Inhaled Titanium Dioxide Nanoparticles: A Review of Their Pulmonary Responses with Particular Focus on the Agglomeration State
Bibliographic record
Abstract
Nanotechnology represents major scientific and economic issues for the future. TiO 2 is used as a reference nanoparticle (NP) for research and workplace exposure assessments due to its important industrial production. However, to date little consistent information exists about its human health effects. Approximately 50% of all TiO 2in vivo studies targeting the respiratory tract have been by inhalation and these exposures are often in the form of agglomerates rather than as individual NPs. Therefore, the size of the NP agglomerates represents the effective size interacting with the biological material and could thereby influence the NP mechanisms of action. Thus, interpretation of nanotoxicological data without considering the agglomeration state could partly explain the heterogeneous results found in the scientific literature for TiO 2 NPs. The objective of this review is to examine the literature concerning the importance of TiO 2 aerosol characterization in the assessment of pulmonary toxicity in rodents. In this way, this review reveals that the pulmonary responses following inhalation of TiO 2 NPs might not depend solely on the primary NP size, but also on the crystal phase, the NP agglomerate size, its structure and the mass concentration. It also shows that TiO 2 NPs may exert their toxicity mechanisms specifically because of the size of their agglomerates in aerosols, thus supporting the concept that aerosols composed essentially of small (< 100 nm) or large (> 100 nm) NP agglomerates do not seem to follow the same pulmonary toxicity mechanisms.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".