Improving the Accumulation of Gold Nanoparticles Using Ultrasound and Microbubbles to Enhance Radiation Therapy
Bibliographic record
Abstract
Gold nanoparticles have long been considered for use in conjunction with radiation therapy to enhance dose in a local tumor regions. However, limitation in cellular accumulation remains a hindrance for treatments to extend to clinical levels. Ultrasound and microbubbles have been shown to enhance the delivery of chemotherapies, genetic material and other molecules. This goal of this study was to demonstrate, for the first time to the best of our knowledge, the increase in PEGylated gold nanoparticle accumulation in cells due to the addition of ultrasound and microbubbles, and survival fraction. The results display approximate 3 fold increase in intracellular gold content independent of nanoparticle size, resulting in a 5 fold increase in cell death. Additionally, it was shown that USMB can facilitate nuclear localization of gold nanoparticles with nuclear localized signals to further enhance radiation 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 | 0.000 | 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) | 0.001 | 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".