Pulmonary response to surface‐coated nanotitanium dioxide particles includes induction of acute phase response genes, inflammatory cascades, and changes in microRNAs: A toxicogenomic study
Bibliographic record
Abstract
Titanium dioxide nanoparticles (nanoTiO(2) ) are used in various applications including in paints. NanoTiO(2) inhalation may induce pulmonary toxicity and systemic effects. However, the underlying molecular mechanisms are poorly understood. In this study, the effects of inhaled surface-coated nanoTiO(2) on pulmonary global messenger RNA (mRNA) and microRNA (miRNA) expression in mouse were characterized to provide insight into the molecular response. Female C57BL/6BomTac mice were exposed for 1 hr daily to 42.4 ± 2.9 (SEM) mg surface-coated nanoTiO(2) /m(3) for 11 consecutive days by inhalation and were sacrificed 5 days following the last exposure. Physicochemical properties of the particles were determined. Pulmonary response to nanoTiO(2) was characterized using DNA microarrays and pathway-specific PCR arrays and related to data on pulmonary inflammation from bronchial lavages. NanoTiO(2) exposure resulted in increased levels of mRNA for acute phase markers serum amyloid A-1 (Saa1) and serum amyloid A-3 (Saa3), several C-X-C and C-C motif chemokines, and cytokine tumor necrosis factor genes. Protein analysis of Saa1 and 3 showed selective upregulation of Saa3 in lung tissues. Sixteen miRNAs were induced by more than 1.2-fold (adjusted P-value < 0.05) following exposure. Real time polymerase chain reaction confirmed the upregulation of miR-1, miR-449a and revealed dramatic induction of miR-135b (60-fold). Thus, inhalation of surface-coated nanoTiO(2) results in changes in the expression of genes associated with acute phase, inflammation and immune response 5 days post exposure with concomitant changes in several miRNAs. The role of these miRNAs in pulmonary response to inhaled particles is unknown and warrants further research.
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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".