MWCNTs of different physicochemical properties cause similar inflammatory responses, but differences in transcriptional and histological markers of fibrosis in mouse lungs
Bibliographic record
Abstract
Multi-walled carbon nanotubes (MWCNTs) are an inhomogeneous group of nanomaterials that vary in lengths, shapes and types of metal contamination, which makes hazard evaluation difficult. Here we present a toxicogenomic analysis of female C57BL/6 mouse lungs following a single intratracheal instillation of 0, 18, 54 or 162 μg/mouse of a small, curled (CNT(Small), 0.8 ± 0.1 μm in length) or large, thick MWCNT (CNT(Large), 4 ± 0.4 μm in length). The two MWCNTs were extensively characterized by SEM and TEM imaging, thermogravimetric analysis, and Brunauer-Emmett-Teller surface area analysis. Lung tissues were harvested 24h, 3 days and 28 days post-exposure. DNA microarrays were used to analyze gene expression, in parallel with analysis of bronchoalveolar lavage fluid, lung histology, DNA damage (comet assay) and the presence of reactive oxygen species (dichlorodihydrofluorescein assay), to profile and characterize related pulmonary endpoints. Overall changes in global transcription following exposure to CNT(Small) or CNT(Large) were similar. Both MWCNTs elicited strong acute phase and inflammatory responses that peaked at day 3, persisted up to 28 days, and were characterized by increased cellular influx in bronchoalveolar lavage fluid, interstitial pneumonia and gene expression changes. However, CNT(Large) elicited an earlier onset of inflammation and DNA damage, and induced more fibrosis and a unique fibrotic gene expression signature at day 28, compared to CNT(Small). The results indicate that the extent of change at the molecular level during early response phases following an acute exposure is greater in mice exposed to CNT(Large), which may eventually lead to the different responses observed at day 28.
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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 | 0.000 |
| 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 | 0.001 |
| 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".