Acute phase response and inflammation following pulmonary exposure to low doses of zinc oxide nanoparticles in mice
Bibliographic record
Abstract
Inhalation of nanosized zinc oxide (ZnO) induces metal fume fever and systemic acute phase response in humans. Acute phase response activation is a cardiovascular risk factor; we investigated whether pulmonary exposure of mice can be used to assess ZnO-induced acute phase response as well as inflammation and genotoxicity. Uncoated (NM-110) and triethoxycaprylylsilane-coated (NM-111) ZnO nanoparticles were intratracheally instilled once at 0.2, 0.7 or 2 µg/mouse (11, 33 and 100 µg/kg body weight). Serum amyloid A3 mRNA level in lung tissue, bronchoalveolar lavage (BAL) fluid cellularity, and levels of DNA strand breaks in BAL fluid cells, lung and liver tissue were assessed 1, 3 and 28 days post-exposure. Global transcription patterns were assessed in lung tissue using microarrays. The acute-phase response serum amyloid A3 mRNA levels were increased on day 1; for uncoated ZnO nanoparticles at the highest dose and for coated ZnO nanoparticles at medium and highest dose. Neutrophils were increased in BAL fluid only after exposure to coated ZnO nanoparticles. Genotoxicity was observed only in single dose groups, with no dose-response relationship. Most changes in global transcriptional response were observed after exposure to uncoated ZnO nanoparticles and involved cell cycle G2 to M phase DNA damage checkpoint regulation. Although, uncoated and coated ZnO nanoparticles qualitatively exerted similar effects, observed differences are likely explained by differences in solubility kinetics. The finding of serum amyloid A3 induction at low exposure suggests that mouse models can be used to assess the nanoparticle-mediated induction of acute phase responses in humans.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".