De novo DUOX2 expression in neutrophil subsets shapes the pathogenesis of intestinal disease
Bibliographic record
Abstract
Infiltrating neutrophils are key effector cells in inflammatory bowel disease (IBD) while providing antimicrobial defense and tissue restitution in the intestine. The complexity of neutrophil functions in local environments underscores our limited understanding of how their adaptation in tissues influences disease progression. Here, we demonstrate that neutrophils recruited in murine colitis and infection models, idiopathic IBD, and chronic granulomatous disease-associated IBD undergo extensive transcriptional reprogramming, resulting in the emergence of neutrophil populations that feature unique DUOX2 NADPH oxidase expression. Functional studies utilizing mice with myeloid and neutrophil specific DUOX2 inactivation reveal a vital and dichotomous role for this NADPH oxidase in both colitis and intestinal infection. Niche-directed reprogramming promoted a DUOX2-dependent chemokine and cytokine-rich intestinal environment that amplified and prolonged inflammatory responses, suggesting that selectively suppressing DUOX2 may constitute an anti-inflammatory strategy for IBD treatment. Altering spatiotemporal redox signaling by de novo expression of a ROS-generating enzyme represents an important feature for functional neutrophil diversification in disease, with implications for other neutrophil-driven diseases in specialized niches.
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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) | 0.000 | 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".