Metabolism‐Related Gene TXNRD1 Regulates Inflammation and Oxidative Stress Induced by Cigarette Smoke through the Nrf2/HO‐1 Pathway in the Small Airway Epithelium
Bibliographic record
Abstract
Chronic obstructive pulmonary disease (COPD), a small airway disease, is regarded as a metabolic disorder. To further uncover the metabolic profile of COPD patients, it is necessary to identify metabolism‐related differential genes in small airway epithelium (SAE) of COPD. Metabolism‐related differential genes in SAE between COPD patients and nonsmokers were screened from GSE128708 and GSE20257 datasets. KEGG, GO, and PPI analyses were performed to evaluate the pathway enrichment, term enrichment, and protein interaction of candidate metabolism‐related differential genes, respectively. RT‐PCR was used to verify the mRNA expression of the top ten differential genes. Western blotting was used to evaluate the protein expression of TXNRD1. TXNRD1 inhibitor auranofin (AUR) was used to assess the impact of TXNRD1 on oxidative stress and inflammation induced by cigarette smoke extraction (CSE). Twenty‐four metabolism‐related differential genes were selected. ALDH3A1, AKR1C3, CYP1A1, AKC1C1, CPY1B1, and TXNRD1 in the top ten genes were significantly upregulated after CSE simulation for 24 h in human bronchial epithelial (16HBE) cells. Among them, CYP1A1 and TXNRD1 also have a significant upregulation in primary SAE after simulation of CSE for 24 h. The overexpression of protein TXNRD1 has also been detected in 16HBE cells, primary SAE stimulated with CSE, and mouse lung exposed to cigarette smoke (CS). Additionally, inhibition of TXNRD1 with 0.1 μ M AUR alleviated the expression of IL‐6 and reactive oxygen species (ROS) induced by CSE by activating the Nrf2/HO‐1 pathway in 16HBE cells. This study identified twenty‐four metabolism‐related differential genes associated with COPD. TXNRD1 might participate in the oxidative stress and inflammation induced by CS by regulating the activation of the Nrf2/HO‐1 pathway.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".