Size-dependent toxicity of CdTe quantum dot aggregates in trout and human hepatocytes
Bibliographic record
Abstract
The objective of this study was to compare the cytotoxicity of monomeric and aggregated cadmium telluride quantum dots (CdTe QD) in human hepatoma (HepG2) and rainbow trout hepatocytes (RTH). Hepatocytes were exposed to concentrations of monomeric CdTe QDs (4 nm diameter) and isolates of different size aggregates for 48 h. The results revealed that the added Cd concentration in the cell culture media increased with the additions of both the monomeric and aggregated QDs where most (72%) of the total Cd was between 100 and 450 nm diameter size range as determined by ultrafiltration. CdTe QDs were cytotoxic to both cell types with an estimated 48 h-EC50 of 3.6 and 7.3 mg/L Cd for monomeric CdTe QDs for the HEPG2 and trout hepatocytes respectively. For the aggregated QDs, analysis of the concentration-response slopes revealed that HepG2 cells were able to significantly discriminate between 2 size ranges: nanoparticles < 4.6 nm and aggregates between 4.6 and 450 nm with the < 4.6 nm group being more toxic than the latter. The RTH model discriminated between 3 distinct size ranges in decreasing order of toxicity: 6.8 nm and smaller > 6.9-50 nm > 50-450 nm. In all cases, the toxicity of QD aggregates decreased with increasing size of the aggregates.
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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".