Effects of multiwalled carbon nanotubes and triclocarban on several eukaryotic cell lines: elucidating cytotoxicity, endocrine disruption, and reactive oxygen species generation
Bibliographic record
Abstract
To date, only a few reports about studies on toxic effects of carbon nanotubes (CNT) are available, and their results are often controversial. Three different cell lines (rainbow trout liver cells (RTL-W1), human adrenocortical carcinoma cells (T47Dluc), and human adrenocarcinoma cells (H295R)) were exposed to multiwalled carbon nanotubes, the antimicrobial agent triclocarban (TCC) as well as the mixture of both substances in a concentration range of 3.13 to 50 mg CNT/L, 31.25 to 500 μg TCC/L, and 3.13 to 50 mg CNT/L + 1% TCC (percentage relative to carbon nanotubes concentration), respectively. Triclocarban is a high-production volume chemical that is widely used as an antimicrobial compound and is known for its toxicity, hydrophobicity, endocrine disruption, bioaccumulation potential, and environmental persistence. Carbon nanotubes are known to interact with hydrophobic organic compounds. Therefore, triclocarban was selected as a model substance to examine mixture toxicity in this study. The influence of multiwalled carbon nanotubes and triclocarban on various toxicological endpoints was specified: neither cytotoxicity nor endocrine disruption could be observed after exposure of the three cell lines to carbon nanotubes, but the nanomaterial caused intracellular generation of reactive oxygen species in all cell types. For TCC on the other hand, cell vitality of 80% could be observed at a concentration of 2.1 mg/L for treated RTL-W1 cells. A decrease of luciferase activity in the ER Calux assay at a triclocarban concentration of 125 μg/L and higher was observed. This effect was less pronounced when multiwalled carbon nanotubes were present in the medium. Taken together, these results demonstrate that multiwalled carbon nanotubes induce the production of reactive oxygen species in RTL-W1, T47Dluc, and H295R cells, reveal no cytotoxicity, and reduce the bioavailability and toxicity of the biocide triclocarban.
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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".