Long-Term Exposure to CdTe Quantum Dots Causes Functional Impairments in Live Cells
Bibliographic record
Abstract
Several studies suggested that the cytotoxic effects of quantum dots (QDs) may be mediated by cadmium ions (Cd2+) released from the QDs cores. The objective of this work was to assess the intracellular Cd2+ concentration in human breast cancer MCF-7 cells treated with cadmium telluride (CdTe) and core/shell cadmium selenide/zinc sulfide (CdSe/ZnS) nanoparticles capped with mercaptopropionic acid (MPA), cysteamine (Cys), or N-acetylcysteine (NAC) conjugated to cysteamine. The Cd2+ concentration determined by a Cd2+-specific cellular assay was below the assay detection limit (<5 nM) in cells treated with CdSe/ZnS QDs, while in cells incubated with CdTe QDs, it ranged from approximately 30 to 150 nM, depending on the capping molecule. A cell viability assay revealed that CdSe/ZnS QDs were nontoxic, whereas the CdTe QDs were cytotoxic. However, for the various CdTe QD samples, there was no dose-dependent correlation between cell viability and intracellular [Cd2+], implying that their cytotoxicity cannot be attributed solely to the toxic effect of free Cd2+. Confocal laser scanning microscopy of CdTe QDs-treated cells imaged with organelle-specific dyes revealed significant lysosomal damage attributable to the presence of Cd2+ and of reactive oxygen species (ROS), which can be formed via Cd2+-specific cellular pathways and/or via CdTe-triggered photoxidative processes involving singlet oxygen or electron transfer from excited QDs to oxygen. In summary, CdTe QDs induce cell death via mechanisms involving both Cd2+ and ROS accompanied by lysosomal enlargement and intracellular redistribution.
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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".