Lung exposure to nanoparticles modulates an asthmatic response in a mouse model
Bibliographic record
Abstract
The aim of this study was to investigate the modulation of an asthmatic response by titanium dioxide (TiO₂) or gold (Au) nanoparticles (NPs) in a murine model of diisocyanate-induced asthma. On days 1 and 8, BALB/c mice received 0.3% toluene diisocyanate (TDI) or the vehicle acetone-olive oil (AOO) on the dorsum of both ears (20 μL). On day 14, the mice were oropharyngeally dosed with 40 μL of a NP suspension (0.4 mg·mL⁻¹ (∼0.8 mg·kg⁻¹) TiO₂ or Au). 1 day later (day 15), the mice received an oropharyngeal challenge with 0.01% TDI (20 μL). On day 16, airway hyperreactivity (AHR), bronchoalveolar lavage (BAL) cell and cytokine analysis, lung histology, and total serum immunoglobulin E were assessed. NP exposure in sensitised mice led to a two- (TiO₂) or three-fold (Au) increase in AHR, and a three- (TiO₂) or five-fold (Au) increase in BAL total cell counts, mainly comprising neutrophils and macrophages. The NPs taken up by BAL macrophages were identified by energy dispersive X-ray spectroscopy. Histological analysis revealed increased oedema, epithelial damage and inflammation. In conclusion, these results show that a low, intrapulmonary doses of TiO₂ or Au NPs can aggravate pulmonary inflammation and AHR in a mouse model of diisocyanate-induced asthma.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".