Dach1 attenuates airway inflammation in chronic obstructive pulmonary disease by activating Nrf2 signaling
Bibliographic record
Abstract
Abstract Background: Chronic obstructive pulmonary disease (COPD)is a small airway chronic inflammatory disease with impaired lung function primarily induced by cigarette smoke (CS). Reduced Dach1 expression has a vicious role in numerous disorders. but its role in COPD is rarely known. This study aims to elucidate the role and underlying mechanism of Dach1 in airway inflammation of COPD. Methods:Dach1 expression in lung tissues of COPD patients has been calculated. Small airway epithelium-specific Dach1 knockdown mice and AAV-transfected Dach1 overexpressed mice were used to explore its role and potential for therapeutic targeting in experimental COPD induced by CS. Furtherly, we uncovered the promising mechanism of Dach1 in inflammation induced by cigarette smoke extract simulation (CSE) in vitro. Results:The expression of Dach1 decreased in COPD patients compared to non-smokers and smoker without COPD, especially in small airway epithelium. Small airway epithelium-specific Dach1 knockdown aggravated mice airway inflammation and lung function decline caused by CS, while Dach1 overexpression protected mice from airway inflammation and lung function decline. In 16 HBE cells, Dach1 knockdown and overexpression promoted and inhibited the secretion of IL-6 and IL-8 after simulation of CSE, respectively. Nuclear factor erythroid 2-related factor 2 (Nrf2) was identified as novel downstream target of Dach1, which directly binds to its promoter. Induction of Dach1 alleviated inflammation by activating Nrf2 signaling. Conclusions: Dach1 is decreased in COPD patients. Dach1 has protective effects against inflammation induced by CS by activating Nrf2 signaling pathway. Targeting Dach1 is a potential therapeutic strategy for 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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".