Toxic Effect of Single Walled Carbon Nanotubes Combined with Cadmium to the Crustacean <i>Daphnia magna</i>
Bibliographic record
Abstract
The aim of this study was to assess the impact of single-walled carbon nanotubes (SWCNT) on the toxicity of cadmium (Cd) using the crustacean Daphnia magna . LC50 of Cd and SWCNT alone and combined were calculated and compared. Sorption of Cd on SWCNT was also quantified in separate batch experiments. Results showed that the maximum adsorption of Cd onto SWCNT calculated by the Langmuir equation was 24.4 mg kg-1. LC50s for Cd and SWCNT alone were 252.3 µg L -1 and 1400 µg L -1 , respectively. In the presence of 500 and 1000 µg L -1 of SWCNT, Cd LC50s were 127.2 and 120.1 µg L -1 respectively. Therefore, Cd toxicity increased when organisms were exposed to both contaminants which indicated that SWCNT induces a synergistic toxic effect on the survival of D. magna. It appears that even if SWCNT had a low adsorption capacity for Cd, toxicity of the metal can be increased. Our study shows the complexity of SWCNT toxicity and how the understanding of their interactions with other contaminants is crucial to determine the consequences of their release into the environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".