Gold Nanoparticles as Radiation Sensitizers in Cancer Therapy
Bibliographic record
Abstract
Among other nanoparticle systems, gold nanoparticles have been explored as radiosensitizers. While most of the research in this area has focused on either gold nanoparticles with diameters of less than 2 nm or particles with micrometer dimensions, it has been shown that nanoparticles 50 nm in diameter have the highest cellular uptake. We present the results of in vitro studies that focus on the radiosensitization properties of nanoparticles in the size range from 14-74 nm. Radiosensitization was dependent on the number of gold nanoparticles internalized within the cells. Gold nanoparticles 50-nm in diameter showed the highest radiosensitization enhancement factor (REF) (1.43 at 220 kVp) compared to gold nanoparticles of 14 and 74 nm (1.20 and 1.26, respectively). Using 50-nm gold nanoparticles, the REF for lower- (105 kVp) and higher- (6 MVp) energy photons was 1.66 and 1.17, respectively. DNA double-strand breaks were quantified using radiation-induced foci of gamma-H2AX and 53BP1, and a modest increase in the number of foci per nucleus was observed in irradiated cell populations with internalized gold nanoparticles. The outcome of this research will enable the optimization of gold nanoparticle-based sensitizers for use in therapy.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".