2 pathway may play an important role in the pathological progression of COPD.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".