Modulation of gold nanoparticle mediated radiation dose enhancement through synchronization of breast tumor cell population
Bibliographic record
Abstract
OBJECTIVE: The incorporation of high atomic number materials such as gold nanoparticles (GNPs) into tumor cells is being tested to enhance the local radiotherapy (RT) dose. It is also known that the radiosensitivity of tumor cells depends on the phase of their cell cycle. Triple combination of GNPs, phase of tumor cell population, and RT for improved outcomes in cancer treatment. METHODS: We used a double-thymidine block method for synchronization of the tumor cell population. GNPs of diameters 17 and 46 nm were used to capture the size dependent effects. A radiation dose of 2 Gy with 6 MV linear accelerator was used to assess the efficacy of this proposed combined treatment. A triple negative breast cancer cell line, MDA-MB-231 was chosen as the model cell line. Monte Carlo (MC) calculations were done to predict the GNP-mediated cell death using the experimental GNP uptake data. RESULTS: There was a 1.5- and 2- fold increase in uptake of 17 and 46 nm GNPs in the synchronized cell population, respectively. A radiation dose of 2 Gy with clinically relevant 6 MV photons resulted in a 62 and 38 % enhancement in cell death in the synchronized cell population with the incorporation of 17 and 46 nm GNPs, respectively. MC data supported the experimental data, but to a lesser extent. CONCLUSION: A triple combination of GNPs, cell cycle synchronization, and RT could pave the way to enhance the local radiation dose while minimizing side effects to the surrounding healthy tissue. ADVANCES IN KNOWLEDGE: This is the first study to show that the combined use of GNPs, phase of tumor cell population, and RT could enhance tumor cell death.
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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 | 0.000 | 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 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".