Nitric Oxide and Protein Nitration are Eosinophil Dependent in Allergen-Challenged Mice
Bibliographic record
Abstract
To explore the possible role of eosinophils in NO-mediated tissue injury, we studied a murine model of allergic asthma. Male A/J mice were sensitized and challenged intranasally with ovalbumin (OVA). Following challenge, the number of eosinophils in bronchoalveolar lavage fluid (BALF) increased from 0.4% of total cells at baseline (0.02 x 10(4) cells/ml) to 60.2% at 48 h after the challenge (9.34 x 10(4) cells/ml). The rise in eosinophil count was accompanied by a 40.3% increase in total NO(2-) plus NO(3-) (NO(x)) in BALF. This in turn was accompanied by expression of inducible NO synthase (NOS II) in airway epithelial and inflammatory cells, as well as by evidence of staining for 3-nitrotyrosine (3NT) in peribronchial inflammatory cells and at the epithelial surface. Both NO(x) production and 3NT were significantly reduced by pretreatment of the challenged mice with the highly specific NOS II inhibitor N-3-aminomethyl-benzyl-acetamidine-dihydrochloride (1400W), as well as by the nonselective NOS inhibitor N(omega)-nitro-L-arginine methyl ester (L-NAME). L-NAME and 1400W also reduced the number of BALF eosinophils (37.2% and 61.5%, respectively, as compared with the control value), suggesting that NO production by NOS II contributes to eosinophil recruitment. To further examine the role of eosinophils, we pretreated additional mice with an anti-interleukin (IL)-5 antibody, which reduced BALF eosinophilia following OVA challenge by 90.1%. In concert with the decrease in eosinophils, the anti-IL-5 antibody reduced NO(x) in BALF almost to the baseline value, and decreased the number of 3NT-positive cells in the peribronchial region by 74.4%. Western blot analysis of protein extracted from whole lung confirmed the reduction in tyrosine nitration by anti-IL-5 antibody. These findings indicate that NO and eosinophilic inflammation are closely coupled, and suggest that eosinophils are an important source of tyrosine nitration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".