Optimization of uptake and transport of gold nanoparticles in two-dimensional and three-dimensional in-vitro cell models
Bibliographic record
Abstract
High atomic number nanomaterials have been explored as a tool for improving cancer therapeutics. Gold nanoparticles are a system that has been introduced as they can act as effective radiation dose enhancers and anticancer drug carries. Gold nanoparticles have unique physiochemical properties that allow them to be probed in cells using techniques such as scanning electron microscopy and hyper spectral imaging. Optimization of gold nanoparticle uptake into 3D in-vitro models is essential to optimizing future cancer therapeutic applications and bridging the gap between in-vitro and in-vivo tumor environments. The uptake of functionalized gold nanoparticles into 2D monolayer and 3D spheroid cell models was tested. Functionalization of the GNPs was confirmed by use of dynamic light scattering, UV-Visible light spectroscopy, the Zeta potential, and imaged with a scanning electron microscope and hyper spectral imaging. These findings suggest that both the size and functionalization of the gold nanoparticles should be considered in future 3D in-vitro studies.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".