Pulmonary instillation of low doses of titanium dioxide nanoparticles in mice leads to particle retention and gene expression changes in the absence of inflammation
Bibliographic record
Abstract
We investigated gene expression, protein synthesis, and particle retention in mouse lungs following intratracheal instillation of varying doses of nano-sized titanium dioxide (nano-TiO2). Female C57BL/6 mice were exposed to rutile nano-TiO2 via single intratracheal instillations of 18, 54, and 162μg/mouse. Mice were sampled 1, 3, and 28days post-exposure. The deposition of nano-TiO2 in the lungs was assessed using nanoscale hyperspectral microscopy. Biological responses in the pulmonary system were analyzed using DNA microarrays, pathway-specific real-time RT-PCR (qPCR), gene-specific qPCR arrays, and tissue protein ELISA. Hyperspectral mapping showed dose-dependent retention of nano-TiO2 in the lungs up to 28days post-instillation. DNA microarray analysis revealed approximately 3000 genes that were altered across all treatment groups (±1.3 fold; p<0.1). Several inflammatory mediators changed in a dose- and time-dependent manner at both the mRNA and protein level. Although no influx of neutrophils was detected at the low dose, changes in the expression of several genes and proteins associated with inflammation were observed. Resolving inflammation at the medium dose, and lack of neutrophil influx in the lung fluid at the low dose, were associated with down-regulation of genes involved in ion homeostasis and muscle regulation. Our gene expression results imply that retention of nano-TiO2 in the absence of inflammation over time may potentially perturb calcium and ion homeostasis, and affect smooth muscle activities.
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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 | 0.000 | 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".