Cytotoxicity and Cellular Uptake of Gold Nanoparticles in Breast Cancer Cells Quantified Using Total Reflection X-Ray Fluorescence
Bibliographic record
Abstract
The field of nanotoxicity is continuously expanding as researchers seek to understand potential consequences of AuNP use in the medical field. Many current results examining cytotoxicity trends with varying nanoparticle parameters lack consistency and rely on methods to measure uptake that have been previously noted as unreliable. In this work, 10 and 50 nm diameter gold nano-spheres and -rods are compared while also measuring absolute gold uptake. The toxicity of naked AuNP in epithelial breast cancer cells were measured with flow cytometry while cellular uptake was analyzed with total reflection X-ray fluorescence (TXRF) spectroscopy. Confirming results seen in many studies, spheres were taken up more effectively and exhibited lower toxicity. Measuring the absolute gold, 10 nm shapes were up to 6% more toxic. Modelling the toxicity, both the Hill and linear-quadratic models are more suitable than the exponential model (p<0.05) where the Hill model is proposed for future use.
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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) | 0.002 | 0.001 |
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".