Effect of Gold Nanoparticle Aggregation on Cell Uptake and Toxicity
Bibliographic record
Abstract
Aggregation appears to be a ubiquitous phenomenon among all nanoparticles and its influence in mediating cellular uptake and interactions remain unclear. Here we developed a simple technique to produce transferrin-coated gold nanoparticle aggregates of different sizes and characterized their uptake and toxicity in three different cell lines. While the aggregation did not elicit a unique toxic response, the uptake patterns were different between single and aggregated nanoparticles. There was a 25% decrease in uptake of aggregated nanoparticles with HeLa and A549 cells in comparison to single and monodisperse nanoparticles. However, there was a 2-fold increase in MDA-MB 435 cell uptake for the largest synthesized aggregates. These contrasting results suggest that cell type and the mechanism of interactions may play a significant role. This study highlights the need to investigate the behavior of aggregates with cells on a case-by-case basis and the importance of aggregation in mediating targeting and intracellular trafficking.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".