A Monte Carlo-based model of gold nanoparticle radiosensitization accounting for increased radiobiological effectiveness
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Bibliographic record
Abstract
Radiosensitization using gold nanoparticles (AuNPs) has been shown to vary widely with cell line, irradiation energy, AuNP size, concentration and intracellular localization. We developed a Monte Carlo-based AuNP radiosensitization predictive model (ARP), which takes into account the detailed energy deposition at the nano-scale. This model was compared to experimental cell survival and macroscopic dose enhancement predictions. PC-3 prostate cancer cell survival was characterized after irradiation using a 300 kVp photon source with and without AuNPs present in the cell culture media. Detailed Monte Carlo simulations were conducted, producing individual tracks of photoelectric products escaping AuNPs and energy deposition was scored in nano-scale voxels in a model cell nucleus. Cell survival in our predictive model was calculated by integrating the radiation induced lethal event density over the nucleus volume. Experimental AuNP radiosensitization was observed with a sensitizer enhancement ratio (SER) of 1.21 ± 0.13. SERs estimated using the ARP model and the macroscopic enhancement model were 1.20 ± 0.12 and 1.07 ± 0.10 respectively. In the hypothetical case of AuNPs localized within the nucleus, the ARP model predicted a SER of 1.29 ± 0.13, demonstrating the influence of AuNP intracellular localization on radiosensitization.
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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 | 0.000 | 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) | 0.000 | 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 it