Neutrophilic oxidative stress mediates organic dust-induced pulmonary inflammation and airway hyperresponsiveness
Bibliographic record
Abstract
Airway exposure to organic dust (OD) from swine confinement facilities induces airway inflammation dominated by neutrophils and airway hyperresponsiveness (AHR). One important neutrophilic innate defense mechanism is the induction of oxidative stress. Therefore, we hypothesized that neutrophils exacerbate airway dysfunction following OD exposure by increasing oxidant burden. BALB/C mice were given intranasal challenges with OD or PBS (1/day for 3 days). Mice were untreated or treated with a neutrophil-depleting antibody, anti-Ly6G, or the antioxidant dimethylthiourea (DMTU) prior to OD exposure. Twenty-four hours after the final exposure, we measured airway responsiveness in response to methacholine (MCh) and collected bronchoalveolar lavage fluid to assess pulmonary inflammation and total antioxidant capacity. Lung tissue was harvested to examine the effect of OD-induced antioxidant gene expression and the effect of anti-Ly6G or DMTU. OD exposure induced a dose-dependent increase of airway responsiveness, a neutrophilic pulmonary inflammation, and secretion of keratinocyte cytokine. Depletion of neutrophils reduced OD-induced AHR. DMTU prevented pulmonary inflammation involving macrophages and neutrophils. Neutrophil depletion and DMTU were highly effective in preventing OD-induced AHR affecting large, conducting airways and tissue elastance. OD induced an increase in total antioxidant capacity and mRNA levels of NRF-2-dependent antioxidant genes, effects that are prevented by administration of DMTU and neutrophil depletion. We conclude that an increase in oxidative stress and neutrophilia is critical in the induction of OD-induced AHR. Prevention of oxidative stress diminishes neutrophil influx and AHR, suggesting that mechanisms driving OD-induced AHR may be dependent on neutrophil-mediated oxidant pathways.
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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".