Interplay between the gold nanoparticle sub-cellular localization, size, and the photon energy for radiosensitization
Bibliographic record
Abstract
There are large variations in the reported efficiency of gold nanoparticle (GNP) radiosensitization. We have previously reported on a predictive model, which accounts for the detailed Auger and photoelectron tracks to calculate the cell survival probability. After validating our model using PC-3 cells incubated with 2 mg/ml of 30 nm GNPs and irradiated with 100 kVp or 300 kVp beams, we evaluated the interplay between photon energy, GNP size (1.9 and 100 nm) and sub-cellular localization. Experiments were in excellent agreement with the model. In predictive modeling, using a 100 kVp source and 1.9 nm nanoparticles, GNP localization had a significant impact on cell survival. A sensitizer enhancement ratio of 1.34 was achieved when GNPs were localized outside the cells, increasing to 2.56 when GNPs were also distributed in the cytoplasm and nucleus. Using a 300 kVp source, which emits photons mainly above the gold K-edge, the dependence on GNP localization and size was barely detectable, since long ranged electrons dominate the energy deposition. In summary, achieving intracellular uptake with targeted-GNPs can significantly enhance radiosensitization for photon energies below the gold K-edge, where Auger electrons contribute significantly to the local energy deposition. For higher energies, this is much less important.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".