Transcriptional profiling reveals gene expression changes associated with inflammation and cell proliferation following short‐term inhalation exposure to copper oxide nanoparticles
Bibliographic record
Abstract
Abstract Our recent studies revealed a dose‐dependent proinflammatory response to copper oxide nanoparticles (CuO NPs) in rats following short‐term inhalation exposure for five consecutive days. Here transcriptomics approaches were applied using the same model to assess global gene expression in lung tissues obtained 1 day post‐exposure and after a recovery period of 22 days from rats exposed to clean air or 6 hour equivalent doses of 3.3 mg m −3 (low dose) and 13.2 mg m −3 (high dose). Microarray analyses yielded about 1000 differentially expressed genes in the high‐dose group and 200 in low‐dose compared to the clean air control group, and less than 20 after the recovery period. Pathway analysis indicated cell proliferation/survival and inflammation as the main processes triggered by exposure to CuO NPs. We did not find significant perturbations of pathways related to oxidative stress. Upregulation of epithelial cell transforming protein 2 ( Ect2 ), a known oncogene, was noted and ECT2 protein was upregulated in the lungs of exposed animals. Proliferation of alveolar epithelial cells was demonstrated based on Ki67 expression. The gene encoding monocyte chemoattractant protein 1 (or CCL2) was also upregulated and this was confirmed by immunohistochemistry. However, no aberrant DNA methylation of inflammation‐associated genes was observed. In conclusion, we have found that inhalation of CuO NPs in rats causes upregulation of the oncoprotein ECT2 and the chemokine CCL2 and other proinflammatory markers as well as proliferation in bronchoalveolar epithelium after a short‐term inhalation exposure. Thus, pathways known to be associated with neoplastic processes and inflammation were affected in this model.
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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".