Regulation of xanthine dehydrogensase gene expression and uric acid production in human airway epithelial cells
Bibliographic record
Abstract
INTRODUCTION: The airway epithelium is a physical and immunological barrier that protects the pulmonary system from inhaled environmental insults. Uric acid has been detected in the respiratory tract and can function as an antioxidant or damage associated molecular pattern. We have demonstrated that human airway epithelial cells are a source of uric acid. Our hypothesis is that uric acid production by airway epithelial cells is induced by environmental stimuli associated with chronic respiratory diseases. We therefore examined how airway epithelial cells regulate uric acid production. MATERIALS AND METHODS: Allergen and cigarette smoke mouse models were performed using house dust mite (HDM) and cigarette smoke exposure, respectively, with outcome measurements of lung uric acid levels. Primary human airway epithelial cells isolated from clinically diagnosed patients with asthma and chronic obstructive pulmonary disease (COPD) were grown in submerged cultures and compared to age-matched healthy controls for uric acid release. HBEC-6KT cells, a human airway epithelial cell line, were grown under submerged monolayer conditions for mechanistic and gene expression studies. RESULTS: HDM, but not cigarette smoke exposure, stimulated uric acid production in vivo and in vitro. Primary human airway epithelial cells from asthma, but not COPD patients, displayed elevated levels of extracellular uric acid in culture. In HBEC-6KT, production of uric acid was sensitive to the xanthine dehydrogenase (XDH) inhibitor, allopurinol, and the ATP Binding Cassette C4 (ABCC4) inhibitor, MK-571. Lastly, the pro-inflammatory cytokine combination of TNF-α and IFN-γ elevated extracellular uric acid levels and XDH gene expression in HBEC-6KT cells. CONCLUSIONS: Our results suggest that the active production of uric acid from human airway epithelial cells may be intrinsically altered in asthma and be further induced by pro-inflammatory cytokines.
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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) | 0.001 | 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 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".