Nanotechnology Driven Cancer Chemoradiation: Exploiting the Full Potential of Radiotherapy with a Unique Combination of Gold Nanoparticles and Bleomycin
Bibliographic record
Abstract
One of the major issues in current radiotherapy (RT) is the associated normal tissue toxicity. Enhancement of the RT effect with novel radiosensitizers can address this need. In this study, gold nanoparticles (GNPs) and bleomycin (BLM) were used as a unique combination of radiosensitizers. GNPs offer a two-fold promise as a delivery vehicle for BLM and as a radiosensitizing agent. In this study, GNPs were functionalized and complexed with BLM using a gold-thiol bond (denoted GNP-BLM). Our results show that there was a 40% and 10% decrease in cell growth with GNP-BLM vs. free BLM for the MIA PaCa-2 and PC-3 cell lines, respectively. Testing the GNP-BLM platform with RT showed an 84% and 13% reduction in cell growth in MIA PaCa-2 cells treated with GNP-BLM and GNPs, respectively. Similar results were seen with PC-3 cells. The efficacy of this approach was verified by mapping DNA double-strand breaks (DSBs) as well. Therefore, this proposed incorporation of nanomedicine with RT is promising in achieving a significantly higher therapeutic ratio which is necessary to make a paradigm change to the current clinical approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".